Medicine, Faculty of
Pathology and Laboratory Medicine, Department of
DSpace
UBCV
Lauener, Madeline
Doctor of Philosophy - PhD
University of British Columbia
Chronic graft-versus-host disease (cGvHD) occurs in ~25% of pediatric and ~60% of adult Hematopoietic Stem Cell Transplant (HSCT) patients and is a major cause of mortality. In large study cohorts (~500 patients), our group has shown a CD56ᵇʳⁱᵍʰᵗPerforin⁻ Natural Killer population, consistent with described regulatory NK cells (NKreg), to strongly associate with protection from cGvHD development. Therefore, I hypothesized that NKreg cells suppress cGvHD through inflammatory cell inhibition, and these cells can be distinguished as a unique cell subset which can be expanded. In my project, I characterized NKreg cells according to transcriptome, proteome, metabolome, phenotype, and function; evaluated the in vitro suppressive effect of NKreg cells on cGvHD immune populations; and optimized the expansion of functional NKreg cells in vitro. Transcriptome analysis revealed that NKreg cells express high RNA levels of Granzyme K, IL-7R, GPR183, RANK, GM-CSFR, CD62L, and LEF1. These NKreg cells can be isolated by sorting for CD56⁺CD16⁻ NK cells, and this population can suppress allogeneic CD4⁺ T cells, but not Treg cells, CD8⁺ T cells, CD56ᵈⁱᵐCD16⁺ cytolytic NK cells, or B cells, through a contact-dependent mechanism, which is partially reliant on the PD-1, LAG-3, and/or TRAIL inhibitory pathways. Additionally, NKreg cells demonstrate a lack of cytotoxicity towards K562, MOLT-4, and Jurkat leukemic cells, and CD4⁺ T cells. Further, I determined two alternative approaches for obtaining clinically relevant numbers of NKreg cells, achieving up to 300-fold expansion, with use of IL-2, TGF-β1, and rapamycin for cells from peripheral blood, or approximately 350-fold expansion when expanding and differentiating NKreg cells from cord blood-hematopoietic stem and progenitor cells. In further characterization of the expanded NKreg cells, I describe their metabolism to be consistent with cytolytic NK cells, though they also secrete regulatory cytokines, including IL-10, TGF-β1, adenosine, and TRAIL. This work has established that a CD56ᵇʳⁱᵍʰᵗCD16⁻ NKreg population associates with protection from cGvHD development and has several unique characteristics. Further investigations may utilize these findings to evaluate functional efficacy in in vivo models of GvHD and translate the expansion protocol to one which is clinically applicable, with the goal of using these cells as a cGvHD cellular therapy.
CHARACTERIZATION AND EXPANSION OF REGULATORY NATURAL KILLER CELLS FOR THE THERAPY OF CHRONIC GRAFT-VERSUS-HOST DISEASE by MADELINE LAUENER B.Sc., Simon Fraser University, 2020 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Pathology and Laboratory Medicine) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) June 2024 © Madeline Lauener, 2024 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Characterization and expansion of regulatory natural killer cells for the therapy of chronic graft-versus-host disease submitted by Madeline Lauener in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Pathology and Laboratory Medicine Examining Committee: Kirk Schultz, MD, Professor, Department of Pediatrics, UBC Supervisor Kevin Hay, MD, Associate Professor, Department of Medicine, University of Calgary Cumming School of Medicine, Department of Medicine Supervisory Committee Member Gregor Reid, PhD, Associate Professor, Department of Pediatrics, UBC University Examiner Alexander Beristain, PhD, Associate Professor, Department of Obstetrics and Gynaecology, UBC University Examiner Denis-Claude Roy, MD, Professor, Department of Medicine, Université de Montréal External Examiner Additional Supervisory Committee Members: Laura Sly, PhD, Professor, Department of Pediatrics, UBC Supervisory Committee Member Ramon Klein Geltink, PhD, Assistant Professor, Department of Pathology and Laboratory Medicine, UBC Supervisory Committee Member iii Abstract Chronic graft-versus-host disease (cGvHD) occurs in ~25% of pediatric and ~60% of adult Hematopoietic Stem Cell Transplant (HSCT) patients and is a major cause of mortality. In large study cohorts (~500 patients), our group has shown a CD56brightPerforin- Natural Killer population, consistent with described regulatory NK cells (NKreg), to strongly associate with protection from cGvHD development. Therefore, I hypothesized that NKreg cells suppress cGvHD through inflammatory cell inhibition, and these cells can be distinguished as a unique cell subset which can be expanded. In my project, I characterized NKreg cells according to transcriptome, proteome, metabolome, phenotype, and function; evaluated the in vitro suppressive effect of NKreg cells on cGvHD immune populations; and optimized the expansion of functional NKreg cells in vitro. Transcriptome analysis revealed that NKreg cells express high RNA levels of Granzyme K, IL-7R, GPR183, RANK, GM-CSFR, CD62L, and LEF1. These NKreg cells can be isolated by sorting for CD56+CD16- NK cells, and this population can suppress allogeneic CD4+ T cells, but not Treg cells, CD8+ T cells, CD56dimCD16+ cytolytic NK cells, or B cells, through a contact-dependent mechanism, which is partially reliant on the PD-1, LAG-3, and/or TRAIL inhibitory pathways. Additionally, NKreg cells demonstrate a lack of cytotoxicity towards K562, MOLT-4, and Jurkat leukemic cells, and CD4+ T cells. Further, I determined two alternative approaches for obtaining clinically relevant numbers of NKreg cells, achieving up to 300-fold expansion, with use of IL-2, TGF-β1, and rapamycin for cells from peripheral blood, or approximately 350-fold expansion when expanding and differentiating NKreg cells from cord blood-hematopoietic stem and progenitor cells. In further characterization of the expanded NKreg cells, I describe their iv metabolism to be consistent with cytolytic NK cells, though they also secrete regulatory cytokines, including IL-10, TGF-β1, adenosine, and TRAIL. This work has established that a CD56brightCD16- NKreg population associates with protection from cGvHD development and has several unique characteristics. Further investigations may utilize these findings to evaluate functional efficacy in in vivo models of GvHD and translate the expansion protocol to one which is clinically applicable, with the goal of using these cells as a cGvHD cellular therapy. v Lay Summary Stem Cell Transplantation (SCT), the infusion of a donor’s immune system into a recipient, is an important therapy for high-risk and recurring blood cancers. However, SCT can cause long-term health complications, the most severe being chronic graft-versus-host disease (cGvHD), in which donor immune cells attack the patients’ tissues causing organ dysfunction and scarring. We have identified increased numbers of specific immune system cells known as regulatory Natural Killer cells (NKreg) in patients who are protected from cGvHD. Thus, I reasoned that NKreg cells may function to suppress cGvHD, and that these cells may be distinguished as a unique population that could be expanded and used to prevent cGvHD. I now understand the characteristics of human NKreg cells that associate with protection from cGvHD and have established a method for cell expansion. This data provides a biological understanding for developing strategies to prepare NKreg cells as a future therapy for cGvHD. vi Preface Chapter 1: The work contained in Chapter 1 is currently unpublished. I conducted a literature review regarding the characteristics of regulatory natural killer cells (NKreg), and natural killer cells in the context of chronic graft-versus-host disease (cGvHD). This literature review was researched and written by me and reviewed and edited by my supervisor Dr. K. Schultz and my supervisory committee members, including Dr. L. Sly, Dr. R. Klein Geltink, and Dr. K. Hay. Chapter 2: A portion of the work described in Chapter 2 has been published in 1 manuscript, and the unpublished work described in Chapter 2 is in preparation for publication. The specific contributions are described below. Sections 2.3.1-2.3.3 and associated background, methods, and conclusions have been published: Lauener M, AzadPour S, Abdossamadi S, et al. CD56brightCD16- natural killer cells as an important regulatory mechanism in chronic graft-versus-host disease. Haematologica. 2023;108(3):761-771. Published 2023 Mar 1. doi:10.3324/haematol.2022.280653 The majority of the research was performed and analyzed by me at the BC Children’s Hospital Research Institute in Vancouver, BC. Dr. K. Schultz edited and reviewed the manuscript in its entirety and oversaw all aspects of the study and the evaluation of the results. Dr. S. AzadPour, Dr. S. Abdossamadi, and Dr. Parthasarathy performed and interpreted the transcriptome studies. Dr. B. Ng performed all transcriptome statistical analyses. Dr. E. Ostoumov managed the ethics applications and funding of the study. Dr. G. Cuvelier completed the clinical patient data analysis for the transcriptome study. The Centre for Heart Lung Innovation at St. Paul’s Hospital (Vancouver, BC, Canada) performed the nanoString assays. vii Section 2.3.4 and associated background, methods, and conclusions have not been published, and a manuscript is in preparation for submission. This work was completed in collaboration with Ao Mei (PhD student) and Dr. S. Malarkannan at the Versiti Blood Research Institute. I prepared the patient samples for analysis, collected associated clinical data, and interpreted and wrote the methods, results, and conclusions of the work, as described in this dissertation. Ao Mei completed the sample processing, single-cell RNA sequencing, and statistical analysis, while Dr. S. Malarkannan and Dr. K. Schultz oversaw all aspects of the study design and interpretation. Chapter 3: A portion of the work described in Chapter 3 has been published in 1 manuscript, and the unpublished work described in Chapter 3 is in preparation for publication. The specific contributions are described below. Sections 3.3.1, 3.3.4-3.3.6 and associated background, methods, and conclusions have been published: Lauener M, AzadPour S, Abdossamadi S, et al. CD56brightCD16- natural killer cells as an important regulatory mechanism in chronic graft-versus-host disease. Haematologica. 2023;108(3):761-771. Published 2023 Mar 1. doi:10.3324/haematol.2022.280653 Most of the research was performed and analyzed by me at the BC Children’s Hospital Research Institute in Vancouver, BC. Dr. K. Schultz edited and reviewed the manuscript in its entirety and oversaw all aspects of the study and the evaluation of the results. Dr. E. Ostoumov managed the ethics applications and funding of the study. Dr. A. Kariminia oversaw aspects of the design of the suppression and apoptosis detection assays and the evaluation of the results. Dr. M.K. Levings and Dr. K.N. Macdonald provided expanded, cryopreserved Treg cells, and guidance regarding working with regulatory immune cells. The Reid lab from the BC Children’s Hospital Research Institute, including Mohammad Reza Rahavi and Dr. Ali Farokhi, provided Luciferin transfected K562 cells and imaged the plates in the NK cell versus K562 cell killing assay. The viii Lim lab from the BC Children’s Hospital Research Institute, including Pascal Leclair, contributed Jurkat and MOLT-4 leukemic cell lines for the leukemic cell apoptosis detection assay. Sections 3.3.2, 3.3.3, and 3.3.7 and associated background, methods, and conclusions have not been published, and a manuscript is in preparation for submission. I completed most of the experimental work, analysis, and interpretation, and wrote the background, methods, results, and conclusions, as described in this dissertation. Chapter 4: The work described in Chapter 4 is unpublished and is in preparation for publication. The specific contributions are described below. I completed the majority of the experimental work, analysis, and interpretation, and wrote the background, methods, results, and conclusions, as described in this dissertation, at the BC Children’s Hospital Research Institute in Vancouver, BC. Dr. K. Schultz oversaw all aspects of the study and the evaluation of the results. Dr. E. Ostoumov managed the ethics applications and funding of the study. Section 4.3.3 and associated methods and conclusions were done in collaboration with other research groups. Dr. R. Klein Geltink and Erin Tanaka (PhD student) from the BC Children’s Hospital Research Institute in Vancouver, BC provided guidance and reagents regarding the expansion of NKreg cells and performed the metabolism studies and analyses. Dr. S. Malarkannan and Ao Mei (PhD student) at the Versiti Blood Research Institute performed the transcriptome studies and analyses. Dr. Paul Keown and Dr. Karen Sherwood from Vancouver Coastal Health were involved in the preparation and submission of samples to Olink Proteomics for proteomic analysis. ix Chapter 5: The work contained in Chapter 5 is currently unpublished. This conclusion and discussion section was researched and written by me and reviewed and edited by my supervisor Dr. K. Schultz. My supervisor Dr. K. Schultz and my supervisory committee members, including Dr. L. Sly, Dr. R. Klein Geltink, and Dr. K. Hay reviewed and edited my dissertation in its entirety. Ethics applications This study was conducted under the approval of the UBC Research Ethics Boards, with use of two separate applications, the first entitled “NKreg expansion (H18-00022)” and the second entitled “NKreg profiling (H16-00533)”. The approved ethics application H18-00022 was for all work involving the optimization of the expansion of functional NKreg cells, and the application H16-00533 was for all work involving the identification, sorting, and characterization of the NKreg cells. x Table of Contents Abstract………………………………………………………………………………………….iii Lay Summary………………………………………………………………………………….....v Preface………………………………………………………………………………………...….vi Table of Contents…………………………………………………………………………….......x List of Tables…………………………………………………………………………….......…xvi List of Figures……………………………………………………………………………...…xviii List of Abbreviations………………..………………………...………………………………xxii Acknowledgements……………………………………………………………….…...….....xxxiii Dedication……………………………………………………………………………......…...xxxv Chapter 1: Introduction….…...………………………...…………………………………….....1 1.1 Hematopoietic stem cell transplantation…...……………………………………...………1 1.2 Graft-versus-host disease…………………………….……………………………………2 1.3 Natural killer cells and chronic graft-versus-host disease ..………………………………4 1.4 Natural killer cells in the biological context…………………………………………..…..8 1.5 Human Natural killer cells…………………………..………...…………………………11 1.6 Human Natural killer cell lineage and development…………………………………..…13 1.7 Phenotypic characteristics of human regulatory natural killer cells…………………..…15 1.8 Metabolism of human regulatory natural killer cells………………………………...…..16 1.9 Functional characteristics of regulatory natural killer cells………………………..…….18 1.9.1 Suppression of T cell proliferation………………………………………..……..18 xi 1.9.2 Cytokine production……………………………………………………………...21 1.10 Project hypothesis, objective, and aims………………………………………………….22 Chapter 2: NKreg cells associated with cGvHD suppression may be characterized as a transcriptionally and phenotypically unique NK cell population…………………..........….24 2.1 Introduction.…..………………………………………………………………….........…24 2.2 Methods…………………………………………………………………………….…….26 2.2.1 Immune cell populations in HSCT patients associated with cGvHD..…..........…26 2.2.2 NanoString study sample collection, cell sorting, RNA extraction, and analysis.31 2.2.3 Characterization of CD56bright NK cells according to phenotype………………..33 2.2.4 Cell sorting of viable con-cytolytic NKreg cells……………………………....….34 2.2.5 Identification of NKreg cell subpopulations associated with cGvHD suppression through single-cell RNA sequencing……………………...………….…….……35 2.3 Results………………………………………………………………………………...….39 2.3.1 Identification of cell populations in HSCT patients associated with cGvHD…...39 2.3.2 NK cell transcriptome expression in HSCT patients………………………….…42 2.3.2.1 Comparison of CD56bright to CD56dim NK cells………………….…....…42 2.3.2.2 CD56bright NK cells associated with a lack of late aGvHD and cGvHD…43 2.3.3 Phenotyping of CD56bright NK cells and sorting of NKreg cells………………..…45 2.3.4 Transcriptomic characterization of unique NK cell subpopulations associated with cGvHD development or suppression……………………………………...….….50 2.3.4.1 Transcriptionally unique subpopulations of NK cells in HSCT patients...50 2.3.4.2 Transcriptome changes in NKreg cells associated with cGvHD………….54 xii 2.3.4.3 Quantitative associations of NK cell subpopulations in HSCT patients with or without cGvHD………………………………………...….…….58 2.3.4.4 Pseudotime analysis of NKreg cells and cytolytic NK cells in HSCT patients with and without cGvHD…………………………………….….60 2.4 Discussion…………………………………………………………………………..……62 Chapter 3: NKreg cells may function to prevent cGvHD through selective suppression of CD4+ T cells through a PD-1, LAG-3, and/or TRAIL dependent mechanism………….…..67 3.1 Introduction..…..………………………………………………………………..…......…67 3.2 Methods…………………………………………………………………………….…….69 3.2.1 NK cell isolation for all functional evaluations………………………...…..……69 3.2.2 Evaluation of NKreg cell suppression……………………………………..…...…70 3.2.2.1 Suppression of CD4+ T cell proliferation……………………………..…70 3.2.2.2 Suppression of CD4+ naïve and memory T cell proliferation………....…72 3.2.2.3 Suppression of CD4+ T helper cell subset (Th1/2/17) cell proliferation..…73 3.2.2.4 Suppression of CD8+ T cell proliferation……………….………………..73 3.2.2.5 Suppression of Treg cell proliferation………………………………….....74 3.2.2.6 Suppression of Treg cell proliferation with dendritic cells…………….…74 3.2.2.7 Suppression of cytolytic NK cell proliferation……………………….….75 3.2.2.8 Suppression of B cell proliferation…………………………………..…..75 3.2.3 Evaluation of cell-cell contact dependence in NKreg suppression of CD4+ T cell proliferation………………………………………………………………………76 3.2.4 Evaluation of GPR183, NKp44, and NKp46 receptor dependence in NKreg suppression of CD4+ T cell proliferation………………………………....…...…77 xiii 3.2.5 Evaluation of PD-1, LAG-3, and TRAIL receptor dependence in NKreg suppression of CD4+ T cell proliferation……………………………………...…77 3.2.5.1 NKreg and CD4+ T cell surface expression of PD-1, PD-L1, LAG-3, HLA- DR, TRAILR1, and TRAIL…………………………………..………….78 3.2.6 Evaluation of NKreg cell induction of responder cell death…………………...…79 3.2.7 Evaluation of NKreg cell induction of K562 cell killing………………....…....…81 3.2.8 Functional assay statistical analysis summary………………….……………..…82 3.3 Results………………………………………………………………………………...….82 3.3.1 Evaluation of NKreg cell ability to suppress T cell proliferation…………………82 3.3.2 Evaluation of NKreg cell ability to suppress cytolytic NK cell proliferation…..…91 3.3.3 Evaluation of NKreg cell ability to suppress B cell proliferation…………………94 3.3.4 Evaluation of the cytolytic ability of NKreg cells……………………………...…97 3.3.5 Evaluation of cell-cell contact dependence for NKreg cell suppression……...…102 3.3.6 Evaluation of GPR183, NKp46, and NKp44 receptor dependence for NKreg cell suppression………………………….………………………..…………….…..106 3.3.7 Evaluation of PD-1, LAG-3, and TRAIL receptor dependence……………..…110 3.3.7.1 NKreg suppression of CD4+ T cell proliferation……………………...…110 3.3.7.2 NKreg and CD4+ T cell surface expression of PD-1, PD-L1, LAG-3, HLA- DR, TRAILR1, and TRAIL……………………………………....…….115 3.4 Discussion…………………………………………………………………………....…118 Chapter 4: Suppressive NKreg cells may be optimally expanded from peripheral blood or stem and progenitor cells……………………………………………………………………...131 4.1 Introduction..…..……………………………………………………..........................…131 xiv 4.2 Methods…………………………………………………………………...……….……133 4.2.1 Optimization of the in vitro expansion of peripheral NKreg cells………...….…133 4.2.1.1 Expansion of total NK cells with use of ligands associated with immune tolerance…………………………………………………………...……133 4.2.1.2 Expansion of total NK cells with use of candidate ligands to prevent NK cell differentiation…………………...…………………………….....…134 4.2.1.3 Expansion and suppressive capacity of expanded NKreg cells…….....…135 4.2.1.4 Phenotypic evaluation of expanded NK cells………………………..…136 4.2.1.5 Expansion, function, and phenotype of NKreg cells expanded with three differing media conditions………………………………………...……137 4.2.2 Comparison of cord and peripheral blood NKreg cell proliferation, phenotype, and h function…………………………………………………………………………138 4.2.3 Characterization of optimally expanded peripheral NKreg cells…………..……138 4.2.3.1 Transcriptome……………………………………………………..……138 4.2.3.2 Metabolic phenotype……………...……………………………….……139 4.2.3.3 Proteomics/cytokine production..………………………………………140 4.2.4 Expansion and differentiation of NKreg cells from CD34+ hematopoietic stem and progenitor cells………………………………………………………….………141 4.3 Results…………………………………………………………………………………..142 4.3.1 Optimization of the in vitro expansion of peripheral NKreg cells …….....……..142 4.3.1.1 Expansion of total NK cells with use of ligands associated with immune tolerance………………..…………………………………………...…..142 4.3.1.2 Expansion of total NK cells with use of candidate ligands to prevent NK xv cell differentiation………………...………………………...…………..146 4.3.1.3 Evaluation of the phenotype and suppressive capacity of the expanded NKreg cells…………………………………………...…………….……151 4.3.1.4 Expansion, function, and phenotype of NKreg cells expanded with three differing media conditions………………………………………...……154 4.3.2 Comparison of cord and peripheral blood NKreg cell proliferation, phenotype, and function…………………………………………………………………………157 4.3.3 Characterization of optimally expanded peripheral NKreg cells……….……….159 4.3.3.1 Transcriptome…………………………………………………….…….159 4.3.3.2 Metabolic phenotype…...……………………………………………….164 4.3.3.3 Proteomics/cytokine production…..……………………………………166 4.2.4 Expansion and differentiation of NKreg cells from CD34+ hematopoietic stem and progenitor cells………………………………………………………………….170 4.4 Discussion……………………………………………………………………..……..…174 Chapter 5: Conclusion……………………………..…………..…………………………...…187 5.1 Conclusions and chapter summaries..………………………………………………..…187 5.1.1 Chapter 2 summary……………………………………………………..………188 5.1.2 Chapter 3 summary………………………………………………………..……191 5.1.3 Chapter 4 summary………………………………………………………..……193 5.2 Study limitations ………………………...…………………………………….…...…..196 5.3 Contribution to the field, future directions, and final notes..………………………..….200 References……………………………………………………………………………….......…206 xvi List of Tables Table 1 HSCT patient baseline characteristics…...………………………………..……..29 Table 2 Clinical characteristics of HSCT patient samples utilized in scRNAseq study….37 Table 3 Differences between CD56bright and CD56dim NK cells that are associated with a lack of GvHD and differences in gene expression between CD56bright NK cells in HSCT patients who were immune tolerant (no late aGvHD or cGvHD) versus those who developed GvHD measured on samples from day 100 post HSCT….44 Table 4 Gene expression of unique NK cell clusters among all HSCT patient samples....51 Table 5 Gene expression of unique NK cell clusters among HSCT patients that developed cGvHD………………………………………………………………………...…55 Table 6 Expansion and differentiation of total NK cells expanded with use of ligands associated with a lack of cGvHD development in the CD56bright NK cell subset……………………………………………………………………………146 Table 7 Expansion and differentiation of total NK cells expanded with use of candidate ligands to prevent NK cell differentiation……………………………..……….150 Table 8 Expansion, differentiation, and CD4+ T cell suppression of NKreg cells…….....154 Table 9 Expansion and differentiation of NKreg cells cultured with different media..….155 Table 10 Phenotypic and functional characteristics of expanded cord and peripheral NKreg cells……………………………………………………………………………..157 xvii Table 11 Bulk RNA sequencing of CD56brightCD16- NKreg cells………………………...160 Table 12 Identification genes for regulatory NK cells; Bulk RNA sequencing of untreated CD56brightCD16- NKreg cells compared to expanded CD56brightCD16- NKreg cells……………………………………………………………………………..161 Table 13 Protein expression of fresh NKreg cells compared to fresh cytolytic NK cells (NKdim)……………………………………………………………………….…167 Table 14 Protein expression of expanded NKreg cells compared to expanded cytolytic NK cells (NKdim)…………………………………………………………………….167 Table 15 Phenotypic and functional characteristics of NKreg cells differentiated from CD34+ hematopoietic stem and progenitor cells……………………………….171 xviii List of Figures Figure 1 Immune cell populations in HSCT patients associated with cGvHD ...…..…..…41 Figure 2 Cell surface and intracellular characteristics of the NK cell population in healthy donor peripheral blood..…………………………………………………….....…47 Figure 3 Sorting strategy for CD56brightCD16- NKreg cells, and the perforin and Granzyme B expression of sorted NKreg cells.……………………………………..……..…49 Figure 4 Transcriptome of NK cell subpopulations in HSCT patients, with and without cGvHD……………………………………………………………………….…..52 Figure 5 Gene set enrichment assay, comparing Cluster 1 (CD56bright NKreg cells) to Cluster 0 (cytolytic CD56dim NK cells)…………………………………………………..56 Figure 6 Quantitative analysis of transcriptionally unique NK cell clusters in HSCT patients with and without cGvHD…………………………………………...…...59 Figure 7 Pseudotime analysis of cluster 0 (CD56dim NK) and 1 (CD56bright NKreg) cells in HSCT people with and without cGvHD……………………….………..………61 Figure 8 Evaluation of CD56brightCD16- NKreg cell ability to suppress CD4+ T cell proliferation…………………………………………………..………………..…85 Figure 9 Evaluation of CD56brightCD16- NKreg cell ability to suppress CD4+ T helper cell subset 1, 2, or 17 proliferation………………………………………………...…87 xix Figure 10 Evaluation of CD56brightCD16- NKreg cell ability to suppress CD8+ T cell proliferation………………………………………………………………………89 Figure 11 Evaluation of CD56brightCD16- NKreg cell ability to suppress Treg cell proliferation in the presence of dendritic cells……………………………………..…………..90 Figure 12 Evaluation of CD56brightCD16- NKreg cell ability to suppress NK cell proliferation………………………………………………………..……………..92 Figure 13 Evaluation of CD56brightCD16- NKreg cell ability to suppress B cell proliferation…………………………………………………………...………….95 Figure 14 CD56brightCD16- NKreg cell induction of K562 cell killing………………..……..98 Figure 15 CD56brightCD16- NKreg cell induction of CD4+ T cell death…..…………..……..99 Figure 16 CD56brightCD16- NKreg cell induction of Jurkat and MOLT-4 leukemic cell death……………………………………………...………………………..……101 Figure 17 Evaluation of cell-cell contact dependence for CD56brightCD16- NKreg cell suppression…………………………………………………………………...…103 Figure 18 Evaluation of CD56brightCD16- NKreg cell supernatant suppression of CD4+ T cell proliferation………………………………………………………………..……105 Figure 19 Evaluation of NKp44, NKp46, and GPR183R dependence for CD56brightCD16- NKreg cell suppression…………………………………………………...…..….108 Figure 20 Evaluation of CD56brightCD16- NKreg cell ability to suppress CD4+ T cell proliferation with PD-1 and LAG-3 receptor blockers………………………....112 xx Figure 21 Evaluation of CD56brightCD16- NKreg cell ability to suppress CD4+ T cell proliferation when blocking TRAIL…………………………………………....114 Figure 22 Evaluation of phenotypic expression of activated CD56brightCD16- NKreg cells and CD4+ T cells………………………………………………………………..116 Figure 23 20-day fold-expansion of NKreg cells grown in different expansion media……156 Figure 24 20-day fold-expansion of peripheral and cord blood isolated NKreg cells…..….158 Figure 25 Bulk RNA sequencing of untreated NKreg cells compared to expanded NKreg cells………………………………………………………………………..……162 Figure 26 Metabolic characteristics of expanded NK cells………………………………..165 Figure 27 Heatmap of Normalized Protein Expression (NPX) of expanded CD56brightCD16- NKreg cells compared to expanded CD56dimCD16+ NK cells...168 Figure 28 Evaluation of CD56brightCD16- NKreg cell ability to suppress CD4+ T cell proliferation when blocking proteomic candidates: TGF-β, A2AR, or IL-10R..169 Figure 29 Evaluation of the phenotypic expression of CD34+ HSPC differentiated and sorted CD56brightCD16- NKreg cells………………………………………………...…..172 Figure 30 Evaluation of CD34+ differentiated CD56brightCD16- NKreg cell function…...…173 Figure 31 Thesis chapter 2 main results summary……………………………………...…190 Figure 32 Thesis chapter 3 main results summary……………………………………...…192 Figure 33 Thesis chapter 4 main results summary……………………………………...…195 xxi Figure 34 Functional and phenotypic characteristics of NKreg cells (visual summary)...…205 xxii List of Abbreviations A2AR Adenosine 2A Receptor ABLE/PBMTC 1202 Applied Biomarkers in Late Effects trial ADA Adenosine Deaminase ADCC Antibody Dependent Cell Mediated Cytotoxicity ADGRG3 Adhesion G Protein-Coupled Receptor G3 aGvHD Acute Graft-versus-Host Disease ALL Acute Lymphoblastic Leukemia AML Acute Myelogenous Leukemia AMP Adenosine Monophosphate AMPK Adenosine Monophosphate-activated Protein Kinase APC Antigen-presenting Cell AREG Amphiregulin ATG Anti-thymocyte Globulin ATP Adenosine Triphosphate AUC Area Under the Curve BAFF B Cell Activating Factor Breg Regulatory B cells xxiii BTK Bruton’s Tyrosine Kinase B3GAT1 3-beta-glucuronosyltransferase 1 cAMP Cyclic Adenosine Monophosphate CBMTG/CTTC Canadian Blood and Marrow Transplant Group/Cell Therapy Transplant Canada CBS Canadian Blood Services CCLX C-C Chemokine Ligand type X CCL4L2 Chemokine Ligand 4 Like 2 CCRX C-C Chemokine Receptor type X cKIT Proto-oncogene c-KIT cDNA Complementary DNA CDX Cluster of Differentiation X CD16/FcγRIII Fc Gamma Receptor III cGvHD Chronic Graft-versus-Host Disease CISH Cytokine-inducible SH2-containing protein CML Chronic Myelogenous Leukemia COL24A1 Collagen Type XXIV Alpha 1 Chain COTL1 Coactosin-like protein CO2 Carbon Dioxide xxiv CPD Cell Proliferation Dye CSF-1R Colony Stimulating Factor-1 Receptor CST7 Cystatin F CTLA-4 Cytotoxic T-lymphocyte-associated protein 4 CXCRX C-X-C Chemokine Receptor X CX3CR1 CX3C Chemokine Receptor 1 DAMP Damage-associated Molecular Pattern DMEM Dulbecco's Modified Eagle's Medium DNA Deoxyribonucleic Acid DNAM-1 DNAX Accessory Molecule 1 ECAR ExtraCellular Acidification Rate ECP Extracorporeal Photopheresis EGFR Epidermal Growth Factor Receptor EOMES Eomesodermin EPHA1 Ephrin type A receptor 1 ER Effect Ratio ERK Extracellular-signal-regulated Kinase ETS1 Erythroblast Transformation Specific transcription factor 1 xxv E4BP4 Nuclear factor IL-3 FACS Fluorescence-activated Cell Sorting FAO Fatty Acid Oxidation FasL Fas Ligand FBS Fetal Bovine Serum FCCP Carbonyl Cyanide-4 (trifluoromethoxy) Phenylhydrazone FCGR2X Fc Gamma Receptor 2X FCGR3X Fc Gamma Receptor 3X FDA Food and Drug Administration FGFBP2 Fibroblast Growth Factor Binding Protein 2 FSC-A Forwards Scatter – Area FSC-H Forward Scatter – Height FSC-W Forward Scatter – Width FOXP3 Forkhead box P3 F2RL1 F2R Like Trypsin Receptor 1 GAPDH Glyceraldehyde-3-Phosphate Dehydrogenase GATA3 GATA-binding protein 3 G-CSF Granulocyte Colony Stimulating Factor xxvi GLUTX Glucose Transporter X GM-CSF Granulocyte Macrophage-colony-stimulating factor GMP Good Manufacturing Practice GOLGA8F Golgin A8 Family Member F GPR183 G-protein Coupled Receptor 183 GUCY1A1 Guanylate Cyclase 1 Soluble Subunit Alpha 1 GvL Graft-versus-Leukemia GvT Graft-versus-Tumor GZMX Granzyme X HBV Hepatitis B HIF1α Hypoxia-inducible Factor 1-alpha HLA-X Human Leukocyte Antigen HSCT Hematopoietic Stem Cell Transplantation HSPC Hematopoietic Stem and Progenitor cells HSPE1-MOB4 Heat Shock Protein 1- MOB family member 4 ID2 Inhibitor of DNA binding 2 IFITX Interferon Induced transmembrane protein X IKZF3 Ikaros family Zinc Finger protein 3 xxvii IL Interleukin ILC Innate Lymphoid Cell IFIT2 Interferon Induced Transmembrane protein 2 IFNγ Interferon gamma IKZF3 Ikaros family Zinc Finger protein 3 IRF4 Interferon Regulatory Factor 4 ISM1 Isthmin 1 JAK1/2 Janus Kinase 1/2 JMML Juvenile Myelomonocytic Leukemia KIR Killer-cell Immunoglobulin-like Receptor KLF2 Krüppel-like Factor 2 KLRG1 Killer cell Lectin-like Receptor G1 KRT7 Keratin 7 LDHA Lactate Dehydrogenase A LEF1 Lymphoid Enhancer-binding Factor 1 LFA-1 Lymphocyte Function-associated Antigen 1 LGALS12 Galectin 12 LNCDAT LncRNA Divergent Activator Of TBXT xxviii LTB Lymphotoxin-beta MAPKK Mitogen-activated Protein Kinase Kinase MDS Myelodysplastic Syndrome MHC Major Histocompatibility Complex MKI67 Antigen Kiel 67 MSCs Mesenchymal Stem Cells MS4A1 Membrane Spanning 4-Domains A1 mTORC1 Mammalian Target of Rapamycin Complex 1 MUSTN1 Musculoskeletal Embryonic Nuclear Protein 1 Myc Myelocytomatosis MyD88 Myeloid Differentiation primary response 88 NFAT Nuclear Factor of Activated T Cell NF-kB Nuclear Factor Kappa B NIH National Institutes of Health NK Natural Killer NKG2X Natural Killer Group X NKp30 Natural cytotoxicity triggering receptor 3 NKp44 Natural cytotoxicity triggering receptor 2 xxix NKp46/CD335 Natural cytotoxicity triggering receptor 1 NKp80 Natural cytotoxicity triggering receptor NKreg Regulatory NK cells NS Not Significant OCAR Oxygen Consumption Rate OXPHOS Oxidative Phosphorylation PAC Pearson Average Correlation PAMP Pathogen-associated Molecular Pattern PBMC Peripheral Blood Mononuclear Cell PBS Phosphate-buffered Saline PDGFRB Platelet Derived Growth Factor Receptor Beta PDK1 Phosphoinositide-dependent Kinase 1 PD-L1 Programmed Death Ligand 1 PD-1 Programmed Death-1 PEDS1-UBE2V1 Plasmanylethanolamine Desaturase 1-Ubiquitin Conjugating Enzyme E2 V1 PGK1 Phosphoglycerate Kinase 1 PI3K Phosphoinositide 3-kinase PMAIP1 Phorbol-12-Myristate-13-Acetate-Induced Protein 1 xxx PRDM1 PR Domain zinc finger binding protein 1 PRF1 Perforin PSMB9 Proteasome subunit beta type-9 PTP Protein Tyrosine Phosphatase p21 Cyclin-dependent kinase inhibitor 1 RANK Receptor Activator of Nuclear factor Kappa-β RAP1GAP2 RAP1 GTPase activating protein 2 RNA Ribonucleic Acid ROC Receiver Operating Characteristic ROCK Rho-kinase ROR1 Receptor Tyrosine Kinase Like Orphan Receptor 1 RPS26 Ribosomal Protein S26 SAGSIN1 Salivary Gland Specific Protein SCID Severe Combined Immunodeficiency ScRNAseq Single-cell RNA sequencing SEM Standard Error of the Mean SHP2 Src Homology region 2-containing protein tyrosine Phosphatase 2 SOX18 SRY-Box Transcription Factor 18 xxxi SPON2 Spondin 2 SRGAP3 Slit-Robo GTPase Activating Protein 3 SSC-A Side Scatter – Area STAT3 Signal Transducer and Activator of Transcription 3 STAT5 Signal Transducer and Activator of Transcription 5 STMN1 Stathmin 1 S1PR1 Sphingosine-1-Phosphate Receptor 1 TBC1D3 TBC1 Domain Family Member 3D T-BET T box Transcription factor TBX21 TBXT T-Box Transcription Factor T TCF1 T Cell Factor 1 TCF7 Transcription Factor 7 TCR T Cell Receptor TGF-β1 Transforming Growth Factor beta 1 Th1/2/17 Thelper 1, 2, or 17 cells TJP1 Tight Junction Protein 1 TLR Toll-like Receptor TIGIT T cell Immunoreceptor with Immunoglobulin and Immunoreceptor Tyrosine-Based Inhibitory Motif Domains xxxii TIM3 T cell Immunoglobulin and Mucin domain-containing protein 3 TNFα Tumor Necrosis Factor alpha TNFβ Tumor Necrosis Factor beta TNFRSF6B TNF Receptor Superfamily Member 6b TRAIL Tumor necrosis factor-related Apoptosis Inducing Ligand Treg cells Regulatory T cells TSC22D3 TSC22 Domain Family Member 3 TUBA1B Tubulin alpha 1b UMAP Uniform Manifold Approximation Projection UMI Unique Molecular Identifier VEGF Vascular Endothelial Growth Factor XCL1 X-C motif chemokine Ligand 1 XIST X Inactive Specific Transcript ZEB1 Zinc finger E-box-Binding homeobox 1 2-DG 2-deoxy-glucose 7-AAD 7-amino-actinomycin D xxxiii Acknowledgements I am sincerely grateful to the faculty, staff, and fellow students at the University of British Columbia and in the department of Pathology and Laboratory Medicine who have provided abiding positivity, encouragement, support, and inspiration to pursue and complete a doctorate degree and continue my career in the fields of translational and clinical research and medicine. In particular, I would like to thank my supervisor Dr. K. Schultz for his strong support and motivation to consider research questions from differing perspectives, collaborate with others, and share my work through various avenues. I would also like to thank my supervisory committee, including Dr. B. Verchere, Dr. L. Sly, Dr. R. Klein Geltink, and Dr. K. Hay for their scientific expertise and contribution towards the improvement of my study designs and analysis, in addition to their moral support in pursuing my studies and a career in science and medicine. Further, I would like to thank the current Schultz lab members, including Dr. S. Abdossamadi, Dr. B. Ng, Dr. E. Ostroumov, Dr. T. Baker, Ms. F. Wuwu, Ms. D. Lau, and Ms. D.J. Zheng, in addition to the past Schultz lab members, including Ms. A. Suleimenova, Dr. A. Kariminia, Dr. S. AzadPour, Dr. V. Parthasarathy, Mr. B. Malong, and Mr. L. Johnston, for their persistent optimism and scientific and moral support throughout the completion of my doctoral degree. xxxiv I would also like to thank the funding sources which supported my research and studies, including a CIHR Foundation grant, CIHR Team grant, the Bjorknas Foundation, a Michael Cuccione Fellowship, a CIHR Canada Graduate Scholarship, the Vanier Canada Scholarship, and UBC Faculty of Medicine funding. A special thanks are owed to my family, including my husband Jacob Osborne, my parents Mark and Jannah Lauener, and sisters Paige, Hilary, and Victoria, all of whom have greatly supported me throughout my years of education, both morally and financially. I owe much of my success to them. xxxv Dedication I dedicate this achievement to my family, including my husband Jacob, parents Mark and Jannah, and sisters Paige, Hilary, and Victoria. My success can largely be attributed to their unwavering kindness, support, and encouragement in the pursuit of my dreams to work as a translational and clinical scientist in the field of medicine, improving the clinical care, treatments, and health services available to cancer and autoimmune patients and survivors. I would also like to dedicate this work to the physicians and scientists who came before me, working to also improve care and treatments in oncology, work which resulted in my health state to pursue a similar objective. 1 1 Chapter 1: Introduction 1.1 Hematopoietic stem cell transplantation Hematopoietic stem cell transplantation (HSCT) is the process in which a donor’s immune system (graft) is transplanted into a recipient (host).1 HSCT is a critical immune-based therapeutic option for patients with a non-malignant disease, such as immune deficiency/dysregulation and marrow dysfunction, acting to replace the hematopoietic system, or as cell-based immune therapy for patients with high-risk and refractory hematopoietic malignancies.2 In the case of HSCT being utilized as a cancer therapy, it is advantageous as it allows the application of higher doses of chemotherapy than conventionally used, to deplete the patient’s immune system, and induces an immune response, including inflammatory, innate, and adaptive immune components using a donor who has not been tolerized to the recipient’s malignancy.3 This confers a substantial graft-versus-tumor (GvT) or graft-versus-leukemia (GvL) effect, contributing to cancer eradication in patients.3 However, the HSCT may be followed by acute or chronic inflammation due to tissue self-antigen mismatches among the transplant donor and recipient resulting in acute graft-versus-host disease (aGvHD). GvHD is also associated with an increased risk of long-term debilitating health complications and death, in a chronic form of graft-versus-host-disease (cGvHD).4 2 1.2 Graft-versus-host disease Both aGvHD and cGvHD are a systemic disorder that may occur as a result of HSCT, in which the graft's immune cells recognize the host as foreign and attack the recipient’s body cells.5 GvHD is a clinical diagnosis that may be supported with appropriate biopsies (removal and analysis of tissue from the affected area), and is defined as acute or chronic based on the clinical presentation of disease and also the timing of presentation, typically using a cut-off of 100 days post-transplant.5 Classic aGvHD may present within 100 days of receiving the transplant, and in some cases progresses to cGvHD.5 Late aGvHD is defined as a patient presenting with aGvHD symptoms but after 100 days. The earliest that cGvHD may present is at 60 days of receiving the transplant, though is typically presented after 100 days. In Canada, based on the Canadian Blood and Marrow Transplant Group/Cell Therapy Transplant Canada (CBMTG/CTTC) registry with data gathered between 2008 and 2019, ~7000 HSCT survivors among ~13,000 transplant patients have been diagnosed with aGvHD or cGvHD. cGvHD has been estimated to occur in 25% of pediatric and 60% of adult HSCT survivors (defined by the time of transplant), and may contribute to metabolic syndrome, cardiovascular events, infection, and restricted mobility, in addition to stunted growth and joint deformities in growing children.6 Further, cGvHD is known to cause chronic, and often irreversible organ damage and has a mortality rate at least twice as high compared with HSCT patients that do not develop cGVHD.6 3 cGvHD is a multisystemic disorder that is typically described according to three phases of pathogenesis which may occur simultaneously. Phase 1 is characterized by tissue damage resulting in the translocation of bacteria and fungi through epithelial surfaces, leading to the release of pathogen-associated molecular patterns (PAMPs).7 Cell death due to chemotherapy or radiation leads to the release of damage-associated molecular patterns (DAMPs)), which result in activation of purinergic receptors, the interleukin (IL)-33 receptor, toll-like receptors (TLRs), nucleotide-binding oligomerization domain–like receptors, the high-mobility group box protein, and the NOD-like receptor protein 3 inflammasome.7 As a consequence, T cells are activated. Phase 2 is characterized by dysregulated adaptive responses by B cells and T cells, primed by antigen-presenting cells (APCs), which leads to their expansion and polarization toward cluster of differentiation 4+ (CD4+) helper T cells, which produce IL-17A, maintaining inflammation, and activated follicular helper T cells, which produce IL-21, leading to germinal-center formation.7 At the same time, there is a loss of thymic epithelial cells and regulatory cells.7 Phase 3 includes fibroblast activation with aberrant healing as mediated by platelet-derived growth factor α and transforming growth factor β (TGF-β).7 The production of isotype-switched immunoglobulin by differentiated B cells results in pathogenic immunoglobulin deposition in organs, contributing to the organ damage and fibrosis observed in cGvHD.7 Currently, the treatment of cGvHD utilizes immune suppressive therapies, such as corticosteroids, mammalian target of rapamycin (mTOR) inhibitors (sirolimus), 4 mycophenolate mofetil, and monoclonal antibodies (anti-thymocyte globulin, and rituximab) which act to both prevent and treat chronic organ rejection. US Food and Drug Administration (FDA) more recently approved and targeted cGvHD drugs include ibrutinib (Bruton’s tyrosine kinase (BTK) inhibitor), belumosudil (Rho-kinase (ROCK) inhibitor), and ruxolitinib (Janus kinase 1/2 (JAK1/2) inhibitor), which inhibit various cellular functions, such as that of B cells and T cells,8 and soon to be approved Axatilimab (CSF-1R inhibitor). Although these therapies have improved outcomes compared to those previously utilized for cGvHD patients, they generally induce only partial or variable responses.9,10 Further, drug and physician costs have been estimated as being at least twice as high for HSCT patients who develop cGvHD as compared to those who do not.11 Moreover, there is a lack of complete understanding of the complex heterogeneity and biology of cGvHD, as there have been few comprehensive studies in humans, and mouse models of cGvHD do not fully recapitulate the human disease.12 As a result, the clinical approach to cGvHD therapy continues to be one of applying drugs in a rotating manner to induce a partial response. Therefore, an improved understanding of cGvHD mechanisms and therapeutic responses are crucial to develop both biologically guided, and cost-effective therapies. 1.3 Natural killer cells and chronic graft-versus-host disease Various immune suppressive cell populations appear to associate with suppression of cGvHD, including Treg cells, Breg cells, M2 macrophages, peripheral dendritic cells, 5 and CD56bright NK cells.13 To date, strategies targeted to augment immune suppressive populations in cGvHD have focused on increasing the number and function of Treg cells. One approach was to adoptively transfer Treg cells which suppresses aGvHD and suppressed cGvHD in one patient.10,14 Two alternative approaches, Extracorporeal Photopheresis (ECP) and low-dose IL-2, have attempted to expand Treg cells to inhibit cGvHD.15 It has been determined that an early increase of CD56bright NK cells is a hallmark effect to ECP for treating cGvHD, and the higher CD56bright versus CD56dim ratio in this treatment setting was correlated to a complete response.16 Additionally, it is now well established that low dose IL-2 increases both the number of Treg cells and the number of CD56bright NK cells and it is suggested that the ratio of Treg cells to conventional T cells correlates to therapeutic outcomes in low-dose IL-2 therapy for cGvHD.17 While the association of Treg expansion and therapeutic outcome is considered the primary explanation, one group proposed an alternative mechanism where low‐dose IL‐2-induced expansion of human CD56bright NK cells results in a contact‐dependent cell cycle arrest of effector T cells through the NK receptors natural cytotoxicity triggering receptor 2 (NKp44) and natural cytotoxicity triggering receptor 1 (NKp46).18 It has also been demonstrated that low dose IL-2 as treatment of systemic lupus erythematosus successfully suppresses disease activity through both an increase in Treg cells and NK cells.19 Further, in contrast to T cells, NK cells do not require antigen priming and are human leukocyte antigen (HLA) agnostic, potentially making NK cells a more promising option for an off-the-shelf adoptive cellular transfer therapy for cGvHD.20-22 6 The proposed association between NK cells and cGvHD development is not a novel concept and has been studied over numerous years. However, it is important to note that these studies mainly focused on evaluating the ability of NK cells to ensure engraftment and induce a GvL effect after HSCT, as NK cells were considered potentially advantageous in this setting for their similar cytotoxic capacity to T cells, but lack of GvHD induction. Early studies which attempted to promote bone marrow engraftment in a major mismatch murine model investigated the potential of adoptively transferred NK cells purified from C.B-17 severe combined immunodeficiency (SCID) (H-2d) mice into lethally irradiated C57BL/6J (H-2b) mice together with non-T-cell depleted bone marrow cells from BALB/cJ (H-2d) mice with or without splenocytes.23 In mice not receiving splenocyte-derived T cells, transferred NK cells did not induce GvHD, though in mice receiving splenocytes, activated NK cells prevented the development of GvHD.23 This revealed that not only can NK cells be safely adoptively transferred without inducing GvHD but also that they can prevent T cell-mediated GvHD development.24 The results of this first study were confirmed by several other murine based studies.20,25-30 Following this work, multiple studies in humans also suggested that higher numbers of NK cells31-38 and NK cell alloreactivity20,39-42 reduce GvHD development. Other studies have shown that NK cells can modulate immune responses through cytokine production, though whether this mechanism plays a role in GvHD prevention by NK cells is unknown.24 One of the earliest studies showed that administration of anti-TGF-β monoclonal antibody significantly limited the NK cell 7 suppressive effect on GvHD.25 However, whether or not NK cells were the primary source of TGF-β and whether this cytokine was a partial or full contributor to the NK cell mechanism of GvHD suppression is still unclear.24 Treg cells are also known to produce TGF-β, which may be a contributing factor to this GvHD suppression. Nonetheless, these initial studies begin to suggest the role of a specific NK cell subpopulation involved in the suppression of GvHD, which functions to secrete cytokines and thus have regulatory effects. Though these previous studies strongly suggest a role for NK cells in the GvHD setting, the evaluation of the various subpopulations of NK cells and the specific roles they may have in immune tolerance have been minimally described. Our labs previous studies have shown to be consistent with other researchers’ findings regarding the correlation of NK cells and GvHD, though we have focused on differentiating these associations according to NK cell subset. Our research has demonstrated that HSCT patients with cGvHD and late aGvHD have increased CD56dimCD16+ cytolytic NK cells and a loss of CD56bright NK cells before the onset of cGvHD. Further, in a large adult cohort, we observed an increased number of CD56bright CD335+ C-X-C chemokine receptor 3+ (CXCR3+) NK cells in patients who did not develop cGvHD.43 In a separate phase 3 trial on adults comparing granulocyte colony stimulating factor (G-CSF) mobilized marrow compared to G-CSF-mobilized peripheral blood we identified that a decreased number of CD56bright NK cells in the donor product correlated with the development of cGvHD.44 In a third separate study in children (N = 302), we identified a decreased number of non-cytolytic (perforin-, 8 Granzyme B-) CD56bright NK cells present at 3 months post HSCT and before the onset of cGvHD (≥114 days) (14 days later than typical cGvHD characterization of ≥100 days), with no decrease in Treg cells.6 Further analysis demonstrated that at the onset of cGvHD a lack of this same NK cell population persisted in those who developed cGvHD, and the proportion of Treg cells at this time point was also decreased.45 A number of studies show that aGvHD is associated with reduced Treg cell frequency or numbers.46 Thus, the immunosuppressive properties of Treg cells are being utilized in clinical trials for GvHD prevention and treatment.46 Our work significantly and consistently suggests the immunoregulatory role of a non-cytolytic CD56bright regulatory NK (NKreg) cell population in the suppression of GvHD after HSCT in both adult and pediatric patients. These findings also point to the potential role of NKreg cells in modulating the function and proliferation of Treg cells and its association with GvHD suppression. 1.4 Natural killer cells in the biological context NK cells have also been identified as important meditators in other biological settings, particularly autoimmunity and the placenta. In some of these contexts, NK cell subset has been differentiated, though in others only the effects of total NK cells are described. 9 In terms of autoimmunity, genetic correlations between total NK cells and the risk of developing an autoimmune disorder are depicted. Specifically, defects or variations of the killer-cell immunoglobulin-like receptor (KIR)/HLA genotypes have shown to affect NK cell ability for target cell recognition and their following activation and self-tolerance.47 Further, there is evidence of NK cells, particularly CD56bright NKreg cells, being enriched in tolerant organs, such as the liver, lungs, uterine and intestine.48 The decreased NK cell frequency and impaired NK cell effector function observed in the context of multiple autoimmune diseases suggests a protective role of NK cells in controlling autoimmunity. Some of this data links this outcome to NKreg cell’s ability to limit proliferation and activation of auto-reactive T cells, as well as the activation of macrophages and dendritic cells.49 In the case of multiple sclerosis, CD56bright NK cells can demonstrate a regulatory effect through inducing caspase-independent apoptosis of activated T cells in a Granzyme K-dependent manner, with anti-CD25 treatment significantly enhancing this effect by expanding the CD56bright NK cells.50 NK cells have also demonstrated a role in diabetes. In a murine model, one study showed that with use of non-obese diabetic mice, administration of complete Freund's adjuvant (which acts to enhance immune response to antigens) induced the trafficking and activation of NK cells, which led to the suppression of β cell-specific T cell activation, preventing diabetes.49 Additionally, in a hepatitis model, it has been shown that poly I:C-activated NK cells exhibit a protective role in Con A-induced hepatitis by suppressing T or NKT cell activation, promoting NKT and T cell apoptosis, and decreasing inflammatory cytokine production.51 Further, defects in NK cell number, maturation, and/or functional activation have been 10 observed in rheumatoid arthritis, systemic lupus erythematosus, psoriasis, Graves' disease, and other autoimmune diseases.52,53 Decidual NK cells are another CD56bright NK cell population which share phenotypic and functional characteristics with CD56bright peripheral NKreg cells, including immunoregulation. Decidual NK cells result in a well-balanced microenvironment to enable proper development and functioning of the placenta, and preclude excessive trophoblast invasion, with the uterus exhibiting the highest frequency of CD56bright NK cells as compared to peripheral organs.54 After ovulation, the surge of IL-15 and prolactin induces a rapid proliferation and differentiation of uterine NK cells.55 This proliferation will increase further when implantation is successful and this is maintained throughout the second trimester, though decidual NK cell numbers decline from mid-gestation onward.54 Decidual NK cells are poorly cytotoxic,56 are mainly CD56brightCD16−KIR+, and are similar but distinct from the CD56brightCD16- NKreg cells found in peripheral blood, which are also poorly cytotoxic but lack KIR expression.54 Additionally, decidual NK cells express most of the peripheral NK cell receptors including NKp46, natural cytotoxicity triggering receptor (NKp80), natural killer group 2D (NKG2D), and CD94/NKG2A.54 Further, several chemokine receptors including CXCR3, CXCR4, C-C chemokine receptor type 1 (CCR1), and CCR9, similar to peripheral NKreg cells, are expressed by decidual NK cells.57-59 According to transcriptome and secretome profiling, activated decidual NK cells produce a large array of cytokines including interferon-gamma (IFNγ), tumor necrosis factor-alpha (TNFα), granulocyte macrophage-colony-stimulating factor 11 (GM-CSF), TGF-β, and IL-10, similar to peripheral NKreg cells.59,60 Regarding cytotoxic function, though decidual NK cells express functional activating receptors, granzymes, granulysin, and perforin (unlike peripheral NKreg cells), they lack cytolytic activity in healthy pregnancies.56,57,61,62 1.5 Human natural killer cells NK cells are a group of innate lymphocytes which are typically distinguished based on their cell surface expression of the markers CD56 and CD16, along with a lack of CD3 expression and expression of the T cell or B cell receptors.63 In humans, NK cells may be phenotypically differentiated into five subgroups, including CD56brightCD16-, CD56brightCD16dim, CD56dimCD16-, CD56dimCD16+, and CD56-CD16bright NK cells.64-66 However, NK cells are usually described as two major subsets which are distinguishable in terms of both phenotype and function. This includes what is commonly referred to as the immature subset of CD56brightCD16- NK cells, and the mature subset of CD56dimCD16+ NK cells.64 These subpopulations of NK cells may also be referred to as the regulatory and cytotoxic subsets, respectively. CD56dimCD16+ NK cells are fully mature, account for approximately 90-95% of the NK cells in peripheral blood, and predominantly function as a cytolytic cell subset.63 The CD56dimCD16+ NK cells engage in cytotoxicity through four major known pathways, including the perforin/granzyme pathway, tumor necrosis factor-related apoptosis inducing ligand (TRAIL) or Fas ligand (FasL) pathway, cytokine pathway, 12 and antibody dependent cell mediated cytotoxicity (ADCC). The perforin/granzyme pathway involves the use of granzymes (e.g. Granzyme A and B) along with the pore forming protein perforin.67 Perforin forms a transmembrane channel on the target cell membrane, resulting in increased permeability and osmotic lysis and ultimately apoptosis of the target cell, as the perforation channel facilitates the entry of granzyme into the target cell.68 The second pathway involves the induction of death receptor-mediated apoptosis by expressing the TRAIL and/or FasL to engage TRAIL-R1/-R2 or CD95/Fas, respectively, on the surface of diseased cells, including virus/bacteria-infected cells, and malignant cells.69 When TRAIL or FasL binds to TRAIL-R1/R2 or Fas, TRAIL-R1/R2 or Fas can deliver a signal to the target cell, resulting in apoptosis within a few hours.70,71 The cytokine pathway for causing death of target cells occurs through the release of cytokines, such as TNFα, which alters the stability of lysosomes leading to leakage of hydrolases which may activate the target cell endonuclease to degrade genomic deoxyribonucleic acid (DNA).67 NK cells are potent ADCC effector cells through cell surface expression of CD16/FcγRIII which may recognize antibodies on the surface of target cells for cytolytic effect.72,73 CD56brightCD16- NK cells are considered an immature NK cell subset which make up approximately 5-10% of the NK cells in peripheral blood, and are predominant in tissues and secondary lymphoid organs.63 CD56bright NK cells express high levels of CD56, CD94/NKG2A, CD62L, and a high-affinity IL-2 receptor, but little to no CD16 and KIR.63 In contrast to the CD56dim NK cells, CD56bright NK cells have been described to function primarily through secretion of cytokines, such as IFNγ, TNFα, 13 and GM-CSF which are known to have immunomodulatory and regulatory effects.63 The CD56bright NK cells were first considered immunoregulatory due to their increased production of cytokines and reduced cytotoxicity compared to CD56dim NK cells.64 NK cells are inhibited or activated to engage in their cytolytic or regulatory functions through the upregulation or downregulation of inhibitory and activating signals. NK cells are inhibited through recognition of the HLA-I molecules on autologous normal cells by KIRs,74,75 the leukocyte immunoglobulin-like receptor,76 and/or the CD94-NKG2A heterodimer (most relevant to CD56bright NK cells).77 NK cells are able to recognize foreign particles, virus or bacteria-infected cells, and malignant cells as these targets typically have little to no surface expression of HLA-I molecules, and thus the NK cells fail to be inhibited and are able to activate and kill the invaders through the various cytolytic pathways.78 In the case of HLA-I expression on foreign particles, virus or bacteria-infected cells, or malignant cells, NK cells may still kill the invaders through an upregulation of activating receptors.78 1.6 Human natural killer cell lineage and development Regulatory and cytolytic NK cells can be further understood according to their differentiation and lineage development. Transcriptional regulation of NK cell development is initially dependent on the transcription factor nuclear factor IL-3 (E4BP4), which is required for commitment to the NK cell progenitor lineage from 14 the common lymphoid progenitors.79 T cell factor 1 (TCF1) and erythroblast transformation specific transcription factor 1 (ETS1) are required for differentiation of NK cell progenitors to immature CD56brightCD16- NK cells (NKreg).79 Further, a host of transcription factors are crucial in NKreg cell maturation to classic cytolytic NK cells, including signal transducer and activator of transcription 5 (STAT5), inhibitor of DNA binding 2 (ID2), T box transcription factor TBX21 (T-BET), eomesodermin (EOMES), PR domain zinc finger binding protein 1 (PRDM1), GATA-binding protein 3 (GATA3), and others.79 The CD56bright NK cells, which have a regulatory and cytokine producing role, may be more comprehensively recognized at the phenotypic level as a CD34-CD117lowCD94+CD16- population. Further, it has been identified that there are two different stages of NKreg cell development which differ according to NKp80 expression.80,81 The NKp80- NK cells lack cytolytic ability, and have high expression of NKG2D, natural cytotoxicity triggering receptor 3 (NKp30), NKp46, CD94/NKG2A, and CD161. In contrast, the NKp80+ NK cells produce high levels of IFNγ and facilitate perforin-dependent cytotoxicity.82 CD56bright NK cells will begin to gradually mature at a rate dependent on the environment (e.g. maturation is promoted in conditions with IL-2 and IL-15)83 and gain expression of CD16, KIR, and cytotoxic granules, such as Granzyme B, resulting in the cytolytic CD56bright subset which is commonly investigated for its role in anti-tumorogenicty.84,85 The final maturation of human NK cells involves the loss of CD117, CD127, and CD94/NKG2A receptor expression, along with a gain of CD94/NKG2C and down-15 regulation of CD56.86,87 This results in the CD56dimCD16+ subset which makes up the majority of NK cells in human peripheral blood. However, the loss and acquisition of these cell surface markers do not necessarily occur in a fixed order, making it difficult to determine the exact intermediate stages of NK cell differentiation.86,88-91 Further, although this proposed process of lineage development is the most widely accepted model, there are studies which have suggested that the CD56dim and CD56bright NK cells originate from two separate lineages, though this evidence is limited and has mainly been demonstrated in murine NK cells.92-96 1.7 Phenotypic characteristics of human regulatory natural killer cells CD56bright NKreg cells have been characterized according to their strong phenotypic expression of CD127, CD62L, CXCR3, CD25, CD94/NKG2, proto-oncogene c-KIT (c-KIT), CCR5, CCR7, and CXCR4.63 Additionally, the phenotype of NK cell subsets can also be distinguished based on cell-surface activating and inhibitory receptors. NK cells do not express antigen-specific recognition receptors, but instead express various activating and inhibitory receptors modulating their function, which may differ depending on the NK cell subset.68 Examples of NK cell activating receptors include NKp46, NKp30, NKp44, and CD16, all of which are expressed by both cytolytic and regulatory NK cells, excluding CD16.68 Examples of NK cell inhibitory receptors include T cell immunoglobulin and mucin domain-containing protein 3 (TIM3), T cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domains (TIGIT), CD161, and CD96 which may be expressed 16 by both regulatory and cytolytic NK cells.68 NK cells also express receptors which may engage in both an inhibitory and activating role, such as NKG2, expressed by both regulatory and cytolytic NK cells, and KIR which is exclusively expressed by cytolytic NK cells.68 Lastly, there are cytokine receptors which are of particular high expression on the NKreg subset, such as the IL-2R, IL-4R, IL-10R, and IL-18R.68 A comprehensive phenotyping of human peripheral blood NK cell surface receptors was published by Del Zotto et al in 2020.97 Further, single-cell RNA-seq data has shown the CD56bright NK cell subset of healthy blood donors to express G-protein coupled receptor 183 (GPR183), CD127, Lymphotoxin-beta (LTB), Granzyme K, CD62L, CCR7, CD2 and NKG2A.98 1.8 Metabolism of human regulatory natural killer cells The investigation of NK cell metabolomics is a recent area of study, with the majority of research having been performed in murine type models. Of the human NK cell metabolism studies, most have investigated the total NK cell population, as opposed to their subsets. Thus far, it has been determined that NK cells use both glycolysis and oxidative phosphorylation (OXPHOS) to fuel various processes, including proliferation.99 These pathways have shown to be strongly upregulated when NK cells are stimulated with use of the cytokines IL-2, IL-12, IL-15, and/or IL-18.100-102 Similar to T cell subsets, which have clearly shown differences in their cellular metabolism,103 NK cell subsets are expected to differ in their metabolic configurations and processes. When stimulated with cytokines, CD56bright NK cells 17 appear more responsive to metabolic change and upregulate several metabolic markers, such as glucose transporters and nutrient receptors more strongly than the cytolytic CD56dim NK cells.100 It has also been suggested that glycolysis may support synthesis of effector molecules associated with the increased cytotoxic function of NK cells,104 and that TGF-β may be a candidate to inhibit NK cell metabolism through blocking of nutrient transporter expression, OXPHOS, and glycolysis.105,106 Comparatively, TGF-β signals have been shown to be crucial in safe-guarding specific Treg cell functions, including immunosuppression and the maintenance of immune tolerance.107 Recent data has shown that mTORC1, a multiprotein serine threonine kinase complex that functions as a nutrient/energy/redox sensor and controls protein synthesis,99-102,105 is a key regulator of NK cell metabolism. Rapamycin, a selective inhibitor of mTORC1, can block changes in NK cell metabolism which associate with effector cell function, including cytotoxicity, and this has been demonstrated in both the in vivo and in vitro settings.108 This may suggest that the CD56bright NK cell activation and differentiation towards the CD56dim mature, and cytolytic NK cell population may be driven by a mTORC1-regulated pathway. This is similar to Treg cells, of which differentiation is also dependant on an mTOR-regulated pathway which can be prevented with use of rapamycin.109 However, it is important to note that at this time there is very little known about the unique metabolic pathways of NKreg cells, and the above are suggestions based on known NK cell and Treg cell metabolism. 18 1.9 Functional characteristics of regulatory natural killer cells 1.9.1 Suppression of T cell proliferation Activation of the CD56dim NK cell subset attributes to increased cytotoxicity. However, the function of the activated CD56bright NK cells have been shown to differ from the classic subset as they have shown to function in the homeostasis and modulation of adaptive immune populations, including T cells. For example, IFNγ secreted by CD56bright NK cells in response to T cell-derived IL-2 has been demonstrated to stimulate T cells in lymph nodes.110 Although T cells express the high-affinity form of the IL-2 receptor CD25, CD56bright NK cells express both high-affinity and intermediate-affinity forms of the IL-2 receptor.111,112 This has been suggested to activate the NK cells, and result in the control of T cell activation and proliferation through multiple proposed mechanisms.113 One mechanism may occur through direct killing,114,115 involving the release of the cytotoxic Granzyme K.50 Further, IL-27-stimulated CD56bright NK cells have been shown to suppress the proliferation of autologous CD4+ T cells in a contact-dependent manner associated with increased perforin content.116 Additionally, CD56bright NK cells stimulated with IL-12 and IL-15 have shown to prevent autologous CD4+ T cell proliferation through a cytotoxic mechanism involving the engagement of the natural cytotoxicity receptors NKp30 and NKp4680 and the release of Granzyme B.117 The cytolytic expression observed in these studies can likely be attributed to the partial maturation of the CD56bright subset due to the stimulation with IL-27, IL-12, and/or IL-15, cytokines 19 known to mature NK cells.83 Further, while these studies describe the effects of CD56bright NK cells on T cells undergoing activation, other studies have reported direct cytotoxicity of CD56bright NK cells on previously activated T cells.113 Nielsen and coauthors demonstrated that killing of pre-activated T cells by CD56bright NK cells involves the activating receptors NKG2D, lymphocyte function-associated antigen 1 (LFA-1), and TRAIL and is enhanced when blocking NKG2A.118 Another study demonstrated that both CD56bright and CD56dim NK cells kill autologous antigen-activated CD4+ T cells through engagement of DNAX accessory molecule 1 (DNAM-1) and CD244 and their receptors CD155 and CD48, respectively.115 These studies reveal that different stimuli activate NK cells toward maturation, cytotoxicity and/or suppression of T cell proliferation, and that differing NK cell subsets throughout their maturation process may be involved in these mechanisms.113 Investigations into the specific suppressive mechanism of the CD56bright NK cell subset which is also CD16- (non-cytolytic, NKreg cells) have demonstrated that low-dose IL-2 (induces maturation of NK cells) expands CD56brightCD16- NKreg cells resulting in a contact-dependent cell cycle arrest of effector T cells via retention of the kinase-dependent cell cycle inhibitor p21.18 This same group has also shown that blocking of the NK receptors NKp44 and NKp46 but not NKp30 abrogates the regulation of proliferation associated with low-dose IL-2.18 Further, the increase in NK cells was also accompanied by an increase in Treg cells, which was dependent on the presence of CD56bright NK cells, highlighting the functional importance of NKreg cells and their modulation of other regulatory cell subsets in the immune suppressive 20 setting.18 Additional studies have shown that the CD56brightCD16- NKreg cells can limit antigen specific T cell proliferation in vitro through an IL-10 dependent pathway.119 Other researchers have also proposed regulatory roles for NK cells, either by production of IL-10 or by counter-balancing the ongoing inflammation.120-122 Further, IL-15 stimulated CD56brightCD16- NKreg cells were shown to inhibit proliferation of autologous CD4+ T cells by secreting the immunosuppressive molecule adenosine113 (also produced by other immune cell types, such as B cells, and associated with suppression of immune cell proliferation).123,124 It was demonstrated that inhibition of CD38, an enzyme involved in the production of adenosine, restored proliferation of T cells in the presence of CD56bright NK cells.125 It is important to note that the investigation into the suppressive mechanism of CD56bright NKreg cells has only occurred within the last few years and much work is required to clearly differentiate the pathways which result in the NKreg cell immunosuppressive function and how this is affected by different stimulatory conditions. However, the research into the mechanism of Treg cell suppression has been investigated for far longer with a greater output of data, which may be useful to the discovery of NKreg cell suppressive pathways. There are many similarities which can be drawn between these two regulatory subsets, and likely much can be learned about NKreg cell suppression through reviewing what has been demonstrated regarding Treg cell suppression. Though the mechanism of Treg cell suppression has not been clearly elucidated, there is evidence pointing to a number of factors. One group has shown that similar to some studies regarding NKreg cell suppression, 21 adenosine may facilitate Treg cell generation and also suppressive function.126 Further, evidence has shown that glycolysis promotes human Treg cell growth and migration at the cost of its immune suppressive function,127 which may also be related to NKreg cells, of which glycolysis may be associated with maturation and gain of cytolytic function. Further, the function of Treg cells has been observed to be mainly cell-cell contact-dependent,128 though the secretion of soluble factors such as IL-10 and TGF-β have also been shown to be crucial for Treg cell function.129 Comparatively, as discussed earlier, NKreg cells have also been suggested to engage in their suppressive function through cell-cell contact or use of soluble factors, including IL-10 and TGF-β. Thus, like Treg cells, NKreg cells may engage in various suppressive mechanisms depending on the disease setting or stimulatory environment, and there are potentially different NKreg cell subpopulations that result in immune suppression. 1.9.2 Cytokine production CD56bright NK cells express receptors for cytokines such as IL-12, IL-15, and IL-1895,130,131 which are produced by activated APCs. These cytokines can trigger proliferation of CD56bright NK cells and their production of molecules such as IFNγ, IL-10, IL-13, tumor necrosis factor beta (TNFβ), and GM-CSF.132 Thus, APCs can modulate NK cell function and phenotype.133-135 Further, it is also proposed that infections may modulate the function of CD56bright NK cells indirectly through APCs, as it has been shown that co-culturing CD56bright NK cells with APCs activated via 22 TLR4 (macrophages, dendritic cells) or TLR9 (plasmacytoid dendritic cells) stimulate CD56bright NK cell proliferation and cytokine production.87,132,136,137 1.10 Project hypothesis, objective, and aims Based on data describing the correlation between CD56bright NK cells and cGvHD, I hypothesized that NKreg cells suppress cGvHD through inflammatory cell inhibition, and that these cells can be distinguished as a unique NK cell subset which may be optimally expanded for the cellular therapy of cGvHD. My main objective was to identify, isolate, characterize, and expand the CD56bright, non-cytolytic NK cell subset associated with a lack of cGvHD. To meet this objective, I first determined the genes of CD56bright NK cells which are associated with cGvHD suppression after HSCT. Based on the transcriptome results and our previous phenotypic studies,6 I determined the optimal cell surface markers to purify the NKreg cell population. I then completed a more detailed transcriptomic characterization of HSCT patient samples, including groups of patients which either developed or failed to develop cGvHD, to identify the unique NK cell subpopulations associated with cGvHD development or suppression, and the potential cell differentiation pathways. Second, I evaluated the in vitro suppressive effect and mechanism of NKreg cells on cGvHD immune populations, including CD4+ T cells (naïve and memory cells and Thelper 1, 2, or 17 (Th1/2/17 subsets)), CD8+ T cells, Treg cells +/- dendritic cells, B cells, and NK cells. Third, I optimized the in vitro expansion of NKreg cells, defined the NKreg cell subset 23 according to proteome and metabolome, and verified the maintenance of the cell’s regulatory phenotype, transcriptome, and suppressive function after expansion. 24 2 Chapter 2: NKreg cells associated with cGvHD suppression may be characterized as a transcriptionally and phenotypically unique NK cell population 2.1 Introduction To date, strategies targeted to augment immune suppressive populations in cGvHD have focused on increasing the number and function of Treg cells. Two approaches, low dose IL-2 and ECP, have been used to expand Treg cells to inhibit cGvHD.15 While the association of Treg expansion and therapeutic outcome is considered the primary explanation for GvHD suppression, an alternative mechanism was identified as cGvHD inhibition being mediated by a CD56bright NK cell contact‐dependent cell cycle arrest of effector T cells through the NK receptors NKp44 and NKp46.18 Further, low dose IL-2 as treatment of systemic lupus erythematosus has shown to successfully suppress disease activity through both an increase in Treg cells and NK cells.19 Similarly, recent evidence supports that ECP therapy suppresses cGvHD primarily through increased CD56bright NK cells.16 Though these studies have clearly described a potential role of CD56bright NK cells in modulating cGvHD, minimal research has focused on better characterizing this population, and investigating its potential functional use in a clinical context. Thus, I hypothesized that there is a subset of CD56bright NK cells, which suppress the development of cGvHD, and are functionally consistent with described regulatory NK cells (NKreg),138,139 and proposed to better characterize the CD56bright NK cell subset associated with a lack of cGvHD. To meet my objective, I first identified the NKreg 25 subpopulation most significantly associated with immune tolerance in a large HSCT patient cohort. Second, in a smaller HSCT patient cohort, I determined the genes of CD56bright NK cells as compared to CD56dim NK cells which are associated with cGvHD suppression, utilizing nanoString technology. Third, based on the previous transcriptome results, I determined the optimal cell surface markers to isolate the NKreg cell subpopulation while also defining the phenotype of NK cells. Lastly, I completed a more detailed transcriptomic characterization of HSCT patient samples, including groups of patients which either developed or failed to develop cGvHD, to identify the unique NK cell subpopulations associated with cGvHD development or suppression, and potential cell differentiation pathways in the two patient groups. The immunophenotypic evaluation of a large pediatric population identified the CD56bright NK population associated with a lack of cGvHD to be perforin-, Granzyme B-, and CD335+. The initial nanoString transcriptome analysis of a small patient cohort of CD56bright compared to CD56dim NK cells identified the NKreg cells to also overexpress Granzyme K, IL-7R, GPR183, RANK, GM-CSFR, TCF7, and IL23A. Further analysis of this CD56bright NKreg population identified a subpopulation that overexpressed IRF1, and TNF. I also identified that viable NKreg cells may be isolated by sorting on CD56+ and CD16- NK cells. In the detailed transcriptomic characterization, I identified 7 transcriptionally unique NK cell populations, of which 1 or potentially 2 of these populations associate with cGvHD suppression in HSCT patients and can be characterized according to a unique phenotype and transcriptome. Further, I identified unique differentiation pathways of the NKreg cell populations, of which in patients with 26 cGvHD, CD56bright NKreg cells differentiate to CD56dim cytolytic NK cells, and the opposite effect is seen in patients without cGvHD. These findings provide further supportive data in that NKreg cells associate with a lack of cGvHD, offer a sorting approach for viable NKreg cells for use in functional analysis, and deduce further information regarding the potential function of the cells and signalling pathways which may be crucial to inhibit or promote to harness NKreg cell function, and prevent cGvHD. 2.2 Methods 2.2.1 Immune cell populations in HSCT patients associated with cGvHD HSCT patient peripheral blood mononuclear cells (PBMC) were utilized from a multi-centre pediatric cohort (Applied Biomarkers in Late Effects (ABLE)/PBMTC 1202 trial) (previously described7,140,141) (table 1) for the identification of immune cell populations associated with cGvHD. Twenty-seven pediatric transplant centers enrolled 302 patients. Patients were placed into 5 cohorts [no late aGvHD and no cGvHD (n = 132), late aGvHD (n = 30), cGvHD (including overlap syndrome; n = 41), active aGvHD day +100 to 114 (n = 28), or active cGvHD before day +114 (n = 10)]. 27 For performing the statistical analysis, we were interested in whether CD56bright and CD56dim NK cells show differential expression for each group (cGvHD, aGvHD, and controls) as well as whether each of these cell subtypes show differential expression between controls and GvHD subjects. To test for differential expression between CD56bright and CD56dim NK cells of each gene, we applied a paired t-test on samples from each group. To test for group differences of each gene, we applied a Student’s t-test on samples from each cell subtype. The expression value of each gene was normalized by dividing its value by the l2-norm of expression values of house-keeping genes (phosphoglycerate kinase 1 (PGK1) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH)) prior to analysis. For the cell subtype contrast, we declared a gene as relevant if its p-value is <0.05 and its effect ratio is >5 or <0.2, where effect ratio was defined as the mean expression of CD56bright over the mean expression of CD56dim NK cells for each group. For the group contrast, we declared a gene as relevant if its p-value is <0.05 and its effect ratio is >2 or <0.5, where effect ratio was defined as the mean expression of controls over the mean expression of GvHD subjects for each cell subtype. We further estimated the Pearson’s correlation between CD56bright perforin- NK cells and 74 cellular markers using measurements of all subjects collected at 3-, 6-, and 12-months post HSCT. Confounding factors including graft type (peripheral blood stem cells, bone marrow, or cord), donor source (sibling or unrelated), HLA mismatch, sex (donor and recipient), ABO mismatch, reduced intensity conditioning or Myeloablative conditioning, serotherapy (including anti-thymocyte globulin - ATG and alemtuzumab), recipient age, the use of total body irradiation, and number of days post HSCT to sample collection, as 28 well as binary variables encoding groups 1 to 6 were regressed out from the marker values prior to estimating Pearson’s correlation. To combine correlation values across the three time points, we simply took the average. To combine p-values across the three time points, we performed aggregated Cauchy association test. Significant correlation was declared at an α of 0.05 with Bonferroni correction (a multiple-comparison correction used when several dependent or independent statistical tests are being performed simultaneously, and the alpha value needs to be lowered to account for the number of comparisons). 29 Table 1. HSCT patient baseline characteristics. ALL, Acute Lymphoblastic Leukemia; AML, Acute Myelogenous Leukemia; HLA, Human Leukocyte Antigen; MDS, Myelodysplastic Syndrome; NIH, National Institutes of Health. Characteristic Chronic GVHD Group (N=44) Control Group (N=190) Age at HCT, years (median) (range) 12.0 (2.0 – 18) 8.9 (0.2 – 18.1) Sex Male Female 28 (64%) 16 (36%) 101 (53%) 89 (47%) Indication for Transplant Malignant (n=161, 69%) ALL MDS/AML Other Non-Malignant (n=73, 31%) Inherited Marrow Failure Primary Immune Deficiency Severe Aplastic Anemia Sickle Cell Anemia Thalassemia Metabolic N=35 (80%) 14 14 7 N=9 (20%) 2 1 2 3 0 1 N=126 (66%) 56 57 13 N=64 (34%) 8 15 13 16 5 7 Graft Source Bone Marrow Peripheral Blood Stem Cells Umbilical Cord 22 (50%) 16 (36%) 6 (14%) 126 (66%) 32 (17%) 32 (17%) Type of Donor / HLA Match Matched Sibling Matched-Related Non-Sibling Matched Unrelated Mismatched Unrelated Haploidentical Family Member 8 (18%) 0 (0%) 19 (43%) 16 (36%) 1 (2%) 66 (35%) 6 (3%) 80 (42%) 34 (18%) 4 (2%) Conditioning Regimen Myeloablative Reduced Intensity 39 (89%) 5 (11%) 164 (86%) 26 (14%) 30 Chronic GVHD Group Control Group Serotherapy Anti-Thymocyte Globulin Alemtuzumab None 19 (43%) 2 (5%) 23 (52%) 83 (44%) 24 (12%) 83 (44%) Acute GVHD in First Year After Transplant None Classical Acute GVHD Only Before Day 100 Late Acute GVHD After Day 100 N/A N/A N/A 87 (46%) 45 (24%) 58 (30%) Maximal Grade Classical Acute GVHD (n=45) Grade 1 Grade 2 Grade 3 Grade 4 N/A N/A N/A N/A 19 (42%) 17 (38%) 7 (16%) 2 (4%) Type of Late Acute GVHD (n=58) De Novo (no previous classical acute) Recurrent (previous classical acute that resolved then returned as late acute GVHD) Progressive (classical acute GVHD that progressed after day 100 into late acute GVHD) N/A N/A N/A 12 (21%) 18 (31%) 28 (48%) Type of Chronic GVHD (N=44) De Novo (no previous history of any GVHD before onset of chronic GVHD) Quiescent (history of previous acute GVHD that resolved and later developed chronic GVHD) Progressive (history of classical acute or late acute GVHD that developed into chronic GVHD, including all cases of overlap syndrome) 7 (16%) 19 (43%) 18 (41%) N/A N/A N/A Maximal NIH Severity of Chronic GVHD in First Year Post Transplant (n=44) Mild Moderate Severe 10 (23%) 16 (36%) 18 (41%) N/A N/A N/A 31 2.2.2 NanoString study sample collection, cell sorting, RNA extraction, and analysis Select day 100 HSCT archived patient PBMC samples from three separate cohorts [cGvHD (N = 4), late aGvHD ≥114 days after HSCT (N = 4), or no late aGvHD or cGvHD (N = 4)] were utilized from a well characterized multi-centre pediatric cohort (Applied Biomarkers in Late Effects (ABLE)/PBMTC 1202 trial) as previously described (table 1).7,140,141 Patient samples were selected from this cohort based on the number of cells (samples with the highest cell number were selected). PBMC were isolated within 24 hrs after blood collection in DB Sodium Heparin tubes by Lymphoprep (StemCell Technologies, Vancouver, BC, Canada) density gradient centrifugation and cryopreserved in the vapor phase of liquid nitrogen. To differentiate NK cell subpopulations, PBMC samples were stained by CD45-PB, CD3-PE, CD19-PE, CD14-PE, CD66-PE, CD235-PE, CD56-APC, and CD16-FITC (BioLegend, San Diego, CA, USA) conjugated antibodies for 30min at 4°C in the dark. After two washes with 2% FBS PBS (Gibco, Grand Island, NY, USA) 7-AAD was added (BioLegend, San Diego, CA, USA), and samples were sorted using fluorescence-activated cell sorting (FACS) Aria IIu (BD Biosciences). Dead cells, monocytes, and T and B lymphocytes were gated out, and NK cell subpopulations were sorted based on the differential CD56 and CD16 expression. 32 Total RNA was extracted from NK cell subpopulations using the RNeasy Mini Kit according to manufactures procedures (QIAGEN, Valencia, CA, USA). We determined the quantity of RNA samples by using a NanoDrop 1000 Spectrophotometer. The quality and quantity of RNA samples were tested using the Agilent 2100 Bioanalyzer system at the Centre of Molecular Medicine and Therapeutics core facility at the University of British Columbia (Vancouver, BC, Canada). The average RNA Integrity Numbers were 9.4 +/- 0.7 and 9.1 +/- out of 10 for the CD56dim and CD56bright subpopulations, respectively. To determine gene expression analysis in CD56bright compared to CD56dim NK Cells, the nCounter Immunology Panel was used. NanoString data was obtained utilizing the automated Prep Station followed by data collection on a nCounter FLEX Digital Analyzer. The resulting data was analyzed by the nSolver 4.0 Analysis Software System (nanoString, Seattle). For performing the statistical analysis, we were interested in whether CD56bright and CD56dim NK cells show differential expression for each group (cGvHD, aGvHD, and controls) as well as whether each of these cell subtypes show differential expression between controls and GvHD subjects. To test for differential expression between CD56bright and CD56dim NK cells of each gene, we applied a paired t-test on samples from each group. To test for group differences of each gene, we applied a Student t-test on samples from each cell subtype. The expression value of each gene was normalized by 33 dividing its value by the l2-norm of expression values of house-keeping genes (PGK1 and GAPDH) prior to analysis. For the cell subtype contrast, we declared a gene as relevant if its p-value is <0.05 and its effect ratio is >5 or <0.2, where effect ratio was defined as the mean expression of CD56bright over the mean expression of CD56dim for each group. For the group contrast, we declared a gene as relevant if its p-value is <0.05 and its effect ratio is >2 or <0.5, where effect ratio was defined as the mean expression of controls over the mean expression of GvHD subjects for each cell subtype. Given the low number of samples, we opted to use a nominal p-value threshold of <0.05 to get a more encompassing view of the differential expression patterns. Since numerous tests were conducted, the probability of a Type I error likely exceeded 0.05 but would be moderated by the additional effect ratio criteria. 2.2.3 Characterization of CD56bright NK cells according to phenotype Peripheral whole blood samples were collected into BD Vacutainer Sodium Heparin tubes (Becton, Dickinson, Franklin Lake, NJ, USA) from consenting healthy donors (Human Ethics ID’s H16-00533 and H18-00022). Blood samples were processed within 24 hrs of collection. From blood samples, PBMC were isolated by Ficoll Hypaque (StemCell Technologies, Vancouver, BC, Canada) density gradient centrifugation. PBMCs were stained for protein expression identification of NK cells using: [CD56-PE, CXCR3-FITC, Perforin-BV785 (Miltenyi Biotec, Auburn, CA, USA)], [CD16-APC Fire 750, Granzyme K-AF647, GPR183-BV421, KIR/CD158-APC (KIR2DL2, 2DL3, 2DS2, and 2DS4), CD25-PE, NKp44(CD336)-APC, NKp46(CD335)-BV421, CD116(GM-34 CSFR)-PE/Cy7 (BioLegend, San Diego, CA, USA)], [CD3-BUV805, Granzyme B-PE CF594, CD127-APC R700, CD62L-BUV737 (BD Biosciences, Franklin Lake, NJ, USA)]. Cell surface antibodies were added, the samples incubated for 20 min at 4oC in the dark, then were washed, followed by the Invitrogen IC Fixation Buffer procedure (Invitrogen, Waltham, MA, USA). Next, the cells were washed and FACS permeabilizing solution 2 (BD Biosciences, Franklin Lake, USA) was added according to manufactures procedures. The cells were then washed, and intracellular antibodies were added, and samples incubated for 20min at room temperature in the dark, then were washed before acquisition. The phenotypic expression of the NK cells was investigated through the BD FACSymphony flow cytometer. Analysis was completed using Kaluza version 2.1 software (Beckman Coulter, Mississauga, ON, Canada). The gating strategy included gating for lymphocytes using FSC-A and SSC-A, gating for single cells using FSC-H and FSC-W, and gating for the total NK cell population by selecting the CD56+ and CD3- cells. Phenotyping was completed with use of three differing fresh healthy donor blood samples. 2.2.4 Cell sorting of viable non-cytolytic NKreg cells Peripheral whole blood samples were collected and processed for PBMC. PBMC samples were enriched for total NK cells using the NK Cell Isolation Kit (StemCell Technologies, Vancouver, BC, Canada) according to manufacturer’s procedures. To differentiate the CD56brightCD16- NKreg cells from CD56dimCD16+ NK cells, enriched cells were stained using CD56-PE, CD3-APC, and CD16-FITC conjugated antibodies (BioLegend, San 35 Diego, CA, USA) for 20 min at 4°C in the dark. After two washes, 7-AAD (BioLegend, San Diego, CA, USA) was added, and the samples were sorted using sterile Beckman Coulter Astrios FACS sorting. The gating strategy included gating for lymphocytes using FSC-A and SSC-A, gating for single cells using FSC-H and FSC-W, gating for live NK cells by selecting 7-AAD- and CD3- lymphocytes, and finally the NK cell subpopulations were sorted based on the differential expression of CD56 and CD16 (CD56brightCD16- cells and CD56dimCD16+ cells). 2.2.5 Identification of NKreg cell subpopulations associated with cGvHD suppression through single-cell RNA sequencing HSCT patient PBMC were utilized from a multi-centre pediatric cohort (ABLE)/PBMTC 1202 trial) (previously described7,140,141) (table 2) for the transcriptomic identification of NK cell populations associated with cGvHD development or suppression. Twenty-seven pediatric transplant centers enrolled 302 patients. Patients were placed into 5 cohorts [no late aGvHD and no cGvHD (n = 132), late aGvHD (n = 30), cGvHD (including overlap syndrome; n = 41), active aGvHD day +100 to 114 (n = 28), or active cGvHD before day +114 (n = 10)]. Day 100 (n = 9) or 6-month (n = 2) HSCT archived patient samples were selected from two groups of this pediatric cohort [cGvHD (n = 5), or no late aGvHD or cGvHD (n = 6)]. Samples were selected from this cohort based on the number of cells (samples with the highest PBMC numbers were selected). 36 Single-cell RNA sequencing (scRNAseq) was performed on isolated NK cells using the 10X Chromium machine (8000 cells/sample). Single-cell Complementary DNA (cDNA) libraries were sequenced via Illumina Novaseq 6000 to a depth of ~30,000 reads/cell. Raw data from each sample was demultiplexed, aligned to a custom reference genome, and the unique molecular identifier (UMI) counts were quantified using 10X Genomics CellRanger software v3.0.0 (default parameters). Single-cell clustering was performed using Seurat package (v3.0). Statistical analysis was performed using Wilcoxson Rank-Sum or t-test. 37 Table 2: Clinical characteristics of HSCT patient samples utilized in scRNAseq study. ALL, Acute Lymphoblastic Leukemia; MDS, Myelodysplastic Syndrome; AML, Acute Myelogenous Leukemia; JMML, Juvenile Myelomonocytic Leukemia; CML, Chronic Myelogenous Leukemia; HLA, Human Leukocyte Antigen; PBSC, Peripheral Blood Stem Cells; ATG, Anti-Thymocyte Globulin. Characteristic (overall percentages of entire evaluable cohort; n = 11) No aGVHD or cGVHD (n = 6) cGVHD (n = 5) Time of sample collection (post-transplant) Day 100 5 4 ~6 months 1 1 Diagnoses Malignant (n = 10) 5 5 ALL, n 2 3 MDS/AML, n 3 2 Nonmalignant (n = 1) 1 0 Severe aplastic anemia, n 1 0 Sex Male (n = 5) 2 3 Female (n = 5) 4 1 N/A (n = 1) 0 1 Age at transplant Mean (range), years 10.1 (5.2-17.0) 12.6 (2.0-16.7) Donor and HLA match HLA-matched sibling donor (8/8) (n = 3) 2 1 HLA-matched non-sibling family donor (8/8) (n = 1) 1 0 HLA-matched unrelated donor (8/8) (n = 5) 2 3 HLA-mismatched unrelated donor (≤7/8) (n = 1) 1 0 Double cord blood (n = 1; 9.1%) 0 1 Stem cell source Bone marrow (n = 8) 5 3 38 Table 2: Clinical characteristics of HSCT patient samples utilized in scRNAseq study. ALL, Acute Lymphoblastic Leukemia; MDS, Myelodysplastic Syndrome; AML, Acute Myelogenous Leukemia; JMML, Juvenile Myelomonocytic Leukemia; CML, Chronic Myelogenous Leukemia; HLA, Human Leukocyte Antigen; PBSC, Peripheral Blood Stem Cells; ATG, Anti-Thymocyte Globulin. Characteristic (overall percentages of entire evaluable cohort; n = 11) No aGVHD or cGVHD (n = 6) cGVHD (n = 5) PBSC (n = 2) 1 1 Double cord blood (n = 1) 0 1 Serotherapy Rabbit ATG (n = 3) 2 1 Horse ATG (n = 1) 1 0 None (n = 7) 3 4 History of aGVHD Yes (n = 2) 0 2 No (n = 9) 6 3 39 2.3 Results 2.3.1 Identification of cell populations in HSCT patients associated with cGvHD A previous analysis of a pediatric cohort (N=241) from the PBMTC 1202/ABLE1.0 study demonstrated that patients at day 100 after HSCT who later developed cGvHD had decreased CD56brightCD3- NK cell numbers, similar to our previously described research in adult cohorts.43,44 Using the identical strict criteria of biological significance limited to significant p value, ROC AUC of ≥0.60, and effect ratio of either ≤0.7 or ≥1.3 after a Bonferroni correction, further immunophenotypic evaluation was performed on the CD56brightCD3- NK populations from the PBMTC1/ABLE cohort. Of samples taken before the onset of cGvHD at day 100, we observed a lack of cGvHD to be associated with CD56brightCD3- NK cells which were further characterized by being perforin- (Effect Ratio (ER)=0.67; p=0.007; AUC=0.63), CD335+ (ER=0.67; p=0.004; AUC=0.64), and close to meeting the criteria for Granzyme B- (ER=0.54; p=0.03; AUC=0.59)) (Figure 1a). A second analysis performed at cGvHD onset compared patients with cGvHD to time matched samples of patients that had no cGvHD (onset of cGvHD <4 months linked to non cGvHD controls at 3 months, onset >4 months to 8 months linked to 6-month controls, and cGvHD onset >8 months to 12 months linked to non cGvHD controls). The samples taken at the onset of cGvHD showed that CD56brightCD3- NK cells were perforin- (ER=0.51; p=2.3x10-7; AUC=0.64), CD335+ (ER=0.61; p=3.7x10-5; AUC=0.64), or Granzyme B- (ER=0.41; p=2.2x10-6; AUC=0.69) (Figure 1b). Since the association of a 40 lack of cGvHD was most significant with a subpopulation that was perforin-, a regression analysis evaluated CD56brightCD3-perforin- NK cells against all markers and observed a significant correlation with CD56brightCD3-Granzyme B- NK cells (Pearson average correlation (PAC)=0.78; p<1x10-17) and inverse relationship with CD56dimperforin+ and CD56dimGranzyme B+ NK cells (PAC=-0.76; p<1x10-17 and PAC=-0.79; p<1x10-17, respectively) (Figure 1c). Based on these findings, I concluded that perforin negativity is most significantly associated with the NKreg subpopulation important in suppressing cGvHD. 41 Figure 1: Immune cell populations in HSCT patients associated with cGvHD. CD56bright and CD56dim NK cell immunophenotypic expression for each group of HSCT patients (cGvHD and no cGvHD controls) at day 100 before and at the onset of cGvHD and the differential expression between controls and GvHD subjects. a) NKreg cell subpopulations of HSCT patients at day 100 before the onset of cGvHD compared to HSCT patients without cGvHD, b) NKreg cell subpopulations of HSCT patients at cGvHD onset compared to no cGvHD, c) Correlation of CD56brightperforin- NKreg cells with other immune cell populations. For the cell subtype contrast, significance identified as p <0.05 and effect ratio >5 or <0.2. For the group contrast, significance identified as p <0.05 and effect ratio >2 or <0.5. To test for differential expression between CD56bright and CD56dim NK cells of each gene, a paired t-test on samples from each group was performed. To test for group differences of each gene, a Student’s t-test on all samples was performed. GvHD, N=44; no GvHD, N=190. CD56brightCD335+ CD56dimGranzyme B+ CD56brightGranzyme B+ CD56brightGranzyme B- CD56dimPerforin+ CD56brightCD69+ c) a) b) 42 2.3.2 NK cell transcriptome expression in HSCT patients 2.3.2.1 Comparison of CD56bright to CD56dim NK cells To further evaluate for additional markers associated with a lack of cGvHD and the CD56brightCD3- NK cell population, we performed transcriptome analysis in a representative cohort of patients from the larger ABLE/PBMTC cohort. This was measured by nanoString on PBMC samples at Day 100 after HSCT in immune tolerant patients (N = 6) that had neither late aGvHD nor cGvHD. In this patient set, I compared the expression of CD56bright to CD56dim NK cells (column 1, table 3). I confirmed that the CD56bright NK cells had low expression of perforin and Granzyme B, and increased expression of NKp46, though this was not significant (p=0.08). Additional significant markers associated with this population were characterized by overexpression of Granzyme K (28.9-ER), IL-7R (31.3-ER), GPR183 (20.5-ER), RANK (18.3-ER), GM-CSFR (10.8-ER), CD62L (9.3-ER), and LEF1 (8.3-ER). I also identified a significant lack of expression of select genes in CD56bright NK cells compared to CD56dim NK cells (ER≤0.2), including FcRγ (FCGR3A/B; 0.03-ER), CX3CR1 (0.09-ER), and IKZF3 (0.10-ER) (table 3). To investigate for markers that had expression most closely within induction of immune tolerance I evaluated whether the CD56bright:CD56dim NK cell expression ratio is altered in patients with GvHD. I focused on the CD56bright population for transcriptome expressions differing in the late aGvHD (N = 6) or cGvHD (N = 6) patients. I observed 43 that there was a lower ratio for Granzyme K in the late aGvHD group (14.0-ER), and even lower in the cGvHD group (5.4-ER). Additional markers decreased in either late aGvHD or cGvHD in the CD56bright:CD56dim ratio included GPR183, RANK, GM-CSFR, CD62L, and LEF1. Ratios that increased in patients with GvHD included FcRγ (FCGR3A/B), IKZF3, and IRF4. Ratios that did not change in patients with either late aGvHD or cGvHD included IL7R, TCF7, IL23A, and IL18R1 (table 3, columns 2 and 3). 2.3.2.2 CD56bright NK cells associated with a lack of late aGvHD and cGvHD To determine if any of the markers identified in the transcriptome were characteristic of a subpopulation of CD56bright NK cells most closely associated with a lack of cGvHD, I evaluated CD56bright NK cells in HSCT patients with no GvHD compared to patients that developed cGvHD. I identified the CD56bright NK cells in the no GvHD group to overexpress GM-CSFR (5.7-ER), IL-23A (3-ER), GPR183 (2.5-ER), and TCF7 (2.5-ER) (table 3, column 4). Further, I verified the significant low expression of perforin (0.62-ER) among the CD56bright NK cells in HSCT patients with no GvHD compared to patients that developed cGvHD. 44 Table 3. Differences between CD56bright and CD56dim NK cells that are associated with a lack of GvHD and differences in gene expression between CD56bright NK cells in HSCT patients who were immune tolerant (no late aGvHD or cGvHD) versus those who developed GvHD measured on samples from day 100 post HSCT CD56bright:CD56dim NK cells Effect ratio (p value < 0.05) CD56bright NK cells Effect Ratio (p value) Gene No late aGvHD or cGvHD N = 6 Late aGvHD N = 6 cGvHD N = 6 No GvHD (immune tolerant):cGvHD N = 6:6 Increased expression in CD56bright cells of HSCT patients with no GvHD reported as mean ratios ER (p value) ER (p value) ER (p value) ER (p value) IL7R (CD127) 31.3 (0.007) 29.8 (0.02) 13.3 (0.11) NS 2.6 (0.33) NS Granzyme K 28.9 (0.009) 14.0 (0.04) 5.4 (0.03) 1.4 (0.17) NS GPR183 (EBI2) 20.5 (0.005) 6.0 (0.10) NS 10.2 (0.08) NS 2.5 (0.02) TNFRSF11A (RANK) 18.3 (0.006) 11.4 (0.08) NS 6.9 (0.09) NS 1.9 (0.09) NS CSF2 (GM-CSFR) 10.8 (0.04) 8.6 (0.21) NS 2.9 (0.05) 5.7 (0.02) SELL (CD62L) 9.3 (0.02) 4.1 (0.04) 4.4 (0.17) NS 1.2 (0.68) NS LEF1 8.3 (0.03) 3.7 (0.03) 2.8 (0.03) 1.2 (0.57) NS XCL1 6.9 (0.03) 5.1 (0.04) 1.0 (0.85) NS 2.2 (0.09) NS TCF7 6.6 (0.009) 7.7 (0.009) 4.3 (0.03) 2.5 (0.02) IL23A 5.8 (0.01) 3.3 (0.02) 2.6 (0.26) NS 3.0 (0.02) IL18R1 5.6 (0.0006) 4.5 (0.005) 3.6 (0.08) NS 1 (1.0) NS ZEB1 5.5 (0.004) 4.4 (0.17) NS 2.6 (0.04) 1.7 (0.09) NS NKp46 (CD335) 1.18 (0.08) NS* 1.16 (0.50) NS 0.91 (0.48) NS 1.0 (0.53) NS Decreased expression in CD56bright cells of HSCT patients with no GvHD reported as mean ratios FCGR3A/B 0.03 (0.02) 0.04 (0.08) NS 0.1 (0.03) 0.28 (0.08) NS CX3CR1 0.09 (0.03) 0.05 (0.28) NS 0.11 (0.07) NS 0.49 (0.3) NS IKZF3 0.10 (0.005) 0.19 (0.07) NS 0.3 (0.002) 0.33 (0.1) NS FCGR2A/C 0.11 (0.02) 0.18 (0.27) NS 0.54 (0.13) NS 0.23 (0.3) NS PRDM1 0.14 (0.01) 0.29 (0.01) 0.27 (0.004) 0.60 (0.06) NS IRF4 0.14 (0.05) 0.13 (0.16) NS 0.66 (0.05) 0.29 (0.04) CISH 0.15 (0.02) 1.2 (0.68) NS 0.61 (0.20) NS 0.30 (0.09) NS B3GAT1 0.17 (0.008) 0.50 (0.50) NS 0.21 (0.04) 1.3 (0.67) NS CD160 0.17 (0.03) 0.17 (0.15) NS 0.24 (0.15) NS 0.45 (0.29) NS CCL5 0.20 (0.009) 0.28 (0.07) NS 0.33 (0.01) 0.59 (0.41) NS Granzyme B 0.27 (<0.001) 0.27 (0.09) NS 0.45 (0.005) 0.68 (0.16) NS Perforin 0.39 (0.009) 0.27 (0.21) NS 0.46 (0.05) 0.62 (0.03) Abbreviations: NKp46 (CD335) – Natural cytotoxicity triggering receptor 1; (IL7R (CD127) – Interleukin 7 receptor; GPR183 (EBI2) – G-protein coupled receptor 183 (Epstein-Barr virus-induced G-protein coupled receptor 2); TNFRSF11A (RANK) – Tumor necrosis factor receptor superfamily member 11A (Receptor activator of nuclear factor kappa-Β); CSF2 (GM-CSFR) – Colony stimulating factor 2 (Granulocyte-macrophage colony-stimulating factor receptor); SELL (CD62L) – L-selectin; LEF1 – Lymphoid enhancer-binding factor 1; XCL1 – X-C Motif Chemokine Ligand 1; TCF7 – Transcription factor 7; IL23A – Interleukin-23 subunit alpha; IL18R1 – Interleukin-18 receptor 1; ZEB1 – Zinc finger E-box-binding homeobox 1; FCGR3A/B – Low affinity immunoglobulin gamma Fc region receptor III-A (polymorphism); CX3CR1 – CX3C chemokine receptor 1; IKZF3 – Ikaros family zinc finger protein 3; FCGR2A/C – Low affinity immunoglobulin gamma Fc region receptor III-A (polymorphism); PRDM1 – PR domain zinc finger protein 1; IRF4 – Interferon regulatory factor 4; CISH – Cytokine-inducible SH2-containing protein; B3GAT1 – 3-beta-glucuronosyltransferase 1; CD160 – Cluster of differentiation 160; CCL5 – Chemokine (C-C motif) ligand 5. *NS = not significant. Selected for ER ≥ 5 or ≤ 0.20 and p < 0.05 for no late aGvHD or cGvHD patients (column 1). 45 2.3.3 Phenotyping of CD56bright NK cells and sorting of NKreg cells Based on the immunophenotypic NK cell characterization of the larger HSCT patient populations and the confirmation by nanoString, I hypothesized that a subpopulation of CD56bright NK cells that are perforin- and Granzyme B- (NKreg) may have the greatest ability to act as a cGvHD suppressor. However, isolation of this population based on cytoplasmic perforin and granzyme staining results in non-viable cells. Therefore, I aimed to determine the optimal cell surface-expression approach to isolate the NKreg cell population based on the candidates identified in the nanoString analysis. The selected markers were significantly associated with a lack of GvHD development in the CD56bright NK cell subset and expressed on the cell surface. Using these criteria, I selected the following markers: CD56, IL-7R, GPR183, GM-CSFR, CD62L, and CD16. I also investigated CXCR3 expression based on previous data which showed this marker to be highly expressed by CD56bright NK cells associated with immune tolerance.43 Using flow cytometry phenotyping I verified that expression of Granzyme K, GPR183, IL-7R, CXCR3, and CD62L was present on the CD56bright NK cell population. Additionally, I confirmed the CD25, NKp44, and NKp46 expression (Figure 2), and lack of KIR expression among the CD56bright NK cells. In contrast, the CD56dim NK cells show RNA and protein expression of KIR, Granzyme B, and perforin. However, unlike the transcriptome findings, GM-CSF showed minimal protein expression among the 46 CD56bright NK cells. When investigating the optimal cell-surface marker combination for sorting the NKreg cells I identified that the greatest purity (>95%) for perforin- Granzyme B- NK cells (Figure 3) was in a CD56bright and CD16- NK cell population. In contrast, the CD56brightCD16+ subset is >70% perforin+ Granzyme B+. The other investigated markers (IL-7R, GPR183, GM-CSFR, CXCR3, and CD62L) in combination with CD56 did not result in consistent isolation of pure (>95%) perforin-, Granzyme B- NKreg cells across healthy donors. Therefore, I define the NKreg subpopulation as CD56brightCD16- NK cells and utilized these isolated cells for all NKreg functional evaluations. 47 CD16 GPR183R CD127 CD62L CXCR3 Granzyme K Perforin Granzyme B CD56 CD56 CD56 CD56 CD56 CD56 CD56 CD56 CD56 CD56 CD56 CD25 NKp46 NKp44 9% 5% 6% 3% 7% 7% 83% 4% 86% 80% 3% 7% 3% 58% 14% 26% 7% 25% 3% 64% 4% 3% 90% 10% 4% 3% 18% 68% 10% 3% 14% 73% 3% 4% 90% 3% 3% 3% 91% 4% 87% 3% 6% 3% 48 Figure 2: Cell surface and intracellular characteristics of the NK cell population in healthy donor peripheral blood. Healthy donor PBMC were stained for NK cell surface and intracellular expression of select markers and analyzed by flow cytometry. Lymphocytes were first gated using FSC and SSC. Single cells were gated using FSC-H and FSC-W. NK cells were gated as CD56+CD3- cells. CD56bright (PE) NK cells have low expression of CD16 (APC Fire 750), perforin (BV785), and Granzyme B (PE CF594), unlike the CD56dim NK cells. However, CD56bright NK cells show high expression of GPR183R (BV421), CD127 (IL7R), CD62L (SELL) (BUV737), Granzyme K (AF647), CXCR3 (FITC), CD25 (PE), NKp44 (APC), and NKp46 (BV421). The data is from a single experiment representative of 3 experiments (n=3 donors). 49 a) b) Figure 3: Sorting strategy for CD56brightCD16- NKreg cells, and the perforin and Granzyme B expression of sorted NKreg cells. CD56brightCD16- NKreg cells were sorted from healthy donor peripheral blood. Enriched NK cells were stained with the conjugated antibodies CD56-PE, CD3-APC, CD16-FITC, and 7-AAD. a) With use of FSC-A and SSC-A, lymphocytes were gated (gate A) and using FSC-H and FSC-W single cells were gated (gate B). After, live NK cells were gated by selecting 7-AAD- and CD3- cells (gate C). Lastly, the NKreg cells were gated as the CD56brightCD16- population, and for control assays, the CD56dimCD16+ NK cells were also gated, and both NK cell subsets were sorted. Note that the percentages shown are representative of the percentage of cells within the specified gate from the total initial cell population taken for sorting. b) Sorted CD56brightCD16- NK cells are 95% Granzyme B- (PE CF594) and perforin- (PB). The data is from a single experiment representative of all experiments performed (n>100 donors). 95% 4% 1% 0% 50 2.3.4 Transcriptomic characterization of unique NK cell subpopulations associated with cGvHD development or suppression 2.3.4.1 Transcriptionally unique subpopulations of NK cells in HSCT patients We aimed to investigate the heterogeneity of NK cells, being the unique NK cell subpopulations present in HSCT patients with and without cGvHD. Single-cell transcriptome analysis revealed 7 transcriptionally unique NK cell subpopulations (table 4, figure 4), 3 of which strongly associate with cGvHD development or suppression. As previously described, we identified Cluster 0 (cytotoxic CD56dim NK cells) to associate with patients with cGvHD. Interestingly, we observed two distinct NKreg-like subpopulations associated with cGvHD suppression, clusters 1 and 2. Cluster 1 and 2 are characterized by high expression of Granzyme K (GZMK) and X-C motif chemokine ligand 1 (XCL1), and interferon induced transmembrane protein 2 (IFIT2) and phorbol-12-Myristate-13-Acetate-Induced Protein 1 (PMAIP1), respectively. 51 Table 4: Gene expression of unique NK cell clusters among all HSCT patient samples (n=11; n = 6 no cGvHD, n = 5 cGvHD) Cluster Gene Log2FC p value 0 FGFBP2 1.23 < 1 x 10-300 0 CCL5 1.20 < 1 x 10-300 0 CST7 1.09 < 1 x 10-300 1 GZMK 1.55 < 1 x 10-300 1 XCL1 1.50 < 1 x 10-300 1 COTL1 1.32 < 1 x 10-300 2 IFIT2 2.88 < 1 x 10-300 2 PMAIP1 2.85 < 1 x 10-300 2 IFIT3 2.60 < 1 x 10-300 3 CCL3 4.03 < 1 x 10-300 3 CCL4 3.98 < 1 x 10-300 3 CCL4L2 2.52 < 1 x 10-300 4 HLA-DRA 2.24 < 1 x 10-300 4 HLA-DRB1 1.67 < 1 x 10-300 4 LGALS12 1.53 1.21 x 10-125 5 STMN1 3.69 < 1 x 10-300 5 TUBA1B 3.54 < 1 x 10-300 5 MKI67 2.93 < 1 x 10-300 6 AC253572.21 3.74 < 1 x 10-300 6 AC007952.41 3.10 < 1 x 10-300 6 AC245014.3 2.98 < 1 x 10-300 FGFBP2, Fibroblast growth factor binding protein 2; CCL5, Chemokine ligand 5; CST7, Cystatin F; GZMK, Granzyme K; XCL1, X-C motif chemokine ligand 1; COTL1, Coactosin-like protein; IFIT2, Interferon induced transmembrane protein 2; PMAIP1, Phorbol-12-Myristate-13-Acetate-Induced Protein 1; IFIT3, Interferon induced transmembrane protein 3; CCL3, Chemokine ligand 3; CCL4, Chemokine ligand 4; CCL4L2, Chemokine ligand 4 like 2; HLA-DRA, Major Histocompatibility Complex, Class II, DR Alpha; HLA-DRB1, Major Histocompatibility Complex, Class II, DR Beta 1; LGALS12, Galectin 12; STMN1, Stathmin 1; TUBA1B, Tubulin alpha 1b; MKI67, Antigen Kiel 67. 52 a) b) cGvHD No cGvHD 53 Figure 4: Transcriptome of NK cell subpopulations in HSCT patients, with and without cGvHD. a) Identification of 7 transcriptionally unique CD56+ NK cell clusters. 0 = cytolytic CD56dim NK cells; 1 = CD56bright NKreg cells, 2 = Type 1 interferon responsive NK cells; 3 = Activated NK cells; 4 = MHCII NK cells; 5 = Proliferating NK cells; 6 = Terminally mature NK cells (n = 11). b) Gene expression and NK cell clusters of HSCT patients with or without cGvHD, irrespective of cell cluster (n = 6 no cGvHD, n = 5 cGvHD). 54 2.3.4.2 Transcriptome changes in NKreg cells associated with cGvHD When we restricted our NK cell subpopulation transcriptome analysis to only patients that developed cGvHD, we identified a substantial change in the gene expression of the NK cell clusters, particularly among clusters 1 and 2, the regulatory-like NK cells. In patients with cGvHD, NKreg cells appear to lose regulatory associated gene expressions, such as GZMK and XCL1, and gain expression of cytolytic NK cell-associated or inflammatory genes, including chemokine ligand 5 (CCL5), granzyme B (GZMB), and amphiregulin (AREG) (table 5). Completion of a gene-set enrichment assay suggested that upregulation of TNFα signalling via NFκβ and inflammatory response signalling pathways among NKreg cells compared to cytolytic NK cells may be contributing to this change in NKreg cell gene expression and potentially cGvHD development (Figure 5). 55 Table 5: Gene expression of unique NK cell clusters among HSCT patients that developed cGvHD (n = 5) Cluster Gene Log2FC p value 0 TSC22D3 0.81 < 1 x 10-300 0 PRF1 0.79 3.08 x 10-287 0 CST7 0.78 < 1 x 10-300 1 AREG 1.55 < 1 x 10-300 1 CCL5 1.24 4.38 x 10-219 1 GZMB 1.02 1.03 x 10-301 2 GZMB 1.05 9.71 x 10-88 2 AREG 1.02 6.97 x 10-55 2 RPS26 0.86 5.09 x 10-121 3 TSC22D3 0.91 6.48 x 10-45 3 PSMB9 0.79 4.14 x 10-31 3 PRF1 0.68 6.48 x 10-17 4 CCL5 1.46 7.51 x 10-107 4 HLA-DRB1 1.31 4.81 x 10-71 4 GZMH 1.27 2.64 x 10-58 5 HLA-DRB1 1.27 2.04 x 10-22 5 IL32 1.06 1.59 x 10-13 5 PRF1 1.06 7.94 x 10-15 6 TSC22D3 1.03 7.59 x 10-07 6 SPON2 1.00 2.60 x 10-03 6 XIST 0.91 2.71 x 10-04 TSC22D3, TSC22 Domain Family Member 3; PRF1, Perforin; CST7, Cystatin F; AREG, Amphiregulin; CCL5, Chemokine ligand 5; GZMB, Granzyme B; RPS26, Ribosomal protein S26; PSMB9, Proteasome subunit beta type-9; HLA-DRB1, Major Histocompatibility Complex, Class II, DR Beta 1; GZMH, Granzyme H; IL32, Interleukin 32; SPON2, Spondin 2; XIST, X Inactive Specific Transcript. 56 a) No cGvHD b) cGvHD 57 Figure 5: Gene set enrichment assay, comparing Cluster 1 (CD56bright NKreg cells) to Cluster 0 (cytolytic CD56dim NK cells). A Gene set enrichment analysis was performed to identify genes signficantly expressed by Cluster 1 (CD56bright NKreg cells) compared to Cluster 0 (cytolytic CD56dim NK cells), and group the overrepresented genes according to established transcriptomic signalling pathways. a) Comparison of Cluster 1 (CD56bright NKreg cells) to Cluster 0 (cytolytic CD56dim NK cells) in HSCT patients with no cGvHD (n =6). b) Comparison of Cluster 1 (CD56bright NKreg cells) to Cluster 0 (cytolytic CD56dim NK cells) in HSCT patients with cGvHD (n =5). 58 2.3.4.3 Quantitative associations of NK cell subpopulations in HSCT patients with or without cGvHD In addition to evaluating the NK cell clusters and gene expressions associated with cGvHD development or suppression, I was also interested in investigating quantitative associations of the NK cell subpopulations in patients that developed or failed to develop cGvHD. I observed a statistically significant increase in the number and proportion of cluster 0 cells (cytolytic, CD56dim NK cells) in patients who developed cGvHD (p = 0.017). Further, I observed a significant decrease in the number and proportion of cluster 1 cells (CD56bright NKreg cells) in patients who developed cGvHD (p = 0.014). In cluster 2, I saw a decrease in the cell number in patients who develop cGvHD, though this wasn’t determined to be statistically significant (p = 0.09) (figure 6). 59 Figure 6: Quantitative analysis of transcriptionally unique NK cell clusters in HSCT patients with and without cGvHD. The proportion of 7 identified transcriptionally unique NK cell clusters is reported as mean +/- SD for samples from 11 people, including those who did not develop (dark grey bars) or did develop cGvHD (light grey bars). *P < 0.05, NS = not significantly different. Statistical analyses were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. (n = 6 no cGvHD, n = 5 cGvHD). 0102030405060700 1 2 3 4 5 6Proportion of total NK cells (%)Transcriptionally unique NK cell clustersNo cGvHD cGvHD* p = 0.02* p = 0.01NS, p = 0.09NS, p = 0.1NS, p = 0.5NS, p = 0.3NS, p = 0.460 2.3.4.4 Pseudotime analysis of NKreg cells and cytolytic NK cells in HSCT patients with and without cGvHD Pseudotime analysis in single-cell RNA sequencing is a computational method used to infer the developmental progression of individual cells within a heterogeneous population. Established algorithms predict the NK cell differentiation trajectory, and the psudeotime analysis groups individual cells along this trajectory according to their gene expression. Such analyses provide insights into molecular events associated with cell fate decisions or developmental transitions. I focused the analysis on the differentiation of cluster 0 (cytolytic CD56dim NK cells) and cluster 1 (CD56bright NKreg cells) cells in patients that developed or failed to develop cGvHD. As a result of this analysis, I identified distinct differentiation pathways among NK cells in the two different patient groups, where patients that develop cGvHD mainly have a differentiation endpoint in classic cytolytic CD56dim NK cells, while patients that did not develop cGvHD mainly have a differentiation endpoint in CD56bright NKreg cells. This suggests the potential of two distinct NK cell populations, rather than an immature and mature population of the same lineage (Figure 7). 61 Figure 7: Pseudotime analysis of cluster 0 (CD56dim NK) and 1 (CD56bright NKreg) cells in HSCT people with and without cGvHD. (n=11; n = 6 no cGvHD, n = 5 cGvHD). Pseudotime analysis was performed on the single-cell RNA sequenced cells to infer the developmental progression of cluster 0 and 1 cells, comparing samples from people that developed or did not develop cGvHD. Monocle 3 scRNAseq analysis statistical package was applied on the Uniform Manifold Approximation Projection (UMAP) embedding for pseudotime analysis. The green line shows the potential developmental connection between clusters, as the established algorithm predicts the NK cell differentiation trajectory, and the pseudotime analysis groups the individual cells along this trajectory according to their gene expression. CD56bright NK (NKreg) CD56dim NK (Classic NK) CD56bright NK (NKreg) CD56dim NK (Classic NK) No cGvHD cGvHD 62 2.4 Discussion In this thesis, I hypothesized that NKreg cells suppress cGvHD through inflammatory cell inhibition, and that these cells can be distinguished as a unique NK cell subset which may be optimally expanded for the cellular therapy of cGvHD. To address this hypothesis, my first objective was to determine the genes of CD56bright NK cells which are associated with cGvHD suppression after HSCT, and based on these initial transcriptome and phenotypic studies, determine the optimal cell surface markers to purify the NKreg cell population. I then further defined the immune tolerant NKreg cell subset according to single-cell RNA sequencing analysis and investigated NK cell subpopulations quantitatively and qualitatively associated with cGvHD development or suppression, including associated cell differentiation pathways. I first characterized the NKreg subpopulation through immunophenotypic analysis, identifying CD56brightperforin- cells to have the most significant association both before and at the onset of cGvHD, with Granzyme B- cells strongly correlating with the perforin- group. Within a smaller cohort of HSCT patient samples, transcriptome analysis identified additional markers that may be characteristic of this distinct CD56brightperforin- NK cell subpopulation associated with the suppression of GvHD as compared to the CD56dim NK cell subset. This included the overexpression of the genes Granzyme K, IL-7R, GPR183, RANK, GM-CSFR, CD62L, and LEF1, in addition to the lack of expression of the genes in FcRγ, CX3CR1, and IKZF3. Further, in analysing the gene expression of the CD56bright NK cell subset, comparing the gene expression of the cells 63 within the immune tolerant group to the aGvHD and cGvHD groups, I identified the overexpression of the genes GM-CSFR, IL-23A, GPR183, and TCF7 in addition to the low expression of perforin to significantly associate with a lack of GvHD development. These findings were consistent with other groups showing similar results, with regulatory NK cells typically having low transcriptomic expression of cytotoxic genes, such a perforin, Granzyme B, and FcRγ, with high expression of genes associated with immunoregulatory roles, such as GPR183, IL7R, and Granzyme K.98 Additionally, expression of the transcription factor TCF7 has been described as being required for early NK cell development.142 Studies have shown that TCF7−/− mice have severely reduced numbers of NK cells at all stages of development.142 Further, although TCF7 is highly expressed in early developing and immature NK cells (which would include the NKreg cell population), its expression has shown to decrease in mature or cytolytic NK cells, and may even antagonize NK cell maturation.142 My thesis objectives did not include delving deep into the differentiation pathway of the NKreg cell population, but this finding may suggest that later studies focusing on the constitutive transcription/expression of TCF7 could be useful in further studying how NKreg cells develop, and may provide a candidate method to prevent NKreg cell maturation. This immunophenotypic and transcriptomic identification of the regulatory NK cell population associated with immune tolerance in the cGvHD setting not only aided in the initial transcriptomic characterization of this unique subset, but also identified potential markers for selectively sorting for viable NKreg cells for further analysis. Based on these transcriptome findings, I determined that I could sort CD56bright and 64 CD16- NK cells to obtain a high purity of the viable NKreg (perforin-) cell subpopulation for manipulation in vitro. This work involved intracellular and cell surface phenotyping of the NK cells, resulting in the further characterization of this NKreg cell population associated with cGvHD suppression as a CD56bright, CD3-, CD16-, KIR-, CD25+, CXCR3+, NKp44+, NKp46+, GPR183R+, CD62L+, CD127+, Granzyme K+, Granzyme B-, and perforin- subset. The observed phenotype is consistent with other descriptions of the phenotype of CD56brightCD16- NK cells, confirming our findings.63,68,97 However, although we utilized this phenotypic information to determine that sorting on CD56brightCD16- NK cells was our most optimal option to obtain viable CD56brightperforin- NK cells, as compared to all other combinations of cell surface markers tested, this did not result in full purity of perforin- cells, with up to 5% of sorted cells being perforin+. Thus, there is room for greater investigation into the optimization of the NKreg cell sorting approach, to determine if perhaps a third cell surface marker could further purify this population. Additionally, further investigations into NKreg cell specific biomarkers or transcription factors which correlate with suppressive and regulatory function, such as that described for FOXP3+ Treg cells,143 may also be useful in purely selecting for the NKreg subpopulation, of which all cells demonstrate suppressive function. Following the completion of the initial transcriptome and phenotyping characterization studies, we wished to a complete a more thorough and comprehensive analysis of the transcriptome of NK cell subpopulations present in HSCT patients. This was done to gain further insight into transcriptionally unique NK cell populations and genes which 65 associate with cGvHD suppression or development, and the potential differentiation of the cells over time among the two patient groups. We first investigated for unique NK cell subsets in patients with and without cGvHD. Single-cell transcriptome analysis revealed 7 unique NK cell subsets, 3 of which strongly associated with cGvHD development or suppression. As previously described, we identified a significant cell increase in Cluster 0 (cytotoxic CD56dim NK cells) in patients with cGvHD. Interestingly, we observed two distinct NKreg subpopulations associated with cGvHD suppression. We identified an increase in the cell proportions of Cluster 1 (classic CD56bright NKreg cells) and cluster 2 (Type I interferon-responsive NKreg cells) among immune tolerant patients. Cluster 1 and 2 are characterized by high expression of GZMK and XCL1, and IFIT2 and PMAIP1, respectively. The gene expression of cluster 0 showed much overlap with the nanoString transcriptome results of the CD56dim NK cells, and cluster 1 showed much overlap with the nanoString transcriptome results of the CD56bright NK cells, confirming our previous findings regarding NK cell subpopulation associations with cGvHD development and suppression, respectively. In both NKreg-like subpopulations (clusters 1 and 2), the development of cGvHD was associated with differentiation towards a cytolytic, inflammatory-like NK cell population, with upregulation of AREG and GZMB. AREG has been described to play crucial roles in cell-cell signaling, epithelial cell proliferation, and mammary gland development through its interaction with the epidermal growth factor receptor (EGFR). Others have described elevated levels of AREG in patients with late aGvHD,144 suggesting that this may also be a biomarker of cGvHD in relevance to NK cell differentiation. GZMB is a serine protease, which plays a crucial role for target cell death induced by cytolytic NK cells and is a major intracellular marker 66 for cytolytic NK cells.145 This expression indicates the differentiation of regulatory and non-cytolytic NK cells to that which may induce granzyme-specific cytolytic function. Pseudotime and Gene Set Enrichment Assay analysis suggested the upregulation of TNFα via NFκβ and inflammatory signalling to be associated with NKreg cell differentiation towards an inflammatory phenotype and cGvHD development. These pathways include upregulation of genes such as CD83, CD44, AREG, MAP3K8, and others. For example, CD83 can be expressed on the cell surface and is known to activate T cells. In fact, the blocking of CD83 expression has already been described to suppress CD4+ T cells, where the use of a CD83 antibody inhibited both human B cell responses to antigens as well as CD4+ T cell responses, associating with the prevention of aGvHD.146 This may suggest that future work focusing on inhibiting these pathways may serve as a novel method to promote NKreg cell expansion and/or regulatory phenotype/function for the suppression of cGvHD associated inflammation. 67 3 Chapter 3: NKreg cells may function to prevent cGvHD through selective suppression of CD4+ T cells through a PD-1, LAG-3, and/or TRAIL dependent mechanism 3.1 Introduction In previous correlative studies, our lab observed an increased number of CD56brightCD335+CXCR3+ NK cells in adult HSCT patients who did not develop cGvHD43 and a similar lack of CD56brightCD3- NK cells in a large pediatric cohort before the onset of cGvHD.6 In a separate large adult clinical trial comparing G-CSF-mobilized marrow to G-CSF-mobilized peripheral blood, a decreased number of CD56bright NK cells in the donor product correlated with the development of cGvHD, and statistical analysis of the donor product suggested that the low number of CD56bright NK cells was the mechanism for this increased cGvHD.44 Further, other groups analyses have suggested an immune suppressive role of CD56bright NK cells, which may correlate to their associations with a lack of cGvHD. For example, the use of low-dose IL-2 to expand CD56brightCD16- NKreg cells, which result in a contact-dependent cell cycle arrest of effector T cells via retention of p21, mediated by the NK receptors NKp44 and NKp46.18 Additional studies have shown that the CD56brightCD16- NKreg cells can limit antigen specific T cell proliferation in vitro through an IL-10 dependent pathway.119 Further, IL-15 stimulated CD56brightCD16- NKreg cells were shown to inhibit proliferation of autologous CD4+ T cells by secreting the immunosuppressive molecule adenosine.113 68 As a result of these observations, I hypothesized that CD56bright NK cells may suppress the development of cGvHD through inflammatory cell inhibition. I utilized the previously determined transcriptomic and phenotypic characterization findings (thesis, chapter 2) to sort for the non-cytolytic regulatory NK cell population, and evaluate their in vitro suppression of various immune cells involved in cGvHD pathogenesis or regulation, including CD4+ T cells (naïve and memory), CD8+ T cells, Treg cells (+/- dendritic cells), B cells, and cytolytic NK cells, and how this suppression compares to classic NK cells and Treg cells. Further, I investigated whether the suppressive mechanism was dependent on cell-cell contact and/or gain in cytolytic function. Next, I investigated whether NKreg suppression of CD4+ T cell proliferation was dependent on a specific CD4+ T helper cell subset (Th1, Th2, Th17). Following these observations, I investigated whether select inhibitory receptors/ligands were involved in the suppressive mechanism, including NKp44, NKp46, GPR183, programmed death-receptor 1 (PD-1) and Lymphocyte activation gene 3 (LAG-3). I then investigated the cytokine secretion/protein expression of NKreg cells to better characterize this population and evaluate potential candidate proteins which may also be involved in the suppressive mechanism, identifying TRAIL as a potential mediator of NKreg cell suppression. Lastly, I completed cell surface phenotyping to better understand the PD-1, LAG-3 and TRAIL cell-cell interaction and determine which cell type (NKreg cells or CD4+ T cells) are likely responsible for the PD-1, LAG-3, or TRAIL expression which contributes to the suppressive mechanism. In completion of this work, I described the functional characteristics of NKreg cells, including their non-cytolytic, contact-dependent selective suppression of CD4+ T cells, 69 and deciphered three potential mechanisms of suppression, including mediation by PD-1, LAG-3, and TRAILR inhibitory pathways. 3.2 Methods 3.2.1 NK cell isolation for all functional evaluations Peripheral whole blood samples were collected and processed for PBMC. PBMC samples were enriched for total NK cells using the NK Cell Isolation Kit (StemCell Technologies, Vancouver, BC, Canada) according to manufacturer’s procedures. To differentiate the CD56brightCD16- NKreg cells from CD56dimCD16+ NK cells, enriched cells were stained using CD56-PE, CD3-APC, and CD16-FITC conjugated antibodies (BioLegend, San Diego, CA, USA) for 20 min at 4°C in the dark. After two washes, 7-AAD (BioLegend, San Diego, CA, USA) was added, and the samples were sorted using sterile Beckman Coulter Astrios FACS sorting. The gating strategy included gating for lymphocytes using FSC-A and SSC-A, gating for single cells using FSC-H and FSC-W, gating for live NK cells by selecting 7-AAD- and CD3- lymphocytes, and finally the NK cell subpopulations were sorted based on the differential expression of CD56 and CD16 (CD56brightCD16- cells and CD56dimCD16+ cells). 70 3.2.2 Evaluation of NKreg cell suppression 3.2.2.1 Suppression of CD4+ T cell proliferation Peripheral whole blood samples were collected and processed for PBMC. CD4+ T cells were isolated using the EasySep™ Human CD4+ T Cell Isolation Kit (StemCell Technologies, Vancouver, BC, Canada). The T cells were stained using Cell Proliferation Dye (CPD) eF450 (eBioscience, Mississauga, ON, Canada) and activated at the time of co-culture via the ImmunoCult™ Human CD3/CD28 T Cell Activator (StemCell Technologies, Vancouver, BC, Canada) according to manufacturer’s procedures. The CD56brightCD16- NKreg cells and CD56dimCD16+ NK cells were sorted (as described in section 2.2.4). The CD56brightCD16- and CD56dimCD16+ NK cells were co-cultured with allogeneic activated CD4+ T cells in a round-bottom 96-well plate (Sarstedt Inc, Newton, NC, USA) at the ratios 1:1 (100K:100K), 1:2 (50K:100K), 1:4 (25K:100K), and 1:8 (12.5K:100K) NK cells to CD4+ T cells, respectively, in a volume of 200µl. Control wells included activated CD4+ T cells, and non-activated CD4+ T cells. On day zero, BD LSRII Flow Cytometric analysis was completed to determine the initial cell proportion, cell viability, and baseline for the day-4 proliferation analysis. The co-culture was incubated at 37°C and 5% CO₂ for 96 hrs with complete DMEM medium (10% FBS, 1% glutamine, 1% Penicillin/Streptomycin) (Gibco, Grand Island, NY, USA). The NKreg and CD56dimCD16+ NK cell suppression experiments were repeated five times using cells derived from five different healthy donors. For the Treg versus CD4+ T cell control assay, the above procedures were performed identically using Treg cells as the suppressor 71 population, which were provided by collaborators (previously sorted, expanded, and cryopreserved, expansion protocol previously described (protocol F)147). Prior to use, the Treg cells were thawed using a 37oC water bath, washed once with 2% FBS PBS, and cultured overnight with Immunocult medium (StemCell Technologies, Vancouver, BC, Canada) at 1x106 cell/ml. The Treg suppression experiment was repeated twice using cells derived from two different healthy donors. On day 4, the proliferation and viability of the CD4+ T cells in co-culture were evaluated via cell proliferation dye dilution, 7-AAD dye (BioLegend, San Diego, CA, USA), and cell counting beads (Invitrogen, Waltham, MA, USA) using BD LSRII flow cytometry, and the data was analysed using Flowjo software (version 10.7.1). The flow cytometry analysis included gating for eF450 positive and 7-AAD negative cells (live T cells). The proliferation modeling function was used to determine the division index of gated live T cells. The activated T cell division index is normalized to 100% for calculation purposes, with all other indices scaled accordingly. This calculation was completed using the following standard formula: percentage of suppression = 1 – (division index of target cells co-cultured with suppressor cells / division index of target cells co-cultured without suppressor cells) x 100%. Statistical analyses for suppression experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. I aimed to identify significant differences in the proliferation of the activated responder cell (CD4+ T cell) control and the proliferation of the activated responder cells (CD4+ T cells) co-72 cultured with NKreg cells, CD56dim NK cells, or Treg cells over 96 hrs at the 1:1, 1:2, 1:4, and 1:8 ratios (P < 0.05 = *, P < 0.005 = **, P < 0.0005 = ***, NS = not significant). 3.2.2.2 Suppression of CD4+ naïve and memory T cell proliferation The NKreg versus CD4+ naïve (CD45RA+) and memory (CD45RO+) T cell suppression assay was performed identically to the method described above, though only at the 1:1 ratio of NKreg cells to CD4+ T cells. To identify and differentiate naïve CD4+ T cells from memory CD4+ T cells, on day 0 and 4 of the assay the cultured and co-cultured CD4+ T cells were stained with CD45RA BV785 and CD45RO eF650 conjugated antibodies (BioLegend, San Diego, CA, USA), in addition to the standard eF450 and 7-AAD staining, to identify the naïve and memory CD4+ T cells, respectively. Analysis was performed identically to that described above, though NKreg suppression of CD45RA+CD45RO- naïve CD4+ T cells was compared to the proliferation of the gated CD45RA+CD45RO- naïve CD4+ T cell control and the NKreg suppression of CD45RA-CD45RO+ memory CD4+ T cells was compared to the proliferation of the gated CD45RA-CD45RO+ memory CD4+ T cell control. This experiment was repeated three times using cells derived from three different healthy donors. 73 3.2.2.3 Suppression of CD4+ T helper cell subset (Th1/2/17) cell proliferation To determine if NKreg suppression of CD4+ T cell proliferation was specific to a CD4+ T helper cell subset, prior to and after the 96hr suppression assay co-culture, as per the methods described above, the cells were stained via the Human Th1/Th2/Th17 Phenotyping Kit (BD Biosciences, Franklin Lake, USA) according to manufactures procedures, and the data was acquired and analyzed using BD FACSymphony flow cytometry and Kaluza version 2.1 software (Beckman Coulter, Mississauga, ON, Canada). This experiment was repeated three times using cells derived from three different healthy donors. 3.2.2.4 Suppression of CD8+ T cell proliferation Further, I investigated the suppressive capacity of NKreg cells towards allogeneic CD8+ T cells. The CD8+ T cells were isolated using the EasySep™ Human CD8+ T Cell Isolation Kit (StemCell Technologies, Vancouver, BC, Canada), and all other steps and analyses were identical to the CD4+ T cell suppression assay (though only at the 1:1 ratio of NKreg cells to CD8+ T cells). This experiment was repeated three times using cells derived from three different healthy donors. 74 3.2.2.5 Suppression of Treg cell proliferation The NKreg versus Treg cell suppression assay was performed identically to the method described above, though only at the 1:1 ratio of NKreg cells to Treg cells. The Treg cells, being the responder cells in this case, were stained, activated, and analyzed identically to the CD4+ and CD8+ responder cells used in the above assays. The Treg cells were activated via CD3/CD28, with the typical Treg activation additive IL-2, being excluded due to potential deleterious effects of this cytokine on the function and phenotype of NKreg cells. The CD4+CD25+FOXP3+ thymic Treg cells were previously isolated and expanded according to the described protocol F.147 These Treg cells were cryopreserved and provided by collaborators at the BC Children’s Hospital Research Institute. 24hrs before the co-culture the Treg cells were thawed in a 37oC water bath, washed once using 2% FBS PBS, and cultured overnight in Immunocult medium (StemCell Technologies, Vancouver, BC, Canada) at 1x106 cells/ml. This experiment was repeated three times using cells derived from six different healthy donors. 3.2.2.6 Suppression of Treg cell proliferation with dendritic cells The NKreg versus Treg cell suppression assay with/without dendritic cells was performed identically to the method described above, though at the 1:1:1 ratio of NKreg cells to Treg cells to dendritic cells. The Treg cells, being the responder cells in this case, were stained and analyzed identically to the CD4+ and CD8+ responder cells used in the above assays. The CD4+CD25+FOXP3+ thymic Treg cells were previously isolated and expanded 75 according to the described protocol F.147 These Treg cells were cryopreserved and provided by collaborators at the BC Children’s Hospital Research Institute. 24hrs before the co-culture the Treg cells were thawed in a 37oC water bath, washed once using 2% FBS PBS, and cultured overnight in Immunocult medium (StemCell Technologies, Vancouver, BC, Canada) at 1x106 cells/ml. The dendritic cells were isolated from human PBMC using the EasySep™ Human Pan-DC Pre-Enrichment Kit (StemCell Technologies, Vancouver, BC, Canada). This experiment was repeated three times using cells derived from nine healthy donors. 3.2.2.7 Suppression of cytolytic NK cell proliferation I investigated the suppressive capacity of NKreg cells towards allogeneic total NK cells (~90-95% cytolytic NK cells). The NK cells were isolated using the EasySep™ Human NK Cell Isolation Kit (StemCell Technologies, Vancouver, BC, Canada), and all other steps and analyses were identical to the CD4+ T cell suppression assay (though only at the 1:1 ratio of NKreg cells to NK cells). This experiment was repeated three times using cells derived from six different healthy donors. 3.2.2.8 Suppression of B cell proliferation I investigated the suppressive capacity of NKreg cells towards allogeneic B cells. The B cells were isolated using the EasySep™ Human B Cell Enrichment Kit (StemCell 76 Technologies, Vancouver, BC, Canada), and all other steps and analyses were identical to the CD4+ T cell suppression assay (though only at the 1:1 ratio of NKreg cells to B cells, and B cells were activated via 10µg/ml CD40L (StemCell Technologies, Vancouver, BC, Canada) and 25ng/ml IL-4 (BioLegend, San Diego, CA, USA)). This experiment was repeated four times using cells derived from eight different healthy donors. 3.2.3 Evaluation of cell-cell contact dependence in NKreg suppression of CD4+ T cell proliferation To determine if the suppressive capacity of CD56brightCD16- NKreg cells on allogeneic CD4+ T cells was contact dependent the above suppression assay procedures were followed using a 96-well transwell plate (Corning, Corning, NY, USA), which prevents direct contact between the two cell types. The NKreg cells were inserted to the lower chamber at a volume of 200µl and the CD4+ T cells were inserted to the upper chamber at a volume of 75µl. To verify this finding, I removed the supernatant from a 96hr 1:1 NKreg versus CD4+ T cell suppression assay and cultured the supernatant with fresh allogeneic activated CD4+ T cells for 72 hrs and analysed the CD4+ T cell proliferation as described above in the suppression assay procedure. The transwell suppression assay experiment was repeated five times using cells derived from five different healthy donors. 77 3.2.4 Evaluation of GPR183, NKp44, and NKp46 receptor dependence in NKreg suppression of CD4+ T cell proliferation To determine if the suppressive mechanism of NKreg cells is reliant on NKp44, NKp46, or GPR183 receptors the above procedures were followed for preparing and analyzing the suppression assay. The soluble antibody blockers or antagonists were added separately to a 1:1 NKreg:CD4+ condition at the following concentrations (previously reported to be optimal for in vitro blocking): 1µg/ml Ultra-LEAF™ Purified anti-human NKp4618 (BioLegend, San Diego, CA, USA), 1µg/ml Ultra-LEAF™ Purified anti-human NKp4418 (BioLegend, San Diego, CA, USA), and 25 nM NIBR189148 (Sigma Aldrich, Oakville, CA, USA). Additional control wells included respective blockers being added to responder cells. The suppression assay with blocker experiments were repeated three times using cells derived from three different healthy donors. 3.2.5 Evaluation of PD-1, LAG-3, and TRAIL receptor dependence in NKreg suppression of CD4+ T cell proliferation To determine if the NKreg cell suppressive mechanism of CD4+ T cells is reliant on the PD-1, LAG-3, or TRAIL inhibitory pathways the above procedures were followed for preparing and analyzing the suppression assay. The following soluble neutralizing antibodies were added to a 1:2 NKreg:CD4+ condition (as well as a control CD4+ T cell condition) at the following concentrations (reported to be optimal for in vitro 78 receptor/ligand blocking by the manufacturer): 10µg/ml LAG-3 Antibody (17B4) (Novus Biologicals Canada, Burlington, ON, Canada), 10µg/ml Human PD-1 monoclonal antibody (Clone 1015829) (R&D Systems Inc., Minneapolis, MN, USA), and 8ng/ml Human TRAIL/TNFSF10 Antibody (R&D Systems, Inc, Minneapolis, MN, USA). 3.2.5.1 NKreg and CD4+ T cell surface expression of PD-1, PD-L1, LAG-3, HLA-DR, TRAILR1, and TRAIL NKreg cells were sorted and cultured for 3 days for activation with 25 ng/ml IL-2 (Biolegend, San Diego, CA, USA) + 2 ng/ml TGF-β1 (StemCell Technologies, Vancouver, BC, Canada) + 300 nM rapamycin (Sigma Aldrich, Oakville, CA, USA) in complete Immunocult NK Cell Expansion media (StemCell Technologies, Vancouver, BC, Canada). Complete media includes 1% penicillin/streptomycin + 1% L-glutamine + 10% human AB serum (Gibco, Grand Island, NY, USA). NKreg cells were stained for protein expression identification using the following conjugated antibodies: CD56-PE, CD3-PE/Cy7, CD16-FITC (BioLegend, San Diego, CA, USA). CD4+ T cells were obtained via peripheral whole blood samples, which were collected and processed for PBMC, and then selected by using the EasySep™ Human CD4+ T Cell Isolation Kit. The CD4+ T cells were stained for protein expression identification using the following conjugated antibodies: CD4-BV605, CD3-FITC (BioLegend, San Diego, CA, USA). To identify PD-1/programmed death-ligand 1 (PD-L1), LAG-3/HLA-DR, or TRAIL/TRAIL-R1 expression, the following antibodies were used: PD-1-AF647, PD-L1-APC, LAG-3-AF488, HLA-DR-APC, TRAIL-APC, TRAIL-R1-APC (BioLegend, San 79 Diego, CA, USA). Cell surface antibodies were added, the samples incubated for 20 min at 4oC in the dark, then were washed. The phenotypic expression of the cells was investigated through the BD FACSymphony flow cytometer. The gating strategy included gating for lymphocytes using FSC-A and SSC-A, gating for single cells using FSC-H and FSC-W, and gating for the NKreg cell population by selecting the CD56+, CD16-, and CD3- cells, while selecting CD3+ CD4+ cells to identify the CD4+ T cells. Analysis was performed using Kaluza version 2.1 software (Beckman Coulter, Mississauga, ON, Canada). 3.2.6 Evaluation of NKreg cell induction of responder cell death The FITC Annexin V apoptosis detection kit (BioLegend, San Diego, CA, USA) was utilized according to manufacturers procedures. After 96hrs, the allogeneic CD56brightCD16- NKreg cell vs. CD4+ T cell and CD56dimCD16+ NK cell vs. CD4+ T cell suppression assay co-cultured cells were harvested. To phenotypically identify the two co-cultured cell populations, the NK cells were stained with CD56-APC and the T cells were stained with CD4-PB, in addition to Annexin V-FITC and 7-AAD (BioLegend, San Diego, CA, USA) for identification of dead CD4+ T cells. With use of FSC-A and SSC-A, lymphocytes were gated and using CD4 and 7-AAD, live and dead CD4+ T cells were gated. After, Annexin V and 7-AAD were plotted. BD LSRII flow cytometry and Kaluza software (version 2.1) was utilized for acquiring and analysing the data. Annexin V and 7-AAD may be used to determine the proportion of dead CD4+ T cells after co-culture [early stage of cell death or apoptosis (7-AAD-, Annexin V+) and late stage of cell death 80 or necrosis (7-AAD+, Annexin V+)]. This apoptosis detection assay was repeated three times using cells derived from three different healthy donors. Statistical analyses for the CD4+ T cell apoptosis detection experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. I aimed to identify significant differences in the percentage of dead CD4+ T cells in the control (no NK cells added) and the percentage of dead CD4+ T cells when co-cultured with NKreg cells or NKdim cells over 96 hrs at the 1:1 ratio (P < 0.05 = *, P < 0.005 = **, P < 0.0005 = ***, NS = not significant). Further, this kit was utilized to determine the cytolytic effect of NKreg cells towards MOLT-4 (ATCC® CRL¬1582™), and Jurkat, Clone E6¬1 (ATCC® TIB¬152™) leukemic cell lines at the 10:1 (50K:5K) and 1:1 (50K:50K) ratios (NK cell:leukemic cell). The NKreg cells and leukemic cells were co-cultured for 72 hrs at 37oC and 5% CO2 in a total volume of 200 µl complete DMEM medium in a round-bottom 96-well plate. The leukemic cell lines were provided by collaborators at the BC Children’s Hospital Research Institute. This apoptosis detection assay was repeated two times using cells derived from two different healthy donors. Statistical analyses for the Jurkat and MOLT-4 cell apoptosis detection experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. I aimed to identify significant differences in the percentage of dead Jurkat and MOLT-4 cells in the control (no NK cells added) and the percentage 81 of dead Jurkat and MOLT-4 cells when co-cultured with NKreg cells over 72 hrs at the 10:1 and 1:1 ratios (P < 0.05 = *, P < 0.005 = **, P < 0.0005 = ***, NS = not significant). 3.2.7 Evaluation of NKreg cell induction of K562 cell killing Peripheral whole blood samples were collected and processed for PBMC as described previously. The CD56brightCD16- NKreg cells and CD56dimCD16+ NK cells were co-cultured with luciferase-tagged K562 cells (Gold Biotechnology, St Louis, MO, USA) at the ratios 2:1 and 1:1 (NK:K562) in a black 96-well plate (Corning, Corning, NY, USA) and complete medium [MACS NK expansion medium (Miltenyi Biotec, Auburn, CA, USA), 25ng/ml IL-2 (BioLegend, San Diego, CA, USA), 1/5000 anti-CD2 and anti-CD335 (Biolegend, San Diego, CA, USA), and 10% human AB serum (Corning, Corning, NY, USA)]. Luciferin was added at a 1/1000 dilution. The proportion of live K562 cells after incubation at 37oC and 5% CO2 for 24 hrs was determined using Spectral Instruments luminescence imaging (Ami-X). This experiment was repeated twice using cells derived from two different healthy donors. Statistical analyses for the K562 cytotoxicity experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. I aimed to identify significant differences in the percentage of live K562 cells in the control (no NK cells added) and the percentage of live K562 cells when co-cultured with NKreg cells or CD56dim NK cells over 24 hrs at the 2:1 and 1:1 ratios (P < 0.05 = *, P 82 < 0.005 = **, P < 0.0005 = ***, NS = not significant). 3.2.8 Functional assay statistical analysis summary Kaluza Analysis version 2.1 software (Beckman Coulter, Mississauga, ON, Canada) was used for all FACs sorting and flow cytometry phenotyping analysis, including creation of flow cytometry dot plots, and apoptosis detection assay experiments. For the suppression assay experiments, analysis was performed using Flowjo software version 10.7.1 (proliferation modeling function) (BD Biosciences, Franklin Lake, USA). Statistical analyses for all functional experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. *P < 0.05, **P < 0.005, ***P < 0.0005, NS = not significant. 3.3 Results 3.3.1 Evaluation of NKreg cell ability to suppress T cell proliferation A major characteristic of Treg cells is that they suppress CD4+ T cell function,149 which is crucial in the suppression of the development of GvHD. The evaluation of CD56brightCD16- NKreg cell’s ability to suppress allogeneic CD4+ T cell proliferation showed the NKreg cells to strongly suppress CD4+ T cell proliferation, particularly at the 1:1 ratio (approximately 96% suppression) (Figure 8a). In contrast, the CD56dimCD16+ 83 NK cells have minimal suppressive capacity (Figure 8b), differentiating their function from NKreg cells. The suppressive capacity of Treg cells was comparable to that of NKreg cells (Figure 8c). There was observed to be no significant differences in NKreg suppression of naïve as compared to memory CD4+ T cells (p<0.05) (figure not shown). Further, I was interested in determining whether NKreg suppression of CD4+ T cell proliferation was specific to a CD4+ T helper cell subset, particularly because previous studies have identified Th17 cells as playing a significant role in cGvHD pathogenesis.150 When co-culturing NKreg cells with allogeneic CD4+ T cells at a ratio of 1:6 I observed no significant difference in the suppression of CD4+ T cells among the Th1, Th2, or Th17 subsets, but rather similar suppression of all T helper cell subsets, as compared to the NKreg cell suppression of all CD4+ T cells (figure 9a). This finding was confirmed when testing expanded NKreg cell suppression of CD4+ T helper cell subsets (figure 9b). Interestingly, the NKreg cells suppress CD4+ T cell proliferation significantly stronger than CD8+ T cell proliferation at the 1:1 ratio (7.67% suppression of CD8+ T cell proliferation, compared to 94% of CD4+ T cell proliferation) (Figure 10). Other researchers have shown that NK cells may induce tolerance through priming dendritic cells via the release of various cytokines, such as TGF-β, IFNγ, and TNF to then result in the expansion of CD4+CD25+ Treg cells,151 which similar to NKreg cells, engage in regulatory functions to suppress GvHD. Therefore, I was interested in whether NKreg cells promote increased proliferation among allogeneic Treg cells in the presence of dendritic cells, thus being involved in an alternate and indirect suppressive mechanism of cGvHD through promoting Treg cell proliferation. At the 1 to 1 ratio of NKreg cells to 84 allogeneic Treg cells, I did not observe NKreg cells to induce a statistically significant suppressive or proliferative effect towards the Treg cells. When dendritic cells were added to the co-culture at a ratio of 1 to 1 to 1 NKreg cells to Treg cells to dendritic cells, though the average proliferation of the Treg cells co-cultured with NKreg cells and dendritic cells compared to just NKreg cells was greater (111% proliferation compared to 100% proliferation, respectively), I did not observe NKreg cells to induce a statistically significant proliferative effect towards the Treg cells in the presence of dendritic cells (figure 11). 85 a) CD4+ T cells NKreg cell : CD4+ T cell b) CD4+ T cells Dim NK cell : CD4+ T cell c) CD4+ T cells Treg cell : CD4+ T cell d) -2030801301 to 1 1 to 2 1 to 4 1 to 8Suppression of CD4+T cell proliferation (%)Effector cell to target cell ratioCD56brightCD16- NKreg cells Treg cells CD56dimCD16+ NK cells CPD Count Count Count Count Count Count CPD CPD * * * * *** * 86 Figure 8: Evaluation of CD56brightCD16- NKreg cell ability to suppress CD4+ T cell proliferation. CD56brightCD16- NKreg cells, CD56dimCD16+ NK cells, and Treg cells were isolated via sterile FACS cell sorting from unique healthy donor peripheral blood samples. CD4+ T cells were negatively isolated from unique healthy donor peripheral blood samples, stained with cell proliferation dye, and activated. The CD56brightCD16- NKreg cells, CD56dimCD16+ NK cells, and Treg cells were cocultured with allogeneic CD4+ T cells for 96hrs, and the proliferation of the CD4+ T cells was evaluated. a) Suppressive effect of CD56brightCD16- NKreg cells, b) Suppressive effect of CD56dimCD16+ NK cells, and c) Suppressive effect of Treg cells towards allogeneic CD4+ T cells. On the histograms, the x-axis displays the cell proliferation dye (CPD) eF450 and the y-axis displays the cell count. The green peaks indicate the individual proliferative populations, as determined by CPD expression. d) Suppressive capacity of CD56brightCD16- NKreg cells, CD56dimCD16+ NK cells, and Treg cells towards allogeneic CD4+ T cells at the 1:1, 1:2, 1:4, and 1:8 ratios as compared to the activated CD4+ T cell control (mean +/- SD). P < 0.05 = *, P < 0.0005 = ***. Statistical analyses for suppression experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. The data is representative of 5 separate experiments (n=5 donors) for the NK cell vs CD4+ T cell assays, and 2 experiments (n=2 donors) for the Treg cell vs CD4+ T cell assay. 87 0102030405060NKreg to CD4+T (1:6)NKreg to Th1(1:6)NKreg to Th2(1:6)NKreg to Th17(1:6)Suppression of T cell proliferation (%)NS, p = 0.501020304050607080NKreg to CD4+T (1:1)NKreg to Th1(1:1)NKreg to Th2(1:1)NKreg to Th17(1:1)Suppression of T cell proliferation (%)NS, p = 0.9 NS, p = 0.4 NS, p = 0.3 b) NS, p = 0.5 NS, p = 0.5 a) 88 Figure 9: Evaluation of CD56brightCD16- NKreg cell ability to suppress CD4+ T helper cell subset 1, 2, or 17 proliferation. CD56brightCD16- NKreg cells were isolated via sterile FACS cell sorting from unique healthy donor peripheral blood samples, and either used for the functional assay immediately, or cultured for 21-days for expansion. CD4+ T cells were negatively isolated from unique healthy donor peripheral blood samples, stained with cell proliferation dye, and activated. The CD56brightCD16- NKreg cells were cocultured with allogeneic CD4+ T cells for 96hrs, and the proliferation of the CD4+ Th1/2/17 cell subsets was evaluated. Suppressive effect of a) fresh CD56brightCD16- NKreg cells or b) expanded CD56brightCD16- NKreg cells towards allogeneic CD4+ Th1, Th2, or Th17 cells at the 1:6 ratio (for fresh NKreg cells) or 1:1 ratio (for expanded NKreg cells) as compared to the activated CD4+ T cell control (mean +/- SD). NS = not significant. Statistical analyses for suppression experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. The data is representative of 3 separate experiments utilizing cells from unique healthy donors (n=3). 89 020406080100120CD4 control NKreg to CD4(1:1)CD8 control NKreg to CD8(1:1)Proliferation of CD4+or CD8+T cells (%) Figure 10: Evaluation of CD56brightCD16- NKreg cell ability to suppress CD8+ T cell proliferation. CD56brightCD16- NKreg cells were isolated via sterile FACS cell sorting from unique healthy donor peripheral blood samples. CD4+ T cells or CD8+ T cells were negatively isolated from unique healthy donor peripheral blood samples, stained with cell proliferation dye, and activated. The CD56brightCD16- NKreg cells were cocultured with allogeneic CD4+ T cells or CD8+ T cells for 96hrs, and the proliferation of the CD4+ T cells or CD8+ T cells was evaluated. a) Suppressive effect of CD56brightCD16- NKreg cells towards allogeneic CD8+ T cells compared to the CD8+ T cell control. On the histograms, the x-axis displays the cell proliferation dye (CPD) eF450 and the y-axis displays the cell count. The green peaks indicate the individual proliferative populations, as determined by CPD expression. b) Proliferation of CD8+ or CD4+ T cells after 96 hr co-culture with allogeneic CD56brightCD16- NKreg cells at the 1:1 ratio as compared to the activated CD8+ or CD4+ T cell controls (mean +/- SD). P < 0.05 = *, P < 0.0005 = ***. Statistical analyses for suppression experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. The data is representative of 8 separate experiments utilizing cells from unique healthy donors (n=8). a) CD8+ T cells NKreg cell : CD8+ T cell b) CPD Count Count * *** *** 90 Figure 11: Evaluation of CD56brightCD16- NKreg cell ability to suppress Treg cell proliferation in the presence of dendritic cells. CD56brightCD16- NKreg cells and Treg cells were isolated via sterile FACS cell sorting from unique healthy donor peripheral blood samples. Dendritic cells were negatively isolated from unique healthy donor peripheral blood samples. The Treg cells were stained with cell proliferation dye and activated. The CD56brightCD16- NKreg cells were cocultured with allogeneic Treg cells with or without dendritic cells for 96hrs, and the proliferation of the Treg cells was evaluated. a) Suppressive effect of CD56brightCD16- NKreg cells towards allogeneic Treg cells in the presence of dendritic cells at the 1:1:1 ratio as compared to NKreg cell suppression towards allogeneic Treg cells. On the histograms, the x-axis displays the cell proliferation dye (CPD) eF450 and the y-axis displays the cell count. The green peaks indicate the individual proliferative populations, as determined by CPD expression. b) Proliferation of Treg cells after 96 hr co-culture with allogeneic CD56brightCD16- NKreg cells +/- dendritic cells at the 1:1:1 ratio as compared to the activated Treg cell or Treg cells + dendritic cell controls (mean +/- SD). NS = not significant, P > 0.05. Statistical analyses for suppression experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. The data is representative of 8 separate experiments utilizing cells from unique healthy donors (n=8). 020406080100120140Treg control 1:1 NKreg toTregTreg +dendriticcontrol1:1:1 NKreg toTreg todendriticProliferation of Tregcells (%)NS, p = 0.5NS, p = 0.1NS, p = 0.1a) Treg cells NKreg cell : Treg cell Treg + dendritic cells NKreg cell : Treg cell : dendritic cell dend Count Count Count Count CPD b) 91 3.3.2 Evaluation of NKreg cell ability to suppress cytolytic NK cell proliferation Cytolytic NK cells play an important role in the HSCT setting among malignant patients by mediating and promoting the GvT effect.28 Therefore, I was interested in whether NKreg cells exert regulatory or suppressive function towards total NK cell activation/proliferation (~90-95% of total NK cells are cytolytic NK cells). When co-culturing NKreg cells with allogeneic total NK cells at the 1:1 ratio I observed no statistically significant suppression of NK cell proliferation as compared to the activated NK cell control, but rather a statistically significant increase in total NK cell proliferation when co-cultured with NKreg cells (143% proliferation, SD=16.6, p=0.02) (figure 12). 92 020406080100120140160180TNK NKreg to TNK(1:1)CD4+ T NKreg to CD4+T (1:1)Responder cell proliferation (%)******a) NK cells NKreg cell : NK cell CPD Count Count b) 93 Figure 12: Evaluation of CD56brightCD16- NKreg cell ability to suppress NK cell proliferation. CD56brightCD16- NKreg cells were isolated via sterile FACS cell sorting from unique healthy donor peripheral blood samples. CD4+ T cells or NK cells were negatively isolated from unique healthy donor peripheral blood samples, stained with cell proliferation dye, and activated. The CD56brightCD16- NKreg cells were cocultured with allogeneic CD4+ T cells or NK cells for 96hrs, and the proliferation of the CD4+ T cells or NK cells was evaluated. a) Suppressive effect of CD56brightCD16- NKreg cells towards allogeneic total NK (TNK) cells at the 1:1 ratio as compared to the activated TNK cell control. On the histograms, the x-axis displays the cell proliferation dye (CPD) eF450 and the y-axis displays the cell count. The green peaks indicate the individual proliferative populations, as determined by CPD expression. b) Proliferation of TNK cells or CD4+ T cells after 96 hr co-culture with allogeneic CD56brightCD16- NKreg cells at the 1:1 ratio as compared to the activated TNK cell or CD4+ T cells controls (mean +/- SD). P < 0.05 = *, P < 0.005 = **, P < 0.0005 = ***. Statistical analyses for suppression experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. The data is representative of eight separate experiments utilizing cells from unique healthy donors (n=8). 94 3.3.3 Evaluation of NKreg cell ability to suppress B cell proliferation Various studies have demonstrated a role for B cells in cGvHD, as B cells may be promoted by antigen and excessive B cell activating factor (BAFF) levels to survive and produce antibodies, directly and indirectly mediating cGvHD pathology and T cell activation.152 Therefore, I was interested in whether NKreg cells exert regulatory or suppressive function towards B cell proliferation. When co-culturing NKreg cells with allogeneic B cells at the 1:1 ratio I observed no statistically significant suppression of B cell proliferation as compared to the activated B cell control (1.5% suppression, SD=14.98, p=0.85) (Figure 13). 95 NS, p = 0.4 *** *** a) B cells NKreg cell : B cell CPD Count Count b) 020406080100120B NKreg to B(1:1)CD4+ T NKreg to CD4+T (1:1)Responder cell proliferation (%)96 Figure 13: Evaluation of CD56brightCD16- NKreg cell ability to suppress B cell proliferation. CD56brightCD16- NKreg cells were isolated via sterile FACS cell sorting from unique healthy donor peripheral blood samples. CD4+ T cells or B cells were negatively isolated from unique healthy donor peripheral blood samples, stained with cell proliferation dye, and activated. The CD56brightCD16- NKreg cells were cocultured with allogeneic CD4+ T cells or B cells for 96hrs, and the proliferation of the CD4+ T cells or B cells was evaluated. a) Suppressive effect of CD56brightCD16- NKreg cells towards allogeneic B cells at the 1:1 ratio as compared to the activated B cell control. On the histograms, the x-axis displays the cell proliferation dye (CPD) eF450 and the y-axis displays the cell count. The green peaks indicate the individual proliferative populations, as determined by CPD expression. b) Proliferation of B cells or CD4+ T cells after 96 hr co-culture with allogeneic CD56brightCD16- NKreg cells at the 1:1 ratio as compared to the activated B cell or CD4+ T cells controls (mean +/- SD). P < 0.0005 = ***, NS = not significant. Statistical analyses for suppression experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. The data is representative of nine separate experiments utilizing cells from unique healthy donors (n=9). 97 3.3.4 Evaluation of the cytolytic ability of NKreg cells NKreg cells were observed to not be cytotoxic towards K562 cells, but CD56dimCD16+ NK cells significantly lysed the target (Figure 14). Additionally, in the suppression assay co-culture, NKreg cells, which strongly suppressed CD4+ T cell proliferation, did not induce death of CD4+ T cells, but CD56dimCD16+ NK cells induced substantial death of CD4+ T cells (Figure 15). Further, as expected, coculture analysis of NKreg cells with target cells did not result in significant reduction of leukemic cell viability at the 10:1 (10.5% death of Jurkat cells, SD=4.95; 6% death of MOLT-4 cells, SD=0) or 1:1 (9% death of Jurkat cells, SD=4.36; 3% death of MOLT-4 cells, SD=0) ratios (Figure 16). 98 Figure 14: CD56brightCD16- NKreg cell induction of K562 cell killing. Cytotoxic effect of sorted CD56brightCD16- and CD56dimCD16+ NK cells towards K562 cells at the ratios 2:1 and 1:1 over a 24-hr period. The percentage of live K562 cells in the K562 cell control as opposed to the K562 cells co-cultured with NKreg cells or CD56dim NK cells are shown (mean +/- SD). *P < 0.05. Statistical analyses were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. The data is representative of 2 separate experiments from unique healthy donors (n=2). -20020406080100120K562 control 2 to 1 1 to 1Live K562 (%)Effector cell to target cell ratioCD56brightCD16- NKreg cells CD56dimCD16+ NK cellsNS, p = 0.3NS, p = 1* * 99 a) CD4+ T cells b) NKreg cell : CD4+ T cell c) CD56dim NK cell : CD4+ T cell 11% 31% 10% 0 10 20 30 40 50 60 70 80 90CD4+ T cell controlCD56brightCD16- NKreg cellCD56dimCD16+ NK cellDead CD4+ T cells (%)NK cells to CD4+T cells (1:1)NS, p = 0.1 NS, p = 0.2 d) 100 Figure 15: CD56brightCD16- NKreg cell induction of CD4+ T cell death. Dead CD4+ T cells after the 96 hr suppression assay co-culture were identified with use of Annexin V and 7-AAD flow cytometric staining. Conditions tested included: a) Activated CD4+ T cells in the absence of suppressor cells (control), b) CD56brightCD16- NKreg cells, and c) CD56dimCD16+ NK cells co-cultured with allogeneic CD4+ T cells at the 1:1 ratio. With use of FSC-A and SSC-A, lymphocytes were gated and using CD4 and 7-AAD staining live and dead CD4+ T cells were gated (plots not shown). After, Annexin V and 7-AAD were plotted. For the histogram, Annexin V negative and 7-AAD negative (live) CD4+ T cells are shown in blue, and annexin V positive, 7-AAD negative (early stage of death/apoptosis) and annexin V positive, 7-AAD positive (late stage of death/necrosis) CD4+ T cells are shown in purple. d) The percentage of dead CD4+ T cells in the CD4+ T cell control as compared to the NKreg and CD56dim NK cell co-culture conditions are shown (mean +/- SD). NS = not significant. Statistical analyses were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. The data is representative of 3 separate experiments utilizing cells from unique healthy donors (n=3). 101 a) b) Figure 16: CD56brightCD16- NKreg cell induction of Jurkat and MOLT-4 leukemic cell death. Cytotoxic effect of sorted CD56brightCD16- NKreg cells towards Jurkat or MOLT-4 leukemic cells at the 10:1 and 1:1 ratios over 72 hrs. a) Percentage of dead Jurkat cells when co-cultured with NKreg cells as compared to the Jurkat cell control, b) Percentage of dead MOLT-4 cells when co-cultured with NKreg cells as compared to the MOLT-4 cell control (mean +/- SD). P < 0.05 = *. The data is representative of 2 experiments utilizing cells from unique healthy donors (n=2). Statistical analyses were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. 024681012141618NKreg to Jurkat Jurkat controlDead Jurkat cells (%)10 to 1 1 to 1NS, p = 0.3NS, p = 0.40123456789NKreg to MOLT-4 MOLT-4 controlDead MOLT-4 cells (%)10 to 1 1 to 1NS, p = 0.1 * 102 3.3.5 Evaluation of cell-cell contact dependence for NKreg cell suppression To evaluate whether NKreg cells suppress through cell-cell contact, NKreg cells were co-cultured with allogeneic CD4+ T cells in a transwell plate to prevent direct contact between the two cell types, but still allow transfer of soluble factors through the permeable membrane. In this environment, there was observed to be a significant decrease in the suppressive effect of the NKreg cells (91% of CD4+ T cells continued to proliferate at the 1:1 ratio) (Figure 17). In confirming that suppression was not mainly occurring through a soluble factor secreted by NKreg cells, I identified minimal/lack of significant suppression of CD4+ T cell proliferation when co-culturing with the NKreg cell suppression assay supernatant (Figure 18). 103 a) CD4+ T cells b) NKreg cell : CD4+ T cell c) NKreg cell : CD4+ T cell (transwell plate) d) Count Count Count CPD *** 0 20 40 60 80 100CD4+ T cell proliferationNKreg cell : CD4+T cell (1:1)TranswellplateNS, p = 0.05 CD4+ T cell control Standard plate 104 Figure 17: Evaluation of cell-cell contact dependence for CD56brightCD16- NKreg cell suppression. Suppressive effect of CD56brightCD16- NKreg cells towards allogeneic CD4+ T cells when cells are co-cultured for 96 hrs at the ratio 1:1 in a standard round-bottom 96-well plate or 96-well transwell plate. a) Proliferation of CD4+ T cells (control), b) proliferation of CD4+ T cells co-cultured with NKreg cells in a standard plate, c) proliferation of CD4+ T cells co-cultured with NKreg cells in a transwell plate. On the histograms, the x-axis displays the cell proliferation dye (CPD) eF450 and the y-axis displays the cell count. The green peaks indicate the individual proliferative populations, as determined by CPD expression. d) Proliferation of CD4+ T cell control compared to CD4+ T cells co-cultured with NKreg cells in a standard or transwell plate (mean +/- SD). ***P < 0.0005, NS = not significantly difference. Statistical analyses were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. The data is representative of 10 experiments utilizing cells from unique healthy donors (n=10). 105 Figure 18: Evaluation of CD56brightCD16- NKreg cell supernatant suppression of CD4+ T cell proliferation. Suppressive effect of CD56brightCD16- NKreg cell supernatant towards allogeneic CD4+ T cells when co-cultured for 72 hrs. a) Proliferation of CD4+ T cells in the absence of NKreg cell supernatant (control), b) proliferation of CD4+ T cells co-cultured with NKreg cell supernatant. On the histograms, the x-axis displays the cell proliferation dye (CPD) eF450 and the y-axis displays the cell count. Percentage of suppression = 1 – (division index of target cells cultured with supernatant / division index of target cells cultured without supernatant) x 100%. The green peaks indicate the individual proliferative populations, as determined by CPD expression. CPD Count Count a) CD4+ T cells b) NKreg cell supernatant and CD4+ T cells 22% suppression of CD4+ T cell proliferation 106 3.3.6 Evaluation of GPR183, NKp46, NKp44 receptor dependence for NKreg cell suppression Based on the nanoString transcriptome study results and previous studies,18 I investigated the protein expression of GPR183, NKp44, and NKp46 to determine if these receptors play a role in the NKreg cell suppressive mechanism (all three receptors highly expressed on the cell surface of NKreg cells (Figure 2)). GPR183 is a G-couple receptor reported to play a key role in regulating innate lymphoid cell (ILC), B cell, and T cell migration and responses.153 The GPR183R, which was significantly expressed (transcriptome and cell surface, shown in table 3 and figure 2, respectively) by NK cells associated with a lack of cGvHD will normally bind to its ligand 7α-25, di-hydroxycholesterol, but may be blocked using the antagonist NIBR189.154 My investigation observed there to be no significant difference in NKreg cell suppressive capacity towards CD4+ T cells when the GPR183 receptor was blocked in solution (Figure 19). NKp44 and NKp46 are natural cytotoxicity receptors present on the cell surface of CD56bright NK cells (shown in phenotyping Figure 2). Other researchers have proposed that low-dose IL-2 expands CD56brightCD16- NKreg cells resulting in a contact-dependent cell cycle arrest of effector T cells via retention of the cycle inhibitor p21.18 This same group had shown that blocking of the NK receptors NKp44 and NKp46 abrogates the 107 regulation of proliferation associated with low-dose IL-2. Therefore, I wished to investigate whether the NKp44 and NKp46 receptors may be involved in the suppressive capacity of non-cytokine treated NKreg cells towards CD4+ T cells. This was investigated with use of ULTRA-leafTM purified A-NKp44 and A-NKp46 antibodies which block these receptors in solution. My investigation revealed there to be no significant difference in non-stimulated NKreg cell suppressive capacity towards CD4+ T cell proliferation when the NKp44 or NKp46 receptors were blocked (Figure 19). 108 c) NKreg cell : CD4+ T cell NKp44 blocker d) NKreg cell : CD4+ T cell NKp46 blocker e) NKreg cell : CD4+ T cell GPR183R blocker Count Count Count Count Count CPD CPD CPD 020406080100120No blocker NKp44blockerNKp46blockerGPR183RblockerSuppression of CD4+T cell proliferation (%)NKreg cell : CD4+ T cell (1:1)NS, p = 0.5 NS, p = 0.4 NS, p = 0.5 a) CD4+ T cells b) NKreg cell : CD4+ T cell f) 109 Figure 19: Evaluation of NKp44, NKp46, and GPR183R dependence for CD56brightCD16- NKreg cell suppression. Suppressive effect of CD56brightCD16- NKreg cells towards allogeneic CD4+ T cells when cells are co-cultured for 96 hrs at the ratio 1:1 with the NKp44 antibody blocker, NKp46 antibody blocker, or GPR183R antagonist. a) Proliferation of CD4+ T cells (control), b) proliferation of CD4+ T cells co-cultured with NKreg cells with no soluble blocker/antagonist, c) proliferation of CD4+ T cells co-cultured with NKreg cells with NKp44 antibody blocker, d) proliferation of CD4+ T cells co-cultured with NKreg cells with NKp46 antibody blocker, e) proliferation of CD4+ T cells co-cultured with NKreg cells with GPR183R antagonist. On the histograms, the x-axis displays the cell proliferation dye (CPD) eF450 and the y-axis displays the cell count. The green peaks indicate the individual proliferative populations, as determined by CPD expression. f) Proliferation of CD4+ T cell control compared to CD4+ T cells co-cultured with NKreg cells with or without the NKp44, NKp46, or GPR183R soluble antibody blockers/antagonists (mean +/- SD). NS = not significant. Statistical analyses were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. The data is representative of 12 separate experiments utilizing cells from unique healthy donors (n=12). 110 3.3.7 Evaluation of PD-1, LAG-3, and TRAIL receptor dependence 3.3.7.1 NKreg cell suppression of CD4+ T cell proliferation In the above studies I observed the strong suppressive function of NKreg cells towards allogeneic T cells to be specific to the CD4+ T cell population, and that this suppression of CD4+ T cell proliferation is cell-cell contact dependent. Therefore, I selected immune checkpoints which result in CD4+ T cell inhibition, and have an associated receptor/ligand highly expressed on NKreg cells. This led to my investigation of the PD-1 and LAG-3 immune checkpoint pathways. When co-culturing NKreg cells with allogeneic CD4+ T cells at the 1:2 ratio, I observed a statistically significant decrease in the suppression of CD4+ T cells when blocking either the PD-1 receptor (12% decrease in suppression, SD=5.5, p=0.03), or the LAG-3 receptor (25% decrease in suppression, SD=13.0, p=0.004) (figure 20). I then wished to further verify these findings by co-culturing NKreg cells with allogeneic CD4+ T cells at the 1:2 ratio with neutralizing PD-L1 or HLA-DR (MHCII) antibodies, to verify if I observe similar findings to PD-1 or LAG-3 blocking when blocking one possible ligand for each receptor. Though I did not observe a statistically significant decrease in the suppression of CD4+ T cells when blocking either the PD-L1 ligand (8% decrease in suppression, SD=11.6, p>0.05), or the MHCII ligand (21% decrease in suppression, SD=21.3, p>0.05), I observed a similar pattern in that blocking either ligand decreased suppressive ability, and more so for the LAG-3 ligand than PD-1 ligand (figure not shown). The more minimal effects observed may be attributed to the fact that there are multiple ligands that could bind the LAG-3 or 111 PD-1 receptors. Note that the suppression observed is less than previously shown as these experiments were completed at a ratio of 1:2 NKreg cells to CD4+ T cells, as opposed to 1:1. Further, based on proteomics analysis (section 4.3.3.3) I wished to investigate the effect of TRAIL on NKreg cell suppressive function, which may be expressed in both soluble and cell surface-form on NKreg cells. Further, data described by other researchers has shown that TRAIL-R signaling inhibits phosphorylation of proximal T cell receptor (TCR)-associated tyrosine kinases in activated CD4+ T cells, ultimately suppressing CD4+ T cell activation.155 Thus, I identified TRAIL as a strong candidate for my mechanistic studies. At the 1:2 ratio of NKreg cells to CD4+ T cells, I observed a statistically significant decrease in the NKreg cell induced suppression of CD4+ T cells when blocking TRAIL (26% decrease in suppression, SD=11, p=0.04) (figure 21). Note that the suppression observed is less than previously shown as these experiments were completed at a ratio of 1:2 NKreg cells to CD4+ T cells, as opposed to 1:1. 112 0102030405060NKreg to CD4 NKreg to CD4 (+LAG3 blocker)NKreg to CD4 (+PD-1 blocker)Suppression of CD4+ T cell proliferation (%)** * a) NKreg cell : CD4+ T cell NKreg cell : CD4+ T cell NKreg cell : CD4+ T cell + LAG-3 blocker + PD-1 blocker CPD Count Count Count b) 113 Figure 20: Evaluation of CD56brightCD16- NKreg cell ability to suppress CD4+ T cell proliferation with PD-1 and LAG-3 receptor antibody blockers. CD56brightCD16- NKreg cells were isolated via sterile FACS cell sorting from unique healthy donor peripheral blood samples. CD4+ T cells were negatively isolated from unique healthy donor peripheral blood samples, stained with cell proliferation dye, and activated. The CD56brightCD16- NKreg cells were cocultured with allogeneic CD4+ T cells with or without PD-1 or LAG-3 antibody blockers for 96hrs, and the proliferation of the CD4+ T cells was evaluated. a) Suppressive effect of CD56brightCD16- NKreg cells towards allogeneic CD4+ T cells at the 1:2 ratio as compared to the suppressive effect of CD56brightCD16- NKreg cells towards allogeneic CD4+ T cells with the addition of LAG-3 or PD-1 blocking antibodies. On the histograms, the x-axis displays the cell proliferation dye (CPD) eF450 and the y-axis displays the cell count. The green peaks indicate the individual proliferative populations, as determined by CPD expression. b) Suppressive effect of CD56brightCD16- NKreg cells towards allogeneic CD4+ T cells at the 1:2 ratio as compared to NKreg suppression of CD4+ T cells in the presence of the PD-1, or LAG-3 receptor blockers (neutralizing antibodies) (mean +/- SD). *P < 0.05, **P < 0.005 =. Statistical analyses for suppression experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. The data is representative of 8 separate experiments utilizing cells from unique healthy donors (n=8). 114 Figure 21: Evaluation of CD56brightCD16- NKreg cell ability to suppress CD4+ T cell proliferation when blocking TRAIL. CD56brightCD16- NKreg cells were isolated via sterile FACS cell sorting from unique healthy donor peripheral blood samples. CD4+ T cells were negatively isolated from unique healthy donor peripheral blood samples, stained with cell proliferation dye, and activated. The CD56brightCD16- NKreg cells were cocultured with allogeneic CD4+ T cells with or without the TRAIL antibody blocker for 96hrs, and the proliferation of the CD4+ T cells was evaluated. a) Suppressive effect of CD56brightCD16- NKreg cells towards allogeneic CD4+ T cells at the 1:2 ratio as compared to the suppressive effect of CD56brightCD16- NKreg cells towards allogeneic CD4+ T cells with the addition of a TRAIL blocking antibody. On the histograms, the x-axis displays the cell proliferation dye (CPD) eF450 and the y-axis displays the cell count. The green peaks indicate the individual proliferative populations, as determined by CPD expression. b) Suppressive effect of CD56brightCD16- NKreg cells towards allogeneic CD4+ T cells at the 1:2 ratio as compared to NKreg suppression of CD4+ T cells in the presence of the TRAIL receptor blocker (neutralizing antibody) (mean +/- SD). * = p < 0.05. Statistical analyses for suppression experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. The data is representative of 3 separate experiments utilizing cells from unique healthy donors. 0102030405060NKreg to CD4 (1:2) NKreg to CD4 (TRAILblocker) (1:2)Suppression of CD4+T cell proliferation (%) *a) NKreg cells: CD4+ T cells NKreg cells : CD4+ T cells + TRAIL blocker CPD Count Count b) 115 3.3.7.2 NKreg cell and CD4+ T cell surface expression of PD-1, PD-L1, LAG-3, HLA-DR, TRAILR1, and TRAIL Through a cell surface phenotypic analysis, we evaluated the expression of inhibitory ligands/receptors (PD-1/PD-L1, LAG-3/HLA-DR, TRAILR1/TRAIL) that are present on NKreg cells, which when engaged may result in significant inhibition of the activation/proliferation of CD4+ T cells. This was performed in an effort to more clearly elucidate which cell type, NKreg cells or CD4+ T cells, express the inhibitory receptor or ligand which may be involved in the suppressive mechanism. The phenotypic evaluation of the activated NKreg cells and CD4+ T cells identified both cell types to highly express PD-L1, though only CD4+ T cells highly express PD-1. In addition, it was observed that NKreg cells have substantially greater expression of HLA-DR than CD4+ T cells, and neither cell type highly expresses LAG-3, though CD4+ T cells show some expression while NKreg cells show no expression. Lastly, both cell types highly express TRAILR1, however only NKreg cells highly express TRAIL (figure 22). 116 a)b) 100% 100% 96% 4% 99% 1% 73% 27% 6% 94% 65% 35% 90% 10% 81% 17% 2% 99% 1% 20% 80% 20% 80% 117 Figure 22: Evaluation of the phenotypic expression of activated CD56brightCD16- NKreg cells and CD4+ T cells. Healthy donor isolated and activated NKreg cells and CD4+ T cells were stained for cell surface expression of select markers (PD-1 AF647, PD-L1 APC, LAG-3 AF488, HLA-DR APC, TRAIL-R1 APC, TRAIL APC) and analyzed by flow cytometry. Lymphocytes were first gated using FSC and SSC. Single cells were gated using FSC-H and FSC-W. a) NKreg cells were gated as CD56+ (PE) CD16- (FITC) CD3- (FITC) cells. b) CD4+ T cells were gated as CD3+ (FITC) CD4+ (BV605) cells. The data is from a single experiment representative of 3 experiments. 118 3.4 Discussion In this thesis, I hypothesized that NKreg cells suppress cGvHD through inflammatory cell inhibition, and that these cells can be distinguished as a unique NK cell subset which may be optimally expanded for the cellular therapy of cGvHD. In order to attend to this hypothesis, my second objective was to evaluate the in vitro suppressive effect of NKreg cells on cGvHD-related immune populations and investigate the mechanism of NKreg cell induced suppression. To begin the discussion and interpretation of the functional study results, reviewing Treg cell suppressive data may provide much useful insight to the NKreg cell suppressive mechanism, as many parallels can be drawn between NKreg cells and Treg cells, which are a better characterized and studied suppressive immune cell population. Similar to my findings with NKreg cells, different mechanisms of suppression have been described for Treg cells, with no consensus on one universal mechanism.156 Contrasts in data may be partially explained by different mechanisms operating in the differing immune reaction and activation contexts, including cytokine-induced stimulatory environments and disease settings. This may also describe the discrepancies seen in my and others work of investigating the NKreg cell functional mechanism. Currently, there are four main mechanisms, which include both soluble factors and/or cell-cell contact, that describe Treg cell suppression of conventional T cells (Tcon) (T cells that express an αβ T cell receptor, as well as the CD4 or CD8 co-receptor, and are present in the peripheral blood, lymph nodes, and 119 tissues). Firstly, Treg cells have shown to suppress Tcon cells through adenosine production,156 adenosine being an immunomodulatory molecule that has also been suggested as important in NKreg suppression in some contexts. Treg cells can also suppress Tcon cell proliferation through suppressing TCR-induced Calcium2+, nuclear factor of activated T cell (NFAT), and NF-κβ signaling.156 Again, at least in terms of induced NF-κβ signaling, this has also been described as a mechanism for NKreg cell suppression. Further, Treg cells can produce immunosuppressive cytokines, such as IL-10, TGF-β, and IL-35 which can suppress Tcon cells by IL-2 consumption or induce effector cell death via granzyme and perforin.156 In the case of NKreg cells, as previously discussed, different works have highlighted the importance of IL-10 and/or TGF-β in T cell suppression, in addition to the relevance of granzyme and perforin expression in T cell suppression by cytokine-induced NKreg cells. In terms of the suggestion of the scavenging of IL-2 resulting in a lack of Tcon cell proliferation, at least in the context of healthy-donor derived and freshly isolated NKreg cell function, this may not be as relevant. It is well established that IL-2 promotes proliferation of both CD4+ and CD8+ T cells. If the scavenging of IL-2 by NKreg cells was their primary mechanism of suppression I would expect NKreg cells to strongly suppress both CD4+ and CD8+ T cells, which is not the case. Lastly, Treg cells have shown to suppress Tcon cells indirectly by downregulating costimulatory molecules on APCs (such as dendritic cells) via cytotoxic T-lymphocyte-associated protein 4 (CTLA-4).156 This may also be relevant to NKreg suppression in some immune stimulatory contexts, but in my case of studying healthy donor-derived and freshly isolated NKreg cells in a functional assay which doesn’t include classic APCs, such as 120 dendritic cells, macrophages, Langerhans cells, or B cells, this mechanism may not be as relevant. Other studies have proposed soluble mediators of suppression by cytokine induced NKreg cells, though cytokine-stimulation can result in NK cells that are both phenotypically and functionally different from the freshly isolated NKreg cells I describe.83,116 However, it is important to note that though I determined NKreg suppressive ability to be dependent on cell-cell contact, soluble factors may still play a role in this mechanism, and thus considering these factors may be useful in associated investigations. As described in chapter 1, previous studies have shown that CD56brightCD16- NKreg cells can limit antigen specific T cell proliferation in vitro through an IL-10 dependent pathway,119 and IL-15 stimulated CD56brightCD16- NKreg cells can inhibit proliferation of autologous CD4+ T cells by secreting the immunosuppressive molecule adenosine.113 One study suggested a mechanism for NKreg cell regulatory function involving both cell-cell contact and soluble factors. Their work showed Hepatitis B (HBV)-induced PD-L1 and HLA-E on monocytes to interact with their receptors PD-1 and CD94 on NK cells to educate IL-10+ regulatory NK cell differentiation, which produce the inhibitory cytokine IL-10, preventing proliferation of both CD4+ and CD8+ T cells in an IL-10 dependent manner.157 However, though this mechanism may also be relevant in GvHD pathogenesis, where similar to HBV, myeloid differentiation primary response 88 (MyD88) and NF-kβ signaling may result in induction of suppressive monocytes and production of regulatory cytokines, including IL-10 and TGF-β1, which are also produced by 121 suppressive NKreg cells, my findings only show this to be relevant to the CD4+ T cell subset. In the above-mentioned study, in the context of educated NKreg cells induced by HBV, when IL-10 antibody was added to co-cultured NK cells and T cells they observed that neutralisation of IL-10 restored the proliferation of CD4+ T cells and CD8+ T cells.157 This contrast in findings may suggest that NKreg cells employ multiple suppressive mechanisms which are context dependent, and in my case of studying the suppressive effect of healthy donor NKreg cells in vitro, with a lack of CD8+ T cell suppression observed, IL-10 may not be the (only) candidate cause of suppression. Further, this study highlights the potential importance of cell-cell contact to induce inhibitory cytokine secretion by NKreg cells. Other studies have also suggested the importance of both cell-cell contact and soluble factors in the role of NKreg cell suppressive function. One group demonstrated the ecto-5′-nucleotidase (CD73) metabolic immune checkpoint to orchestrate a crucial homeostatic balance of extracellular adenosine levels as part of a negative feedback mechanism to control inflammatory responses by NKreg cells.158 CD73 has been implicated in immune suppression and tumor progression and has also been observed in cancer patients who progress on anti–PD-1 immunotherapy. Treg cells have shown to express CD73 and inhibit T cell responses via associated production of adenosine. CD73+ NK cells were observed to upregulate IL-10 and TGF-β production via signal transducer and activator of transcription 3 (STAT3) transcriptional activity, suppressing CD4+ T cell activity.158 These regulatory NK cells may acquire the expression of CD73 after physical contact with human umbilical cord–derived 122 mesenchymal stem cells (MSCs), dental pulp stem cells, tumor cells, endothelial cells, or fibroblasts.158 Further, it was shown that STAT3 negatively regulates several NK cell functions and drives the expression of PD-L1,158 potentially linking to the PD-1 dependent pathway in educating IL-10 secretion for NKreg suppression of T cell proliferation described above. Though I did not investigate whether CD73 expression was present on the healthy donor-derived freshly isolated NKreg cells that I characterized, I may suspect that without prior induction through cell-cell-contact with cord–derived MSCs, dental pulp stem cells, tumor cells, endothelial cells, or fibroblasts in my co-culture of which I observed CD4+ T cell suppression, this suppressive mechanism may not be identical to what I am observing. In my studies, the sorted CD56brightCD16- NKreg cell population was observed to strongly suppress allogeneic CD4+ T cell proliferation through a non-cytolytic, and primarily cell-cell contact dependant mechanism. Additionally, the suppressive capacity of the NKreg cells was shown to be significantly stronger than the classic CD56dim NK cell population (further classifying NKreg cells as a functionally unique NK cell subset) but was similar to the suppressive capacity of Treg cells. Further, I identified a lack of NKreg cell suppression towards a specific CD4+ Th cell subset, CD8+ T cells, Treg cells +/- dendritic cells, B cells, and cytolytic NK cells. The selectivity of NKreg cell suppression not only differentiates them from most other regulatory immune cells described to date which generally engage in a broader 123 suppressive function, but it also may serve a beneficial effect in maintaining immune cell functions which hold a crucial purpose in HSCT patient outcomes, particularly relevant to preventing malignancy relapse. I observed NKreg cells to not significantly suppress cytolytic NK cell or CD8+ T cell proliferation. This effect may be beneficial in maintaining a GvL effect, an important contributor to positive patient outcomes and lower rates of cancer relapse after HSCT, as donor cytolytic NK cells and CD8+ T cells act to remove residual malignant cells.159 Additionally, I observed a statistically significant increase in the proliferation of NK cells co-cultured with NKreg cells. I may hypothesize that this was observed due to the increased cytokine producing role of NKreg cells. NKreg cells have been described to produce a variety of cytokines which may enhance NK cell proliferation. However, functional studies would be required to confirm this relationship. Further, I observe NKreg cells to not significantly supress B cell proliferation. Though B cells have been associated with GvHD development due to their constitutive antibody production and antigen presentation which can contribute to immune activation and inflammation,152 they heavily rely on helper T cells for their activation. Therefore, in NKreg cells strongly suppressing CD4+ T cell activation and proliferation, they may in turn downregulate B cell activation. Further, our studies only investigated the proliferative effect of NKreg cells on B cells, but did not measure B cell function, such as antibody production. It is possible that NKreg cells may not directly prevent B cell proliferation but have an inhibitory effect on function. Thus, future functional studies may be designed towards evaluating this relationship. 124 In addition to showing that NKreg cells engage in a suppressive effect towards CD4+ T cells but not CD8+ T cells, NK cells, or B cells, I also observed these NKreg cells to engage in a lack of suppression towards Treg cells. I then further evaluated the suppressive effect of NKreg cells towards Treg cells in the presence of dendritic cells, as our previous studies have suggested that NKreg cells may promote Treg cell proliferation,6 and other researchers have shown that NK cells prime dendritic cells via the release TGF-β, IFNγ, and TNF to expand Treg cells.151 Thus, I hypothesized that I may observe a statistically significant increase in the proliferation of Treg cells co-cultured with NKreg cells if dendritic cells are added. Though I observed increased proliferation among the Treg cells with NKreg cells and dendritic cells, this was not determined to be significant. This may suggest that NKreg cells do not induce substantial proliferation of Treg cells, though in the clinical setting of which other cell and cytokine mediators are present, the effects may vary. In an environment more representative of the human body, it is possible that the results may better correspond to our observations in previous clinical studies of which NKreg cells were significantly low in HSCT patients both before and at the onset of cGvHD, while Treg cells were only observed as being significantly low at the onset.6 This suggested that NKreg cells may have a modulatory effect on Treg cell proliferation or function. Thus, this initial experiment may suggest that NKreg cells do not directly induce proliferation of Treg cells, but it is possible they promote an alterative mechanism of support. This may be demonstrated by a change in Treg cell phenotype, of which activation or suppressive ligand/receptor expression may be increased, and/or the suppressive capacity of Treg cells is increased. This would be consistent with other research which has shown 125 strong correlations between Treg cells and CD56bright NK cells. It has been well established that low dose IL-2 increases both the number of Treg cells and the number of CD56bright NK cells which correlate to therapeutic outcomes for cGvHD.17 Further, low-dose IL-2 which expands CD56bright NK cells, accompanied by an increase in Treg cells, has been observed to be dependent on the presence of CD56bright NK cells.18 As described earlier, it has also been observed that low dose IL-2 as treatment of systemic lupus erythematosus successfully suppresses disease activity through both an increase in Treg cells and NK cells.19 Therefore, the potential modulatory mechanism of NKreg cells towards Treg cells appears to be a feasible explanation to these observations demonstrated by our group and others, and future research may focus on elucidating this mechanism. After determining that NKreg cell suppression was selective of CD4+ T cells, I was interested in whether the suppression is specific to a particular CD4+ T helper cell subset (Th1, Th2, Th17). I hypothesised that NKreg suppression may be strongest towards Th1 and Th17 cells, as these subsets have shown to contribute to cGvHD pathogenesis through their secretion of inflammatory cytokines.160 I evaluated both fresh and expanded NKreg suppression of Th1, Th2, and Th17 cell proliferation and identified no significant difference in NKreg suppression across the three groups, suggesting that the NKreg suppressive mechanism is primarily occurring through direct contact via a receptor/ligand interaction which is consistently expressed among all CD4+ T cells. However, a limitation to this experiment was that I utilized a Th cell phenotyping kit to identify the different subsets, with all CD4+ T cells being co-126 cultured together with the NKreg cells. It may be considered that the presence of differing Th cell subsets may affect the results, and this experiment could be repeated in future with FACS sorted Th1, Th2, and Th17 cells to verify the findings. After determining that all CD4+ T cells are likely affected by NKreg cells, I wished to further investigate the direct contact mechanism of NKreg cells. I started by investigating receptor candidates which were described by others to be involved in the suppressive mechanism of CD56brightCD16- NKreg cells, including NKp44 and NKp46. Contrary to others, my studies show there to be no significant difference in the NKreg cell suppressive capacity when the NKp44 or NKp46 receptors were blocked in solution. However, these previous studies utilized CD56bright NK cells expanded with low-dose IL-2, which may activate and mature the cells towards the cytolytic CD56bright population, affecting their function or mechanism.83 My analyses were performed on freshly isolated, unexpanded NKreg cells to be more reflective of their native function. Additionally, I identified there to be no significant difference in the NKreg cell suppressive capacity when the candidate receptor GPR183R was blocked in solution. In the next steps of investigating the mechanism of NKreg cell suppression, I limited the potential candidates of interest to inhibitory checkpoints which when engaged may contribute to CD4+ T cell inhibition. Further, I only considered those which have a potential ligand/receptor that is also expressed by activated CD56bright NK cells. 127 This led to my evaluation of the PD-1 and LAG-3 immune checkpoint binding pathways, as these candidates have been described as being expressed by CD56bright NK cells161 and CD4+ T cells,162,163 and have an associated ligand expressed by activated CD56bright NK cells and/or CD4+ T cells. When engaged with a ligand, PD-1 becomes phosphorylated at tyrosine residues, leading to binding of protein tyrosine phosphatases (PTPs), such as Src homology region 2-containing protein tyrosine phosphatase 2 (SHP2).163 These PTPs can dephosphorylate kinases and antagonize positive signals that occur through the TCR and CD28, affecting downstream signalling pathways including those involving phosphoinositide 3-kinase (PI3K)-AKT.163 The functional outcome of these effects is decreased T cell activation, proliferation, survival, cytokine production, and altered metabolism.163 The LAG-3 pathway is less understood than that of PD-1, but has been described to associate with the TCR:CD3 complex at the T cell membrane and negatively regulates TCR signal transduction, which in turn terminates cell proliferation and cytokine secretion in response to CD3 signaling.164 When blocking either the PD-1 or LAG-3 receptors I observed a significant decrease in the suppressive effect of the NKreg cells/increase in the proliferation of the CD4+ T cells. However, neither of these methods resulted in a full inhibition of the NKreg suppressive effect. This suggests that there may be multiple mechanisms occurring at once, contributing to the suppressive capacity, and/or that the PD-1 and LAG-3 blocking antibodies are not completely effective at blocking the receptors over the 96-hour co-culture period, allowing some engagement of these receptors to occur. Future work investigating the knockout of PD-1 and LAG-3 in NKreg cells and/or CD4+ T cells in co-culture experiments may be a useful 128 analysis to decipher if full blockade of either pathway fully prevents the NKreg cell suppressive mechanism. As a result of other groups describing the potential importance of cytokines in the mediation of NKreg cell’s regulatory function, I performed proteomics analysis on expanded NKreg cells compared to expanded cytolytic NK cells. This allowed for the greater characterization of the cytokine profile of the regulatory NK cell population, and also the ability to identify potential candidate cytokines which are significantly upregulated among suppressive NKreg cells compared to cytolytic CD56dim NK cells and evaluate the effect of these cytokines on NKreg suppression of CD4+ T cell proliferation (further details on proteomics study described in chapter 4 as this characterization was completed on optimally expanded NKreg cells). Through this analysis I identified 4 proteins which were significantly upregulated among NKreg cells compared to CD56dim NK cells, which also associate to regulatory function. This included TRAIL,155 IL-10,165 Adenosine deaminase (ADA),166 and TGF-β.167 Following this analysis, I utilized appropriate neutralizing antibodies or antagonists to block these receptors or ligands and evaluate the NKreg suppressive effect towards the CD4+ T cells in co-culture. In these experiments, I identified a significant decrease in NKreg suppression of CD4+ T cell proliferation when TRAIL was blocked, suggesting that TRAIL-mediated suppression may contribute to NKreg suppressive function (note that TRAIL can be secreted by NKreg cells, and may also be expressed on the cell surface). This data is consistent with the findings of other groups which have shown that TRAIL-R signaling inhibits phosphorylation of proximal TCR-associated 129 tyrosine kinases in activated CD4+ T cells, ultimately suppressing CD4+ T cell activation.155 It is important to highlight that our proteomics analysis was completed on non-CD4+ T cell-co-cultured cells, and it is possible that additional inhibitory cytokines, which may only be secreted by NKreg cells in response to direct contact with CD4+ T cells, may be identified through a proteomics analyses of co-cultured cells, and this could be a topic of future study. Since the TRAIL, PD-1, and LAG-3 receptors and ligands have been described as being potentially expressed by both activated NKreg cells and CD4+ T cells on the cell surface, I then performed a phenotypic analysis to observe the expression of the markers to gain a clearer understanding of how this direct contact mechanism may be occurring. The results suggested that the NKreg cells are likely responsible for the PD-L1, HLA-DR (LAG-3 ligand), and TRAIL expression, while the CD4+ T cells are likely responsible for the PD-1, LAG-3, and TRAILR1 expression, ultimately inducing inhibition of the CD4+ T cells. As a result of these studies, I have confirmed the NKreg cell immune suppressive function towards CD4+ T cell proliferation, a main contributor to cGvHD development, and demonstrated PD-1/LAG-3/TRAIL at least partially dependent mechanisms of NKreg cell suppression, which is selective of total CD4+ T cells, with a lack of suppressive effect towards CD8+ T cells, Treg cells, B cells, and NK cells. The results of these studies contribute to the better understanding of how NKreg cells may 130 induce a cell-specific suppressive function to promote immune tolerance, and also provide potential cell therapeutic applications for enhancing NKreg cell suppressive function, such as through increasing PD-1, LAG-3, and/or TRAILR ligand expression on NKreg cells. 131 4 Chapter 4: Suppressive NKreg cells may be optimally expanded from peripheral blood or stem and progenitor cells 4.1 Introduction In previous correlative studies, we observed an increased number of non-cytolytic regulatory CD56brightCD335+CXCR3+ NK cells in adult patients who did not develop cGvHD6 and a similar lack of CD56brightCD3- NK cells in a large pediatric cohort before the onset of cGvHD.43 Following these observations, I identified the unique transcriptome of NKreg cells associated with immune tolerance (chapter 2), determined a cell surface sorting approach to obtain viable NKreg cells, being CD56brightCD3-CD16- cells (chapter 2), and verified their strong in vitro selective suppression of allogeneic CD4+ T cell proliferation through a PD-1/LAG-3/TRAILR, non-cytolytic, cell-to-cell contact-dependent mechanism (chapter 3). Based on this data, I hypothesized that CD56brightCD16- regulatory NK cells suppress the development of cGvHD and may serve as an effective cellular therapy to prevent or treat cGvHD among HSCT patients.138,139 However, I must note a major obstacle in using these cells as an adoptive transfer cell therapy. CD56bright NKreg cells represent less than 10% of peripheral NK cells, with total peripheral NK cells making up a small proportion of leukocytes, being 1 - 6%. Based on data describing the use of Treg cells as an adoptive transfer cell therapy, a comparable functional cell type to NKreg cells, I suspect that it will be necessary to infuse 10,000 – 3,000,000 CD56bright NKreg cells/kg per infusion to be 132 effective in a HSCT patient.168 When beginning the CD56bright NKreg cell preparations with such a small initial population, expansion will be necessary to achieve clinical application. Therefore, I aimed to determine an optimized in vitro expansion approach for CD56brightCD16- NKreg cells, while maintaining their native phenotype and function. To meet my objective, I first investigated the effects of candidate cytokines for expansion and prevention of differentiation/maturation. After determining the optimal cytokine combination for promoting NKreg cell expansion and regulatory phenotype, I investigated the fold-expansion, phenotype, suppressive capacity, cytotoxicity, and metabolic characteristics of expanded NKreg cells cultured with three different NK cell expansion medias. The expanded cells were then further characterized according to their transcriptome, and proteomic profile. Further, I utilized my optimized expansion protocol to compare the fold-expansion, phenotype, and function of NKreg cells derived from peripheral blood to cord blood. Lastly, I investigated an alternate source for NKreg cell derivation, being expansion and differentiation of NKreg cells from cord blood CD34+ hematopoietic stem and progenitor cells (HSPCs), in an effort to reach a greater final cell number. As a result of these studies, I determined that the optimal method to expand NKreg cells was via isolation from peripheral blood, followed by a 3-week culture with complete Immunocult NK Cell Expansion media, supplemented with IL-2, TGF-β1, and a pulse of rapamycin prior to the end of culture. These expanded cells maintained similar phenotype, transcriptome, and T cell suppression to fresh NKreg cells. The metabolic profile of NKreg cells and cytolytic NK cells was not significantly different, though rapamycin induced a lower Oxygen Consumption Rate (OCR)/Extracellular Acidification Rate (ECAR). Additionally, expanded NKreg cells compared to cytolytic NK cells 133 upregulate various proteins, including those associated with regulatory function, such as TGF-β1, TRAIL, IL10, and ADA (p<0.01). Further, suppressive NKreg cells may alternatively be expanded from CD34+ cells. As a result of this work, I have further characterised the suppressive NKreg cell population and developed two alternative methods for deriving clinically relevant numbers of functional NKreg cells which may be utilized in a comparable Good Manufacturing Practice (GMP) approach for downstream clinical study analysis. 4.2 Methods 4.2.1 Optimization of the in vitro expansion of peripheral NKreg cells 4.2.1.1 Expansion of total NK cells with use of ligands associated with immune tolerance Total NK cells were enriched from human peripheral blood using the NK Cell Enrichment Kit (StemCell Technologies, Vancouver, BC, Canada). Total NK cells were expanded for up to 24 days at 1x106 cells/ml, splitting and re-stimulating the cells every 2-4 days. Cells were expanded in complete MACS NK expansion media (Miltenyi Biotec, Auburn, CA, USA), which includes 1% penicillin/streptomycin, 1% L-glutamine, and 10% human AB serum (Gibco, Grand Island, NY, USA), and the following list of 134 cytokines/ligands, which were identified as being significantly associated with immune tolerance in the CD56bright NK cell subset from my transcriptome study: • 25 ng/ml IL-2 (BioLegend, San Diego, CA, USA) • 25 ng/ml IL-4 (BioLegend, San Diego, CA, USA) • 25 ng/ml IL-7 (BioLegend, San Diego, CA, USA) • 25 ng/ml IL-10 (BioLegend, San Diego, CA, USA) • 25 ng/ml IL-18 (BioLegend, San Diego, CA, USA) • 25 ng/ml IL-23 (BioLegend, San Diego, CA, USA) • 0.02 nM 7a-25, di-hydroxycholesterol (Sigma Aldrich, Oakville, CA, USA) • 25 ng/ml GM-CSF (BioLegend, San Diego, CA, USA) Expansion was monitored through microscopic visualization of the cells in the culture plate using the ZEISS Primovert Inverted Microscope (ZEISS, Oberkochen, Germany). 4.2.1.2 Expansion of total NK cells with use of candidate ligands to prevent NK cell differentiation Based on the previous results, the optimal candidate cytokine for expansion (25ng/ml IL-2 (BioLegend, San Diego, CA, USA)) was combined with the following combinations of cytokines/ligands for expansion of enriched total NK cells at 1x106 cells/ml for up to 24 days, splitting and re-stimulating the cells every 2-4 days. Cells were expanded in complete MACS NK expansion media (Miltenyi Biotec, Auburn, CA, USA), which includes 1% penicillin/streptomycin, 1% L-glutamine, and 10% human AB serum 135 (Gibco, Grand Island, NY, USA). Expansion was quantified with use of a hemocytometer. • 100-300 nM rapamycin (Sigma Aldrich, Oakville, CA, USA) • 2 ng/ml TGF-β1 (StemCell Technologies, Vancouver, BC, Canada) • 1 µM NECA (A2AR agonist) (Sigma Aldrich, Oakville, CA, USA) • 200 µM metformin (Sigma Aldrich, Oakville, CA, USA) • 10-10 M dexamethasone (Sigma Aldrich, Oakville, CA, USA) 4.2.1.3 Expansion and suppressive capacity of expanded NKreg cells FACS sorted human peripheral CD56brightCD16- NKreg cells were expanded for up to 24 days at 1x106 cells/ml, splitting and re-stimulating the cells every 2-4 days. Cells were expanded with 25 ng/ml IL-2 (Biolegend, San Diego, CA, USA), and the following cytokines/ligands in complete MACS NK expansion media in preparation for suppression assay co-culture. Complete MACS media includes NK expansion media (Miltenyi Biotec, Auburn, CA, USA) + 1% penicillin/streptomycin + 1% L-glutamine + 10% human AB serum (Gibco, Grand Island, NY, USA). 300 nM rapamycin (Sigma Aldrich, Oakville, CA, USA) was added to each cell condition 72hrs before the suppression assay co-culture. The suppression assay method is identical to that described above. Expansion was quantified with use of a hemocytometer. • 25 ng/ml IL-2 (BioLegend, San Diego, CA, USA) 136 • 25 ng/ml IL-2 (BioLegend, San Diego, CA, USA) + 2 ng/ml TGF-β1 (StemCell Technologies, Vancouver, BC, Canada) • 25 ng/ml IL-2 (BioLegend, San Diego, CA, USA) + 1µM NECA (adenosine agonist) (Sigma Aldrich, Oakville, CA, USA) • 25 ng/ml IL-2 (BioLegend, San Diego, CA, USA) + 2 ng/ml TGF-β1 (StemCell Technologies, Vancouver, BC, Canada) + 1 µM NECA (adenosine agonist) (Sigma Aldrich, Oakville, CA, USA) 4.2.1.4 Phenotypic evaluation of expanded NK cells At day 0, after initial NK cell isolation or cell sorting, and every 2-4 days in culture (at the time of cell splitting/re-stimulation), cell phenotype was evaluated. NK cells were stained for protein expression identification using: CD56-PE, CD3-PE/Cy7, CD16-FITC, Granzyme K-AF647, Granzyme B-PE/Dazzle 594, and perforin-Pacific Blue (BioLegend, San Diego, CA, USA). Cell surface antibodies were added, the samples incubated for 20 min at 4oC in the dark, then were washed, followed by the Invitrogen IC Fixation Buffer procedure (Invitrogen, Waltham, MA, USA). Next, the cells were washed and FACS permeabilizing solution 2 (BD Biosciences, Franklin Lake, USA) was added according to manufactures procedures. The cells were then washed, and intracellular antibodies were added, and samples incubated for 20 min at room temperature in the dark, then were washed before acquisition. The phenotypic expression of the NK cells was investigated through the BD FACSymphony flow cytometer. The gating strategy included gating for lymphocytes using FSC-A and SSC-A, gating for single cells using 137 FSC-H and FSC-W, and gating for the total NK cell population by selecting the CD56+ and CD3- cells. Analysis was performed using Kaluza version 2.1 software (Beckman Coulter, Mississauga, ON, Canada). 4.2.1.5 Expansion, function, and phenotype of NKreg cells expanded with three differing media conditions FACS sorted human peripheral CD56brightCD16- NKreg cells were expanded for up to 21 days at 1x106 cells/ml, splitting and re-stimulating the cells every 3-4 days. Cells were expanded with 25 ng/ml IL-2 (Biolegend, San Diego, CA, USA) + 2 ng/ml TGF-β1 (StemCell Technologies, Vancouver, BC, Canada) in complete MACS NK Cell Expansion media (Miltenyi Biotec, Auburn, CA, USA), Immunocult NK Cell Expansion media (StemCell Technologies, Vancouver, BC, Canada), or ExCellerate NK Cell Expansion media (R&D Systems, Inc, Minneapolis, MN, USA). Complete media includes 1% penicillin/streptomycin + 1% L-glutamine + 10% human AB serum (Gibco, Grand Island, NY, USA). 300 nM rapamycin (Sigma Aldrich, Oakville, CA, USA) was added to each cell condition 48hrs before use of cells in functional analysis. Expansion was quantified with use of a hemocytometer. 138 4.2.2 Comparison of cord and peripheral blood NKreg cell proliferation, phenotype, and function FACS sorted fresh human peripheral blood or fresh cord blood CD56brightCD16- NKreg cells were expanded for up to 21 days at 1x106 cells/ml, splitting and re-stimulating the cells every 3-4 days. Cells were expanded with 25 ng/ml IL-2 (Biolegend, San Diego, CA, USA) + 2 ng/ml TGF-β1 (StemCell Technologies, Vancouver, BC, Canada) in complete Immunocult NK Cell Expansion media (StemCell Technologies, Vancouver, BC, Canada). Complete media includes 1% penicillin/streptomycin + 1% L-glutamine + 10% human AB serum (Gibco, Grand Island, NY, USA). 300 nM rapamycin (Sigma Aldrich, Oakville, CA, USA) was added 48hrs before use of cells in functional and phenotypic analysis. Expansion was quantified with use of a hemocytometer. 4.2.3 Characterization of optimally expanded peripheral NKreg cells 4.2.3.1 Transcriptome Healthy donor fresh peripheral NKreg cells (N=3) and healthy donor NKreg cells expanded for 21 days via complete Immunocult media and IL-2, TGF-β1, and rapamycin (N=3) were utilized for bulk RNA sequencing. After collection, the NKreg cells were resuspended in TRIzol reagent (Invitrogen), and total RNA was extracted following the manufacturer’s instruction. Library preparation and sequencing were performed by 139 Novogene via Novaseq 6000 (Illumina). Raw sequencing reads underwent processing using the nf-core/rnaseq pipeline (v3.13.2) and were aligned to the GRCh38.110 reference genome. The resulting gene expression matrix of the samples was log2 transformed and calculated with DESeq2 (v1.34.0). 4.2.3.2 Metabolic phenotype FACS sorted human peripheral CD56brightCD16- NKreg cells and CD56dimCD16+ NK cells were expanded for up to 21 days at 1x106 cells/ml, splitting and re-stimulating the cells every 3-4 days. NKreg cells were expanded as described above, and CD56dimCD16+ NK cells were expanded in identical media conditions though with 50 ng/ml IL-2 (Biolegend, San Diego, CA, USA) and 25 ng/ml IL-15 (StemCell Technologies, Vancouver, BC, Canada). Supernatant from the expanding cells was collected at the time of cell splitting and feeding. The ExtraCellular Acidification Rate (ECAR) and Oxygen Consumption Rate (OCR) was measured using a Seahorse XFe96 Bioanalyser (Agilent). NK cells (1.5×105 cells per well; minimum of three wells per sample) were spun into previously poly-d-lysine-coated 96-well plates (Seahorse) and preincubated at 37°C for a minimum of 45min in a CO2-free incubator. Basal OCR and ECAR were measured in cells incubated in unbuffered 1640 medium supplemented with 1mM pyruvate and 4mM l-glutamine adjusted to pH 7.4, followed by the addition of 1µM oligomycin, 1.5uM of Carbonyl cyanide-4 (trifluoromethoxy) phenylhydrazone (FCCP), 1uM of antimycin A 100nM rotenone, and 50 mM 2-deoxy-glucose (2-DG) (Sigma Aldrich, Oakville, CA, USA). Seahorse Extracellular Flux analysis was performed on the NKreg cells expanded 140 in the 3 different NK cell expansion medias. Analysis was also performed on CD56dim NK cells and compared to NKreg cells. Concentrations of glucose and glutamine were measured in the cell culture media with the Roche Cedex Bio analyzer using colorimetric assays following manufacturer’s protocols. Data is representative of 3 biological replicates. Data are presented as mean ± standard error of the mean (SEM) and P values are determined by two-tailed Student’s t-test. 4.2.3.3 Proteomics/cytokine production Healthy donor fresh (24hr) peripheral NKreg cells (N=3) and CD56dim NK cells (N=3), in addition to healthy donor NKreg cells expanded for 21 days via complete Immunocult media and IL-2, TGF-β1, and rapamycin (N=3) or CD56dim NK cells expanded for 21 days via complete Immunocult media and IL-2 and IL-15 (N=3) were utilized for proteomics analysis. Cells were prepared as described above, and 50µl of the supernatant of each cultured sample was collected and frozen at -80oC. Sample supernatant was then analysed by Olink Proteomics, utilizing the Proximity Extension Assay, Target 96 inflammation panel (Olink Proteomics, Uppsala, Sweden). The final assay read-out is presented in Normalized Protein eXpression (NPX) values, which is an arbitrary unit on a log2-scale where a high value corresponds to a higher protein expression. Following the proteomics analysis, proteins identified as being significantly upregulated (p<0.01) among expanded NKreg cells compared to CD56dim NK cells which have a 141 known regulatory/suppressive function were tested within the NKreg vs CD4+ T cell suppression assay, according to the above-mentioned procedure (section 3.2.21). For the functional assays, the following neutralizing antibody blockers or antagonists were utilized at manufacturer recommended concentrations: 8ng/ml Human TRAIL/TNFSF10 Antibody (R&D Systems, Inc, Minneapolis, MN, USA), 100ng/ml Human IL-10 R alpha Antibody (R&D Systems, Inc, Minneapolis, MN, USA), 1µM Adenosine A2A Receptor Antagonist I (Sigma Aldrich, Oakville, CA, USA), 1µM Galunisertib (TGF-β inhibitor) (Sigma Aldrich, Oakville, CA, USA). All experiments were repeated three times using cells derived from differing healthy donors. 4.2.4 Expansion and differentiation of NKreg cells from CD34+ hematopoietic stem and progenitor cells CD34+ stem and progenitor cells were isolated from fresh cord blood using the EasySep™ Human Cord Blood CD34 Positive Selection Kit III (StemCell Technologies, Vancouver, BC, Canada). The cells were then applied to the StemSpan™ NK Cell Generation Kit (StemCell Technologies, Vancouver, BC, Canada), a 28-day protocol for differentiating NK cells from cord blood CD34+ cells. After the 28-day protocol was complete, CD56brightCD16- NK cells were FACS sorted via the above-mentioned sorting method (section 2.2.4). Sorted NKreg cells were then cultured for 3 days with complete 142 Immunocult NK Cell Expansion media (StemCell Technologies, Vancouver, BC, Canada), 25ng/ml IL-2 (Biolegend, San Diego, CA, USA), 2ng/ml TGF-β1 (StemCell Technologies, Vancouver, BC, Canada), +/- 300nM rapamycin (Sigma Aldrich, Oakville, CA, USA). After the 3-day culture, the cells were evaluated according to phenotype and function via a NKreg cell vs. allogeneic CD4+ T cell suppression and apoptosis assay (methods described above, sections 3.2.2.1 and 3.2.6) (n=6). 4.3 Results 4.3.1 Optimization of the in vitro expansion of peripheral NKreg cells 4.3.1.1 Expansion of total NK cells with use of ligands associated with immune tolerance Cytokine/ligand receptors identified as being significantly associated with immune tolerance in the CD56bright NK cell subset (nanoString study, section 2.3.2), included the IL-2, IL-4, IL-7, IL-10, IL-18, IL-23, GPR183, and GM-CSF receptors. The associated ligands which may be used in culture for expansion purposes include the IL-2, IL-4, IL-7, IL-10, IL-18, IL-23, and GM-CSF cytokines and 7α-25, di-hydroxycholesterol (GPR183R ligand). The results are summarized in table 6 (maturation/differentiation of NK cells identified by perforin expression). 143 IL-2R expression correlates with target cell induced cytotoxic activity and/or cytokine secretion in human NK cells,169 and IL-2 is a stimulatory cytokine that promotes the activation and proliferation of NK cells. As expected, total NK cells cultured with use of 25ng/ml IL-2 and complete MACS NK expansion media resulted in significant cell expansion, but also maturation/differentiation of the immature NKreg cell subset (within the total NK cells), identified through changes in phenotype including gain of CD16, Granzyme B, and perforin expression. Of all cytokines evaluated, IL-2 addition resulted in the greatest NK cell expansion. The IL-4 cytokine acts through the type 1 IL-4R, inducing Stat6-dependent IFNγ secretion by NK cells, contributing to Th1 cytokine-associated immune effector functions.170 Total NK cells cultured with use of 25ng/ml IL-4 and complete MACS NK expansion media resulted in no cell expansion and low cell viability. This correlated with a lack of NKreg cell maturation/differentiation. Of all cytokines evaluated, IL-4 addition resulted in the least NK cell expansion and differentiation. IL-4 used in addition with other cytokines that promoted expansion, including IL-2 and/or IL-7 resulted in less expansion and differentiation than when IL-4 was not added. IL-7 is a homeostatic cytokine with a role in immune cell development, activation, proliferation, and cytokine secretion.171 Regarding NK cells, the IL-7Rα chain is expressed on NK cells, with greatest abundance on the CD56brightCD16- subset.171 IL-7 has been demonstrated to induce CD69 expression (associated with cell activation), as well as IFNγ production, thus having specific functional promotional roles for NK 144 cells.171 Total NK cells cultured with use of 25ng/ml IL-7 and complete MACS NK expansion media resulted in some cell expansion, and this correlated with NKreg cell maturation/differentiation (identified through gain of CD16, perforin and Granzyme B expression). IL-10 is an immunoregulatory cytokine that controls NK cell activity and can antagonize the stimulatory effects of IL-2, IL-12, IL-15, and IL-18, inhibiting NK cell activation, proliferation, differentiation, and cytokine production.172-174 Interestingly, 25ng/ml IL-10 resulted in some NK cell expansion and this was enhanced when combined with stimulatory cytokines such as IL-2 and/or IL-7. This expansion also correlated with NKreg cell maturation (identified through gain of CD16, perforin, and Granzyme B expression). IL-18 is a stimulatory cytokine that often works cooperatively with other cytokines like IL-21, IL-2, and/or IL-15 to induce NK cell proliferation, cytotoxicity, and cytokine production.175,176 IL-18 may also be characterized as a proinflammatory and immunoregulatory cytokine.177 25ng/ml IL-18 addition resulted in some NK cell expansion (though less than that observed with IL-7 and/or IL-2 addition), and also NKreg cell differentiation (identified through gain of CD16, perforin and Granzyme B expression). IL-23 is a pro-inflammatory cytokine178 that has been reported to activate NK cells and contributes to antitumor immune responses by mediating a Th1-type response in 145 combination with IL-12.179 Addition of 25ng/ml IL-23 resulted in some expansion of NK cells, particularly when in combination with IL-2, but also maturation of NKreg cells (gain of perforin expression). GM-CSF induces granulocyte and macrophage populations from precursor cells, also acting as an immune-modulatory cytokine, affecting phenotype and activation of immune cells.180 Addition of 25ng/ml GM-CSF resulted in minimal NK cell expansion, with a lack of perforin expression differentiation. Combining GM-CSF with IL-2 did not further promote expansion or further prevent differentiation. GPR183R is a G-couple receptor reported to play a key role in regulating ILC, B, and T cell migration and responses.153 Addition of 0.02nM of the GPR183 ligand, 7α, 25-di-hydroxycholesterol, resulted in a lack of NK cell expansion, and minimal NKreg cell differentiation (minimal gain of CD16, perforin, and Granzyme B expression). Due to IL-2 being the strongest candidate for expansion (resulting in the highest degree of NK cell proliferation compared to all other cytokines and combinations tested), I chose to move forward in optimizing my NKreg expansion protocol with use of IL-2. Next, I aimed to investigate various candidates to try and maintain or promote the proliferation achieved with IL-2 addition but prevent the associated differentiation and maturation of the NKreg cells (most strongly identified through gain in perforin expression). 146 Table 6: Expansion and differentiation of total NK cells expanded with use of ligands associated with a lack of cGvHD development in the CD56bright NK cell subset Gene Ligand Proliferation Differentiation (perforin and Granzyme B expression) IL-2R IL-2 +++ +++ IL-4R IL-4 - - IL-7R IL-7 ++ + IL-10R IL-10 + ++ IL-18R IL-18 + ++ IL-23R IL-23 ++ + GM-CSFR GM-CSF + ++ GPR183R 7a-25, di-hydroxycholesterol - + + = increase in cell number/expansion, gain in perforin/granzyme B expression. - = no increase in cell number/expansion, no change in perforin/granzyme B expression. 4.3.1.2 Expansion of total NK cells with use of candidate ligands to prevent NK cell differentiation Based on the previous results, IL-2 was determined as the optimal cytokine for expanding NK cells. I then wished to maintain/promote the expansion achieved with use of IL-2 but prevent the associated maturation of NK cells. Candidate ligands investigated to possibly prevent NK cell maturation included initial expansion of total NK cells with rapamycin, TGF-β1, NECA (A2AR agonist), metformin, or dexamethasone. Additionally, I investigated initial expansion with IL-2 and later addition of rapamycin. Results are summarized in table 7 (maturation/differentiation of NK cells identified by perforin expression). 147 Rapamycin is a chemical inhibitor of mTOR.181 The activation of mTOR signaling, a regulator of glycolysis, is progressively downregulated as NK cells mature, consistent with reduced glucose uptake during maturation.99 Additionally, NK cells with specific mTOR deletion have shown to have compromised development due to impaired transition from immature to intermediate subsets.99 I investigated the effects on total NK cell proliferation and differentiation of 100nM-300nM rapamycin in addition to 25ng/ml IL-2. Though all concentrations of rapamycin slowed NK cell differentiation compared to when just IL-2 was added, the only concentration that prevented differentiation (identified through no/minimal gain of perforin (and also granzyme B and CD16) expression over up to 21 days of expansion) was the 300nM concentration. These cells were also Granzyme K positive (characteristic of NKreg cells). Addition of rapamycin also decreased proliferation compared to when just IL-2 was added. These findings were dose-dependant (higher concentrations of rapamycin correlated to a greater decrease in NK cell proliferation and differentiation). Expanding NK cells for up to 21 days, pulsing cells with 300nM rapamycin, and then investigating the change in phenotype after 3 days (day 24) showed a significant loss of perforin expression, and maintenance of the initial NK cell expansion achieved with IL-2 (but minimal expansion once rapamycin was added). TGF-β1 is a multifunctional cytokine demonstrated to inhibit anaerobic glycolysis105 in addition to downregulating the expression of NK cell activating receptors and effector functions, limiting metabolic changes that accompany NK cell activation, including that which is induced by IL-2.105,106,182-186 TGF-β may suppress nutrient availability, 148 inhibiting mTOR and associated metabolism and function of NK cells,105,106,183 thus promoting regulatory functions, and reducing cytotoxicity of NK cells.105,106 I investigated the effect on total NK cell proliferation and differentiation of 2ng/ml TGF-β1 in addition to 25ng/ml IL-2. Addition of TGF-β1 increased proliferation compared to when just IL-2 was added, and also decreased differentiation (gain of perforin expression) though not fully, as seen with the use of 300nM rapamycin. Addition of TGF-β1 also promoted some phenotypic expression of regulatory NK cells among the total NK cells, including the loss of CD16 expression. NECA is a cell-permeable adenosine analog that acts a potent non-selective agonist of adenosine receptors. Extracellular adenosine concentration is increased in hypoxic conditions which promote activity of the ectonucleotidases CD39 and CD73, catalyzing the conversion of extracellular adenosine triphosphate (ATP) to adenosine monophosphate (AMP), and AMP to adenosine.187-190 The stimulation of NK cells through adenosine receptors has been shown to suppress their effector functions and maturation by inhibiting their OXPHOS and glycolytic capacity.191 I investigated the effect on total NK cell proliferation and differentiation of 1uM NECA in addition to 25ng/ml IL-2 over 21 days. Addition of NECA increased proliferation compared to when just IL-2 was added, and also decreased differentiation (gain of perforin expression), though not fully, as seen with the use of 300nM rapamycin. The expansion achieved with IL-2 and NECA was similar that achieved with IL-2 and TGF-β1. 149 Metformin is a drug used to treat type 2 diabetes mellites. The insulin-sensitizing effects of metformin are linked to AMP-activated protein kinase-acetyl-CoA carboxylase-mediated changes, regulating lipid and glucose metabolism, but more recently metformin was also shown to directly inhibit mitochondrial respiratory complex I.192,193 Metformin has been associated with reductions in Th1/Th17 cells and increases in Th2 and Treg cell populations, but the specific effects of metformin treatment on NK cell metabolism and function is currently unknown.181 I investigated the effect on total NK cell proliferation and differentiation of 200µM metformin in addition to 25ng/ml IL-2 over up to 21 days. Addition of metformin decreased proliferation compared to when just IL-2 was added, and also maintained NK cell differentiation (identified by gain of CD16, perforin, and Granzyme B expression). Thus, metformin was determined as a suboptimal candidate for promoting further NK cell proliferation and preventing NK cell maturation induced by IL-2. Dexamethasone is a glucocorticoid which is utilized in vivo for GvHD prevention and treatment. Glucocorticoid treatment of NK cells has been shown to reduce NK cell cytolytic activity by reduction of histone promoter acetylation for perforin and Granzyme B, in addition to increasing histone acetylation and chromatin accessibility at NK cell regulatory regions for IFNγ and IL-6.194 I investigated the effect on total NK cell proliferation and differentiation of 10-10 M dexamethasone in addition to 25ng/ml IL-2 over up to 21 days. Addition of dexamethasone increased proliferation compared to when just IL-2 was added (though less so than the proliferation induced by TGF-β1 or NECA in combination with IL-2), but also maintained NK cell differentiation (identified by gain 150 of CD16, Granzyme B, and perforin expression). Thus, dexamethasone was determined as a suboptimal candidate for preventing NK cell maturation induced by IL-2. Due to NECA and TGF-β1 being the strongest candidates for combining with IL-2 for NK cell expansion, and rapamycin being the strongest candidate for preventing NK cell differentiation, I chose to move forward in optimizing my NKreg expansion protocol with use of IL-2, TGF-β1, and/or NECA with later pulsing of rapamycin. Next, I aimed to investigate the proliferative and maturation effects of these cytokines/ligands on the isolated NKreg cell subset, in addition to evaluating the suppressive capacity of the expanded NKreg cells. Table 7: Expansion and differentiation of total NK cells with use of candidate ligands to prevent NK cell differentiation (N=3 biological replicates per condition) Ligand Day 20 proliferation (mean fold-increase) Day 20 differentiation (mean perforin expression) IL-2 50 98% IL-2 + 100nM rapamycin 5 77% IL-2 + 300nM rapamycin 5 4% IL-2 + (pulse 300nM rapamycin) 50 4% IL-2 + TGF-β1 150 58% IL-2 + NECA 150 38% IL-2 + metformin 15 89% IL-2 + dexamethasone 100 97% 151 4.3.1.3 Evaluation of the phenotype and suppressive capacity of the expanded NKreg cells Based on the previous results, IL-2, TGF-β1, and/or NECA with later addition of rapamycin was determined as the optimal methods for expanding total NK cells, while also preventing the associated maturation of NK cells. Candidate cytokine/ligand combinations investigated to promote NKreg cell expansion and prevent NKreg cell maturation included initial expansion with use of IL-2, IL-2 + TGF-β1, IL-2 + NECA, and IL-2 + TGF-β1 + NECA, with day 18 pulsing of rapamycin. In addition to determining the proliferation and differentiation of NKreg cells in the previously mentioned conditions, I also reported the suppressive capacity of these expanded NKreg cells towards allogeneic CD4+ T cells over a 96hr co-culture. Results are summarized in table 8 (maturation/differentiation of NK cells identified by perforin expression). I investigated the effects on NKreg cell proliferation and differentiation of IL-2 and pulsing cells with rapamycin at day 18. This method resulted in IL-2-induced expansion of NKreg cells, which correlated with differentiation/maturation of the NKreg subset towards a cytolytic NK cell-like phenotype (gain in perforin expression). However, after 18 days of expansion, when 300nM rapamycin was added, the NKreg cells reverted in phenotype back towards their characteristic expression (low perforin expression, low Granzyme B expression, low CD16 expression, high Granzyme K expression). After rapamycin was added, the cells slowed/stopped expanding. The investigation of the suppressive capacity of the IL-2 + rapamycin expanded NKreg cells showed them to be 152 suppressive of allogeneic CD4+ T cells over a 96hr co-culture (83% suppression of CD4+ T cell proliferation) at a 1:1 ratio. Next, I investigated the effects on NKreg cell proliferation and differentiation of IL-2 and TGF-β1, pulsing cells with rapamycin at day 18. This method resulted in IL-2 + TGF-β1-induced expansion of NKreg cells, which correlated with some differentiation/maturation of the NKreg subset towards a cytolytic NK cell-like phenotype (some gain in perforin expression). However, after 18 days of expansion, when 300nM rapamycin was added, the NKreg cells reverted in phenotype back towards their characteristic expression (low perforin expression). The expansion achieved with use of IL-2 + TGF-β1 was greater than that achieved with only IL-2. After rapamycin was added, the cells slowed/stopped expanding. The investigation of the suppressive capacity of the IL-2 + TGF-β1 + rapamycin expanded NKreg cells showed them to be suppressive of allogeneic CD4+ T cells over a 96hr co-culture (88% suppression of CD4+ T cell proliferation) at a 1:1 ratio. Additionally, I investigated the effects on NKreg cell proliferation and differentiation of IL-2 and NECA, pulsing cells with rapamycin at day 18. This method resulted in IL-2 + NECA-induced expansion of NKreg cells, which correlated with some differentiation/maturation of the NKreg subset towards a cytolytic NK cell-like phenotype (some gain in perforin expression). However, after 21 days of expansion, when 300nM rapamycin was added, the NKreg cells reverted in phenotype back towards their characteristic expression (low perforin expression). The expansion achieved with use of 153 IL-2 + NECA was greater than that achieved with only IL-2, and comparable to that achieved with IL-2 + TGF-β1. After rapamycin was added, the cells slowed/stopped expanding. The investigation of the suppressive capacity of the IL-2 + NECA + rapamycin expanded NKreg cells showed them to be suppressive of allogeneic CD4+ T cells over a 96hr co-culture (90% suppression of CD4+ T cell proliferation, though higher proportion of dead cells (7-AAD+ cells)) at a 1:1 ratio. Lastly, I investigated the effects on NKreg cell proliferation and differentiation of IL-2 + NECA + TGF-β1, pulsing cells with rapamycin at day 18. This method resulted in IL-2 + NECA + TGF-β1-induced expansion of NKreg cells, which correlated with some differentiation/maturation of the NKreg subset towards a cytolytic NK cell-like phenotype (some gain in perforin expression). However, after 18 days of expansion, when 300nM rapamycin was added, the NKreg cells reverted in phenotype back towards their characteristic expression (decrease in perforin expression). The expansion achieved with use of IL-2 + TGF-β1 + NECA was greater than that achieved with only IL-2, but comparable to that achieved with IL-2 + TGF-β1 or IL-2 + NECA. After rapamycin was added, the cells slowed/stopped expanding. The investigation of the suppressive capacity of the IL-2 + NECA + TGF-β1 + rapamycin expanded NKreg cells showed them to be suppressive of allogeneic CD4+ T cells over a 96hr co-culture (93% suppression of CD4+ T cell proliferation (though higher proportion of dead cells (7-AAD+ cells)) at a 1:1 ratio. 154 The culture condition that resulted in the greatest expansion, lowest phenotypic differentiation, and strongest suppression of CD4+ T cell proliferation was achieved through culturing NKreg cells with use of 25ng/ml IL-2 + 1uM NECA + 2ng/ml TGF-β1, with later pulsing of 300nM rapamycin. However, though IL-2 and TGF-β1 are currently available in GMP form, NECA is not. Therefore, due to similar findings across the IL-2 + NECA and IL-2 + TGF-β1 functional and phenotypic analysis, and future logistical ease, further expansion studies were conducted on IL-2 + TGF-β1 + rapamycin expanded cells. Table 8: Expansion, differentiation, and CD4+ T cell suppression of NKreg cells (N=3 biological replicates per condition) Ligand Day 20 proliferation mean fold-increase (individual assay fold-increase) Day 20 differentiation (mean perforin expression) Suppressive capacity (mean % of CD4+ T cell suppression) IL-2 60 (42, 59, 80) 85% 38% IL-2 + (pulse 300nM rapamycin) 60 (42, 59, 80) 32% 83% IL-2 + TGF-β1 + (pulse 300nM rapamycin) 150 (125, 150, 175) 51% 88% IL-2 + NECA + (pulse 300nM rapamycin) 150 (200, 110, 140) 66% 90% IL-2 + TGF-β1 + NECA + (pulse 300nM rapamycin) 150 (105, 200, 145) 39% 93% 4.3.1.4 Expansion, function, and phenotype of NKreg cells expanded with three differing media conditions Isolated NKreg cells expanded for up to 21 days with use of the Immunocult NK Cell Expansion base media supplemented with IL-2, TGF-β1 and rapamycin resulted in the 155 greatest degree of expansion, in addition to the lowest perforin expression (correlated with decreased maturation of the NKreg cells). Further, NKreg cells expanded in the Immunocult media were 18% more suppressive than NKreg cells expanded with the Miltenyi media and 15% more suppressive than NKreg cells expanded with the R&D media. Additionally, NKreg cells expanded in the Immunocult media were 23% less cytotoxic towards allogenic CD4+ T cells than NKreg cells expanded with the Miltenyi media and 20% less cytotoxic towards allogenic CD4+ T cells than NKreg cells expanded with the R&D media. Therefore, I concluded that the optimal media to achieve the greatest NKreg cell expansion while maintaining NKreg cell-like phenotypic and functional characteristics is the Immunocult NK Cell Expansion media by Stemcell Technologies. Therefore, all experiments following utilized this media for NKreg cell expansion (table 9, figure 23). Table 9: Expansion and differentiation of NKreg cells cultured with different media (N=3 biological replicates per condition) Ligand Media Day 20 proliferation mean fold-increase (individual assay fold-increase) Day 20 differentiation (mean perforin expression) IL-2 + TGF-β1 + (pulse 300nM rapamycin) MACS NK Cell Expansion media 113 (132, 100, 108) 57% IL-2 + TGF-β1 + (pulse 300nM rapamycin) ExCellerate NK Cell Expansion media 83 (136, 60, 54) 38% IL-2 + TGF-β1 + (pulse 300nM rapamycin) Immunocult NK Cell Expansion media 211 (218, 200, 216) 29% 156 Figure 23: 20-day fold-expansion of NKreg cells grown in different expansion media. Fold-expansion of CD56brightCD16- NKreg cells over a 20-day culture period, utilizing NK cell expansion media sold by R&D System, Miltenyi Biotec, or Stemcell Technologies. Each medium condition was supplemented with 1% penicillin/streptomycin, 10% L-glutamine, 10% human AB serum, 2ng/ml TGF-β1, 25ng/ml IL-2, and 300nM rapamycin (added at day 18) (mean +/- SD). NS = not significant, *P < 0.05, **P < 0.005. Statistical analyses for expansion experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. The data is representative of 3 separate experiments utilizing cells from 3 unique healthy donors. -50-30-101030507090110130150170190210230250Day 0 Day 3 Day 6 Day 10 Day 13 Day 17 Day 20Fold-expansionDays in cultureMiltenyi R+D StemcellNS p = 0.2 ** * 157 4.3.2 Comparison of cord and peripheral blood NKreg cell proliferation, phenotype, and function NKreg cells were isolated from cord or peripheral blood and expanded in vitro under identical conditions. The expanded NKreg cells derived from peripheral blood resulted in significantly greater proliferation than the cord blood expanded NKreg cells, in addition to showing lower perforin expression and greater suppressive capacity towards allogeneic CD4+ T cells at the 1:1 ratio (characteristic of functional NKreg cells) (table 10, figure 24). Both conditions demonstrated a lack of cytotoxic effect towards allogeneic CD4+ T cells at the 1:1 ratio (results not shown). Table 10: Phenotypic and functional characteristics of expanded cord and peripheral NKreg cells (N=3 biological replicates per condition) Cells Blood source Day 20 proliferation mean fold-expansion (individual assay fold-increase) Day 20 differentiation (mean perforin expression) Suppressive capacity (mean % of CD4+ T cell proliferation suppression at 1:1 ratio of NK:T cells) CD56brightCD16- Peripheral blood 211 (218, 200, 216) 29% 88% CD56brightCD16- Cord blood 65 (75, 68, 52) 46% 1% 158 Figure 24: 20-day fold-expansion of peripheral and cord blood isolated NKreg cells. Fold-expansion of CD56brightCD16- NKreg cells isolated from either a 24hr healthy donor peripheral blood or cord blood course. Cells were cultured under identical expansion conditions over a 20-day period. The Immunocult NK Cell Expansion Media from Stemcell Technologies was supplemented with 1% penicillin/streptomycin, 10% L-glutamine, 10% human AB serum, 2ng/ml TGF-β1, 25ng/ml IL-2, and 300nM rapamycin (added at day 18) (mean +/- SD). P < 0.0005 = ***. Statistical analyses for expansion experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. The data is representative of 3 separate experiments utilizing cells from 3 unique healthy donors or 3 unique cord blood units. -50-30-101030507090110130150170190210230250Day 0 Day 3 Day 6 Day 10 Day 13 Day 17 Day 20Fold-expansionDays in culturePeripheral Cord*** 159 4.3.3 Characterization of optimally expanded peripheral NKreg cells 4.3.3.1 Transcriptome The gene expression of optimally expanded healthy donor peripheral NKreg cells was compared to that of untreated NKreg cells to characterize the transcriptome and evaluate substantial transcriptomic similarities or differences among NKreg cells after expansion as compared to previously described NKreg cells which associate with regulatory function in cGvHD (nanoString study, section 2.3.2). To identify genes of significance I utilized a strict biological cutoff of Log2 fold-change > 5, and p < 0.001. Bulk RNA sequencing revealed that untreated NKreg cells overexpress several genes as compared to expanded NKreg cells, such as CX3CR1, F2R Like Trypsin Receptor 1 (F2RL1), Krüppel-like Factor 2 (KLF2), Receptor Tyrosine Kinase Like Orphan Receptor 1 (ROR1), and Guanylate Cyclase 1 Soluble Subunit Alpha 1 (GUCY1A1) (table 11). Similarly, expanded NKreg cells overexpress several genes as compared to untreated cells, including TNF Receptor Superfamily Member 6b (TNFRSF6B), Adhesion G Protein-Coupled Receptor G3 (ADGRG3), SRY-Box Transcription Factor 18 (SOX18), Keratin 7 (KRT7), and Collagen Type XXIV Alpha 1 Chain (COL24A1) (table 11). However, there were no/minimal transcriptomic differences identified among genes previously described as being associated with cGvHD suppressive NKreg cells (p>0.001) (e.g. granzyme K, CXCR3, perforin, GM-CSFR, and FCGR2A) (table 12). (Figure 25). 160 Table 11: Bulk RNA sequencing of CD56brightCD16- NKreg cells (Log2 Fold Change > 5.0, p < 0.001) Untreated CD56brightCD16- NKreg cells compared to expanded CD56brightCD16- NKreg cells Expanded CD56brightCD16- NKreg cells compared to untreated CD56brightCD16- NKreg cells Gene Log2 Fold Change p-value Gene Log2 Fold Change p-value TBC1D3 11.4 1.8E-20 MUSTN1 8.4 1.7E-11 SAGSIN1 10.2 3.4E-16 TBXT 8.1 1.2E-20 PEDS1-UBE2V1 9.0 2.8E-13 TNFRSF6B 8.0 1.5E-09 HSPE1-MOB4 6.7 7.4E-07 ISM1 7.7 1.5E-09 RAP1GAP2 6.7 7.5E-22 PDGFRB 7.7 5.2E-36 GUCY1A1 6.3 4.1E-44 LNCDAT 7.3 1.9E-17 CX3CR1 6.0 2.0E-35 TJP1 6.9 2.3E-07 F2RL1 5.9 1.9E-07 SOX18 6.4 1.3E-06 KLF2 5.8 1.6E-57 GOLGA8F 5.9 1.5E-07 MS4A1 5.7 9.8E-51 ADGRG3 5.8 4.4E-22 S1PR1 5.5 3.3E-49 KRT7 5.7 4.7E-10 ROR1 5.4 4.2E-06 COL24A1 5.7 3.5E-35 SRGAP3 5.3 2.3E-40 EPHA1 5.2 1.7E-23 TBC1D3, TBC1 Domain Family Member 3D; SAGSIN1, Salivary Gland Specific Protein; PEDS1-UBE2V1, Plasmanylethanolamine Desaturase 1-Ubiquitin Conjugating Enzyme E2 V1; HSPE1-MOB4, Heat shock protein 1- MOB family member 4; RAP1GAP2, RAP1 GTPase activating protein 2; GUCY1A1, Guanylate Cyclase 1 Soluble Subunit Alpha 1; CX3CR1, CX3C chemokine receptor 1; F2RL1, F2R Like Trypsin Receptor 1; KLF2, Krüppel-like Factor 2; MS4A1, Membrane Spanning 4-Domains A1; S1PR1, Sphingosine-1-Phosphate Receptor 1; ROR1, Receptor Tyrosine Kinase Like Orphan Receptor 1; MUSTN1, Musculoskeletal Embryonic Nuclear Protein 1; TBXT, T-Box Transcription Factor T; TNFRSF6B, TNF Receptor Superfamily Member 6b; ISM1, Isthmin 1; PDGFRB, Platelet Derived Growth Factor Receptor Beta; LNCDAT, LncRNA Divergent Activator Of TBXT; TJP1, Tight Junction Protein 1; SOX18, SRY-Box Transcription Factor 18; GOLGA8F, Golgin A8 Family Member F; ADGRG3, Adhesion G Protein-Coupled Receptor G3; KRT7, Keratin 7; COL24A1, Collagen Type XXIV Alpha 1 Chain; SRGAP3, Slit-Robo GTPase activating protein 3; EPHA1, Ephrin type A receptor 1. 161 Table 12: Identification genes for regulatory NK cells; Bulk RNA sequencing of untreated CD56brightCD16- NKreg cells compared to expanded CD56brightCD16- NKreg cells Gene Log2 Fold Change p-value (NS > 0.001) IL7R 1.8 1.5e-04 GPR183 1.7 1.8E-08 TCF7 1.1 2.2E-07 GZMK 0.2 0.7 (NS) CSF2 (GM-CSFR) 0.09 0.8 (NS) CXCR3 0.007 1.0 (NS) IL23A -0.01 1.0 (NS) FCGR2A -0.2 0.6 (NS) PRF1 -0.38 0.08 (NS) GZMB -2.2 3.9E-08 IL7R, Interleukin 7 receptor; GPR183, G-protein coupled receptor 183; TCF7, Transcription factor 7; GZMK, Granzyme K; CSF2 (GM-CSFR), Granulocyte macrophage-colony-stimulating factor receptor; CXCR3, C-X-C chemokine receptor 3; IL23A, Interleukin 23 subunit alpha; FCGR2A, Fc gamma receptor 2a; PRF1, Perforin; GZMB, Granzyme B 162 a) b) c) Expanded Untreated Untreated vs. Expanded 163 Figure 25: Bulk RNA sequencing of untreated NKreg cells compared to expanded NKreg cells. Healthy donor fresh peripheral CD56brightCD16- NKreg cells (N=3) and healthy donor NKreg cells expanded for 21 days (N=3) were utilized for bulk RNA sequencing, performed by Novogene via Novaseq 6000 (Illumina). The transcriptome of the untreated NKreg cells was compared to the expanded NKreg cells. a) Volcano plot identifying the Log2 fold change and p-value of highly expressed genes by untreated NKreg cells compared to expanded NKreg cells. b) Identification of individual sample differences in the gene expression of untreated NKreg cells compared to expanded NKreg cells. c) A Gene set enrichment analysis was performed to identify genes signficantly expressed by untreated NKreg cells compared to expanded NKreg cells, and group the overrepresented genes according to established transcriptomic signalling pathways. 164 4.3.3.2 Metabolic phenotype CD56brightCD16- NKreg cells expanded via three differing NK cell expansion medias and cytolytic CD56dimCD16+ NK cells were evaluated to determine their metabolic characteristics which associated with their cellular functions and proliferation. Though the three commercially available media were observed to have differing compositions of glucose and glutamine (Figure 26a), which may affect the overall proliferation and functional capacity of the cells, the metabolic profile of the NKreg cells grown in the differing media conditions are not significantly different (Figure 26bc). The cell’s metabolic utilization of glycolysis was measured via analyzing the ECAR and mitochondrial oxidative phosphorylation was measured via OCR. The metabolic profile of NKreg cells and cytolytic NK cells were identified to be not significantly different (Figure 26d). The addition of rapamycin, a crucial culture additive to maintain NKreg cell function/phenotype and prevent cell maturation, induces lower OCR to ECAR ratios in both NKreg cells and cytolytic NK cells (Figure 26de). Rapamycin also induces higher spare respiratory capacity in NKreg cells but not in cytolytic NK cells (Figure 26de). 165 Figure 26: Metabolic characteristics of expanded NK cells. NK cell culture medium comparison between three commercially available NK cell expansion media. CD56brightCD16- NKreg cells and CD56dimCD16+ NK cells expanded for 20-days in three different media (NK Cell Expansion media from Miltenyi Biotec, R&D Systems, or Stemcell Technologies), supplemented with 1% penicillin/streptomycin, 10% L-glutamine, 10% human AB serum, and cytokines (2ng/ml TGF-β1, 25ng/ml IL-2, and 300nM rapamycin (added at day 18) for NKreg cells, and 50ng/ml IL-2 and 25ng/ml IL-15 for CD56dim NK cells). Comparisons were made on a) concentration of glucose and glutamine in the media. NKreg cells grown in the three media were compared with a b) mitochondrial stress test assessing mitochondrial respiration represented by oxygen consumption rate (OCR) and glycolytic activity represented by extracellular acidification rate (ECAR). The test was performed using a seahorse extracellular flux analyzer with the addition of inhibitors oligomycin (oligo), the proton uncoupling agent FCCP, Rotenone and Antimycin (R&A), and 2-DeoxyGlucose (2DG). The effect is c) quantified with OCR over ECAR ratios, and spare respiratory capacity (SRC) as a percentage of the basal respiration. Comparison between NKreg, CD56dim, and effects of rapamycin were determined metabolically with d) OCR and ECAR, and e) OCR/ECAR ratios and SRC. Data is representative of 3 separate experiments utilizing cells from unique healthy donors. Data are presented as mean ± SEM and P values are determined by two-tailed Student’s t-test. 166 4.3.3.3 Proteomics/cytokine production Fresh (24hr) and expanded NKreg cells were analyzed for their protein expression as compared to fresh (24hr) and expanded CD56dim NK cells. I utilized a strict cutoff for determining biological significance, being a p value less than 0.001 and effect ratio greater than 2 or less than 0.5. For fresh NKreg cells as compared to CD56dim NK cells, 7 proteins met the criteria, one of which was increased in NKreg cells compared to CD56dim NK cells (IL-2), and the other 6 being decreased in NKreg cells compared to CD56dim NK cells. This included the proteins CCL4, CCL3, TNF, CCL20, IFNγ, and TNFSF14 (table 13). The expanded NKreg cells compared to CD56dim NK cells upregulated several more proteins than fresh NKreg cells, and 5 of these proteins met the biological significance criteria, including TRANCE, IL-2RB, CDCP1, LIF, and 4E-BP1. When considering any effect ratio and p values less than 0.01 I identified 4 proteins which associated with known regulatory/suppressive function upregulated among the expanded NKreg cells compared to CD56dim NK cells, being TGF-β1, TRAIL, ADA, and IL-10RA (table 14) (figure 27). I then investigated the suppressive effect of NKreg cells towards CD4+ T cell proliferation when the receptors or ligands for these cytokines were blocked (excluding TRAIL, as this was previously investigated, section 3.3.7). I observed no statistically significant differences in the NKreg induced suppression of CD4+ T cells at the 1:2 ratio when blocking A2AR, TGF-β1, and IL-10R (p > 0.05) (figure 28). 167 Table 13: Protein expression of fresh NKreg cells compared to fresh cytolytic NK cells (NKdim) Protein 24hr NKreg NPX 24hr NKdim NPX Effect Ratio p-value Increased expression, NKreg cells compared to NKdim cells (all ER, p < 0.001) IL2 13.89 13.52 1.03 0.000861 Decreased expression, NKreg cells compared to NKdim cells (all ER, p < 0.001) CCL4 4.90 11.5 0.428 6.27E-09 CCL3 4.54 13.2 0.343 1.50E-06 TNF 0.0415 3.87 0.0107 1.91E-05 CCL20 1.38 2.11 0.656 0.000317 IFN-gamma 10.4 14.3 0.728 0.000861 TNFSF14 2.29 5.72 0.400 0.000861 NPX = Normalized Protein Expression value (log2-scale) ER = Effect Ratio IL2, Interleukin 2; CCL4, Chemokine Ligand 4; CCL3, Chemokine Ligand 3; TNF, Tumor Necrosis Factor; CCL20, Chemokine Ligand 20; IFN-gamma, Interferon gamma; TNFSF14, Tumor Necrosis Factor Superfamily Member 14. Table 14: Protein expression of expanded NKreg cells compared to expanded cytolytic NK cells (NKdim) Protein Expanded NKreg NPX Expanded NKdim NPX Effect Ratio (ER) p-value ER > 2, p < 0.001 TRANCE 7.08 2.47 2.86 5.63E-07 IL-2RB 1.78 0.276 6.44 1.90E-05 CDCP1 5.61 1.31 4.29 7.68E-05 LIF 9.50 2.30 4.13 0.000180 4E-BP1 3.70 1.06 3.51 0.000744 All ER, p < 0.01, proteins with known association to regulatory/suppressive function TRAIL 7.18 5.34 1.35 1.90E-05 LAP TGF-beta-1 3.89 2.28 1.71 0.000174 ADA 5.79 4.16 1.39 0.00227 IL-10RA 0.503 -0.0429 -11.7 0.00874 NPX = Normalized Protein Expression value (log2-scale) ER = Effect Ratio TRANCE, Tumor Necrosis Factor-Related Activation-Induced Cytokine; IL-2RB, Interleukin 2 Receptor Subunit Beta; CDCP1, CUB Domain-Containing Protein 1; LIF, Leukemia Inhibitory Factor; 4E-BP1, Eukaryotic Translation Initiation Factor 4E-Binding Protein 1; TRAIL, TNF-Related Apoptosis-Inducing Ligand; LAP TGF-beta-1, Latency-Associated Peptide Transforming Growth Factor Beta 1; ADA, Adenosine Deaminase; IL10-RA, Interleukin 10 Receptor Subunit Alpha. 168 Figure 27: Heatmap of Normalized Protein Expression (NPX) of expanded CD56brightCD16- NKreg cells compared to expanded CD56dimCD16+ NK cells. NPX of expanded CD56brightCD16- NKreg cells compared to expanded CD56dimCD16+ NK cells. NKreg cells were cultured in Immunocult NK Cell Expansion Media from Stemcell Technologies which was supplemented with 1% penicillin/streptomycin, 10% L-glutamine, 10% human AB serum, 2ng/ml TGF-β1, 25ng/ml IL-2, and 300nM rapamycin (added at day 18). NKdim cells were cultured in Immunocult NK Cell Expansion Media from Stemcell Technologies which was supplemented with 1% penicillin/streptomycin, 10% L-glutamine, 10% human AB serum, 50ng/ml IL-2, and 25ng/ml IL-15. Statistical analyses for proteomics experiments were performed using the Welch Two Sample t-test. The data is representative cell supernatant collected from 3 unique healthy donors run in duplicate (collecting both NKreg and NKdim from each donor). 169 Figure 28: Evaluation of CD56brightCD16- NKreg cell ability to suppress CD4+ T cell proliferation when blocking proteomics candidates: TGF-β, A2AR, or IL-10R. Suppressive effect of CD56brightCD16- NKreg cells towards allogeneic CD4+ T cells compared to NKreg suppression of CD4+ T cells in the presence of the TGF-β, A2AR, IL-10R, and TRAIL neutralizing antibodies (mean +/- SD). *p < 0.05, NS = not significant. Statistical analyses for suppression experiments were performed using Microsoft Excel version 2110 and a two-tailed T test – two-sample assuming unequal variance. a) CD56brightCD16- NKreg cells towards allogeneic CD4+ T cells at the 1:4 ratio as compared to NKreg suppression of CD4+ T cells in the presence of the TGF-β receptor blocker. The data is representative of 3 separate experiments utilizing cells from unique healthy donors (n=3). b) CD56brightCD16- NKreg cells towards allogeneic CD4+ T cells at the 1:2 ratio as compared to NKreg suppression of CD4+ T cells in the presence of the A2AR blocker. The data is representative of 3 separate experiments utilizing cells from unique healthy donors (n=3). c) CD56brightCD16- NKreg cells towards allogeneic CD4+ T cells at the 1:2 ratio as compared to NKreg suppression of CD4+ T cells in the presence of the IL-10 receptor blocker. The data is representative of 3 separate experiments utilizing cells from unique healthy donors (n=3). 010203040506070NKreg to CD4(1:2)NKreg to CD4(Adenosinereceptorblocker) (1:2)Suppression of CD4+T cell proliferation (%)NS, p = 0.2c) d) 05101520253035404550NKreg to CD4(1:4)NKreg to CD4(TGFBR blocker)(1:4)Suppression of CD4+T cell proliferation (%)NS, p = 0.2020406080100NKreg to CD4(1:2)NKreg to CD4(IL-10R blocker)(1:2)Suppression of CD4+T cell proliferation (%)NS, p = 0.4a) c) b) 170 4.3.4 Expansion and differentiation of NKreg cells from CD34+ hematopoietic stem and progenitor cells CD56bright NKreg cells represent less than 10% of peripheral NK cells, with total peripheral NK cells making up a small proportion of leukocytes, being 1 - 6%. Cord blood contains approximately 1.4x the amount of NK cells and a slightly greater proportion of CD56bright NK cells. Additionally, other groups have shown that CD34+ stem and progenitor cells derived from human cord blood can differentiate to a NK cell population with robust cytokine secretion, as compared to potent degranulation as seen with NK cells differentiated from peripheral blood.195 Therefore, I aimed to test whether I could differentiate and expand functional NKreg cells from a cord blood CD34+ hematopoietic stem and progenitor cell source to reach clinically significant numbers. Using this method, I observed an average of 1.5million CD34+ HSPCs per cord blood unit (~75ml), and from this source reached an average 333-fold expansion and differentiation to CD5+CD7+ lymphoid progenitor cells. At this stage, I then observed an average 7-fold expansion and sort of pure NKreg cells. These resulting NKreg cells show similar phenotypic (figure 29) and functional (figure 30) characteristics to peripheral blood derived NKreg cells, being low perforin and CD16 expression, high CD56 and granzyme K expression, and strong non-cytolytic suppressive capacity towards CD4+ T cell proliferation (mean 72% suppression at the 1:3 ratio of NKreg cells to CD4+ T cells) (table 15). 171 Table 15: Phenotypic and functional characteristics of NKreg cells differentiated from CD34+ hematopoietic stem and progenitor cells Experiment Expansion Phenotypic characteristics (without rapamycin) Phenotypic characteristics (with rapamycin) Co-culture condition Suppressive capacity (% of CD4+ T cell proliferation suppression) Cytotoxic capacity (% of dead CD4+ T cells) (n=6) 1.5mill CD34+ cells (used 60K) 20mill lymphoid progenitor cells (used 600K) 4mill NKreg cells 0% CD16 46% Perforin 72% Granzyme K 0% CD16 25% Perforin 74% Granzyme K 1:3 NKreg:CD4 (- RAPA) 28% 11% (compared to 8% in control) 1:3 NKreg:CD4 (+ RAPA) 72% 5% (compared to 8% in control) 172 Figure 29: Evaluation of phenotypic expression of CD34+ HSPC differentiated and sorted CD56brightCD16- NKreg cells. Differentiated CD56brightCD16- NK cells were isolated via FACS cell sorting, cultured for 72hrs via Immunocult NK Expansion media supplemented with IL-2, TGF-β1, and rapamycin. Cultured cells were stained for cell surface expression of select markers (CD56 PE, CD3 APC, CD16 FITC, Perforin Pacific Blue, Granzyme K AF647) and analyzed by flow cytometry. Lymphocytes were first gated using FSC and SSC. The data is representative of 6 separate experiments utilizing cells from unique healthy donors (n=6). 173 Figure 30: Evaluation of CD34+ differentiated CD56brightCD16- NKreg cell function. a) Suppression: Suppressive effect of CD56brightCD16- NKreg cells towards allogeneic CD4+ T cells when cells are co-cultured for 72 hrs at the ratio 1:4 (72% suppression of CD4+ T cell proliferation, as compared to the activated CD4+ T cell control). On the histograms, the x-axis displays the cell proliferation dye (CPD) eF450 and the y-axis displays the cell count. The green peaks indicate the individual proliferative populations, as determined by CPD expression. The data is representative of 6 experiments utilizing cells from unique healthy donors (n=6). b) Cytotoxicity: Cytotoxic effect of CD56brightCD16- NKreg cells towards allogeneic CD4+ T cells when cells are co-cultured for 72 hrs at the ratio 1:4 (10% of CD4+ T cells are dead after co-culture, as compared to 12% in the activated CD4+ T cell control). Dead CD4+ T cells were identified with use of Annexin V and 7-AAD flow cytometric staining. With use of FSC-A and SSC-A, lymphocytes were gated and using CD4 and 7-AAD staining live and dead CD4+ T cells were gated (plots not shown). After, Annexin V and 7-AAD were plotted. For the histogram, Annexin V negative and 7-AAD negative (live) CD4+ T cells are shown in blue, and annexin V positive, 7-AAD negative (early stage of death) and annexin V positive, 7-AAD positive (late stage of death) CD4+ T cells are shown in purple. The data is representative of 6 experiments utilizing cells from unique healthy donors (n=6). eF450 eF450 Count Count Count Count Annexin V Annexin V NKreg cells : CD4+ T cells 1:4 CD4+ T cells Division index = 0.67 Division index = 0.19 174 4.4 Discussion In this thesis, I hypothesized that NKreg cells suppress cGvHD through inflammatory cell inhibition, and that these cells can be distinguished as a unique NK cell subset which may be optimally expanded for the cellular therapy of cGvHD. In order to attend to this hypothesis, my third objective was to optimize the in vitro expansion of NKreg cells, evaluate multiple blood/cell sources, define the expanded NKreg cell subset according to proteome, and metabolome, and verify the maintenance of the cell’s regulatory phenotype, transcriptome, and suppressive function after expansion. To optimize the expansion of NKreg cells, I first utilized various combinations and concentrations of cytokines/ligands that match genes which were significantly associated with immune tolerance in the CD56bright NK cell subset (nanoString study, thesis section 2.3.2). As a result of these experiments, I observed that 25ng/ml IL-2 was the optimal investigated cytokine for inducing proliferation of NK cells. However, I also identified this proliferation to tightly correlate with differentiation resulting in a change in NKreg cell phenotype and function towards that which is characteristic of cytolytic, mature NK cells. I then wished to combine IL-2 with a candidate ligand which may act to prevent NKreg cell differentiation while also resulting in optimal cell expansion. This led to my investigation into the metabolism of NK cells, as there is much data suggesting that phenotype and metabolism of immune cells are closely functionally linked. Thus, reviewing the known/suggested metabolic characteristics of NK cells that correlate to differentiation and maturation 175 was useful in determining candidate pathways to inhibit this outcome. Though there has been limited data discussing the metabolic features and function of the NKreg cell subset, there are metabolic parallels that can be drawn between NKreg cells and Treg cells, a better characterized immune modulatory and suppressive cell population. Therefore, I reviewed the metabolic features of both NK cells and Treg cells that correlate to maturation and suppressive function, or a lack there of. In terms of function, though the process of activation of NK cells and T cells differs, they share quite a few similarities, including extensive proliferation when stimulated, cytotoxicity against target cells, and production of cytokines, such as IFNγ.196 For NK cells, immature NK cells, which I may interpret as NKreg cells, have shown increased glucose transporter and nutrient receptor expression compared to mature NK cells.99 Further, activation of mTOR signaling is progressively downregulated as NK cells mature, consistent with reduced glucose uptake during maturation.99 In mouse studies, mice with a NK cell-specific mTOR deletion had compromised NK cell development due to impaired transition from immature to intermediate subsets.99 mTOR activity is also upregulated upon T cell activation and exerts numerous functions to promote glycolysis, such as upregulating hypoxia-inducible factor 1-alpha (HIF1α), which stimulates glycolysis, resulting in Th17 differentiation,197 or activating the transcription factor myelocytomatosis (Myc) which promotes glycolysis, glutamine oxidation, and CD98 expression.198 As both T cells and NK cells acquire an effector cell or mature phenotype, respectively, they have shown to rely mainly on fatty acid oxidation (FAO) and OXPHOS to support the change in 176 energetic needs, as these pathways are more energetically efficient with a decreased need for nutrients.181 Activated NK cells have shown to increase metabolic flux through both glycolysis and OXPHOS, with a proportionally increased reliance on glycolysis relative to OXPHOS.181 Elevated glycolysis upon activation is supported by enhanced glucose uptake and glucose transporter 1 (GLUT1) expression.100,102 Further, Treg cell generation is hindered by enhanced glycolysis.181 Treg cells also partially rely on OXPHOS,199 and Treg cell differentiation is enhanced by restricting glycolysis or its precursors.197,200 Treg cells up-regulate GLUT1 expression and anaerobic glycolysis to support proliferation and inhibit suppressive functions.181 In turn, suppressive Treg cells utilize lipid oxidation coincident with reduced glycolysis.181 Further, interferon regulatory factor 4 (IRF4) has shown to act as a T effector cell glycolytic switch point.201 IRF4 knockout CD4+ T cells have reduced glucose uptake, and impaired glycolysis and OXPHOS upon activation.201 This finding may be relevant to NKreg cells, as in the nanoString transcriptome characterization of the CD56bright NK cell population associated with immune tolerance (thesis section 2.3.2), I identified IRF4 as a gene to be significantly low in cells associated with tolerance. Based on this knowledge, I concluded that mTOR-regulated glycolysis is an important metabolic process in the maturation and associated proliferation of activated immature NKreg cells towards mature cytolytic NK cells. Thus, rapamycin, a chemical inhibitor of mTORC1, was a candidate to prevent this differentiation. Genetic or chemical inhibition via rapamycin of mTOR has shown to impair 177 activation-induced increase in NK cell size, glucose uptake, and nutrient transporter expression.99,100,102 Further, rapamycin-induced mTOR inhibition has also been shown to inhibit NK cell proliferation, degranulation, and cytotoxicity.105 Likewise, mTOR inhibition promotes Treg cell differentiation,200 whereas its activation inhibits its suppressive function.202 In my NK cell expansion optimization experiments, I identified the addition of 300nM rapamycin to 25ng/ml IL-2 to prevent NKreg cell maturation, but as expected, also significantly slow the IL-2-induced expansion of NK cells. I then expanded the NK cells for up to 21 days, and after desired expansion was achieved, pulsed cells with 300nM rapamycin, and observed the cells to revert in phenotypic expression to that which was characteristic of the immature NKreg cells. However, I observe that this isn’t a permanent change in phenotype and associated function, as after rapamycin is applied, if stimulatory cytokines such as IL-2 are continually added the cells will begin to mature and change in phenotype. This is important to consider when potentially applying this method to the in vivo setting, of which multiple rapamycin infusions may be necessary, and NKreg persistence and differentiation will need to be investigated. There is also data suggesting that TGF-β may be a strong candidate for inducing proliferation and preventing maturation of NK cells. TGF-β signaling has been shown to inhibit IL-15-induced upregulation of both anaerobic glycolysis and OXPHOS, an effect that occurs via mTOR inhibition.203 mTOR is sensitive to nutrient availability and can be repressed by TGF-β, which inhibits NK cell metabolism and functionality.100,106,203 It has also been demonstrated that TGF-β decreases IL-2-178 induced mitochondrial metabolism, including OXPHOS and maximal respiration in human NK cells.106 Another group demonstrated that both hypoxia and anti-inflammatory cytokines (such as TGF-β) stand out as hallmarks for promoting regulatory NK cell phenotype and function.202 The role of TGF-β in directly polarizing NK cells to a regulatory state was highlighted by a study that demonstrated that in vitro culture of cytotoxic peripheral NK cells in TGF-β + IL-15 under hypoxic conditions converted the peripheral NK cells to NK cells that secreted high levels of vascular endothelial growth factor (VEGF) and had poor cytotoxicity.204 This is characteristic of decidual NK cells, which draw many phenotypical and functional parallels to peripheral regulatory NK cells. In my NK cell expansion optimization experiments, I observed the addition of 2ng/ml TGF-β1 to 25ng/ml IL-2 to not completely prevent NKreg cell maturation but slow it as compared to the IL-2 control, and also promote some NKreg phenotypical characteristics, such as a lack of CD16 expression. Additionally, TGF-β1 rapidly increased proliferation of NKreg cells. I then expanded the NKreg cells for up to 21 days with IL-2 and TGF-β1, and after desired expansion was achieved, pulsed cells with 300nM rapamycin, and similarly observed the cells to revert in phenotypic expression to that which was more characteristic of the immature NKreg cells. Additionally, these expanded NKreg cells maintained similar functional characteristics to fresh NKreg cells, showing strong suppressive capacity towards allogeneic CD4+ T cells. The suppression observed was stronger than that seen with the IL-2 and rapamycin only expanded NKreg cells, suggesting that the metabolic effects of TGF-β1 not only induce proliferation but also phenotypical and functional characteristics of NKreg cells. 179 Evidence to date supports a role for adenosine monophosphate-activated protein kinase (AMPK) and mTOR pathways in limiting NK cell function. One study reported that AMPK activity correlates with impaired function in senescent NK cells with high inhibitory receptor killer cell lectin-like receptor G1 (KLRG1) expression.205 AMPK has shown to play an integral role in integrating nutrient status and Treg cell metabolism by increasing FAO, where AMPK activation promotes Treg cell differentiation both in vivo and in vitro.200 The insulin-sensitizing effects of metformin are linked to AMP-activated protein kinase-acetyl-CoA carboxylase-mediated changes in lipid metabolism and the balance between lipogenesis and FAO in metabolic tissues such as the liver.192,193 One study showed that mice treated with metformin had significant improvements in clinical severity and mortality during acute GvHD, which was associated with metformin-mediated reductions in Th1/Th17 cells and increased Th2 and Treg cell populations.206 However, the effects of metformin treatment on NK cell metabolism and function is currently unknown.181 Due to evidence demonstrating metformin’s efficacy in promoting Treg cell function and differentiation I chose to also investigate its effects on NKreg cells. However, I identified that expansion of NK cells with metformin and metformin in addition to IL-2 was decreased as to that achieved with IL-2 alone, and also had little effect in preventing NKreg cell maturation/differentiation. This suggested that the metabolic effects of metformin are less integral to NKreg cell maturation than that being inhibited by rapamycin, and TGF-β1, for example. Therefore, I ruled out metformin as a potential candidate for inducing proliferation and preventing maturation of NKreg cells. 180 Further, published data has demonstrated that dexamethasone treatment may induce proliferation and prevent maturation of cytolytic NK cells. Specifically, glucocorticoid treatment of NK cells has been shown to reduce NK cell cytolytic activity (which may be interpreted as potential maturation of NK cells) by reduction of histone promoter acetylation for perforin and Granzyme B, in addition to increasing histone acetylation and chromatin accessibility at NK cell regulatory regions for IFNγ and IL-6.194 Another group showed that dexamethasone greatly enhances the proliferation of cytokine-stimulated human NK cells.207 Therefore, I wished to investigate the proliferative and differentiation effects of dexamethasone on NK cells stimulated with IL-2. Though I did observe increased proliferation of NK cells when dexamethasone was added with IL-2, as compared to when NK cells were expanded with use of IL-2 only, I observed minimal effects on preventing NK cell maturation. This finding may be attributed to the culture environment of which dexamethasone was added. Ligands and cytokines may induce significantly different effects on cell proliferation, function, phenotype, and metabolism when combined with differing agonists or culture conditions. The paper which described dexamethasone promoting regulatory NK cells utilized NK92 cells and differing culture and stimulatory conditions than that of my expansion protocol. Due to dexamethasone not achieving the desired outcome of preventing NK cell maturation of IL-2-induced expanding NK cells I did not proceed with further experimentation using this candidate. 181 Lastly, I chose to investigate the effects of utilising an adenosine receptor agonist for NKreg cell proliferation and differentiation, due to its efficacy shown in other works of which adenosine promotes CD56brightCD16- NKreg cell differentiation and regulatory function. Extracellular adenosine concentration has been shown to be increased in the hypoxic conditions of the tumor microenvironment, which promotes regulatory NK cell function and differentiation, and decreases cytolytic NK cell function and differentiation.208 Hypoxia promotes the release of ATP and AMP, and the ectonucleotidases CD39 and CD73 which catalyze the conversion of extracellular ATP to AMP, and then AMP to adenosine.187 Adenosine then stimulates NK cells through the A2AR.188-190 Adenosine impairs metabolic activity of stimulated NK cells by inhibiting their OXPHOS and glycolytic capacity.208 Adenosine has shown to elevate immunoregulatory cytokine production, characteristic of NKreg cells, and decrease cytotoxicity of NK cells, characteristic of classic CD56dim NK cells.208 Another group also demonstrated that adenosine induces a significant inhibition of glycolysis and OXPHOS in NK cells which was inferred by altered transcriptional signatures due to adenosine signaling, including the downregulation of Lactate dehydrogenase A (LDHA) and GAPDH genes.191 LDHA converts pyruvate into lactate and GAPDH is involved in the sixth step of glycolysis and is key to the yielding of ATP from glucose.191 Ultimately, adenosine has shown to impair functions that support NK cell cellular metabolism and division, which may result in inhibition of NK cell maturation and effector functions.191 In review of these findings showing adenosine’s potential efficacy in inhibiting NKreg cell maturation and effector functions, while promoting regulatory NK cell phenotype and function, I 182 utilized NECA, an adenosine receptor agonist, with IL-2 to try and promote NKreg cell expansion and prevent maturation and loss of NKreg cell phenotype and function. I observed that expansion of NKreg cells with NECA in addition to IL-2 induced greater expansion than that achieved with IL-2 alone. Further, NECA slowed phenotypic maturation of the NKreg cells. Addition of 300nM rapamycin after the 21-day expansion further induced a NKreg cell-like phenotype. Additionally, these expanded NKreg cells maintained similar functional characteristics to fresh NKreg cells, showing strong suppressive capacity towards allogeneic CD4+ T cells, which was stronger than that observed with the IL-2 and rapamycin only expanded NKreg cells. The suppressive effect was similar to NKreg cells expanded with use of IL-2, TGF-β1, NECA, and later addition of rapamycin. When considering the proliferation and phenotypic/functional effects of TGF-β1 and NECA to be similar, and the goal of applying such an expansion protocol to the clinic, I decided to pursue the use of TGF-β1 with IL-2 and rapamycin, as TGF-β1 has been well described for in vivo study use, and is widely available as a GMP-grade cytokine, unlike NECA. We then went on to test the effects of three commercially available NK cell specific expansion medias, supplemented identically with the optimized cytokine combination, to compare which media resulted in the greatest proliferation, with maintenance of suppressive function and regulatory phenotype. In these analyses, we observed significantly greater proliferation and suppressive function/lack of cytotoxicity when NKreg cells were expanded with the Immunocult NK Expansion media, compared to others tested. In completion of the Seahorse and media analysis 183 of the expanded cells, we identified differences in glutamine and glucose levels among the three differing media conditions, components which may affect cell proliferation/function. However, these differences were not statistically significant. Thus, the reasoning by which we observed greater expansion with the Immunocult NK Expansion media is currently unknown and may be an area of future investigation. The NKreg cells expanded with the optimized cytokine combination and media were seen to maintain similar phenotype, transcriptome, and suppressive function to fresh/untreated NKreg cells. This suggested that the in vitro expansion approach is not significantly changing the cells from those which have previously been identified and described as being associated with cGvHD suppression in HSCT patients (thesis, chapters 2 and 3). I then went on to test if I may isolate a greater number of NKreg cells from an alternate blood source, being cord blood, when utilizing the optimized expansion protocol, as described above. In this study I observed significantly lower expansion among the cord blood derived cells than the peripheral blood derived cells. Though I did not complete additional analyses to investigate why this difference may have been observed, I could hypothesize that this may be due to the initial lower viability of the cord blood units, as these samples were shipped from out-of-province, being 48-72hrs old at the time of processing, unlike the peripheral blood samples which were 24hrs old. This may suggest a rationale for further investigation of cord blood for the isolation of NKreg cells in the future, if fresh cold blood samples were to be available. Additionally, the initial expansion optimizations were only performed 184 on peripheral blood, and thus this specific protocol (i.e. cytokines and media composition used) may be best suited to a peripheral blood source, though further optimizations may outline an alternative approach best suited to cord blood derived NKreg cells. Further, in the comparisons of regulatory NK cells to classic NK cells we observed similar metabolic profiles, and the induction of a lower OCR/ECAR ratio when rapamycin was added, a necessary additive to maintain NKreg cell phenotype and function, suggesting a potential glycolytic target for future studies to promote NKreg cell phenotype. Further, we observed rapamycin to induce higher spare respiratory capacity in NKreg cells but not in cytolytic NK cells, which may contribute to improved viability and cellular persistence of the NKreg cells, a useful feature for the in vivo application of NKreg cells. I also observe NKreg cells to upregulate a number of cytokines compared to cytolytic NK cells, including 4 proteins which associate with an established regulatory function, all of which have been described above, including TRAIL,155 IL-10,165 ADA,166 and TGF-β.167 Lastly, I wished to test one additional alternate method of obtaining NKreg cells beyond the direct isolation from cord and peripheral blood, being from CD34+ HSPCs. There are many advantages to using HSPCs derived from cord blood as the initial cell source for obtaining NKreg cells. In terms of the differentiation of NK cells from CD34+ HSPCs, cord blood serves as a more efficient source than peripheral 185 blood, as CD34+ cells make up ~0.1-1% of white blood cells in cord blood, as compared to ~0.03-0.09% of white blood cells in peripheral blood. Additionally, NK cells derived from cord blood have shown to reach a late stage of differentiation/maturation and proliferate via IL-2 stimulation, similar to peripheral NK cells, but express fewer KIRs, and have lower cytotoxicity,209 more characteristic of regulatory NK cells as opposed to classic cytolytic NK cells. There are also multiple logistical and functional advantages to using HSPC-derived NKreg cells. Firstly, in keeping clinical applicability in mind, differentiating CD34+ HSPCs to NKreg cells will result in a significantly greater cell number than the direct isolation of NKreg cells from cord or peripheral blood (up to ~6000 NKreg cells produced per CD34+ cell using the StemSpan™ NK Cell Kit (as reported by Stemcell Technologies, Vancouver, BC, Canada)). Additionally, groups have successfully differentiated HSPCs into NK cells and shown that they are similar in phenotype and effector function when compared to primary NK cells.195,210-218 The differentiated cells express several NK-associated receptors such as CD56, CD16, NKp44, NKp46, NKG2D, and TRAIL.210,213-216,219 One study identified two distinct CD34+ cell populations that dictate final effector function.195 The CD34+ progenitor cells derived from human peripheral blood gave rise to a population that exhibits more potent degranulation, while the CD34+ progenitor cells derived from human cord blood resulted in a NK cell population with robust cytokine secretion.195 These findings suggest that it may be beneficial to enrich progenitor populations from cord blood to obtain cells exhibiting robust cytokine secretion, as this is a characteristic of the CD56bright NKreg cell population. This result is also supported by the phenotypic data 186 of the differentiated NK cells that are produced from the StemSpan™ NK Cell Kit (Stemcell Technologies, Vancouver, BC, Canada), which shows that when utilizing cord blood-derived CD34+ cells, the majority of the differentiated NK cells can be characterized as a CD56brightCD16-KIR-NKp44+ population, which is phenotypically characteristic of CD56bright regulatory NK cells, as opposed to CD56dim cytolytic NK cells. The results of the CD34+ HSPC differentiation studies showed that I may indeed alternatively expand functionally and phenotypically similar NKreg cells to that observed from peripheral blood, though reaching substantially greater resulting cell numbers. The experiments were done on a smaller scale, using only 60,000 CD34+ cells and 600,000 lymphoid progenitor cells to obtain an average of 4million NKreg cells. However, I may estimate that if using all CD34+ cells (1.5 million) obtained from a single cord blood unit, we may predict to reach an average of 3.5 billion NKreg cells, appropriate for ~70 infusions of 1million NKreg cells/kg in a 50kg patient. This method allows for the potential of utilizing these NKreg cells for clinical approaches. 187 5 Chapter 5: Conclusion 5.1 Conclusions and chapter summaries cGvHD is disease which may occur after the first 100 days of receiving a HSCT, the infusion of a donor’s immune system into a recipient, which is a critical therapy to treat high risk and relapsed blood cancers and non-malignant diseases. The association between NK cells and immune tolerance in the GvHD setting has been identified by various groups over the last 30 years, with evidence supporting this hypothesis having been demonstrated in in vitro and in vivo studies. In large pediatric and adult HSCT patient population correlative studies, our group has identified CD56bright NK cells to be a consistent cell population associated with a lack of cGvHD and development of immune tolerance. Based on this data, I hypothesized that NKreg cells suppress cGvHD through inflammatory cell inhibition, and that these cells can be distinguished as a unique NK cell subset which may be optimally expanded for the cellular therapy of cGvHD. My main objectives were to identify, isolate, characterize, and expand the CD56bright, non-cytolytic NK cell subset associated with a lack of cGvHD. To meet these objectives, I first determined the phenotype and genes of CD56bright NK cells, which are associated with cGvHD suppression after HSCT. Based on the transcriptome results and immunophenotypic studies, I determined the optimal cell surface markers to purify the NKreg cell population. I then completed a more detailed transcriptomic characterization of HSCT patient samples, including groups of patients which either developed or failed to develop cGvHD, to identify the unique NK cell subpopulations associated with cGvHD 188 development or suppression, and potential differentiation pathways in the two patient groups. Second, I evaluated the in vitro suppressive effect and mechanism of NKreg cells on cGvHD immune populations, including CD4+ T cell (naïve and memory cells and Th1/2/17 subsets), CD8+ T cells, Treg cells +/- dendritic cells, B cells, and NK cells. Third, I optimized the in vitro expansion of NKreg cells, defined the expanded NKreg cell subset according to proteome, and metabolome, and verified the maintenance of the cell’s regulatory phenotype, transcriptome, and suppressive function after expansion. As a result of this thesis work, I have well characterized a rare human peripheral cell population of regulatory NK cells in the context of healthy people and HSCT patients, describing novel phenotypic, transcriptomic, and functional/mechanistic findings, in addition to a clinically relevant cell expansion approach which may be further investigated for the potential of utilizing NKreg cells as a cellular therapy for cGvHD, or other inflammatory diseases. 5.1.1 Chapter 2 summary In large patient populations, we have shown a CD56bright Natural Killer population to strongly associate with a lack of cGvHD and I hypothesized that these cells function to suppress cGvHD. I aimed to isolate and define the characteristics of NKreg cells associated with the suppression of cGvHD. Immunophenotypic evaluation of a large pediatric population identified the CD56bright NK cell population associated with a lack of cGvHD to be perforin-, Granzyme B-, and CD335+. Transcriptome analysis of a small patient cohort of CD56bright compared to CD56dim NK cells identified the NKreg cells to 189 also overexpress Granzyme K, IL-7R, GPR183, RANK, GM-CSFR, TCF7, and IL23A. Further analysis of this CD56bright NKreg cell population identified a subpopulation of cells that overexpressed IRF1, and TNF. I also identified that viable NKreg cells may be isolated by sorting on CD56+ and CD16- NK cells. Further transcriptomic analysis via single-cell RNA sequencing revealed 7 unique NK cell subsets, 3 of which strongly associated with cGvHD development or suppression. As previously described, we identified a significant cell increase in Cluster 0 (cytotoxic CD56dim NK cells) in patients with cGvHD. We observed two distinct NKreg-like subpopulations associated with cGvHD suppression. We identified an increase in the cell proportions of Cluster 1 (classic CD56bright NKreg cells) and cluster 2 (Type I interferon-responsive NKreg cells) among immune tolerant patients. Cluster 1 and 2 are characterized by high expression of GZMK and XCL1, and IFIT2 and PMAIP1, respectively. In both NKreg cell subpopulations, the development of cGvHD was associated with a substantial change in gene expression and differentiation, of which cells lose regulatory transcriptomic features, and gain characteristics of cytolytic or inflammatory-like NK cells, including upregulation of AREG and GZMB. Moreover, these studies have established that a CD56brightCD3-CD16-perforin- NKreg cell population associates with a lack of cGvHD and that there are transcriptionally, and quantitatively distinct NK cell subsets associated with cGvHD development, including 2 unique NKreg cell populations associated with cGvHD suppression. Further analysis may result in a greater understanding of NKreg cell differentiation, and the associated mechanisms which result in immune tolerance, which may be useful in the clinical manipulation and application of NKreg cells in the future. 190 Figure 31: Thesis chapter 2 main results summary. a) Phenotypic and transcriptomic characteristics of regulatory NK cells associated with cGvHD suppression and cytolytic NK cells associated with cGvHD development. b) scRNAseq results of HSCT patient samples with or without cGvHD. Original figure created on Biorender.com. a) b) 191 5.1.2 Chapter 3 summary Previously, in large cohorts of HSCT patients we identified increased numbers of CD56bright, granzyme B-, perforin- NK cells (NKreg) to be associated with a lack of cGvHD development. Functional analysis suggested that the NKreg population suppresses CD4+ T cells through a non-cytolytic, and direct cell-cell contact-dependent mechanism, though the exact receptor and ligand interaction of which CD4+ T cell populations are impacted is unknown. Thus, I hypothesized that NKreg cells may induce immune tolerance by suppressing inflammatory immune cells which contribute to cGvHD pathogenesis and aimed to investigate the suppressive capacity and mechanism of NKreg cells towards immune cell populations relevant to cGvHD through functional assays. I demonstrated that NKreg cells do not result in significant suppression of a specific CD4+ T helper cell subset (or naïve vs memory Th cells), B cells, cytolytic NK cells, or Treg cells, but rather a general suppressive effect towards CD4+ T cell proliferation, which occurs through a non-cytolytic and primarily contact-dependent mechanism. Further investigation of the suppressive mechanism demonstrated it to be at least partially dependent on the PD-1, LAG-3, and TRAIL inhibitory pathways. The results of these studies contribute to the better understanding of how NKreg cells may induce a selective suppressive function to promote immune tolerance and provides potential applications for enhancing NKreg cell suppressive function, such as through increasing PD-1, LAG-3, and/or TRAILR ligand expression. 192 Figure 32: Thesis chapter 3 main results summary. Phenotype, suppressive function, and suppressive mechanism of regulatory natural killer cells towards CD4+ T cells, CD8+ T cells, NK cells, B cells, and Treg cells +/- dendritic cells. Original figure created on Biorender.com. 193 5.1.3 Chapter 4 summary As a result of my prior observations (thesis, chapters 1, 2, and 3), I concluded that NKreg cells may be important in the induction of immune tolerance after HSCT and are a potential candidate for the development of a cGvHD cellular therapy. However, in healthy individuals peripheral NKreg cells represent ~0.3% of white blood cells. Thus, cell expansion is required for NKreg cells to be applicable for the adoptive transfer and clinical setting. Therefore, I aimed to optimally expand CD56brightCD16- NKreg cells, maintaining their regulatory phenotype and function. To meet my objective, total NK cells or NKreg cells were enriched from human peripheral blood and expanded for up to 21 days with IL-2 combined with the following ligands to prevent NK cell differentiation: rapamycin, TGF-β1, NECA, metformin, or dexamethasone. The optimal expansion cytokine combination was then applied and compared in terms of fold-expansion, phenotype, T cell suppressive capacity, cytotoxicity, and metabolic characteristics for three NK cell-specific expansion medias, including those sold from Miltenyi Biotec, R&D Systems, and Stemcell Technologies. The optimally expanded cells were further characterized according to transcriptome (bulk RNAseq), and proteome. Further, I compared the expansion, phenotype, and function of cord blood derived NKreg cells to peripheral blood derived NKreg cells utilizing the optimized expansion protocol. Lastly, I tested an alternative method for NKreg cell expansion, being differentiation of NKreg cells from CD34+ stem and progenitor cells. I observed optimal expansion with use of IL-2 and TGF-β1 with later pulsing of rapamycin in Immunocult NK Cell Expansion media from Stemcell Technologies, achieving up to 300-fold expansion over 21-days. These 194 expanded NKreg cells maintained similar phenotype, transcriptome, and suppressive capacity to fresh NKreg cells, and can be characterized according to their glycolytic metabolic profile and increased spare respiratory capacity. I also observed that cells derived from peripheral blood resulted in significantly greater expansion than those derived from cord blood. Further, HSPC differentiation results in cells of similar phenotypic and functional abilities to peripheral NKreg cells, though in significantly higher numbers, being up to 3.5billion NKreg cells from 1 cord blood unit. As a result of these studies, I have optimized an in vitro expansion approach for NKreg cells associated with a lack of cGvHD and have demonstrated the maintenance of the cells phenotypic and functional characteristics. With further optimization we may work towards utilizing a serum-free expansion protocol and applying this method for clinical grade expansion, with the goal of utilizing these cells as a cellular therapy for cGvHD. 195 Figure 33: Thesis chapter 4 main results summary. Optimized expansion protocol for regulatory natural killer cells, and expanded regulatory natural killer cell’s function, phenotype, metabolome, transcriptome, and proteome. Original figure created on Biorender.com. 196 5.2 Study limitations The strength and importance of this study in the context of immunology, hematopoietic stem cell transplantation, and cellular therapy will be noted, but it is also critical to identify the limitations of the work completed, the interpretation of the results, and the applications of these findings to a clinical setting. One limitation of this research included the small patient sample size in the initial nanoString transcriptome study (18 patients total, 6 patients in each group (aGvHD, cGvHD, no GvHD)). With a larger sample size, I may have identified additional or different genes of importance in characterizing the RNA expression of CD56bright NK cells associated with immune tolerance. Another limitation of this study included the interpretation of the NKreg cell versus naïve and memory CD4+ T cell suppression assay. In this experiment I identified the naïve and memory CD4+ T cell subsets using CD45RA/CD45RO staining of the total CD4+ T cell subset before and after the 96hr co-culture. However, interpreting the effects of NKreg cells on the individual naïve and memory CD4+ T cell subsets may be affected by the inclusion of the total CD4+ group, and thus it would be useful to also complete this same experiment with separately isolated naïve and memory CD4+ T cells. Similarly, my experiment investigating NKreg cell suppression towards CD4+ Th1,2,17 subsets also utilized a flow cytometric staining approach to identify the three Th cell populations, though all subsets were ultimately cultured together over the 96hr co-culture period. Thus, in this case it is also possible that 197 the presence of other Th cells may affect the activation and function of another and be a potential confounding variable in the study, as mentioned in the discussion of chapter 3. Regarding the NKreg cell and Treg cell co-culture experiments, I concluded a lack of suppressive effect of the NKreg cells towards Treg cells, having hypothesized this to be the case, but also that NKreg cells may further induce proliferation of the Treg cells. Though I did not observe this to be true, future experiments may investigate this hypothesis further, by repeating such experiments in an environment of suboptimal Treg cell proliferation to parse out the effects more clearly of NKreg cells on Treg cell proliferation, which could be achieved through utilizing lower concentrations of the CD3/CD28 activator. Additionally, an alternative mechanism by which NKreg cells may modulate Treg cells could be investigated, such as evaluating the phenotype and suppressive capacity of Treg cells after co-culture with NKreg cells. Further, it is mentioned in this dissertation that according to the literature, both NK cells and CD4+ T cells may express PD-1 and LAG-3 receptors and associated ligands. Thus, to elucidate the PD-1 and LAG-3 dependent mechanism of NKreg suppression more clearly, we completed cell surface phenotyping. These experiments suggested CD4+ T cells to be responsible for expressing the receptors involved in these two mechanisms. Another method that is currently under investigation, is completing knockout studies of the candidate receptors and ligands in both NKreg cells and CD4+ T cells to then test in co-culture and see which knockout combinations result in significant effects to the suppressive capacity of the NKreg cells. Further, an additional method that was not explored, though may be tested in future work, could be the evaluation of the activation 198 of downstream signalling events caused by PD-1 or LAG-3 receptor engagement among both the CD4+ T cells and NKreg cells. For example, in the PD-1 signalling pathway, after interacting with its ligands, the phosphatase SHP-2 is recruited in proximity to the TCR, and affects downstream signaling pathways, including the PI3K-phosphoinositide-dependent kinase 1 (PDK1)-AKT-mTOR pathway, mitogen-activated protein kinase kinase (MAPKK)-extracellular-signal-regulated kinase (ERK) pathway, and JAK-STAT pathways.220 Similarly, this same evaluation of signalling activation analysis may be performed on cells when the LAG-3 receptor is engaged. This may serve as an alternate and perhaps more conclusive method of describing the suppressive mechanism, as knockout experiments can cause effects to cell function, which may serve as a confounding variable. Additionally, in the mechanistic studies I utilized neutralizing antibodies specific for in vitro functional analysis to evaluate the effects on the NKreg cell suppressive capacity when blocking various candidate receptors. In the case of blocking the PD-1, LAG-3, and TRAIL receptors I identified a significant decrease in the NKreg cell suppressive capacity towards CD4+ T cells. However, none of these experiments demonstrated 100% inhibition of the suppressive function. This may be due to potentially other mechanisms acting in addition to PD-1/LAG-3/TRAIL, though another likely explanation is the possibility of inefficacious binding of the receptor blockers, particularly over the 96hr co-culture period, allowing for some engagement of the PD-1, LAG-3, or TRAIL receptors. Regarding the cell expansion experiments, though my most optimal expansion protocol has shown to expand NKreg cells while maintaining suppressive capacity and limiting 199 phenotypic maturation, this protocol could be optimized further to try and fully prevent phenotypic maturation, which I would expect to associate with even greater suppressive ability, such as with use of slightly higher rapamycin concentrations, and/or an increased number of pulses with rapamycin. Although, using higher concentrations is also something to be weary of as rapamycin may begin to have deleterious effects on cell function and metabolism if used at too high a concentration. Rapamycin suppresses immune function, potentially causing serious side effects such as thrombocytopenia and hyperlipidemia, impaired wound healing, nephrotoxicity, and altered insulin sensitivity if used long-term.221 Thus, multiple lower concentration rapamycin infusions may be a more efficacious approach, which has safely been demonstrated in various clinical settings, and may be a topic worth investigating in future in vivo studies of NKreg cell persistence and function. Further, in the expansion optimizations I successfully demonstrated a method of expanding and differentiating NKreg cells from CD34+ HSPCs when using a stem cell differentiation kit from Stemcell Technologies. This kit was optimized by the company for NK cell differentiation, and not specifically for NKreg cells. Therefore, though the current work has shown proof of principle in utilizing this concept in a future expansion approach, it may be further optimized by creating an in-house differentiation protocol, which may remove differentiation or activation factors which promote NK cell maturation to the cytolytic phenotype and be even more effective in obtaining NKreg cells. Finally, in any future NKreg cell expansion approach which is aimed to be utilized in a clinical study, the protocol would need to be re-evaluated using GMP-grade reagents. The current protocol was designed with this in mind, and thus most products are currently available in GMP form, though this would need to be tested to 200 confirm similar efficacy. 5.3 Contribution to the field, future directions, and final notes HSCT, the infusion of a donor’s immune system into a recipient, is an important immune-based therapy for patients with high-risk and recurring blood cancers, as well as non-malignant diseases.2 Though HSCT may result in a patient being cured of their underlying malignant or non-malignant disease, HSCT may also result in these same patients developing the treatment-induced, potentially life-long and fatal disease, cGvHD, in which foreign donor immune cells attack the recipient’s tissues.222 cGvHD occurs in about 25% of pediatric and 60% of adult HSCT survivors.6 It is known to cause long-term, and often irreversible organ damage and has a 10-25% mortality rate.6 Currently, the treatment of cGvHD utilizes immune suppressive therapies, such as mTOR inhibitors (sirolimus), mycophenolate mofetil, and monoclonal antibodies (anti-thymocyte globulin, and rituximab) which act to both prevent and treat chronic rejection. FDA approved, and currently more commonly used cGvHD drugs include ibrutinib (BTK inhibitor), belumosudil (ROCK inhibitor), and ruxolitinib (JAK1/2 inhibitor) which inhibit various cellular functions, such as that of B cells and T cells.8 Though none of these drugs target NK cell specific pathways, there are various studies which describe the effects of these drugs on NK cells which may contribute towards their relevancy in GvHD. For instance, one study demonstrated that BTK inhibitors significantly inhibit NK cell cytotoxicity,223 perhaps promoting differentiation or function of the immature, regulatory NK cells. Additionally, JAK1 is known to be involved in the signal transduction of several 201 cytokines crucial for NK cell biology, many of which are important in regulating NK cell development, maturation, and function.224 Therefore, a JAK1/2 inhibitor may result in impaired development, maturation, and function of classic NK cells, potentially promoting the NKreg cell state. In contrast, ROCK inhibitors have shown to promote NK cell cytotoxicity towards various tumor cell lines, including that of ovarian cancer and other solid tumors.225 Previous studies have shown a decreased proportion of NKreg cells in adult and pediatric HSCT patients both before and at the onset of cGvHD.7,43,44 Currently, the focus on regulatory mechanisms in cGvHD have primarily evaluated the role of Treg cells46 and to a lesser extent, Breg cells.226 Thus, strategies to induce immune tolerance through augmentation of regulatory mechanisms have also focused primarily on increasing the function of Treg cells, either by strategies that do not suppress Treg cells, such as ruxolitinib,227 or expansion of Treg cells by low dose IL-2 or ECP.15 Our groups studies suggest that NKreg cells may have an early innate-mediated tolerogenic stimulus on the development of cGvHD with a lack of NKreg cells both before the onset of cGvHD and at the onset of cGvHD. This may be similar to physiological settings, such as in placental tolerance where CD56bright NK cells are present in the first trimester, while only in the second and third trimester are Treg cells present.228 Interestingly, the successful cGvHD therapies of low dose IL-2 and ECP, utilised to augment Treg cells, also simultaneously augment CD56bright NK cells, and some studies have suggested that the CD56bright NK population most closely correlates with suppression of cGvHD.16 Moreover, NKreg cells have been identified as important in the suppression of other autoimmune diseases and 202 settings, including solid organ transplantation and rheumatoid arthritis, and are part of the suppressive tumor immune microenvironment.49 Further, clinical trials of the adoptive transfer of expanded cytolytic NK cells have shown to decrease leukemia relapse with no increase in acute or chronic GvHD or toxicity, suggesting efficacy for an NKreg-based adoptive cell transfer therapy for cGvHD. As a result of my studies, one can now effectively isolate, expand, and characterize (according to phenotype, transcriptome, proteome, metabolome, and function) the human peripheral regulatory CD56bright, non-cytolytic NK cell population. This has defined the CD4+ T-cell selective immune-suppressive regulatory NK cell subset that is strongly associated with suppression of cGvHD development and thus may have therapeutic applications. To my knowledge, this thesis and my associated publications are the first reports of a comprehensive characterization and expansion of human NKreg cells associated with cGvHD. My findings combined with existing evidence support the initiative of greater research into the functioning of NKreg cells in the cGvHD context, particularly regarding their selective suppressive mechanism, and the optimization of the expansion of NKreg cells. Specifically, future work should focus on the further understanding and characterization of the NKreg cell subpopulation associated with cGvHD, including the lineage development and differentiation pathway of NKreg cells in inflammatory and non-inflammatory contexts with the aim of promoting NKreg-like phenotype and function, cell manipulation experiments to induce greater expression of PD-1/LAG3/TRAILR ligands for more efficient suppression of CD4+ T cell proliferation, and the potential modulatory mechanism of NKreg cells towards Treg cells. 203 Additionally, in having established an effective mechanism for isolating and expanding functional NKreg cells, in vivo studies designed to demonstrate efficacy in a humanized mouse model of GvHD would be a valid next step in confirming human NKreg cell suppression of GvHD. This work would also provide for an additional comparison of how NKreg cells fare to Treg cells, which have demonstrated efficacy in humanized mouse models of GvHD.147 Further, more recently a population of murine NK cells demonstrating tissue residency and memory-like characteristics has been described.229 This population of NK cells forms and expands in response to murine CMV infection, is phenotypically and transcriptionally unique with a lack of cytotoxic marker expression, and demonstrates a suppressive and immune regulation/tissue protective function through inhibiting CD4+ T cell proliferation, ectopic lymphoid structure formation, and autoantibody production through a TRAIL-mediated pathway.229 Thus, this newly described subset of NK cells in mice appears to be transcriptionally, phenotypically, and functionally comparable to the peripheral NKreg cells I have described and may serve as a viable option for completing fully murine-based studies, evaluating the effect of murine NKreg-like cells in preventing cGvHD development in mice. It would also be interesting to expand this work to other inflammatory diseases of which CD4+ T cells serve as a main mediator and investigate alternative potential applications of NKreg cells in a translational research setting. Lastly, with the goal of using these cells as an adoptive transfer cell therapy, further investigating the possible sources for deriving and expanding NKreg cells, the effect of multiple cell infusions, and applying the preferred source and method of 204 isolation/expansion to a clinical grade system, such as the Miltenyi Prodigy being used for Treg cell clinical studies, will be crucial. Further optimization and operationalization of the NKreg cells for clinical use will be imperative to their application as an adoptive transfer cell therapy for cGvHD. This future work will advance the clinical relevance of NKreg cells as a potential immunotherapy for cGvHD, which may contribute towards the improvement of the safety and efficacy of HSCT. Figure 34 summarizes the phenotypical and functional characteristics of NKreg cells.7,18,43-45,50,63,68,80,95,97,107,113-117,119,130-132 205 Created on Biorender.com Figure 34: Functional and phenotypic characteristics of NKreg cells (visual summary). 206 References 1. Mahla RS. Stem Cells Applications in Regenerative Medicine and Disease Therapeutics. International journal of cell biology. 2016;2016:6940283-24. 2. Park B, Yoo KH, Kim C. Hematopoietic stem cell expansion and generation: the ways to make a breakthrough. Blood research. 2015;50:194-203. 3. Hatzimichael E, Tuthill M. Hematopoietic stem cell transplantation. Stem Cells Cloning. 2010;3:105-117. 2010. doi:10.2147/SCCAA.S6815 4. Ogonek J, Kralj Juric M, Ghimire S, et al. Immune Reconstitution after Allogeneic Hematopoietic Stem Cell Transplantation. Frontiers in immunology. 2016;7:507-507. 5. Justiz Vaillant AA, Modi P, Mohammadi O. Graft Versus Host Disease. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing. 2021. Available from: https://www.ncbi.nlm.nih.gov/books/NBK538235/ 6. Schultz KR, Kariminia A, Ng B, et al. Immune profile differences between chronic GVHD and late acute GVHD: results of the ABLE/PBMTC 1202 studies. Blood. 2020;135:1287-1298. 7. Zeiser R, Blazar BR. Pathophysiology of Chronic Graft-versus-Host Disease and Therapeutic Targets. The New England journal of medicine. 2017;377:2565-2579. 8. Zeiser R, Lee SJ. Three US Food and Drug Administration-approved therapies for chronic GVHD. Blood. 2022;139(11):1642-1645. doi:10.1182/blood.2021014448 9. Wolff D, Greinix H, Lee SJ, Gooley T, Paczesny S, Pavletic S, Hakim F, Malard F, Jagasia M, Lawitschka A, Hansen JA, Pulanic D, Holler E, Dickinson A, Weissinger E, 207 Edinger M, Sarantopoulos S, Schultz KR. Biomarkers in chronic graft-versus-host disease: quo vadis? Bone Marrow Transplant. 2018;53:832-837. 10. Blazar BR, MacDonald KPA, Hill GR. Immune regulatory cell infusion for graft-versus-host disease prevention and therapy. Blood. 2018;131:2651-2660. 11. Schultz KR, Zhang Y, McBride ML. High Rate Of Health Care Utilization Associated With Chronic Graft-Versus-Host Disease Among Canadian Childhood Cancer Survivors Treated With Blood And Marrow Transplantation. EBMT meeting, Lisbon, March 18, 2018. 12. Cooke KR, Luznik L, Sarantopoulos S, Hakim FT, Jagasia M, Fowler DH, van den Brink MRM, Hansen JA, Parkman R, Miklos DB, Martin PJ, Pazcesny S, Vogelsang G, Pavletic S, Ritz J, Schultz KR*, Blazar BR* (co-senior author). The Biology of Chronic Graft-versus-Host Disease: A Task Force Report From the National Institutes of Health Consensus Development Project on Criteria for Clinical Trials in Chronic Graft-Versus-Host Disease. Biol Blood Marrow Transplant. 2017;3:211-234. 13. Filipovich AH, Weisdorf D, Pavletic S, et al. National Institutes of Health Consensus Development Project on Criteria for Clinical Trials in Chronic Graft-versus-Host Disease: I. Diagnosis and Staging Working Group Report. Biology of blood and marrow transplantation. 2005;11:945-956. 14. Bertaina A, Roncarolo MG. Graft Engineering and Adoptive Immunotherapy: New Approaches to Promote Immune Tolerance After Hematopoietic Stem Cell Transplantation. Front Immunol. 2019;10:1342. 208 15. Koreth J, Kim HT, Belizaire R, et al. Extra-Corporeal Photopheresis Plus Low-Dose Interleukin-2 for Steroid-Refractory Chronic Graft-Vs.-Host Disease: Efficacy, Safety and Immune Correlates. Blood. 2017;130:515-515. 16. Iniesta P, Revilla N, Chen-Liang TH, et al. An early increase of CD56bright natural killer subset as dominant effect and predictor of response to extracorporeal photopheresis for graft-versus-host disease. Transfusion. 2018;58(12):2924-2932. doi:10.1111/trf.14964. 17. Hirakawa M, Matos TR, Liu H, Koreth J, Kim HT, Paul NE, Murase K, Whangbo J, Alho AC, Nikiforow S, Cutler C, Ho VT, Armand P, Alyea EP, Antin JH, Blazar BR, Lacerda JF, Soiffer RJ, Ritz J. Low-dose IL-2 selectively activates subsets of CD4+ Tregs and NK cells. JCI Insight. 2016;1:e89278. 18. McQuaid SL, Loughran ST, Power PA, Maguire P, Szczygiel A, Johnson PA. Low‐dose IL‐2 induces CD56bright NK regulation of T cells via NKp44 and NKp46. Clin Exp Immunol. 2020;200(3):228-241. 19. He J, Zhang R, Shao M, Zhao X, Miao M, Chen J, Liu J, Zhang X, Zhang X, Jin Y, Wang Y, Zhang S, Zhu L, Jacob A, Jia R, You X, Li X, Li C, Zhou Y, Yang Y, Ye H, Liu Y, Su Y, Shen N, Alexander J, Guo J, Ambrus J, Lin X, Yu D, Sun X, Li Z. Efficacy and safety of low-dose IL-2 in the treatment of systemic lupus erythematosus: a randomised, double-blind, placebo-controlled trial. Ann Rheum Dis. 2020;79(1):141-149. 20. Ruggeri L, Capanni M, Urbani E, Perruccio K, Shlomchik WD, Tosti A, et al. Effectiveness of donor natural killer cell alloreactivity in mismatched hematopoietic transplants. Science. 2002;295(5562):2097–100. doi:10.1126/science.1068440. 209 21. Miller JS, Soignier Y, Panoskaltsis-Mortari A, et al. Successful adoptive transfer and in vivo expansion of human haploidentical NK cells in patients with cancer. Blood. 2005;105:3051–7. 22. Rubnitz JE, Inaba H, Ribeiro RC, Pounds S, Rooney B, Bell T, Pui CH, Leung W. NKAML: a pilot study to determine the safety and feasibility of haploidentical natural killer cell transplantation in childhood acute myeloid leukemia. J Clin Oncol. 2010;28:955–9. 23. Murphy WJ, Bennett M, Kumar V, Longo DL. Donor-type activated natural killer cells promote marrow engraftment and B cell development during allogeneic bone marrow transplantation. J Immunol. 1992;148(9):2953–60. 24. Simonetta F, Alvarez M, Negrin RS. Natural Killer Cells in Graft-versus-Host-Disease after Allogeneic Hematopoietic Cell Transplantation. Front Immunol. 2017;8:465. doi:10.3389/fimmu.2017.00465. 25. Asai O, Longo DL, Tian Z-G, Hornung RL, Taub DD, Ruscetti FW, et al. Suppression of graft-versus-host disease and amplification of graft-versus-tumor effects by activated natural killer cells after allogeneic bone marrow transplantation. J Clin Invest. 1998;101(9):1835. doi:10.1172/JCI1268. 26. Lundqvist A, McCoy JP, Samsel L, Childs R. Reduction of GVHD and enhanced antitumor effects after adoptive infusion of alloreactive Ly49-mismatched NK cells from MHC-matched donors. Blood. 2007;109(8):3603–6. doi:10.1182/blood-2006-05-024315. 27. Chen G, Wu D, Wang Y, Cen J, Feng Y, Sun A, et al. Expanded donor natural killer cell and IL-2, IL-15 treatment efficacy in allogeneic hematopoietic stem cell transplantation. Eur J Haematol. 2008;81(3):226–35. doi:10.1111/j.1600-0609.2008.01108.x. 210 28. Olson JA, Leveson-Gower DB, Gill S, Baker J, Beilhack A, Negrin RS. NK cells mediate reduction of GVHD by inhibiting activated, alloreactive T cells while retaining GVT effects. Blood. 2010;115(21):4293–301. doi:10.1182/blood-2009-05-222190. 29. Meinhardt K, Kroeger I, Bauer R, Ganss F, Ovsiy I, Rothamer J, et al. Identification and characterization of the specific murine NK cell subset supporting graft-versus-leukemia- and reducing graft-versus-host-effects. Oncoimmunology. 2015;4(1):e981483. doi:10.4161/2162402X.2014.981483. 30. Huber CM, Doisne JM, Colucci F. IL-12/15/18-preactivated NK cells suppress GvHD in a mouse model of mismatched hematopoietic cell transplantation. Eur J Immunol. 2015;45(6):1727–35. doi:10.1002/eji.201445200. 31. Soiffer RJ, Gonin R, Murray C, Robertson MJ, Cochran K, Chartier S, et al. Prediction of graft-versus-host disease by phenotypic analysis of early immune reconstitution after CD6-depleted allogeneic bone marrow transplantation. Blood. 1993;82(7):2216–23. 32. Yamasaki S, Henzan H, Ohno Y, Yamanaka T, Iino T, Itou Y, et al. Influence of transplanted dose of CD56 + cells on development of graft-versus-host disease in patients receiving G-CSF-mobilized peripheral blood progenitor cells from HLA-identical sibling donors. Bone Marrow Transplant. 2003;32(5):505–10. doi:10.1038/sj.bmt.1704165. 33. Abrahamsen IW, Somme S, Heldal D, Egeland T, Kvale D, Tjonnfjord G. Immune reconstitution after allogeneic stem cell transplantation: the impact of stem cell source and graft-versus-host disease. Haematologica. 2005;90(1):86–93. 34. Kim DH, Sohn SK, Lee NY, Baek JH, Kim JG, Won DI, et al. Transplantation with higher dose of natural killer cells associated with better outcomes in terms of non-relapse mortality and infectious events after allogeneic peripheral blood stem cell transplantation 211 from HLA-matched sibling donors. Eur J Haematol. 2005;75(4):299–308. doi:10.1111/j.1600-0609.2005.00514.x. 35. Larghero J, Rocha V, Porcher R, Filion A, Ternaux B, Lacassagne MN, et al. Association of bone marrow natural killer cell dose with neutrophil recovery and chronic graft-versus-host disease after HLA identical sibling bone marrow transplants. Br J Haematol. 2007;138(1):101–9. doi:10.1111/j.1365-2141.2007.06623.x. 36. Savani BN, Mielke S, Adams S, Uribe M, Rezvani K, Yong AS, et al. Rapid natural killer cell recovery determines outcome after T-cell-depleted HLA-identical stem cell transplantation in patients with myeloid leukemias but not with acute lymphoblastic leukemia. Leukemia. 2007;21(10):2145–52. doi:10.1038/sj.leu.2404892. 37. Tanaka M, Kobayashi S, Numata A, Tachibana T, Takasaki H, Maruta A, et al. The impact of the dose of natural killer cells in the graft on severe acute graft-versus-host disease after unrelated bone marrow transplantation. Leuk Res. 2012;36(6):699–703. doi:10.1016/j.leukres.2011.11.009. 38. Kim SY, Lee H, Han M-S, Shim H, Eom H-S, Park B, et al. Post-transplantation natural killer cell count: a predictor of acute graft-versus-host disease and survival outcomes after allogeneic hematopoietic stem cell transplantation. Clin Lymphoma Myeloma Leuk. 2016;16(9):527.–535. doi:10.1016/j.clml.2016.06.013. 39. Ludajic K, Balavarca Y, Bickeböller H, Rosenmayr A, Fae I, Fischer G, et al. KIR genes and KIR ligands affect occurrence of acute GVHD after unrelated, 12/12 HLA matched, hematopoietic stem cell transplantation. Bone Marrow Transplant. 2009;44(2):97–103. doi:10.1038/bmt.2008.432. 212 40. Clausen J, Kircher B, Auberger J, Schumacher P, Ulmer H, Hetzenauer G, et al. The role of missing killer cell immunoglobulin-like receptor ligands in T cell replete peripheral blood stem cell transplantation from HLA-identical siblings. Biol Blood Marrow Transplant. 2010;16(2):273–80. doi:10.1016/j.bbmt.2009.10.021. 41. Sivori S, Carlomagno S, Falco M, Romeo E, Moretta L, Moretta A. Natural killer cells expressing the KIR2DS1-activating receptor efficiently kill T-cell blasts and dendritic cells: implications in haploidentical HSCT. Blood. 2011;117(16):4284–92. doi:10.1182/blood-2010-10-316125. 42. Ruggeri L, Mancusi A, Capanni M, Urbani E, Carotti A, Aloisi T, et al. Donor natural killer cell allorecognition of missing self in haploidentical hematopoietic transplantation for acute myeloid leukemia: challenging its predictive value. Blood. 2007;110(1):433–40. doi:10.1182/blood-2006-07-038687. 43. Kariminia A, Holtan SG, Ivison S, Rozmus J, Hebert M-J, Martin P, Lee SJ, Wolff D, Subrt P, Samadi S, Sung S, Storek J, Levings M, Aljurf MDSA, Arora M, Cutler C, Gallagher G, Kuruvilla J, Lipton J, Nevill T, Newell LF, Pidala J, Popradi G, Szwajcer D, Tay J, Toze C, Walker I, Couban S, Storer B, Schultz KR. Heterogeneity of chronic graft-versus-host disease biomarkers: the only consistent association is with CXCL10 and CXCR3+ NK cells. Blood. 2016;127:3082-91. 44. Kariminia A, Ivison S, Ng B, Rozmus J, Sung S, Varshney A, Aljurf M, Lachance S, Walker I, Toze C, Lipton J, Lee SJ, Szer J, Doocey R, Lewis I, Smith C, Chaudhri N, Levings MK, Broady R, Devins G, Szwajcer D, Foley R, Mostafavi S, Pavletic S, Wall DA, Couban S, Panzarella T, Schultz KR. CD56bright NK regulatory cells in filgrastim 213 primed donor blood or marrow products regulate chronic GvHD: CBMTG randomized 0601 study results. Haematologica. 2017;102(11):1936-1946. 45. Schultz KR, Zhang Y, McBride ML. High Rate Of Health Care Utilization Associated With Chronic Graft-Versus-Host Disease Among Canadian Childhood Cancer Survivors Treated With Blood And Marrow Transplantation. EBMT meeting, Lisbon, March 18, 2018. 46. Whangbo JS, Antin JH, Koreth J. The role of regulatory T cells in graft-versus-host disease management. Expert Rev Hematol. 2020;13(2):141-154. doi:10.1080/17474086.2020.1709436. 47. Wood SM, Ljunggren H, Bryceson YT. Insights into NK cell biology from human genetics and disease associations. Cellular and molecular life sciences : CMLS. 2011;68:3479-3493. 48. Shi F, Ljunggren H, La Cava A, Van Kaer L. Organ-specific features of natural killer cells. Nature reviews. Immunology. 2011;11:658-671. 49. Tian Z, Gershwin ME, Zhang C. Regulatory NK cells in autoimmune disease. Journal of autoimmunity. 2012;39:206-215. 50. Jiang W, Chai NR, Maric D, Bielekova B. Unexpected role for granzyme K in CD56bright NK cell-mediated immunoregulation of multiple sclerosis. The Journal of immunology (1950). 2011;187:781-790. 51. Wang J, Sun R, Wei H, Dong Z, Tian Z. Pre-activation of T lymphocytes by low dose of concanavalin A aggravates toll-like receptor-3 ligand-induced NK cell-mediated liver injury. International immunopharmacology. 2006;6:800-807. 214 52. Johansson S, Berg L, Hall H, Höglund P. NK cells: elusive players in autoimmunity. Trends in Immunology. 2005;26:613-618. 53. Perricone R, Perricone C, De Carolis C, Shoenfeld Y. NK cells in autoimmunity: A two-edg'd weapon of the immune system. Autoimmunity reviews. 2008;7:384-390. 54. Jabrane-Ferrat N. Features of Human Decidual NK Cells in Healthy Pregnancy and During Viral Infection. Frontiers in immunology. 2019;10:1397-1397. 55. Moffett A, Colucci F. Uterine NK cells: active regulators at the maternal-fetal interface. J Clin Invest. 2014;124:1872–9. doi: 10.1172/JCI68107. 56. Jabrane-Ferrat N, Siewiera J. The up side of decidual natural killer cells: new developments in immunology of pregnancy. Immunology. 2014;141:490–7. doi: 10.1111/imm.12218. 57. Siewiera J, Gouilly J, Hocine HR, Cartron G, Levy C, Al-Daccak R, et al. Natural cytotoxicity receptor splice variants orchestrate the distinct functions of human natural killer cell subtypes. Nat Commun. 2015;6:10183. doi: 10.1038/ncomms10183. 58. Vacca P, Pietra G, Falco M, Romeo E, Bottino C, Bellora F, et al. Analysis of natural killer cells isolated from human decidua: evidence that 2B4 (CD244) functions as an inhibitory receptor and blocks NK-cell function. Blood. 2006;108:4078–85. doi: 10.1182/blood-2006-04-017343. 59. Hanna J, Goldman-Wohl D, Hamani Y, Avraham I, Greenfield C, Natanson-Yaron S, et al. Decidual NK cells regulate key developmental processes at the human fetal-maternal interface. Nat Med. 2006;12:1065–74. doi: 10.1038/nm1452. 215 60. Koopman LA, Kopcow HD, Rybalov B, Boyson JE, Orange JS, Schatz F, et al. Human decidual natural killer cells are a unique NK cell subset with immunomodulatory potential. J Exp Med. 2003;198:1201–12. doi: 10.1084/jem.20030305. 61. Kopcow HD, Allan DS, Chen X, Rybalov B, Andzelm MM, Ge B, et al. Human decidual NK cells form immature activating synapses and are not cytotoxic. Proc Natl Acad Sci USA. 2005;102:15563–8. doi: 10.1073/pnas.0507835102. 62. Moffett A, Shreeve N. First do no harm: uterine natural killer (NK) cells in assisted reproduction. Hum Reprod. 2015;30:1519–25. doi: 10.1093/humrep/dev098. 63. Lünemann A, Lünemann JD, Münz C. Regulatory NK-cell functions in inflammation and autoimmunity. Molecular medicine (Cambridge, Mass.). 2009;15:352-358. 64. Cooper MA, Fehniger TA, Caligiuri MA. The biology of human natural killer-cell subsets. Trends Immunol. 2001;22:633–40. 65. Mavilio D, Lombardo G, Benjamin J et al. Characterization of CD56-/CD16+ natural killer (NK) cells: a highly dysfunctional NK subset expanded in HIV-infected viremic individuals. Proc Natl Acad Sci USA. 2005;102:2886–91. 66. Caligiuri M. Human natural killer cells. Blood. 2008;112:461–9. 67. Zhang J, Zheng H, Diao Y. Natural Killer Cells and Current Applications of Chimeric Antigen Receptor-Modified NK-92 Cells in Tumor Immunotherapy. International Journal of Molecular Sciences. 2019; 20(2):317. https://doi.org/10.3390/ijms20020317 68. Chiossone L, Dumas PY, Vienne M, Vivier E. Natural killer cells and other innate lymphoid cells in cancer. Nat. Rev. Immunol. 2018;18, 671–688. 69. Prager I, Watzl C. Mechanisms of natural killer cell-mediated cellular cytotoxicity. J Leukoc Biol. 2019;105(6):1319-1329. doi:10.1002/JLB.MR0718-269R. 216 70. Wajant H. The Fas Signaling Pathway: More Than a Paradigm. Science. 2002;296, 1635–1636. 71. Waring P, Mullbacher A. Cell death induced by the Fas/Fas ligand pathway and its role in pathology. Immunol. Cell Biol. 1999;77, 312–317. 72. Anegón I, Cuturi MC, Trinchieri G, Perussia B. Interaction of Fc receptor (CD16) ligands induces transcription of interleukin 2 receptor (CD25) and lymphokine genes and expression of their products in human natural killer cells. J Exp Med. 1988;167:452–72. 73. Yeap WH, Wong KL, Shimasaki N, Teo ECY, Quek JKS, Yong HX, Diong CP, Bertoletti A, Linn YC, Wong SC. CD16 is indispensable for antibody dependent cellular cytotoxicity by human monocytes. Sci Rep. 2009;10. https://doi.org/10.1038/srep34310. 74. Moretta A, Bottino C, Vitale M, Pende D, Biassoni R, Mingari MC, Moretta L. Receptors for HLA class-I molecules in human natural killer cells. Annu Rev Immunol. 1996;14:619–648. 75. Biassoni R, Cantoni C, Falco M, Verdiani S, Bottino C, Vitale M, Conte R, Poggi A, Moretta A, Moretta L. The human leukocyte antigen (HLA)-C-specific "activatory" or "inhibitory" natural killer cell receptors display highly homologous extracellular domains but differ in their transmembrane and intracytoplasmic portions. J Exp Med. 1996;183:645–650. 76. Samaridis J, Colonna M. Cloning of novel immunoglobulin superfamily receptors expressed on human myeloid and lymphoid cells: Structural evidence for new stimulatory and inhibitory pathways. Eur J Immunol. 1997;27:660–665. 217 77. Braud VM, Allan DS, O’Callaghan CA, Soderstrom K, D’Andrea A, Ogg GS, Lazetic S, Young NT, Bell JI, Phillips JH, et al. HLA-E binds to natural killer cell receptors CD94/NKG2A, B and C. Nature. 1998;391:795–799. 78. Moretta A, Bottino C, Vitale M, Pende D, Cantoni C, Mingari MC, Biassoni R, Moretta L. Activating receptors and coreceptors involved in human natural killer cell-mediated cytolysis. Annu Rev Immunol. 2001;19:197–223. 79. Bi J, Wang X. Molecular Regulation of NK Cell Maturation. Front Immunol. 2020;11:1945. Published 2020 Aug 11. doi:10.3389/fimmu.2020.01945 80. Freud AG, Keller KA, Scoville SD, Mundy-Bosse BL, Cheng S, Youssef Y, et al. NKp80 Defines a Critical Step during Human Natural Killer Cell Development. Cell Rep. 2016;16(2):379–91. doi: 10.1016/ j.celrep.2016.05.095. 81. Vitale M, Falco M, Castriconi R, Parolini S, Zambello R, Semenzato G, et al. Identification of NKp80, a novel triggering molecule expressed by human NK cells. Eur J Immunol. 2001;31(1):233–42. doi: 10.1002/1521-4141 (200101)31:13.0.CO;2-4. 82. Abel AM, Yang C, Thakar MS, Malarkannan S. Natural Killer Cells: Development, Maturation, and Clinical Utilization. Front Immunol. 2018;9:1869. doi: 10.3389/fimmu.2018.01869. 83. Konjević GM, Vuletić AM, Mirjačić Martinović KM, Larsen AK, Jurišić VB. The role of cytokines in the regulation of NK cells in the tumor environment. Cytokine (Philadelphia, Pa.). 2019;117:30-40. 84. Pesce S, Squillario M, Greppi M, Loiacono F, Moretta L, Moretta A, et al. New miRNA Signature Heralds Human NK Cell Subsets at Different Maturation Steps: Involvement of 218 miR-146a-5p in the Regulation of KIR Expression. Front Immunol. 2018;9:2360. doi: 10.3389/fimmu.2018.02360. 85. Kubo T, Romee R, Koreth J, et al. Low-Dose Interleukin-2 Therapy Enhances Cytotoxicity of CD56bright NK Cells in Patients with Chronic Gvhd. Blood. 2018;132:606-606. 86. Björkström NK, Riese P, Heuts F, Andersson S, Fauriat C, Ivarsson MA, et al. Expression patterns of NKG2A, KIR, and CD57 define a process of CD56 dim NK-cell differentiation uncoupled from NK-cell education. Blood. 2010;116:3853–64. doi:10.1182/blood-2010-04-281675. 87. Vitale M, Della Chiesa M, Carlomagno S, Romagnani C, Thiel A, Moretta L, et al. The small subset of CD56brightCD16- natural killer cells is selectively responsible for both cell proliferation and interferon-gamma production upon interaction with dendritic cells. Eur J Immunol. 2004;34(6):1715–22. doi: 10.1002/eji.200425100. 88. Béziat V, Duffy D, Quoc SN, Le Garff-Tavernier M, Decocq J, Combadière B, et al. CD56brightCD16+ NK cells: a functional intermediate stage of NK cell differentiation. J Immunol. 2011;186:6753–61. doi:10.4049/jimmunol.1100330. 89. Vossen MT, Matmati M, Hertoghs KM, Baars PA, Gent MR, Leclercq G, et al. CD27 defines phenotypically and functionally different human NK cell subsets. J Immunol. 2008;180:3739–45. doi:10.4049/jimmunol.180.6.3739. 90. Yu J, Mao HC, Wei M, Hughes T, Zhang J, Park IK, et al. CD94 surface density identifies a functional intermediary between the CD56bright and CD56dim human NK-cell subsets. Blood. 2010;115:274–81. doi:10.1182/blood-2009-04-215491. 219 91. Juelke K, Killig M, Luetke-Eversloh M, Parente E, Gruen J, Morandi B, et al. CD62L expression identifies a unique subset of polyfunctional CD56dim NK cells. Blood. 2010;116:1299–307. doi:10.1182/blood-2009-11-253286. 92. Zamai L, Del Zotto G, Buccella F, Gabrielli S, Canonico B, Artico M, et al. Understanding the Synergy of NKp46 and Co-Activating Signals in Various NK Cell Subpopulations: Paving the Way for More Successful NK-Cell Based Immunotherapy. Cells. 2020;9(3):753. doi: 10.3390/cells9030753. 93. Zamai L, Galeotti L, Del Zotto G, Canonico B, Mirandola P, Papa S. Identification of a NCR+/NKG2D+/LFA-1(low)/CD94(-) immature human NK cell subset. Cytometry Part A J Int Soc Anal Cytol. 2009;75 (11):893–901. doi: 10.1002/cyto.a.20789. 94. Zamai L, Del Zotto G, Buccella F, Galeotti L, Canonico B, Luchetti F, et al. Cytotoxic functions and susceptibility to apoptosis of human CD56(bright) NK cells differentiated in vitro from CD34(+) hematopoietic progenitors. Cytometry Part A J Int Soc Anal Cytol. 2012;81(4):294–302. doi: 10.1002/ cyto.a.22025. 95. Poli A, Michel T, Theresine M, Andres E, Hentges F, Zimmer J. CD56bright natural killer (NK) cells: an important NK cell subset. Immunology. 2009;126(4):458–65. doi: 10.1111/j.1365-2567.2008.03027.x. 96. Michel T, Poli A, Cuapio A, Briquemont B, Iserentant G, Ollert M, et al. Human CD56bright NK Cells: An Update. J Immunol. 2016;196(7):2923– 31. doi: 10.4049/jimmunol.1502570. 97. Del Zotto G, Antonini F, Pesce S, Moretta F, Moretta L, Marcenaro E. Comprehensive Phenotyping of Human PB NK Cells by Flow Cytometry. Cytometry. Part A. 2020;97:891-899. 220 98. Smith SL, Kennedy PR, Stacey KB, Worboys JD, Yarwood A, Seo S, et al. Diversity of peripheral blood human NK cells identified by single-cell RNA sequencing. Blood Advances. 2020;4(7):1388–406. doi: 10.1182/ bloodadvances.2019000699. 99. Marcais A, Cherfils-Vicini J, Viant C, et al. The metabolic checkpoint kinase mTOR is essential for IL-15 signaling during the development and activation of NK cells. Nat Immunol. 2014;15:749–757. https://doi.org/10.1038/ni.2936 100. Keating SE, Zaiatz-Bittencourt V, Loftus RM, et al. Metabolic Reprogramming Supports IFN-gamma Production by CD56bright NK Cells. J Immunol. 2016;196:2552–2560. https://doi.org/10.4049/ jimmunol.1501783 101. Keppel MP, Saucier N, Mah AY, Vogel TP, Cooper MA. Activation specific metabolic requirements for NK Cell IFN-gamma production. J Immunol. 2015;194:1954–1962. https://doi.org/10.4049/ jimmunol.1402099 102. Donnelly RP, Loftus RM, Keating SE, et al. mTORC1-dependent metabolic reprogramming is a prerequisite for NK cell effector function. J Immunol. 2014;193:4477–4484. https://doi.org/10.4049/ jimmunol.1401558 103. Delgoffe GM, Powell JD. Sugar, fat, and protein: new insights into what T cells crave. Curr Opin Immunol. 2015;33:49–54. https://doi.org/ 10.1016/j.coi.2015.01.015 104. Schafer JR, Salzillo TC, Chakravarti N, et al. Education-dependent activation of glycolysis promotes the cytolytic potency of licensed human natural killer cells. J Allergy Clin Immunol. 2018. https://doi.org/10.1016/j.jaci.2018.06.047. 105. Viel S, Marçais A, Guimaraes FS, et al. TGF-beta inhibits the activation and functions of NK cells by repressing the mTOR pathway. Sci Signal. 2016;9:ra19. https://doi.org/10.1126/scisignal.aad1884 221 106. Zaiatz-Bittencourt V, Finlay DK, Gardiner CM. Canonical TGF-beta signaling pathway represses human NK cell metabolism. J Immunol. 2018;200:3934–3941. https://doi.org/10.4049/jimmunol.1701461 107. Konkel JE, Zhang D, Zanvit P, et al. Transforming Growth Factor-β Signaling in Regulatory T Cells Controls T Helper-17 Cells and Tissue-Specific Immune Responses. Immunity. 2017;46(4):660-674. doi:10.1016/j.immuni.2017.03.015. 108. Mah AY, Rashidi A, Keppel MP, et al. Glycolytic requirement for NK cell cytotoxicity and cytomegalovirus control. JCI Insight. 2017;2:pii: 95128. https://doi.org/10.1172/jci.insight.95128 109. Zeng H, Chi H. mTOR signaling in the differentiation and function of regulatory and effector T cells. Current opinion in immunology. 2017;46:103-111. 110. Fehniger TA, Cooper MA, Nuovo GJ, et al. CD56bright natural killer cells are present in human lymph nodes and are activated by T cell-derived IL-2: a potential new link between adaptive and innate immunity. Blood. 2003;101(8):3052-3057. doi:10.1182/blood-2002-09-2876. 111. Martin JF, Perry JS, Jakhete NR, Wang X, Bielekova B. An IL-2 paradox: blocking CD25 on T cells induces IL-2-driven activation of CD56(bright) NK cells. J Immunol. 2010;185:1311–20. 112. Caligiuri MA, Zmuidzinas A, Manley TJ, Levine H, Smith KA, Ritz J. Functional consequences of interleukin 2 receptor expression on resting human lymphocytes. Identification of a novel natural killer cell subset with high affinity receptors. J Exp Med. 1990;171(5):1509–1526. 222 113. Gross CC, Schulte-Mecklenbeck A, Wiendl H, et al. Regulatory Functions of Natural Killer Cells in Multiple Sclerosis. Front Immunol. 2016;7:606. doi:10.3389/fimmu.2016.00606. 114. Bielekova B, Catalfamo M, Reichert-Scrivner S, et al. Regulatory CD56(bright) natural killer cells mediate immunomodulatory effects of IL-2Ralpha-targeted therapy (daclizumab) in multiple sclerosis. Proc Natl Acad Sci U S A. 2006;103(15):5941-5946. doi:10.1073/pnas.0601335103. 115. Gross CC, Schulte-Mecklenbeck A, Rünzi A, et al. Impaired NK-mediated regulation of T-cell activity in multiple sclerosis is reconstituted by IL-2 receptor modulation. Proceedings of the National Academy of Sciences of the United States of America. 2016;113(21):E2973-82. DOI: 10.1073/pnas.1524924113. PMID: 27162345; PMCID: PMC4889377. 116. Laroni A, Gandhi R, Beynon V, Weiner HL. IL-27 imparts immunoregulatory function to human NK cell subsets. PLoS One. 2011;6(10):e26173. doi:10.1371/journal.pone.0026173. 117. Laroni A, Armentani E, Kerlero De Rosbo N, Ivaldi F, Marcenaro E, Sivori S, et al. Dysregulation of regulatory CD56(bright) NK cells/T cells interactions in multiple sclerosis. J Autoimmun. 2016;72:8–18.10.1016/j.jaut.2016.04.003. 118. Nielsen N, Odum N, Urso B, Lanier LL, Spee P. Cytotoxicity of CD56(bright) NK cells towards autologous activated CD4+ T cells is mediated through NKG2D, LFA-1 and TRAIL and dampened via CD94/NKG2A. PLoS One. 2012;7:e31959.10.1371/journal.pone.0031959. 223 119. Deniz G, Erten G, Kucuksezer UC, Kocacik D, Karagiannidis C, Aktas E, et al. Regulatory NK cells suppress antigen-specific T cell responses. J Immunol. 2008;180(2):850–7. doi: 10.4049/jimmunol.180.2.850. 120. Cosan F, Aktas Cetin E, Akdeniz N, Emrence Z, Cefle A, Deniz G. Natural Killer Cell Subsets and Their Functional Activity in Behcet’s Disease. Immunol Invest. 2017;46(4):419–32. doi: 10.1080/08820139.2017.1288240. 121. Kucuksezer UC, Aktas-Cetin E, Bilgic-Gazioglu S, Tugal-Tutkun I, Gul A, Deniz G. Natural killer cells dominate a Th-1 polarized response in Behcet’s disease patients with uveitis. Clin Exp Rheumatol. 2015;33(6 Suppl 94):S24–9. 122. Tahrali I, Kucuksezer UC, Altintas A, Uygunoglu U, Akdeniz N, Aktas-Cetin E, et al. Dysfunction of CD3(-)CD16(+)CD56(dim) and CD3(-)CD16(-)CD56(bright) NK cell subsets in RR-MS patients. Clin Immunol. 2018;193:88–97. doi: 10.1016/j.clim.2018.02.005. 123. Saze Z, Schuler PJ, Hong CS, Cheng D, Jackson EK, Whiteside TL. Adenosine production by human B cells and B cell-mediated suppression of activated T cells. Blood. 2013;122(1):9-18. doi:10.1182/blood-2013-02-482406. 124. Hoskin DW, Mader JS, Furlong SJ, Conrad DM, Blay J. Inhibition of T cell and natural killer cell function by adenosine and its contribution to immune evasion by tumor cells (Review). Int J Oncol. 2008;32(3):527-535. 125. Morandi F, Horenstein AL, Chillemi A, Quarona V, Chiesa S, Imperatori A, et al. CD56brightCD16- NK cells produce adenosine through a CD38-mediated pathway and act as regulatory cells inhibiting autologous CD4+ T cell proliferation. J Immunol. 2015;195(3):965–72.10.4049/jimmunol.1500591. 224 126. Mandapathil M, Hilldorfer B, Szczepanski MJ, Czystowska M, Szajnik M, Ren J, et al. Generation and accumulation of immunosuppressive adenosine by human CD4+CD25highFOXP3+ regulatory T cells. J Biol Chem. 2010;285:7176–86. doi: 10.1074/jbc.M109.047423. 127. Buck MD, O’Sullivan D, Pearce EL. T cell metabolism drives immunity. J Exp Med. 2015;212:1345–60. doi: 10.1084/jem.20151159. 128. Wang HY, Lee DA, Peng G, Guo Z, Li Y, Kiniwa Y, et al. Tumor-specific human CD4+ regulatory T cells and their ligands: implications for immunotherapy. Immunity. 2004;20:107–18. doi: 10.1016/S1074-7613(03)00359-5. 129. Shevach EM, Thornton AM. tTregs, pTregs, and iTregs: similarities and differences. Immunol Rev. 2014;259:88–102. doi: 10.1111/imr.12160. 130. Carson WE, Giri JG, Lindemann MJ, Linett ML, Ahdieh M, Paxton R, Anderson D, Eisenmann J, Grabstein K, Caligiuri MA. J Exp Med. 1994; 180(4):1395-403. 131. Cichocki F, Schlums H, Theorell J, Tesi B, Miller JS, Ljunggren HG, et al. Diversification and functional specialization of human NK cell subsets. Curr Top Microbiol Immunol. 2016;395:63–94.10.1007/82_2015_487. 132. Cooper MA, Fehniger TA, Turner SC, Chen KS, Ghaheri BA, Ghayur T, et al. Human natural killer cells: a unique innate immunoregulatory role for the CD56bright subset. Blood. 2001;97:3146–51.10.1182/blood.V97.10.3146. 133. Piccioli D, Sbrana S, Melandri E, Valiante NM. Contact-dependent stimulation and inhibition of dendritic cells by natural killer cells. J Exp Med. 2002;195:335–41.10.1084/jem.20010934. 225 134. Mailliard RB, Alber SM, Shen H, Watkins SC, Kirkwood JM, Herberman RB, et al. IL-18-induced CD83+CCR7+ NK helper cells. J Exp Med. 2005;202:941–53.10.1084/jem.20050128. 135. Marcenaro E, Cantoni C, Pesce S, Prato C, Pende D, Agaugue S, et al. Uptake of CCR7 and acquisition of migratory properties by human KIR+ NK cells interacting with monocyte-derived DC or EBV cell lines: regulation by KIR/HLA-class I interaction. Blood. 2009;114:4108–16.10.1182/blood-2009-05-222265. 136. Ferlazzo G, Pack M, Thomas D, Paludan C, Schmid D, Strowig T, et al. Distinct roles of IL-12 and IL-15 in human natural killer cell activation by dendritic cells from secondary lymphoid organs. Proc Natl Acad Sci U S A. 2004;101:16606–11.10.1073/pnas.0407522101. 137. Romagnani C, Della Chiesa M, Kohler S, Moewes B, Radbruch A, Moretta L, et al. Activation of human NK cells by plasmacytoid dendritic cells and its modulation by CD4+ T helper cells and CD4+ CD25hi T regulatory cells. Eur J Immunol. 2005;35:2452–8.10.1002/eji.200526069. 138. Fu B, Tian Z, Wei H. Subsets of human natural killer cells and their regulatory effects. Immunology. 2014;141(4):483-489. doi:10.1111/imm.12224 139. Kucuksezer UC, Aktas Cetin E, Esen F, et al. The Role of Natural Killer Cells in Autoimmune Diseases. Front Immunol. 2021;12:622306. Published 2021 Feb 25. doi:10.3389/fimmu.2021.622306 140. Cuvelier GDE, Kariminia A, Nemecek ER, Kitko C, Wahlstrom JT, Harris AC, Bittencourt H, et al. Naïve helper T-cell and regulatory T- and NK-cell subsets are associated with pediatric chronic graft-versus-host disease: results of the ABLE / 226 PBMTC 1202 study. Blood. 2020;136 (Supplement 1): 11–12. doi: https://doi.org/10.1182/blood-2020-139031. 141. Cuvelier GDE, Nemecek ER, Wahlstrom JT, et al. Benefits and challenges with diagnosing chronic and late acute GVHD in children using the NIH consensus criteria. Blood. 2019;134(3):304-316. doi:10.1182/blood.2019000216. 142. Brillantes M, Beaulieu AM. Transcriptional control of natural killer cell differentiation. Immunology. 2019;156:111-119. 143. Sumida, T.S., Cheru, N.T. & Hafler, D.A. The regulation and differentiation of regulatory T cells and their dysfunction in autoimmune diseases. Nat Rev Immunol. 2024. https://doi.org/10.1038/s41577-024-00994-x 144. Laura F. Newell, Shernan G. Holtan; Acute GVHD: think before you treat. Hematology Am Soc Hematol Educ Program 2021; 2021 (1): 642–647. doi: https://doi.org/10.1182/hematology.2021000300 145. Ida H, Utz PJ, Anderson P, Eguchi K. Granzyme B and natural killer (NK) cell death. Mod Rheumatol. 2005;15(5):315-322. doi:10.1007/s10165-005-0426-6 146. Wong KY, Baron R, Seldon TA, Jones ML, Rice AM, Munster DJ. CD83 Antibody Inhibits Human B Cell Responses to Antigen as well as Dendritic Cell-Mediated CD4 T Cell Responses. J Immunol. 2018;200(10):3383-3396. doi:10.4049/jimmunol.1700064 147. Dijke E, Ellis T, Larsen I, et al. Human Leukocyte Antigen (HLA) Class II Expression on Regulatory T Cells (Tregs) Isolated from Discarded Human Thymus is Induced by In Vitro Expansion Conditions. The Journal of heart and lung transplantation. 2020;39:S178-S179. 227 148. Clottu AS, Mathias A, Sailer AW, et al. EBI2 expression and function: robust in memory lymphocytes and increased by natalizumab in multiple sclerosis. Cell reports (Cambridge). 2017;18:213-224. 149. Sakaguchi S, Wing K, Onishi Y, Prieto-Martin P, Yamaguchi T. Regulatory T cells: how do they suppress immune responses?. Int Immunol. 2009;21(10):1105-1111. doi:10.1093/intimm/dxp095. 150. Forcade E, et al. An activated Th17-prone T cell subset involved in chronic graft-versus-host disease sensitive to pharmacological inhibition. JCI Insight. 2017;2(12):e92111. Published 2017 Jun 15. doi:10.1172/jci.insight.92111 151. Perera Molligoda Arachchige, Arosh Shavinda. Human NK cells: From development to effector functions. Innate Immunity. London, England: SAGE Publications; 2021;27:212-229. 152. McManigle W, et al. B cells in chronic graft-versus-host disease. Human immunology. 2019;80:393-399. 153. Sun S, Liu C. 7α, 25-dihydroxycholesterol-mediated activation of EBI2 in immune regulation and diseases. Frontiers in pharmacology. 2015;6:60-60. 154. Tang J, Shi Y, Zhan L, Qin C. Downregulation of GPR183 on infection restricts the early infection and intracellular replication of mycobacterium tuberculosis in macrophage. Microbial pathogenesis. 2020;145:104234-104234. 155. Chyuan IT, et al. TRAIL-Mediated Suppression of T Cell Receptor Signaling Inhibits T Cell Activation and Inflammation in Experimental Autoimmune Encephalomyelitis. Front Immunol. 2018;9:15. Published 2018 Jan 22. doi:10.3389/fimmu.2018.00015 228 156. Schmidt A, Oberle N, Krammer PH. Molecular mechanisms of Treg-mediated T cell suppression. Frontiers in immunology. 2012;3:51-51. 157. Li H, Zhai N, Wang Z, et al. Regulatory NK cells mediated between immunosuppressive monocytes and dysfunctional T cells in chronic HBV infection. Gut. 2018;67(11):2035-2044. doi:10.1136/gutjnl-2017-314098. 158. Neo SY, Yang Y, Record J, et al. CD73 immune checkpoint defines regulatory NK cells within the tumor microenvironment. J Clin Invest. 2020;130(3):1185-1198. doi:10.1172/JCI128895. 159. Locatelli F, et al. NK Cells Mediate a Crucial Graft-versus-Leukemia Effect in Haploidentical-HSCT to Cure High-Risk Acute Leukemia. Trends Immunol. 2018;39(7):577-590. doi:10.1016/j.it.2018.04.009 160. Normanton M, Marti LC. Current data on IL-17 and Th17 cells and implications for graft versus host disease. Einstein (Sao Paulo). 2013;11(2):237-246. doi:10.1590/s1679-45082013000200019 161. Esen F, et al. PD-1, CTLA-4, LAG-3, and TIGIT: The roles of immune checkpoint receptors on the regulation of human NK cell phenotype and functions. Immunol Lett. 2021;240:15-23. doi:10.1016/j.imlet.2021.09.009 162. Maruhashi, T, et al. LAG-3 inhibits the activation of CD4+ T cells that recognize stable pMHCII through its conformation-dependent recognition of pMHCII. Nat Immunol 19, 1415–1426 (2018). https://doi.org/10.1038/s41590-018-0217-9 163. Sharpe, A, Pauken, K. The diverse functions of the PD1 inhibitory pathway. Nat Rev Immunol 18, 153–167 (2018). https://doi.org/10.1038/nri.2017.108 229 164. Hannier S, Tournier M, Bismuth G, Triebel F. CD3/TCR complex-associated lymphocyte activation gene-3 molecules inhibit CD3/TCR signaling. J Immunol. 1998;161(8):4058-4065. 165. Ouyang W, et al. Regulation and functions of the IL-10 family of cytokines in inflammation and disease. Annu Rev Immunol. 2011;29:71-109. doi:10.1146/annurev-immunol-031210-101312 166. Ernst PB, et al. Much ado about adenosine: adenosine synthesis and function in regulatory T cell biology. J Immunol. 2010;185(4):1993-1998. doi:10.4049/jimmunol.1000108 167. Larson C, et al. TGF-beta: a master immune regulator. Expert Opin Ther Targets. 2020;24(5):427-438. doi:10.1080/14728222.2020.1744568 168. Brunstein, C. G., Miller, J. S., McGlave, P. B., Blazar, B. R., Wagner, J. E., Cao, Q., . . . Rubinstein, P. (2011). Infusion of ex vivo expanded T regulatory cells in adults transplanted with umbilical cord blood: Safety profile and detection kinetics. Blood, 117(3), 1061-1070. doi:10.1182/blood-2010-07-293795. 169. Rudnicka K, Matusiak A, Chmiela M. CD25 (IL-2R) expression correlates with the target cell induced cytotoxic activity and cytokine secretion in human natural killer cells. Acta Biochim Pol. 2015;62(4):885-894. doi:10.18388/abp.2015_1152. 170. Morris SC, Orekhova T, Meadows MJ, Heidorn SM, Yang J, Finkelman FD. IL-4 induces in vivo production of IFN-gamma by NK and NKT cells. J Immunol. 2006;176(9):5299-5305. doi:10.4049/jimmunol.176.9.5299. 171. Judge CJ, Kostadinova L, Sherman KE, et al. CD56bright NK IL-7Rα expression negatively associates with HCV level, and IL-7-induced NK function is impaired during 230 HCV and HIV infections. J Leukoc Biol. 2017;102(1):171-184. doi:10.1189/jlb.5A1116-456R. 172. Konjevic G, Jurisic V, Jovic V, Vuletic A, Mirjacic Martinovic K, Radenkovic S, Spuzic I. Investigation of NK cell function and their modulation in different malignancies. Immunol. Res. 2012;52:139–156. 173. Vuletić A, Jurišić V, Jovanić I, Milovanović Z, Nikolić S, Konjević G. Distribution of several activating and inhibitory receptors on CD3(-)CD56(+) NK cells in regional lymph nodes of melanoma patients. J. Surg. Res. 2013;183:860–868. 174. Vuletić A, Jovanić I, Jurišić V, Milovanović Z, Nikolić S, Spurnić I, Konjević G. Decreased interferon γ production in CD3+ and CD3- CD56+ lymphocyte subsets in metastatic regional lymph nodes of melanoma patients. Pathol. Oncol. Res. 2015;21:1109–1114. 175. Strengell M, Matikainen S, Sirén J, Lehtonen A, Foster D, Julkunen I, Sareneva T. IL-21 in synergy with IL-15 or IL-18 enhances IFN-gamma production in human NK and T cells. J. Immunol. 2003;170:5464–5469. 176. French AR, Holroyd EB, Yang L, Kim S, Yokoyama WM. IL-18 acts synergistically with IL-15 in stimulating natural killer cell proliferation. Cytokine. 2006;35:229–234. 177. Okamura H, Tsutsi H, Komatsu T, Yutsudo M, Hakura A, Tanimoto T, Torigoe K, Okura T, Nukada Y, Hattori K, et al. Cloning of a new cytokine that induces IFN-gamma production by T cells. Nature. 1995;378:88–91. 231 178. Behzadi P, Behzadi E, Ranjbar R. IL-12 family cytokines: general characteristics, pathogenic microorganisms, receptors, and signalling pathways. Acta Microbiol. Immunol. Hung. 2016;63:1–25. 179. Ziblat A, Nuñez SY, Raffo Iraolagoitia XL, Spallanzani RG, Torres NI, Sierra JM, Secchiari F, Domaica CI, Fuertes MB, Zwirner NW. Interleukin (IL)-23 stimulates IFN-γ secretion by CD56(bright) natural killer cells and enhances IL-18-driven dendritic cells activation. Front. Immunol. 2018;8:1959. 180. Bhattacharya P, Thiruppathi M, Elshabrawy HA, Alharshawi K, Kumar P, Prabhakar BS. GM-CSF: An immune modulatory cytokine that can suppress autoimmunity. Cytokine. 2015;75(2):261-271. doi:10.1016/j.cyto.2015.05.030. 181. Poznanski, S.M., Barra, N.G., Ashkar, A.A. et al. Immunometabolism of T cells and NK cells: metabolic control of effector and regulatory function. Inflamm. Res. 2018;67:813–828. https://doi.org/10.1007/s00011-018-1174-3 182. Vitale M, Cantoni C, Pietra G, Mingari MC, Moretta L. Effect of tumor cells and tumor microenvironment on NK-cell function. Eur J Immunol. 2014;44:1582–92. doi: 10.1002/eji.201344272. 183. Viel S, Besson L, Marotel M, Walzer T, Marçais A. Regulation of mTOR, metabolic fitness, and effector functions by cytokines in natural killer cells. Cancers. 2017;9:132. doi: 10.3390/cancers9100132. 184. Castriconi R, Cantoni C, Della Chiesa M, Vitale M, Marcenaro E, Conte R, et al. Transforming growth factor 1 inhibits expression of NKp30 and NKG2D receptors: consequences for the NK-mediated killing of dendritic cells. Proc Natl Acad Sci USA. 2003;100:4120–5. doi: 10.1073/pnas.0730640100. 232 185. Lee J-C, Lee K-M, Kim D-W, Heo DS. Elevated TGF-β1 secretion and down-modulation of NKG2D underlies impaired NK cytotoxicity in cancer patients. J Immunol. 2004;172:7335–40. doi: 10.4049/jimmunol.172.12.7335. 186. Ghiringhelli F, Ménard C, Terme M, Flament C, Taieb J, Chaput N, et al. CD4 + CD25 + regulatory T cells inhibit natural killer cell functions in a transforming growth factor–β-dependent manner. J Exp Med. 2005;202:1075–85. doi: 10.1084/jem.20051511. 187. Chambers AM, Lupo KB, Matosevic S. Tumor microenvironment-induced immunometabolic reprogramming of natural killer cells. Front Immunol. 2018;9:2517. doi: 10.3389/fimmu.2018.02517. 188. Lokshin A, Raskovalova T, Huang X, Zacharia LC, Jackson EK, Gorelik E. Adenosine-mediated inhibition of the cytotoxic activity and cytokine production by activated natural killer cells. Cancer Res. 2006;66:7758–65. doi: 10.1158/0008-5472.CAN-06-0478. 189. Young A, Ngiow SF, Gao Y, Patch A-M, Barkauskas DS, Messaoudene M, et al. A2AR adenosine signaling suppresses natural killer cell maturation in the tumor microenvironment. Cancer Res. 2018;78:1003–16. doi: 10.1158/0008-5472.CAN-17-2826. 190. Sek K, Mølck C, Stewart G, Kats L, Darcy P, Beavis P. Targeting adenosine receptor signaling in cancer immunotherapy. Int J Mol Sci. 2018;19:E3837. doi: 10.3390/ijms19123837. 191. Chambers AM, Wang J, Lupo KB, Yu H, Atallah Lanman NM, Matosevic S. Adenosinergic Signaling Alters Natural Killer Cell Functional Responses. Front Immunol. 2018;9:2533. doi:10.3389/fimmu.2018.02533. 233 192. Gualdoni GA, Mayer KA, Goschl L, Boucheron N, Ellmeier W, Zlabinger GJ. The AMP analog AICAR modulates the Treg/Th17 axis through enhancement of fatty acid oxidation. FASEB J. 2016;30(11):3800–9. https://doi.org/10.1096/fj.201600522R. 193. Fullerton MD, Galic S, Marcinko K, Sikkema S, Pulinilkunnil T, Chen ZP, et al. Single phosphorylation sites in Acc1 and Acc2 regulate lipid homeostasis and the insulin-sensitizing effects of metformin. Nat Med. 2013;19(12):1649–54. https://doi. org/10.1038/nm.3372. 194. Eddy JL, Krukowski K, Janusek L, Mathews HL. Glucocorticoids regulate natural killer cell function epigenetically. Cell Immunol. 2014;290(1):120-130. doi:10.1016/j.cellimm.2014.05.013. 195. Dege C, Fegan KH, Creamer JP, et al. Potently cytotoxic natural killer cells initially emerge from Erythro-myeloid progenitors during mammalian development. Dev Cell. 2020;53:239. https://doi.org/10.1016/j.devcel.2020.02.016. 196. Pearce EL, Mullen AC, Matins GA, Krawczyk CM, Hutch ins AS, Zediak VP, et al. Control of effector CD8+ T cell function by the transcription factor eomesodermin. Science. 2003;302(5647):1041–3. 197. Shi LZ, Wang R, Huang G, Vogel P, Neale G, Green DR, et al. HIF1alpha-dependent glycolytic pathway orchestrates a metabolic checkpoint for the differentiation of TH17 and Treg cells. J Exp Med. 2011;208(7):1367–76. 198. Wang R, Dillon CP, Shi LZ, Milasta S, Carter R, Finkelstein D, et al. The transcription factor Myc controls metabolic reprogramming upon T lymphocyte activation. Immunity. 2011;35(6):871. 234 199. Beier UH, Angelin A, Akimova T, Wang LS, Liu Y, Xiao H, et al. Essential role of mitochondrial energy metabolism in Foxp3+ T-regulatory cell function and allograft survival. FASEB J. 2015;29(6):2315–26. 200. Michalek RD, Gerriets VA, Jacobs SR, Macintyre AN, Mason NJ, Mason EF, et al. Cutting edge: distinct glycolytic and lipid oxidative metabolic programs are essential for effector and regulatory CD4+ T cell subsets. J Immunol. 2011;186(6):3299–303. 201. Mahnke J, Schumacher V, Ahrens S, Käding N, Feldhoff LM, Huber M, et al. Interferon regulatory factor 4 controls TH1 cell effector function and metabolism. Sci Rep. 2016;6:35521. 202. Poznanski SM, Ashkar AA. What Defines NK Cell Functional Fate: Phenotype or Metabolism?. Front Immunol. 2019;10:1414. doi:10.3389/fimmu.2019.01414. 203. Gerriets VA, Kishton RJ, Johnson MO, Cohen S, Siska PJ, Nichols AG, et al. Foxp3 and Toll-like receptor signaling balance Treg cell anabolic metabolism for suppression. Nat Immunol. 2016;17(12):1459–66. 204. Cerdeira AS, Rajakumar A, Royle CM, Lo A, Husain Z, Thadhani RI, et al. Conversion of peripheral blood NK cells to a decidual NK-like phenotype by a cocktail of defined factors. J Immunol. 2013;190:3939– 48. doi: 10.4049/jimmunol.1202582. 205. Muller-Durovic B, Lanna A, Polaco Covre L, Mills RS, Henson SM, Akbar AN. Killer cell lectin-like receptor G1 inhibits NK cell function through activation of adenosine 5′-monophosphate activated protein kinase. J Immunol. 2016;197(7):2891–9. 206. Park MJ, Lee SY, Moon SJ, Son HJ, Lee SH, Kim EK, et al. Metformin attenuates graft-versus-host disease via restricting mammalian target of rapamycin/signal transducer and activator of transcription 3 and promoting adenosine monophosphate-235 activated protein kinase-autophagy for the balance between T helper 17 and Tregs. Transl Res J Lab Clin Med. 2016;173:115–30. https://doi. org/10.1016/j.trsl.2016.03.006 207. Morgan DJ, Davis DM. Distinct Effects of Dexamethasone on Human Natural Killer Cell Responses Dependent on Cytokines. Front Immunol. 2017;8:432. doi:10.3389/fimmu.2017.00432 208. Ohta A. A metabolic immune checkpoint: adenosine in tumor microenvironment. Front Immunol. 2016;7:109. doi: 10.3389/fimmu.2016.00109. 209. Luevano M, Daryouzeh M, Alnabhan R, et al. The unique profile of cord blood natural killer cells balances incomplete maturation and effective killing function upon activation. Human immunology. 2012;73:248-257. 210. Hermanson DL, Bendzick L, Pribyl L, McCullar V, Vogel RI, Miller JS, Geller MA, Kaufman DS. Induced pluripotent stem cell-derived natural killer cells for treatment of ovarian cancer. Stem Cells. 2016;34:93–101. 211. Zeng J, Tang SY, Toh LL, Wang S. Generation of “off-the-shelf” natural killer cells from peripheral blood cell-derived induced pluripotent stem cells. Stem Cell Rep. 2017;9:1796–812 212. Hermanson D, Ni Z, Kaufman DS. Human pluripotent stem cells as a renewable source of natural killer cells. In: Cheng T, editor. Hematop. Differ. Hum. Pluripotent Stem Cells. Dordrecht: Springer; 2015. p. 69–79. 213. Knorr DA, Ni Z, Hermanson D, Hexum MK, Bendzick L, Cooper LJN, Lee DA, Kaufman DS. Clinical-scale derivation of natural killer cells from human pluripotent stem cells for cancer therapy. Stem Cells Transl Med. 2013;2: 274–83. 236 214. Larbi A, Gombert JM, Auvray C, et al. The HOXB4 homeoprotein promotes the ex vivo enrichment of functional human embryonic stem cell-derived NK cells. PLoS One. 2012;7. https://doi.org/10.1371/journal.pone.0039514. 215. Ni Z, Knorr DA, Clouser CL, Hexum MK, Southern P, Mansky LM, Park I-H, Kaufman DS. Human pluripotent stem cells produce natural killer cells that mediate anti-HIV-1 activity by utilizing diverse cellular mechanisms. J Virol. 2011;85:43–50. 216. Woll PS, Grzywacz B, Tian X, Marcus RK, Knorr DA, Verneris MR, Kaufman DS. Human embryonic stem cells differentiate into a homogeneous population of natural killer cells with potent in vivo antitumor activity. Blood. 2009;113: 6094–101. 217. Bock AM, Knorr D, Kaufman DS. Development, expansion, and in vivo monitoring of human NK cells from human embryonic stem cells (hESCs) and induced pluripotent stem cells (iPSCs). J Vis Exp. 2013;74. https://doi. org/10.3791/50337. 218. Ni Z, Knorr DA, Bendzick L, Allred J, Kaufman DS. Expression of chimeric receptor CD4ζ by natural killer cells derived from human pluripotent stem cells improves in vitro activity but does not enhance suppression of HIV infection in vivo. Stem Cells. 2014;32:1021–31. 219. Woll PS, Martin CH, Miller JS, Kaufman DS. Human embryonic stem cell derived NK cells acquire functional receptors and cytolytic activity. J Immunol. 2005;175:5095–103 220. Chen RY, Zhu Y, Shen YY, et al. The role of PD-1 signaling in health and immune-related diseases. Front Immunol. 2023;14:1163633. Published 2023 May 16. doi:10.3389/fimmu.2023.1163633 237 221. Li J, Kim SG, Blenis J. Rapamycin: one drug, many effects. Cell Metab. 2014;19(3):373-379. doi:10.1016/j.cmet.2014.01.001 222. Schultz KR. Pathophysiology of chronic graft versus host disease. In: Cambridge University Press. 2009;17-30. 223. Siernicka M, Bojarczuk K, Bobrowicz M, Dwojak M, Pyrzynska B, Olive D, Winiarska M. Influence of Btk Inhibitors on Antitumor Activity of Natural Killer Cells. Blood. 2014; 124 (21): 2742. doi: https://doi.org/10.1182/blood.V124.21.2742.2742 224. Gotthardt D, Trifinopoulos J, Sexl V, Putz EM. JAK/STAT Cytokine Signaling at the Crossroad of NK Cell Development and Maturation. Frontiers in immunology. 2019;10:2590-2590. 225. Lee G, Karunanithi S, Jackson Z, Wald D. Small Molecule Screening Identifies Rho-Associate Protein Kinase (ROCK) As a Regulator of NK Cell Cytotoxicity Against Cancer. Blood. 2019. 134 (Supplement_1): 3607. doi: https://doi.org/10.1182/blood-2019-131947 226. Nakasone H, Sahaf B, Miklos DB. Therapeutic benefits targeting B-cells in chronic graft-versus-host disease. International journal of hematology. 2015;101:438-451. 227. Spoerl S, Mathew NR, Bscheider M, et al. Activity of therapeutic JAK 1/2 blockade in graft-versus-host disease. Blood. 2014;123:3832-3842. 228. Vacca P, Vitale C, Munari E, Cassatella MA, Mingari MC, Moretta L. Human Innate Lymphoid Cells: Their Functional and Cellular Interactions in Decidua. Front Immunol. 2018;9:1897. 238 229. Schuster IS, Sng XYX, Lau CM, et al. Infection induces tissue-resident memory NK cells that safeguard tissue health. Immunity. 2023;56(9):2173-2174. doi:10.1016/j.immuni.2023.08.004
Thesis/Dissertation
eng
Pathology and Laboratory Medicine
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Schultz, Kirk R.
Characterization and expansion of regulatory natural killer cells for the therapy of chronic graft-versus-host disease
Text