Applied Science, Faculty of
Biomedical Engineering, School of
DSpace
UBCV
Zhang, Yishuang
Master of Applied Science - MASc
University of British Columbia
Chimeric antigen receptor (CAR) T-cell therapy has emerged as a highly promising cell-based approach for the treatment of cancers. A key initial step in biomanufacturing is for T-cells to be activated before their transduction so as to promote their transfection and proliferation into high yields of CAR T-cells. Soluble activators provide an attractive alternative for biomanufacturing since they eliminate the cell losses when magnetic beads are removed, and this also simplifies bioprocessing. However, understanding the soluble activator exposures of human T-cells is a potential critical process parameter in the biomanufacturing of CAR T-cells. As alternative functional assays were assessed, it was found that upon activation, a major change in cell size was observed long before the cell numbers increased. Thus, a functional assay to measure the activity in culture supernates was developed based on measurements of T-cell diameters. Image analysis was used to measure the sizes of T-cells after 24, 48, or 72 hours of culture to determine the duration that most effectively distinguished variable activity levels. This activity assay was then used to determine the soluble activator levels over time, as well as to distinguish mechanisms of activity loss caused by binding to culture vessel surfaces, thermal degradation, or cell binding/internalization. The cell binding/internalization was by far the greatest contributor to activity decreases. Thus, this assay provides a means to monitor a key variable so as to increase the process understanding of CAR T-cell biomanufacturing. Additionally, the feasibility of refreezing many small T-cell aliquots with an acceptable recovery rate was demonstrated.
NOVEL ACTIVITY ASSAY DEVELOPMENT FOR SOLUBLE T-CELL ACTIVATORS IN BIOPROCESSING by Yishuang Zhang A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in The Faculty of Graduate and Postdoctoral Studies (Biomedical Engineering) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) October 2023 © Yishuang Zhang, 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Novel activity assay development for soluble T-cell activators in bioprocessing submitted by Yishuang Zhang in partial fulfilment of the requirements for the degree of MASTER OF APPLIED SCIENCE in Biomedical Engineering Examining Committee: Dr. James M. Piret, Professor, School of Biomedical Engineering, UBC Supervisor Dr. Calvin D. Roskelley, Professor, Department of Cellular & Physiological Sciences, UBC Supervisory Committee Member Dr. Marko Kryworuchko, Adjunct Professor, UBC Chemical and Biological Engineering, UBC Supervisory Committee Member iii Abstract Chimeric antigen receptor (CAR) T-cell therapy has emerged as a highly promising cell-based approach for the treatment of cancers. A key initial step in biomanufacturing is for T-cells to be activated before their transduction so as to promote their transfection and proliferation into high yields of CAR T-cells. Soluble activators provide an attractive alternative for biomanufacturing since they eliminate the cell losses when magnetic beads are removed, and this also simplifies bioprocessing. However, understanding the soluble activator exposures of human T-cells is a potential critical process parameter in the biomanufacturing of CAR T-cells. As alternative functional assays were assessed, it was found that upon activation, a major change in cell size was observed long before the cell numbers increased. Thus, a functional assay to measure the activity in culture supernates was developed based on measurements of T-cell diameters. Image analysis was used to measure the sizes of T-cells after 24, 48, or 72 hours of culture to determine the duration that most effectively distinguished variable activity levels. This activity assay was then used to determine the soluble activator levels over time, as well as to distinguish mechanisms of activity loss caused by binding to culture vessel surfaces, thermal degradation, or cell binding/internalization. The cell binding/internalization was by far the greatest contributor to activity decreases. Thus, this assay provides a means to monitor a key variable so as to increase the process understanding of CAR T-cell biomanufacturing. Additionally, the feasibility of refreezing many small T-cell aliquots with an acceptable recovery rate was demonstrated. iv Lay Summary Cell therapies using patient immune cells are providing promising new medical treatments for cancers. To produce more of these T-cells, they are manufactured in culture vessels. To help optimize the culture process and identify the causes of reduced cell growth rates, a method was developed to quantify one of the key culture variables, an additive that stimulates the cell growth. Such activators are required for T-cells to multiply by division to sufficient numbers for them to effectively treat cancer patients. With this method, we have determined that the T-cells in culture are the greatest contributor to the loss of activity. Manufacturers could use this method to monitor and improve their production of cells for therapy. v Preface None of the materials and chapters have been published yet as of the thesis submission date. I performed the literature review and wrote the majority of the text in my thesis, with suggested edits from my supervisor, Dr. James M. Piret, and coop students, Siqi Chen and Subin Mun. I conceived of designing all the experiments with help from my supervisor, Dr. James M. Piret, my committee members, Dr. Calvin D. Roskelley and Dr. Marko Kryworuchko and colleague Ali Chamkalani and Alina Kunitskaya. I conceived of conducting all experiments with the help of colleague and the coop students except for T-cell enrichment from the buffy coat, which was done by the lab manager, Christopher Sherwood. All research was approved by the University of British Columbia (UBC) Research Ethics Board under the protocol “T Cell Bioprocessing and Analysis” with UBC CREB NUMBER: H22-00254. vi Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ............................................................................................................................... iv Preface .............................................................................................................................................v Table of Contents ......................................................................................................................... vi List of Tables ................................................................................................................................ ix List of Figures .................................................................................................................................x List of Abbreviations ................................................................................................................. xiii Acknowledgments ........................................................................................................................xv Dedication ................................................................................................................................... xvi Chapter 1: Introduction ................................................................................................................1 1.1 T lymphocytes .................................................................................................................. 1 1.1.1 T-cell development and maturation .......................................................................... 2 1.1.2 T-cell activation and regulation ................................................................................ 3 1.2 Leukemia .......................................................................................................................... 4 1.2.1 CAR T-cell therapy and manufacturing .................................................................... 5 1.3 Assays............................................................................................................................... 7 1.3.1 Functional assay ........................................................................................................ 8 1.3.1.1 Immune functional assays ................................................................................. 8 1.3.1.2 Lymphocytes proliferation test (LPT) ............................................................... 9 1.3.1.3 T-cell activation assay ..................................................................................... 10 1.4 Cryopreservation of human cells.................................................................................... 10 1.4.1 Refreezing T-cells and CAR T-cells ....................................................................... 13 vii 1.5 Goals and hypothesis ...................................................................................................... 14 Chapter 2: Materials and methods .............................................................................................16 2.1 T-cell enrichment and cryopreservation ......................................................................... 16 2.1.1 Human T-cell isolation ........................................................................................... 16 2.1.2 Cryopreservation of freshly isolated T-cells ........................................................... 17 2.2 Assay development ........................................................................................................ 17 2.2.1 Thawing cryopreserved T-cells............................................................................... 17 2.2.2 Cell counting using a hemacytometer ..................................................................... 18 2.2.3 T-cell culture and passaging ................................................................................... 18 2.2.4 Biochemical analysis .............................................................................................. 19 2.2.5 T-cell culture dose response to soluble activator .................................................... 19 2.3 Activity assay ................................................................................................................. 20 2.3.1 T-cell culture and supernatant dilution ................................................................... 21 2.3.2 Activity assay by cell diameter or proliferation ...................................................... 22 2.3.3 Initial screening for modes of activity loss ............................................................. 23 2.3.4 Thermal degradation of soluble activator ............................................................... 25 2.3.5 Matrix effect test for functional assay based on cell diameter ................................ 26 2.4 Refreezing T-cell aliquots .............................................................................................. 27 2.4.1 Aliquot and refreezing the T-cells .......................................................................... 27 2.4.2 Thawing of refrozen T-cells and biochemical analysis .......................................... 27 2.4.3 T-cell quality analysis after multiple freeze and thaw cycle ................................... 28 2.5 Software ......................................................................................................................... 29 Chapter 3: Results and discussion ..............................................................................................30 viii 3.1 T-cell soluble activator dose response ........................................................................... 30 3.2 Soluble activator degradation factor screening .............................................................. 35 3.3 Soluble activator thermal degradation............................................................................ 38 3.3.1 Analysis of thermal degradation using diameter method assay .............................. 38 3.4 Activity loss due to T-cell presence in the culture ......................................................... 40 3.4.1 Analysis of T-cell presence effect in activity loss by cell diameter method .......... 40 3.4.1.1 Culture with initial activity of 8 pL/cell .......................................................... 40 3.4.1.2 Culture with initial activity of 25 pL/cell ........................................................ 42 3.4.2 Analysis of T-cell presence effect in activity loss by cell proliferation method .... 44 3.4.3 Effect of cell phenotypes in activity loss ................................................................ 45 3.4.4 Matrix effect in the activity assay ........................................................................... 47 3.4.5 Conclusion .............................................................................................................. 49 3.5 Cryopreservation of aliquot T-cells and multiple freeze-thaw cycle ............................. 50 3.5.1 Effect of refreezing and thawing on T-cell recovery rate and proliferation ........... 51 3.5.2 Effect of time in 10% DMSO and aliquot volume on T-cells ................................ 52 3.5.3 Analysis of multiple freeze-thaw impact on T-cell apoptosis ................................ 54 3.5.4 Conclusion .............................................................................................................. 56 Chapter 4: Conclusion .................................................................................................................58 Bibliography .................................................................................................................................65 Appendices ....................................................................................................................................72 Appendix A Sample calculations .............................................................................................. 72 Appendix B Cell diameter distribution histogram of standard curve from CEDEX (screen shots) ......................................................................................................................................... 74 ix List of Tables Table 1. Dilution plan in term of cell concentration ..................................................................... 19 Table 2. Experimental layout for screening the most impactful parameter in activity loss.......... 23 Table 3. Supernatant sampling time for each well. ....................................................................... 24 Table 4. Dilution plan for different aliquot volume. ..................................................................... 28 Table 5. Fluorochrome dyes used for flow cytometry. ................................................................. 28 Table 6. Summary of live apoptotic T-cells percentage in culture under different conditions. ... 55 x List of Figures Figure 1. The T-cell family is categorized in terms of surface markers. ........................................ 1 Figure 2. T-cell activation and three activation signals. ................................................................. 4 Figure 3. General CAR T-cell manufacture flow. .......................................................................... 6 Figure 4. Three types of immune functional assays. ...................................................................... 9 Figure 5. Lymphocytes proliferation test setup. ........................................................................... 10 Figure 6. The effect of cooling and warming rate on cells. .......................................................... 13 Figure 7. Experimental setup scheme for STEMCELL soluble activator dose response. ............ 20 Figure 8. Experimental setup scheme for T-cell culture for analyzing activity in supernatant. ... 21 Figure 9. Experimental setup scheme for activity assay plate. ..................................................... 22 Figure 10. Experimental layout for screening the most impactful parameter for activity loss. .... 23 Figure 11. Incubation of activators in culture media for analysis of thermal degradation. .......... 25 Figure 12. Activity assay setup for estimating thermal degradation of soluble activators. .......... 26 Figure 13. Fold expansion profile for T-cell growth under variable initial activity. .................... 30 Figure 14. Activator dose response for batch and fed experimental setup. .................................. 31 Figure 15. T-cell size changes during the culture, after activation at day 0. ................................ 31 Figure 16. Activity dose response impact on cell diameter after two days of culture. ................. 33 Figure 17. 8-donor dose response and curve fitting of average results with cubic polynomial equation. ........................................................................................................................................ 34 Figure 18. T-cell diameter dose response with two different soluble activators. ......................... 35 Figure 19. Three modes of activator loss during culture. ............................................................. 36 Figure 20. Standard curve generated for measuring activity and activity profile over 5 days of culture under different conditions. ................................................................................................ 37 xi Figure 21. Standard curve for two donors and the remaining activity after extensive incubation........................................................................................................................................................ 39 Figure 22. Percentage remaining activity in supernatant and evaporation during culture. ........... 41 Figure 23. Cell-specific activator consumption rate for 8 pL/cell condition. ............................... 41 Figure 24. Percentage remaining activity profile and evaporation measurement. ........................ 42 Figure 25. Standard curves up to 2.5 pL/cell activity and cell-specific activator consumption rate........................................................................................................................................................ 43 Figure 26. Standard curve generated from diameter (from Figure 25) and proliferation methods........................................................................................................................................................ 44 Figure 27. Comparison of the measured percentage remaining activity from two assay methods........................................................................................................................................................ 45 Figure 28. Cell growth profile and percentage remaining activity during culture for CD4+ and CD8+ T-cells. ................................................................................................................................ 46 Figure 29. Correlation between cell concentration and percentage remaining activity on day 3 and day 5 based on different cell types and cell-specific activator consumption rate. ................. 47 Figure 30. No significant matrix effect was found. ...................................................................... 48 Figure 31. Matrix effect test results for day 5 supernatants under 25 pL/cell conditions. ........... 49 Figure 32. Percentage recovery of refrozen cell thaw and cell proliferation comparison. ........... 51 Figure 33. Percentage recovery of aliquoted T-cells after the refrozen thaw. .............................. 52 Figure 34. Day 5 cell number fold expansion profile after the refreeze-thaw cycle. ................... 53 Figure 35. Flow cytometry results for fresh thaw and refrozen thaw T-cell apoptosis marker at day 0 and day 5 of culture. ............................................................................................................ 55 Figure 36. Percentage of live apoptotic T-cells in culture. ........................................................... 56 xii Figure 37. 0 pL/cell activator added. ............................................................................................ 74 Figure 38. 0.25 pL/cell activator added. ....................................................................................... 74 Figure 39. 0.5 pL/cell activator added. ......................................................................................... 75 Figure 40. 1 pL/cell activator added. ............................................................................................ 75 Figure 41. 1.5 pL/cell activator added. ......................................................................................... 76 Figure 42. 2 pL/cell activator added. ............................................................................................ 76 Figure 43. 2.5 pL/cell activator added. ......................................................................................... 77 xiii List of Abbreviations Abbreviations Definition APC Antigen presenting cell CAR Chimeric antigen receptor CBS Canadian blood service CCR7 C-C chemokine receptor type 7 CD2 Cluster of differentiation 2 CD28 Cluster of differentiation 28 CD3 Cluster of differentiation 3 CD4 Cluster of differentiation 4 CD45RA Cluster of differentiation 45RA CD8 Cluster of differentiation 8 CEDEX Cedex HiRes Analyzer by Roche CLPs Common lymphoid progenitors DMSO Dimethyl sulfoxide DPBS Dulbecco's phosphate buffered saline ELISA Enzyme-linked immunosorbent assay FDA Food and Drug Administration GMP Good manufacturing practice HEPES 4-(2-Hydroxyethyl)piperazine-1-ethanesulfonic acid HSCs Hematopoietic stem cells IFAs Immune functional assays IL-12 Interleukin 12 IL-18 Interleukin 18 IL-2 Interleukin 2 IL-4 Interleukin 4 IL-7 Interleukin 7 LPT The lymphocyte proliferation test MHC Major histocompatibility complex PBMC Peripheral blood mononuclear cells xiv TCM Central memory T-cell TCR T-cell receptor TEM Effector memory T-cell TLR Toll-like receptor TRM Resident memory T-cell TSCM Stem cell-like memory T-cell xv Acknowledgments I would like to express my deepest appreciation to my supervisor, Dr. James M. Piret, for his invaluable guidance, support, and mentorship throughout this academic journey. His dedication and expertise in research and kindness towards students have encouraged me to pursue my academic goals. I am deeply indebted to my committee chair and members, Dr. Calvin D. Roskelley and Dr. Marko Kryworuchko, for helping me overcome numerous challenges during this project through their support and feedback on my experiments and thesis. I want to present my dearest gratitude to my dearest fiancé Yiran Yu for carrying me through numerous difficulties and challenges we encountered throughout the years of my study. Without her trust and love this journey would not have been possible. I love you! I could not have undertaken this journey without the love from my parents, who have supported me mentally, morally, and financially throughout my years of voyage in academia. xvi Dedication This thesis work is dedicated to my beloved parents, Xiaofan Zhou and Zhigang Zhang for their endless support that enlightened me throughout this journey. I LOVE YOU. By Your son 1 Chapter 1: Introduction 1.1 T lymphocytes T-cells, a type of lymphocyte, are specialized in adaptive immunity as they patrol the host body through the bloodstream and lymphatic system. It was named after the organ (thymus) T-cells finished their development and maturation. Common types of T-cells are either CD4+ T-cells (helper T-cells) or CD8+ T-cells (cytotoxic T-cells), distinguished by these markers expressed on their surface (Figure 1)[1]. Helper T-cells serve critical roles influencing cytotoxic T-cell and B-cells, while cytotoxic T-cells induce cells to undergo apoptosis[2], [3]. Within these two types, a subpopulation of T-cells are memory T-cells[4]. Various types of memory T-cells, including central memory T-cells (TCM), effector memory T-cells (TEM), stem cell-like memory T-cells (TSCM), and resident memory T-cells (TRM), with varied functions[4]–[6]. Figure 1. The T-cell family is categorized in terms of surface markers. (Created using BioRender.com). 2 Different types of T-cells work together for immune response and immunological memories in the human body while maintaining immune homeostasis[7], [8]. To achieve these, T-cells have T-cell receptors (TCR) on the cell surface to recognize the antigen in the form of peptides presented on the surface of antigen-presenting cells (APCs) by major histocompatibility complex (MHC) I and MCH II molecules[7], [9]. Once T-cells are activated by antigens, proliferation is initiated to generate large numbers of antigen-specific effector T-cells that respond and defend the host against pathogens that they recognize (viruses, bacteria, fungi, etc.). As T-cells are essential to the immune system, more insight and knowledge can benefit humanity in treating diseases and increasing lifespans. 1.1.1 T-cell development and maturation To produce functional T-cells, progenitors must go through rigorous selections and quality checks. These checkpoints prevent unqualified T-cells from damaging the host body through autoimmunity and ensure they are active against specific pathogens. The journey of T-cell maturation begins in the bone marrow. Hematopoietic stem cells (HSCs) in adult human bone marrow differentiate toward common lymphoid progenitors (CLPs), and later on, CLPs leave bone marrow by entering the bloodstream. While circulating in the host body, CLPs are attracted to the thymus, where these progenitor cells commit to the T-cell lineage[10]–[12]. Once CLPs enter the thymus, thymic cells, such as thymic stromal cells, will signal CLPs to differentiate into T-cells and provide support through the secretion of IL-7[13], [14]. At this point, the CLPs transform into thymocytes, which are double negative in terms of CD4 and CD8 marker expression. Simultaneously, these thymocytes begin T-cell receptor (TCR) rearrangement and CD3 expression[15], [16]. When thymocytes receive a survival signal through the CD3 proteins, they are committed to the T-cell lineage, and the expression of CD4 and CD8 initiates. Depending on the arrangement of TCR, two types of T-cells will be developed. The majority of the T-cells will be αβ T-cells, which circulate through lymph tissues and respond to antigens. γδ T-cells, which lack expression of CD4 or CD8 markers, make up a small proportion within the T-cell population and are not activated by MHC. γδ T-cells reside in epithelial tissues and respond to stress proteins and non-peptide antigens[17]–[19]. Success 3 arrangement of αβ TCR will direct αβ T-cells to the next stage of checkpoints. αβ T-cells now face the first positive and negative selection, during which thymic cortical epithelial cells assess TCRs with MHC class I and II for successful docking. T-cells will undergo apoptosis if the affinity between MHC and TCR is too strong, or docking is unsuccessful. Double positive T-cells who pass the positive selection and negative selection will test which MHC they fit better. T-cells with higher affinity with MHC I will differentiate to CD8+ T-cells by suppressing the expression of CD4 and vice versa[20], [21]. The second negative selection will occur to ensure host-produced proteins do not activate T-cells since this can be dangerous. Failed T-cells will be instructed to initiate apoptosis[22], [23]. After this selection, T-cells become mature naïve T-cells, ready to enter the bloodstream from the thymus to lymphoid tissues and organs and defend the host body. 1.1.2 T-cell activation and regulation Naïve T-cells circulate throughout the host body while maintaining at the G0 stage of the mitosis cycle. This status is often referred to as the resting phase of the T-cells. Upon the presence of the antigen from APCs and MHC-TCR interaction, signals are transmitted through TCR and CD3 on the T-cell surface to activate antigen-specific T-cells. CD28 and CD2 co-stimulation is also essential for the activation of T cells (Figure 2). Certain reports indicate that the absence of CD28 results in decreased cell proliferation[24]–[31]. The third signal of T-cell activation is induced by the cytokines: interleukin-2 (IL-2), interleukin-4 (IL-4), interleukin-7 (IL-7), interleukin-12 (IL-12), interleukin-18 (IL-18) type I interferon (IFN) and etc.[32]–[34]. After activation, T-cells begin proliferation, and based on the frequency and intensity of the restimulation, T-cells face two distinctive fates. If a strong restimulation signal constantly induces T-cells, T-cells eventually undergo restimulation-induced cell death. However, if a relatively weak restimulation frequently induces T-cells, they become exhausted T-cells, which enter the state of poor effector function and upregulate inhibitory receptor gene expression[35]. As proliferation progresses and immune response weakens, cytokine secretion decreases. As a result, the T-cell population contracts due to cytokine withdrawal, and a small subset of T-cells reprogram to memory T-cells[6], [36], [37]. Besides the regulatory mechanism discussed, 4 specialized T-cells called regulatory T-cells can induce T-cells to undergo apoptosis by cytokine deprivation[38]. However, this type of cell death is not the main contributor to cell death observed during T-cell bioprocessing. Figure 2. T-cell activation and three activation signals. (Created using BioRender.com). 1.2 Leukemia Cancer significantly impacts human longevity; it is predicted that at the age of 60 and above, for every 100 seniors diagnosed, more than one patient has cancer[39]. Among all the cancer types, leukemia is one of the most common types of cancer; it placed more than 60,000 United States patients in life-threatening danger in 2022 alone[40]. Leukemia is a blood cancer in which white blood cells mutate into cancer cells and lose their ability to control their growth. Eventually, these cancerous white blood cells will outgrow the healthy cells and cause fetal damage to the patient’s body. Based on the Surveillance, Epidemiology, and End Results data, around 1.5 percent of humanity has the risk of acquiring leukemia[40]. This report generates a burden on the healthcare system and creates economic challenges. Current treatment for leukemia involves 5 chemotherapy, stem cell transplant, radiation therapy, and chimeric antigen receptor (CAR) T-cell therapy. 1.2.1 CAR T-cell therapy and manufacturing CAR T-cells are genetically engineered T-cells that express chimeric antigen receptors such that they can target cancer cells to eliminate them[41]. These specialized T-cells target cancer cells that CAR gene products are designed to bind. Unlike traditional APCs activation of T-cells through the TCR complex, CAR T-cells activate T-cells through CARs. Once the CAR binds to the target marker, this initiates a T-cell activation process through the intracellular domains of the CAR, as if they had been activated through the TCR. Currently, there are six FDA-approved CAR T-cell treatments, and more than 600 CAR T-cell clinical trials are taking place globally[42]. These approved CAR T-cell therapies are all autologous, meaning all cells are manufactured using the patient's T-cells[43]. This process of CAR T-cell manufacturing limits the accessibility of CAR T-cell therapy for patients not located in major cities. Moreover, single-batch manufacturing for each patient greatly increases the cost, making it difficult for patients to afford it. Companies such as CRISPR Therapeutics AG are working to develop off-the-shelf CAR T-cell therapy, utilizing T-cells from healthy donors to generate CAR T-cells for cancer patients[44]. This approach should significantly increase the accessibility of CAR-T cell therapy and lower the cost due to larger-scale, and thereby more economical manufacturing. 6 Figure 3. General CAR T-cell manufacture flow. (Created using BioRender.com). CAR T-cell manufacturing involves five steps (Figure 3): peripheral blood collection, T-cell enrichment, CAR gene insertion, CAR T-cell culture, and CAR T-cell product infusion. For manufacturers, gene insertion and culture are the most critical processes. Unlike stem cells, T-cells require activation for their population expansion during culture[45], [46]. Antigens such as CD3+, CD25+, and CD2+ bind to the T cell antigen receptor (TCR) to stimulate the T-cells during activation. Once T-cells receive the signal, their metabolic pathways change, and the expansion process initiates[47]. Thus, several critical process parameters are associated with the activation of T-cells to increase the yield and quality of T-cells produced. Three commonly used methods to activate T-cells use APCs, beads coated with activators, or soluble activators[48]. Manufacturers do use APCs since removing them from the produced T-cells is not feasible. Although beads are the most common way to activate T-cells, the need for downstream processing complicates the production process. The soluble synthetic activator 7 would eliminate the need for this downstream processing. Unlike beads which mimic the APCs to activate T-cells, soluble activators are antibody complexes designed specifically for binding to, usually, the CD3 and CD28 receptors that activate T-cells. The rest of the activation process is similar to APCs as TCR complex activated by CD3 and T-cells continues activation through CD28 and, in some cases, other (e.g. CD2) co-stimulation. Due to the self-regulation nature of the immune system, T-cell growth and proliferation are suppressed to avoid damage to the host body. A programmed death through apoptosis is genetically engraved in the DNA[49]. To overcome the reported characteristic of T-cells, restimulation during the later stage of culture is required for the cells to continue their expansion. Our previous experiments showed that the T-cell culture with suboptimal soluble synthetic activator concentration, which can be expressed as activity, reduced T-cell yields. In the current clinical trial, CLIC-01, the first Canadian CAR T-cell clinical trial, some patients had low concentrations of T-cells in their apheresis[50]. Thus, manufacturing the required number of CAR T-cells can be challenging. Thus, CAR T-cell product yields can be critical if insufficient CAR T-cell doses are available to treat the patients. To increase the yield and quality of CAR T-cell product, the impacts of activator restimulation timing and activity levels should be well understood. 1.3 Assays Assays are a common technique used in biology to determine specific properties of the research subject. There are three main categories of assay in biology: ligand-binding assays, immunoassays, and biological assays. Ligand-binding assay is based on the affinity of ligand binding to receptors, as can be measured with methods such as radioactive labelling. In this case, the intensity of the radioactivity reflects the affinity of the binding[51], [52]. Immunoassays are based on the principle of antibody-antigen interaction. One of the most common immunoassays is enzyme-linked immunosorbent assay (ELISA)[53], [54]. Biological assays are an experimental method to determine the function and activity of a substance with living materials. It directly reflects the effect of the target substance on cells[55]–[57]. When analyzing the function and role of proteins or polypeptides on the cellular level, biological assays are often the best choice. 8 1.3.1 Functional assay A functional assay is a type of biological assay that enables monitoring of cellular processes, the toxicity of substances, cell tracking, ion transport, and, most importantly, the effect of protein on the cellular level in in-vitro conditions. Some examples of functional assays include immune functional assays (IFAs), the lymphocyte proliferation test (LPT), T-cell activation assay, NK cell killing function assay, and TLR response assay[58]–[60]. A functional assay has not yet been specifically designed to assess the activity of CD3/CD28/CD2 T-cell soluble activators. Thus, a new functional assay was developed using cells to directly monitor the activity of the protein and its effect on the cells. Such assay can be crucial for manufacturers producing cell therapies since functional assays serve as a robust validation method for clinical trials[61]. Related assays are described in the next sections. 1.3.1.1 Immune functional assays Immune functional assays are commonly used to analyze the functional immune response by stimulating the immune cells. Some commercially available assays include ImmunKnow®, QuantiFERON®-TB Gold, and T-SPOT®.TB. These IFAs measure specific proteins or substances and correlate them to the immune function[60]. ImmunKnow® analyzes the CD4+ T-cell function by measuring adenosine triphosphate (ATP), upon which cellular processes rely. QuantiFERON®-TB Gold and T-SPOT®.TB are both designed to quantify the interferon-gamma production by T-cells (Figure 4). The main difference between these two technologies is the method used to quantify the interferon-gamma and raw material. QuantiFERON®-TB Gold uses whole blood and ELISA for the measurement, while T-SPOT®.TB uses peripheral blood mononuclear cells (PBMC), which contain an enriched T-cell population and enzyme-linked immunosorbent spot. Since PBMC requires further purification from whole blood, QuantiFERON®-TB Gold is sometimes favoured[60]. 9 Figure 4. Three types of immune functional assays. ImmunKnow®(upper picture), QuantiFERON®-TB Gold, T-SPOT®.TB(both in the lower picture) and the general procedure of each assay illustrated by O. Rezahosseini et al.[60]. 1.3.1.2 Lymphocytes proliferation test (LPT) LPT uses the proliferation of the lymphocyte to analyze the effect of substances such as occupational sensitization or to help researchers gain insights into immune system dysregulations[59], [62], [63]. The most typical method of LPT involves the culture of PBMCs and the stimulation of lymphocytes with antigens or substances at multiple concentrations (Figure 5). Later on, thymidine is added to the culture to mark the cells undergoing mitosis through DNA tagging at S-phase as DNA replicates. A higher uptake rate of thymidine indicates an increased cell proliferation. The ratio of the thymidine uptake rate of treated and stimulated T- 10 cells versus untreated and unstimulated T-cells gives a proliferation result. This ratio is termed the stimulation index and is considered positive when it is above a certain threshold[63]. Figure 5. Lymphocytes proliferation test setup. Illustrated by Ganesan et al.[59]. 1.3.1.3 T-cell activation assay Pierre et al. developed an assay to assess T-cell activation and proliferation. T-cells were first treated with the substance at 37 C and 5% CO2 for 45 minutes. Then, T-cells were transferred to a culture plate coated with anti-CD3 for activation, and soluble anti-CD28 was added. After 24 hours from seeding, the IL-2 production was measured through supernatant analysis to evaluate T-cell activation. Flow cytometry was used to analyze the proliferation of the cells after 72 hours of initial stimulation[58]. This less complex functional assay can be adapted to many situations. 1.4 Cryopreservation of human cells Cryopreservation of human tissue and cells has been a topic for decades, and numerous protocols and cryopreserve agents have been investigated to increase the quality and recovery of post-thaw cryopreserved cells. So far, most developments are focused on the cryopreservation of human embryonic stem cells, T-cells, induced pluripotent stem cells, or direct cryopreservation of cord blood[64], [65]. Cryopreservation of these cells enables the development of therapies that have the potential to cure patients for whom traditional therapies are ineffective. Embryonic stem cells and stem cells from the cord blood can be used to generate cells that could be used in cell therapies for treating diseases like type-1 diabetes, spinal cord injury, heart repair, etc.[66], [67]. 11 However, cryopreserving stem cells can be challenging if there is a low recovery percentage after thawing. In some reports, only 5% of the cells were recovered after thaw[68]. The recovery and quality of the cryopreserved cells depend on two critical processes: freezing and thawing. Optimization of both processes aims to reduce the damage inflicted on the cells during the freeze-thaw cycle (Figure 6). Murray and Gibson have investigated this topic thoroughly in their article: chemical approach to cryopreservation[69]. Ice crystal formation during the cooling procedure does the most damage to cells, and if the cooling rate and cryopreserve agent are not appropriately controlled, several catastrophic events can severely damage the cells[69], [70]. Cryoprotectants such as glycerol and dimethyl sulfoxide (DMSO) are commonly used in cryopreserving cells to avoid ice crystals damaging the cells. These chemicals increase the osmotic pressure of the environment, and cells dehydrate. Up to 10v/v% DMSO is the common practice for cryopreserving stem cells[71]. The dehydration process of the cells by adding a cryoprotectant agent has two challenges. If the cryoprotectant concentration is too low, the cell dehydration process is incomplete, and the formation of ice crystals inside the cells can burst the cell membrane, thus killing the cells. If the concentration of the cryoprotectant is too high, the agent’s toxicity can damage the cells, thus causing cell death. Another parameter to consider is the cooling rate since it affects the ice crystallization extracellularly and intracellularly. For slow cooling (<1C/min), cells have more time to adapt to the change of environment by dehydrating, thus preventing intercellular ice formation. A fast cooling rate or vitrification (>100C/min) will cool down the cells too fast without leaving them time to dehydrate, and ice crystallization inside the cells will burst the cell membrane[72]. However, some reports also show that a higher concentration of cryoprotectant combined with vitrification could lead to better recovery[73]. Thawing is the other essential part of this equation for better recovery and quality of cells. Unlike the cooling rate, the warming rate for thawing has conflicting results from multiple publications[70], [72]. Currently, the state-of-the-art method for thawing is to use a fast warming rate (> 6.2C/min) to prevent ice recrystallization around the cells, which could lead to cell death[70], [74]. Typically, a water bath is used in laboratory setups. A warm water bath at 37°C 12 could reach an average warming rate of 65°C/min[72]. However, this rate depends on the storage container and volume of the sample. Since rapid liquid heating can benefit cell recovery, a new method called ‘superparamagnetic nanoparticles induction heating,’ which could warm up the frozen content homogenously with nanoparticles spread evenly in the container, is proposed. Induction will cause the nanoparticles to heat up, allowing the heat transfer directly and evenly to the storage liquid without the several boundaries (water to vial surface, vial to content surface), reducing the heat transfer rate[75]. It has also been demonstrated that biochemical and biophysical changes during the freeze-thaw process would negatively impact the survivability of cells from the molecular and structural level[68], [76], [77]. Aside from cell death during the freeze-thaw cycle reducing the viability, the viability of the cells right after the thaw does not represent the quality of the cells. This phenomenon is called cryopreservation-induced delayed-onset cell death[72], [78]. Apoptosis could occur after the cells have been recovered from cryopreservation state, which would further reduce the number of functional cells[79]. Because of that, apoptosis has been recognized as one of many contributors to cell loss after thaw[80]. To counter this, Heng et al. have shown that inhibiting caspases with synthetic irreversible inhibitor Z-VAD-FMK in the post-thaw media could significantly increase the survivability of embryonic stem cells[81]. 13 Figure 6. The effect of cooling and warming rate on cells. Possible outcomes of unoptimized freeze-thaw process illustrated by Murray and Gibson[69]. 1.4.1 Refreezing T-cells and CAR T-cells To expand the accessibility of CAR T-cell therapy and allow post-production analysis of CAR T-cell products, cryopreservation of T-cells is one of the essential processes in producing off-the-shelf CAR T-cell products. With the success of cryopreserving cord blood and stem cells, T-cells and CAR T-cells can be stored under similar conditions. CAR T-cell samples from clinical trials are cryopreserved to maintain their viability and state. However, since these samples are limited to each patient, aliquot and second cryopreservation would be essential solely for performing multiple types of analysis on these samples. 14 Several reports have demonstrated the feasibility of cryopreserving T-cells in the form of PBMCs[80], [82]–[84]. And currently, multiple groups are optimizing the thawing and refreezing process. Kaiser et al. found that cryopreserving regulatory T-cells with 5% DMSO yielded higher cell viability and recovery rate[85]. Baboo et al., on the other hand, investigated the varying cooling and thawing rates, which confirmed that a slow cooling rate (< 1 °C/min) and high warming rate (> 6.2 °C/min) benefit the recovery and quality of T-cells post-thaw[70]. However, very few groups focused on the effect of T-cell volume and concentration before freezing, which is essential for cryopreserving biological samples from clinical trials. One report from Hope et al. has shown decreased cell viability as the cryopreserved volume goes down from 500 µL to 25 µL. Additionally, the effect of cell concentration before cryopreservation has shown a similar trend: as cell concentration goes down, recovery decreases[86]. However, these cells are cryopreserved as PBMCs, which can differ from enriched T-cell samples. Another related topic to the CAR T-cell industry was the recovery after multiple freeze-thaw cycles. Multiple research and development have been done on the cord blood and stem cell area as they often require multiple refreeze since the number of cells in each vial exceeded the requirement for one therapy. Interestingly, few reports showed promising results for refreezing cord blood as they remain relatively viable and functional after refreezing[87]. Romanov et al. also demonstrated how resilient lymphocytes were (>86% viability) after 3 freeze and thaw cycles using a slow cooling rate[88]. These reports have laid the foundation for refreezing enriched CAR T-cells and T-cells. 1.5 Goals and hypothesis The main goals of this project were to investigate the mechanism of activity loss in T-cell cultures that use a synthetic soluble activator as well as to determine the activator activity levels in culture media to optimize the timing of activator restimulation. To achieve this goal, we first aimed to develop an assay to determine the activity levels. Then, based on the activity data, we aimed to investigate the rates of activity decrease during T-cell culture. With the understanding of the mechanism of activity loss and methods to estimate activity in culture, manufacturers can optimize their process and improve the product yield. Another goal of this project was to 15 determine the feasibility of refreezing and thawing the T-cells multiple times at low volume without causing a significant decrease in recovery. This was needed to refreeze cells from a clinical trial, where the frozen samples need to be aliquoted and frozen for later experiments. For the main goal of this project, we developed the hypothesis that the average cell diameter of T-cells could measure the activity of activator in media, with an increase in average cell diameter corresponds to the rise in activity. Additionally, we hypothesized three processes would explain the loss of activity in T-cell cultures: activator binding to culture plate surfaces; thermal degradation of activator; activator binding to T-cell surface or consumed by T-cells. 16 Chapter 2: Materials and methods The following section describes the materials and methods used in this project. For sample calculation and data processing details, please refer to the appendix. This section will be divided into several parts, each describing the methods and materials involved in the experiments. 2.1 T-cell enrichment and cryopreservation 2.1.1 Human T-cell isolation Peripheral blood was collected by the Canadian Blood Service (CBS) from healthy donors and then processed overnight to make the buffy coat. The buffy coat was collected from the CBS service point near the University of British Columbia campus the following day and transferred at an ambient temperature in a human blood transfer box. The following steps were performed inside the biosafety cabinet to reduce the chance of contamination. The buffy coat was divided into several falcon tubes using serological pipettes, and 100 µL of the buffy coat was transferred to 15 mL for flow cytometry analysis. Took nucleated cell count using 3% acetic acid with methylene blue and a hemacytometer. Diluted the buffy coat with Dulbecco's Phosphate Buffered Saline (DPBS) to 5*107 cells/mL based on the nucleated cell count. The diluted buffy coat was mixed and recorded for the new volume, and STEM CELL RosetteSep™ Human T Cell Enrichment Cocktail (Catalog # 15061,15062,15063) was added to the diluted buffy coat (50 µL/mL). The mixture was well mixed and incubated for 10 minutes at room temperature and 20 mL of Lymphoprep™ (Catalog # 07811) was added to 50 mL SepMate™ tubes (Catalog # 85450). The sample was further diluted with DPBS at a 1:1 ratio, then mixed and slowly transferred 30 mL of samples to the loaded SepMate™ tubes. All samples were centrifuged at 1200 x g for 10 minutes with brake on. 1/3 of the top supernatant was removed after centrifugation to reduce the platelet. The remaining supernatant in each SepMate™ was transferred to 50 mL falcon tubes. The supernatant was washed with DPBS by topping the tube to 50 mL and centrifuged at 300 x g for 10 minutes with brake on. The supernatant was removed with a serological pipette, leaving 300 µL. Then the cell pellet was topped up and resuspended with ImmunoCult™-XF T Cell Expansion Medium to 50 mL and 17 centrifuged at 120 x g for 10 minutes with deceleration setting at 1. The supernatant was then removed, and cells number was counted with Trypan Blue and a hemacytometer. Cells were resuspended in cryostorage media (ImmunoCult + 10% V/V DMSO) to achieve cell concentration of 2 * 107 cells/mL and transferred 0.5 mL to the SARSTEDT 1.2 mL CyroPure tubes (catalog # 72.377). To simplify the name, it was called “vial” or “vials” later. 2.1.2 Cryopreservation of freshly isolated T-cells Mr. Frosty™ Freezing Container (Catalog #: 5100-0001) was used to cool down the cells slowly. Mr. Frosty™ was filled with isopropyl alcohol to the mark, and vials containing isolated T-cells were transferred to Mr. Frosty™. The container was stored overnight in a -70 C freezer and transferred to a liquid nitrogen dewar for long-term cryopreservation. 2.2 Assay development 2.2.1 Thawing cryopreserved T-cells The water bath temperature was set to 37 C. ImmunoCult™-XF T Cell Expansion Medium was warmed to 37 C in the water bath. The cryopreserved T-cells were retrieved from the liquid nitrogen dewar and immediately transferred to the water bath. Genteelly swirled the vials inside the water bath for 3 minutes. Removed from the water bath and disinfected with 70 vol% ethanol. The rest of the steps were performed in a biosafety cabinet to keep the T-cells from contamination. 2 mL serological pipettes were used to transfer the T-cells from the vial to the 15 mL falcon tube slowly. 1 mL of media was added to wash the residual cells in the vial and the liquid was transferred to the 15 mL falcon tube drop by drop to dilute the DMSO content. Repeated the step above twice to slowly allow T-cells to recover from the dehydrated state. The falcon tube was toped with media and mixed with a 10 mL serological pipette. The tube was centrifuged for 5 minutes at 300 x g with brake on. The supernatant was removed until 100 µL of liquid was left. 900 µL of media was added to the tube to resuspend the pellet. Number of cells 18 was counted with a hemacytometer with 10 times dilution. The tube containing the washed T-cells was then transferred to the incubator at 37 C and 5% CO2 for later use. 2.2.2 Cell counting using a hemacytometer Unstimulated T-cells were counted using a hemacytometer. Cell samples were diluted to lower than an estimation of 100 counts per square, and 50 µL of the diluted sample was mixed with 50 µL of trypan blue to stain the dead cells. After mixing, 20 µL of the stained sample was loaded to a hemacytometer for counting. 2.2.3 T-cell culture and passaging ImmunoCult™-XF T Cell Expansion Medium was warmed to 37 C in the water bath. The initial seeding concentration of T-cells was 5*105 cells/mL, and the working volume changes depending on the culture plate used. For a 24-well plate, the working volume was 1 mL; for a 6-well plate, the working volume was 3 mL. A culture media was transferred to the plate with the addition of Human Recombinant IL-2 at 200 UI/mL. 25 pL/cell of ImmunoCult™ Human CD3/CD28/CD2 T Cell Activator (Catalog # 10970) was added to activate the T-cell expansion per STEMCELL recommendation. The unused wells were filled with filtered water to reduce water evaporation. Culture plate was then transferred to the incubator (37 C and 5% CO2). These steps were completed on day 0. Passage was conducted on the third, fifth, seventh, and ninth days of the culture period to increase cell expansion and viability. Prior to passaging, the cell concentration was counted. 300uL of well-mix sample was taken from the sample well and loaded to the Cedex HiRes Analyzer (CEDEX) as per manufacturer’s instructions. CEDEX performs cell counting through software optical image analysis where cells were loaded to a microfluidics and a fixed microscope takes multiple images of the cells to feed the software. Dead cells were stained with trypan blue therefore excluded by the software, live cells and aggregates were counted and analyzed using built-in algorithms. Size measurements were enabled through image analysis since the picture taken was on a fixed microscope. The cell concentration used for dilution is shown below in Table 1. For cultures exceeding 9 days, restimulation using activators was also required. 19 Table 1. Dilution plan in term of cell concentration Days after seeding T-cells Cell concentration after dilution (cells/mL) 3 1 * 105 5 3 * 105 7 3 * 105 9 5 * 105 Warm media was added to the plate before cells were transferred to the wells. Transferred the plate to the incubator (37 C and 5% CO2) to continue the culture. 2.2.4 Biochemical analysis Biochemical analysis was performed using NOVA to analyze glucose and lactate concentration, which is Stat Profile® pHOx® Ultra (Nova® Biomedical). The measurements were done through the measurement of H2O2 produced from the enzymatic reaction from glucose and lactate with the enzyme coated membrane. 150 µL of the sample was taken, loaded into a 0.7 mL centrifuge tube, and analyzed through NOVA, selecting glucose and lactate analysis options as per manufacturer’s instructions. 2.2.5 T-cell culture dose response to soluble activator To validate the feasibility of using T-cell diameter or proliferation to monitor the activity of the media, serials of dose-response experiments were performed. ImmunoCult™ Human CD3/CD28/CD2 T Cell Activator was used, and activator doses ranging from 0 pL/cell to 25 pL/cell were tested on ten donors. Additionally, two types of soluble activators were tested on two donors. T Cell TransAct™ (Miltenyi Biotech) and ImmunoCult™ Human CD3/CD28/CD2 T Cell Activator (STEMCELL) was compared using activator doses ranging from 0 to 57 pL/cell. 20 The steps in section 2.4 were followed to seed the cells at 5 * 105 cells/mL using a 24-well plate when starting the dose-response experiment (Figure 7). Activators were added accordingly. Two technical replicates were created per donor. Two 300 µL samples were taken from each well for diameter measurements at 24 hours, 48 hours, and 72 hours. Then Cedex HiRes Analyzer was used to estimate the average cell diameter and recorded the cell size distribution through optical image analysis. For cell fold expansion, samples were taken on day 3 and day 5 using the same technique, and cell concentration was measured by the CEDEX. Figure 7. Experimental setup scheme for STEMCELL soluble activator dose response. (Created using BioRender.com). 2.3 Activity assay The activity assay consisted of two parts, and most of the steps were performed inside the biosafety cabinet to prevent contamination. The first part was cell culture (Figure 8), sample taking, and dilution to the optimal range for the assay. The other part involved the generation of a standard curve and sample measurements. 21 Figure 8. Experimental setup scheme for T-cell culture for analyzing activity in supernatant. (Created using BioRender.com). 2.3.1 T-cell culture and supernatant dilution Within a 6-well plate, T cells from two donors were placed, with two replicates for each donor, and the remaining wells were set as control. Two doses of ImmunoCult™ Human CD3/CD28/CD2 T Cell Activator, 8 and 25 pL/cell, were added to each well with 5 *105 cells/mL of T-cells and 200 UI/mL of IL-2. After seeding, plates were transferred to the incubator, allowing the cells to settle for 1 hour. This step reduced the number of activated T-cells being taken with the supernatant. These activated cells could disrupt the measurement of the assay. Two supernatant samples were taken from each well after settling for activity assays, specifically for the measurements using cell diameter and proliferation methods. During the settling time, container vials and dilution media were prepared. To keep the assay within the acceptable operation range of 0.25 to 2.5 pL/cell, supernatants were diluted. The aimed concentration for the diluted supernatant of the first sample from day 0 was 1 pL/cell. For example, if an experiment started with an initial activator concentration of 8 pL/cell, a 1:8 dilution was required on day 0. Following the instructions, 200 µL of the sample was mixed with 1400 µL of fresh media inside a sterile 2 mL vial. Then, the diluted samples were stored at 4 C and sheltered from light inside 22 a box. After collecting the supernatant samples, the plates were returned to the incubator to maintain their culture status. Two additional samplings were performed on days 3 and 5 with a dilution ratio of 1:6 and 1:4, respectively. All the aggregates were broken down when diluting the supernatant, and T-cells were resuspended thoroughly. Put the plate back into the incubator, letting the cells settle to the bottom of the well by gravity. After 1 hour of settling, 200 µL of supernatant was mixed with 1200 µL of fresh media on day 3, and 300 µL of supernatant was mixed with 900 µL of fresh media on day 5. All supernatants were stored inside a box at 4 C for later use. Figure 9. Experimental setup scheme for activity assay plate. (Created using BioRender.com). 2.3.2 Activity assay by cell diameter or proliferation For the activity assay plate, the same donor was used for each experiment and was seeded on the same day with the activator from the same lot, using a 24-well plate (Figure 9). For every activity assay, there were two sections; the first section was standard curve generation, and the second section was sample measurements. To generate standard curve fresh media and activator 23 was used, and sample measurements used diluted supernatant only. For a standard curve, 0, 0.25, 0.5, 1, 1.5, 2, 2.5 pL/cell activator conditions were used. After seeding, the plates were transferred to the incubator for 48 hours of culture. The average cell diameter was measured using CEDEX, and two well-mixed 300 µL samples were taken from each well. However, cell concentrations were measured on days 3 and 5 using CEDEX for the proliferation assay. Once cell diameter data was obtained, a cubic polynomial curve was fitted to the activator added versus the average cell diameter. Given the samples’ average cell diameter, the diluted supernatant’s activity was estimated using the standard curve. A similar procedure was conducted for the proliferation assay. 2.3.3 Initial screening for modes of activity loss Two plates were used for this experiment; one plate was stored in the 4 C fridge (plate F), and the other one was placed inside the incubator (plate I) at 37 C with 5% CO2. The conditions and setup are illustrated below in both figure 10 and table 2. Figure 10. Experimental layout for screening the most impactful parameter for activity loss. (Created using BioRender.com). Table 2. Experimental layout for screening the most impactful parameter in activity loss. Plate Well Activator condition Cell condition Storage condition (C) Fridge Plate F A1 Fresh No cell 4 24 A2 1 week old No cell 4 Incubator Plate I A1 Fresh No cell 37 A2 Fresh No cell 37 A3 1 week old No cell 37 B1 Fresh With cell 37 B2 Fresh With cell 37 B3 Fresh With cell 37 T-cells were seeded at 5*105 cells/mL with 2 pL/cell of ImmunoCult™ Human CD3/CD28/CD2 T Cell Activator. 6-well plates were used, and the working volume was 3 mL per well. ImmunoCult™-XF T Cell Expansion Medium was used to culture and dilute the supernatant. One-week-old activators were mixed with media at 12.5 µL activator per 1 mL media ratio and stored in a 15 mL falcon tube inside the incubator at 37 C under 5% CO2 before use. 250 µL supernatants were collected and diluted 4 times with fresh media following the schedule shown below (Table 3): Table 3. Supernatant sampling time for each well. Plate Well Supernatant sampling time Fridge Plate F A1 Day 1, day 3 and day 5 A2 Day 1, day 3 and day 5 Incubator Plate I A1 Day 1 and day 5 A2 Day 1, day 3 A3 Day 1 and day 3 B1 Day 1, day 3 and day5 B2 Day 1, day 3 and day5 B3 Day 1, day 3 and day5 Then, the supernatants were assayed following the cell diameter methods described in section 2.6.2 to estimate the activity in the culture. 25 2.3.4 Thermal degradation of soluble activator ImmunoCult™ Human CD3/CD28/CD2 T Cell Activator (STEMCELL) was added to ImmunoCult™-XF T Cell Expansion Medium (STEMCELL) in a 15mL falcon tube (12.5 µL activator per 1 mL total volume) to test the thermal degradation of soluble activators. This ratio gave an activity equivalent to 25 pL/cell for cultures starting with 5*105 cells/mL. 4 batches of activators were placed into the incubator at 37 C and 5% CO2 to test thermal degradation after 1 week, 2 weeks, 4 weeks, and 8 weeks. For each time condition, 10mL of stock solution was prepared with two replicates (Figure 11). Figure 11. Incubation of activators in culture media for analysis of thermal degradation. (Created using BioRender.com). When the first batch was cooked for 8 weeks, all stock solutions were diluted 20 times in volume to start the activity assay with 2 different donors (Figure 12). At the same time, two wells of fresh activator were assessed to set the bar for 100% remaining activity. For the activity assay, a standard curve from 0 to 2.5 pL/cell activity was used to estimate the activity of the diluted sample. 26 Figure 12. Activity assay setup for estimating thermal degradation of soluble activators. (Created using BioRender.com). 2.3.5 Matrix effect test for functional assay based on cell diameter Matrix effect tests were done in 8 pL/cell and 25 pL/cell initial activity conditions. Two dilution ratios were used for each initial activity condition. The original 1:6 dilution and 1:12 dilution using the day 5 sample were implemented since these samples contained the most substances excreted by T-cells and the lowest pH. All supernatants were diluted with fresh media and stored at 4 C, shaded from light in a box. Given that the activator concentration of 4 pL/cell exhibited the lowest remaining activity, another method was proposed to test the matrix effect. For 4 pL/cell conditions, day 0, day 3, and day 5 supernatants were analyzed. For day 0 and day 3, the dilution ratio used was 1:6 and 1:8; therefore, the diluted activity stayed in the operational range. For day 5 supernatants from 4 27 pL/cell, after 1:4 dilution, an extra 0.5 µL of activator, equivalent to 1 pL/cell, was introduced into the diluted supernatant sets. All supernatant was analyzed alongside the regular activity assay at each batch. 2.4 Refreezing T-cell aliquots 2.4.1 Aliquot and refreezing the T-cells For thawing T-cells, cryopreserved vials were taken from the liquid nitrogen dewar and immediately placed inside the water bath at 37 C. The vials were gently swirled until the last piece of ice melted and disinfected thoroughly with 70 v/v% ethanol. The rest of the steps were performed inside the biosafety cabinet. The aliquot volume was determined by the fraction of the storage volume of the vial; 1/20, 1/10, and 1/4 of the storage volumes. Six 1mL cryopreservation vials were prepared for each donor in which two identical sets of 3 vails were set up to exam the effect of time in cryopreservation media. Open-bore pipette tips were used for aliquoting cells. First, a 1mL pipette was used to resuspend cells five times inside the original vial gently. Then, 250 µL was transferred to a new vial with the same pipette tip twice. 50 µL and 100 µL were also transferred to a new vial twice, using a 200 µL tip. Cell count from the original vial was taken after the aliquoting step. One batch of 50, 100, and 250 µL samples were placed into Mr. Frosty™ immediately and transferred to a -70 C freezer for overnight storage. Another set of vials was left on the bench at room temperature for 60 minutes. After 60 minutes, this batch of samples was transferred to Mr. Frosty™ and stored overnight in a -70 C freezer. All vials were transferred to liquid nitrogen dewar the next day for 7 days of cryopreservation. 2.4.2 Thawing of refrozen T-cells and biochemical analysis Vials and ImmunoCult™-XF T Cell Expansion Medium were warmed in a 37 C water bath. Vials were gently swirled until the last piece of ice melted. Disinfected and transferred the vials to the biosafety cabinet. To avoid dramatic osmotic pressure change while diluting DMSO, a portion of fresh and warm media, equivalent to 20% of the vial’s total volume, was added to the 28 vial containing the cells. Before the next dilution, cells were rested and swirled for one minute in the vial. Once the total volume reached 10 times the original volume inside the vial (except for 250 µL condition, diluted to 1mL total), T-cells were transferred from the vial to a 15 mL falcon tube. Afterwards, the dilution process continued according to the instructions provided in the table below (Table 4): Table 4. Dilution plan for different aliquot volume. Condition (uL) Final volume inside the cryopreservation vial (uL) Final volume inside the 15 mL tube (mL) Final volume after centrifugation (mL) 50 500 2 1 100 1000 4 2 250 1000 10 5 The cells were centrifuged at 300 x g for 5 minutes and removed the supernatant. Cells were resuspended in fresh and warm media to the final volume shown in Table 2. Cell count was taken for each condition. Cells were transferred to the incubator for biochemical analysis. Following the methods described in section 2.4, cells were seeded and activated for long-term culture. Cell concentration data was taken on day 3 and day 5 to compare the cell growth. 2.4.3 T-cell quality analysis after multiple freeze and thaw cycle Flow cytometry was implemented to analyze the cell quality after the freeze and thaw cycle. Fluorochrome dyes involved in this analysis are listed in the following table (Table 5). Table 5. Fluorochrome dyes used for flow cytometry. Channel Maker Fluorochrome / Antibody Identifier APC Live/Dead BD Horizon™ Fixable Viability Stain 660 Cat# 564405 PB450 CD3 BD Horizon™ V450 Mouse Anti-Human CD3 Cat# 560366 PC5 CD4 BD Pharmingen™ PerCP-Cy™5.5 Mouse Anti-Human CD4 Cat# 566316 APC-A750 CD8 BD Pharmingen™ APC-H7 Mouse anti-Human CD8 Cat# 560179 29 Violet 610 CD45RA BD Horizon™ BV605 Mouse Anti-Human CD45RA Cat# 562886 PE CCR7 BD Pharmingen™ PE Mouse anti-Human CD197 (CCR7) Cat# 560765 FITC Annexin V (apoptosis) BD Pharmingen™ FITC Annexin V Cat# 556420 To start the flow cytometry analysis, the 10X Annexin V Binding buffer (stored at 10X concentration contains 0.1M HEPES at pH 7.4, 1.4M NaCl, and 25 mM CaCl2) was diluted to 1X with deionized water and stored in 4 C fridge. T-cells were counted with CEDEX. 0.1 * 106 cells were taken and transferred to a 96-well plate. If the volume exceeded 200 µL, cells were centrifuged, resuspended using DPBS to 200 µL, and transferred to a 96-well plate. All samples were topped up using DPBS to 200 µL and mixed thoroughly. Centrifugation was done at 700 x g for 3 minutes, and the supernatant was removed by flipping the plate and discharging the liquid to the sink. The pellets were washed with DPBS and the centrifugation was repeated twice more. Cells were resuspended in DPBS and added the dye to the sample wells. Samples were incubated at room temperature for 30 minutes and the plate was covered with tin foil to avoid direct light. The samples were washed and centrifuged with DPBS 2 times. Finally, the samples were resuspended using 150 µL of Annexin V binding buffer. CytoFlex flow cytometer (Beckman Coulter) was implemented for flow cytometry analysis. 2.5 Software For data analysis, Microsoft Excel was used for calculation and data entry and GraphPad Prism was used for statistical analysis and data visualization. Illustrations are generated through Biorender. Flow cytometry data was analyzed with CytExpert (BECKMAN COULTER). 30 Chapter 3: Results and discussion The following sections illustrate the results obtained from experiments and discussion of what these data represent as well as how they could be implemented to benefit both the biomedical industry and academia. 3.1 T-cell soluble activator dose response For cell-based assays, cell proliferation is one of the critical indicators of process performance and effective T-cell activation. Furthermore, cell proliferation is one of the most accessible culture-based results with widely used and standardized measurement methods. Thus, our journey of finding the best candidate for activity assay starts with proliferation. When designing an assay, we first need to determine the range of operation the assay can measure. STEMCELL has recommended 25 µL of the activator for one million T-cells per mL in the culture. Based on the recommended dose, an activity of 25 pL/cell was provided for the cells initially. This value was used as the baseline to compare various activities. The initial experiment examined the dose-response of T-cells, covering activity levels ranging from 0 to 25 pL/cell in a batch culture. Figure 13. Fold expansion profile for T-cell growth under variable initial activity. 500,000 cell/mL initial cell concentration was seeded in 1 mL of volume within a 24 well plate batch culture. STEMCELL medium, activator and IL-2 were supplemented. Starting on day 3, a sample was taken from each condition every day and the CEDEX was used for cell counting. 31 Figure 13 shows the impact of activator dose on the fold expansion of T cells from day 0 to day 6 without adding nutrients during the experimental period. It was noticed that T cells cultured in media supplemented with an activity level greater than 1.56 pL/cell ceased to proliferate after either day 4 or day 5. After investigation, we suspected that nutrient limitation, metabolite accumulation and/or pH decreases negatively impacted the cell proliferation since the experiment was done in batch culture. The following experiment was designed with cell dilution and a fresh medium feed on day 3 (Figure14). And based on this result, a dilution is required at day 3 for cell proliferation to reflect the activity properly. Figure 14. Activator dose response for batch and fed experimental setup. 500,000 cell/mL initial cell concentration within 24-well plates with 1 mL working volume. Fed by a fresh medium dilution of 1:4 on day 3. Figure 15. T-cell size changes during the culture, after activation at day 0. 32 While culturing T-cells, a notable trait was discovered: that their average size exhibited several changes. The change in diameter was greatest during the first three days of culture, and it reached the maximum on day five and then gradually decreased (Figure 15). It was realized that this size increase could be a function of the medium activator activity. Combining all evidence, we proposed our hypothesis, that measuring the average T-cell diameter can be used to measure the activity of activator present in media. An experiment was proposed to test the dose response of T-cell diameter at 24, 48, and 72 hours after activation, with a substantial change in average cell diameter after 48 hours of activation (Figure 16), chosen with a detection range for the assay from 0.5 to 2.5 pL/cell (for a 5*105 cells/mL initial seeding concentration). Upon further investigation, we have discovered that with the increase of activator dose, the population of enlarged T-cells increase proportionally. This is the main driving force to the increase of average cell diameter. For more detailed population data see Appendix B. 33 Figure 16. Activity dose response impact on cell diameter after two days of culture. Two technical replicates were performed for the experiment. 500,000 cell/mL initial cell concentration using 6-well plates at 3 mL working volume was seeded at day 0. Cell diameter was measured through CEDEX every 24 hours after seeding. Cell size distribution for 0.25 pL/cell and 2.5 pL/cell STEMCELL soluble CD3/CD28/CD2 activator at 48 hours was shown above. After confirming the dose-response from the 48-hour culture, a total of 8-donor experiments were performed (Figure 17). When results were analyzed, similar though varied trends were observed across the 8 biological replicates, and a cubic polynomial was fitted to the data points with R2 = 0.87. This result demonstrated that average cell diameter could be used to measure the activity, though a standard curve would need to be generated for each donor used for this assay. 34 Figure 17. 8-donor dose response and curve fitting of average results with cubic polynomial equation. Eight biological replicates were performed for a dose response from 0 to 2 pL/cell using STEMCELL soluble CD3/CD28/CD2 activator. The initial seeding concentration was 500,000 cells/mL using 24-well plates at 1 mL working volume. Another commercially available soluble activator, Human T Cell TransAct™ by Miltenyi Biotec, was tested alongside the STEMCELL activator. This soluble activator is widely used for clinical trials. Due to the difference in the recommended dose by two soluble activators, up to 57 pL/cell of TransAct was tested (this was used for the manufacturing CAR T-cells for the CLIC-01 trial in Canada). It should be noted that, since Human T Cell TransAct™ (Miltenyi Biotech) and ImmunoCult™ Human CD3/CD28/CD2 T Cell Activator (STEMCELL) are fundamentally different in terms of their structure (Tetramers for STEMCELL and antibody-coated nanosheets for Miltenyi), the values of their pL/cell represent different activity levels. The results in Figure 18 confirmed that the cell-size assay is applicable to this other soluble activator, although the cell average maximum cell sizes were significantly different after 48 hours of culture. T-cells stimulated with the Miltenyi activator reached an average size of 11 to 12 m using 57 pL/cell activator. In comparison, T-cells stimulated with the STEMCELL activator were smaller than 9 m with the same dose. It may be that less activation-induced cell 35 death explains why the Miltenyi activator yielded the larger average cell diameters at 48 hours. At 72 hours the cell sizes converged to a similar size. Figure 18. T-cell diameter dose response with two different soluble activators. Two soluble activators (STEMCELL and Miltenyi) were tested with 2 biological replicates using 24-well plates at 1 mL working volume. The initial seeding concentration was 500,000 cells/mL and the average cell diameter was measured at 48 hour and 72 hours using CEDEX. In conclusion, with the implementation of the fed culture technique, the dose response of soluble activator for T-cell growth was observed, and fold expansion after 4 or 5 days of culture showed distinctive differences with different initial activities. However, since CAR T-cell production can be time-sensitive, a shorter-time and simpler method using 48-hour cell diameter measurements was adopted. So far, the diameter assay has been tested with two different types of soluble activators. 3.2 Soluble activator degradation factor screening Although many publications have illustrated the need for restimulation for T-cell expansion, the progressive activity loss during culture remains understudied. STEMCELL soluble activators are monoclonal antibodies with tetramer structure. Essentially, soluble activators are proteins; thus, protein degradation studies can serve as the foundation for investigating activity loss. Three modes of activator loss were proposed for this study (Figure 19). 36 Due to the nature of protein, activators can bind to the suspension culture plate bottom or wall, which can make the active site unable to contact T-cell receptors, by steric hindrance, conformation changes or binding to side-surfaces while the cells settle to the bottom. This was illustrated in Figure 19 as the first mode of activator loss: binding to the plate surface. Antibodies in the human body are relatively stable at 37 C; however, especially since soluble activators are artificial antibodies, they could be less stable at temperatures higher than the recommended storage temperature (4 C). This hypothesis made the second mode of activator loss (Figure 19): thermal degradation. T-cell activation requires signals initiated through direct contact between the activator and the receptor. If activators bind to the cell surface and do not detach, this binding will make activators unavailable for other T-cells and reduce the activity in the media. Finally, since T-cells have previously been reported to internalize IL-2, a similar principle can be applied to activators, in which activators are internalized with the receptor after the activation of T-cells. Therefore, the third proposed activator loss mode is: binding to or internalization by T-cells. All three modes of activator loss can contribute to the activity loss simultaneously at different magnitudes. To answer the question of which mode is the most significant contributor to activity loss in media, the above three proposed modes of activity loss were tested during the screening experiment. Figure 19. Three modes of activator loss during culture. (Created using BioRender.com). 37 Figure 20. Standard curve generated for measuring activity and activity profile over 5 days of culture under different conditions. For detailed culture and incubation setup for collecting the supernatant, please refer to section 2.3.3. One donor with three technical replicates was implemented using 24-well plate at 1 mL working volume for the supernatant activity assay. Initial cell concentration was 500,000 cells/mL with two technical replicates for the standard curve. For the assay portion of the experiment, a single donor was used to generate the standard curve and measure the activity of the sample on the same day using an activator from the same lot. These were to minimize the variability caused by biological differences of donors and inconsistency between different lots. The Figure 20 standard curve obtained from this experiment had a similar trend to the previous 8 donors. Overall, from the activity profile, the presence of T-cells was the greatest contributor to activity loss, with less than 15% of activity remaining after day 5. A sharp and consistent decline in activity was observed from day 1 to day 5. Although the last data point falls on 0.5 pL/cell, the actual activity of the sample might be lower than 0.5 pL/cell, as 0.5 pL/cell is the lower bound of the operation range for this assay. Below the lower bound, the activity assay cannot detect the activity accurately. It is still unclear whether binding or internalization dominates the loss of activity. A few possible methods to distinguish these two factors include transmission electron microscopy, which captures the activator location in T-cells, and fluorescence labelling, which can observe the overall intake or binding of the activator. However, this was beyond the scope of this master project. 38 When analyzing the incubation temperature effect on T-cells, the results did not indicate that thermal degradation was a major activity loss factor. However, since the thermal impact might not be high enough in short-term cultures, follow-up experiments below were proposed to examine the thermal degradation effect on the scale of weeks. Concurrently, the plate surface binding test did not reveal a distinguishable impact on activity loss, likely due to using a low-binding suspension plate used in the experiment. 3.3 Soluble activator thermal degradation Antibodies in the human biological system typically have 1 to 3 weeks of half-life, and their stability decreases with the increase in temperature[89],[90]. For the manufacturing of CAR T-cells, the culture is often performed at 37 C, and the time of culture can be as long as two weeks. Thus, the thermal degradation effect can be more noticeable than short-term cultures. With this, a new experiment was performed to investigate thermal degradation on a scale of months. 3.3.1 Analysis of thermal degradation using diameter method assay Four batches of 12.5 µL/mL activators were incubated for 8 weeks, 4 weeks, 2 weeks, and 1 week at 37 C. To avoid the matrix effect caused by the thermal degradation of other ingredients during incubation, a dilution of 1:20 with fresh media was used. Theoretically, the baseline activity should be 1.25 pL/cell (0.625 µL activator per 5*105 T-cells), and the percentage of remaining activity in the media should decrease as time increases. 39 Figure 21. Standard curve for two donors and the remaining activity after extensive incubation. Four sets of 25 pL/cell STEMCELL activator were incubated at 37 C at 5% CO2 for 1, 2, 4 and 8 weeks in culture media. A 1:20 dilution was performed to dilute the stock activator to around 1.25 pL/cell. Two biological replicates were implemented with 500,000 cells/mL initial seeding concentration in 24-well plate at 1mL working volume. Two biological replicates, one female donor and one male donor, were used for this experiment. The standard curve showed again that the dose response can vary somewhat for different donors (Figure 21). However, at 1.25 pL/cell, the targeted activity was within the functional range of the standard curve. As hypothesized, the overall trend of the percentage remaining activity gradually decreased as the incubation time increased. One of the common models used for decay processes like thermal degradation is exponential decay (Figure 21). From the trend of two donor average, a decrease of activity loss had been observed and exponential decay functions generate similar trend. Thus, an exponential decay curve was fitted. The generated function was 𝑌 = 102.6 ∗𝑒−0.051𝑋 − 2.6 with R2 = 0.89 which gave an exponential decay. The estimated half-life of ImmunoCult™ Human CD3/CD28/CD2 T Cell Activator stored at 12.5 L/mL is close to 14 weeks. Since a typical CAR T-cell manufacturing process lasts for 2 weeks or less, then only a 10% of the activity loss would be expected. Therefore, thermal degradation can be considered a minor factor affecting the activity in culture. In conclusion, the above two experiments with diameter and proliferation methods validated the hypothesis of degradation of the activator in an incubation environment at 37 C and 5% CO2. However, the effect of thermal degradation was discovered to be significant after weeks of incubation. An exponential decay model was proposed to describe the process. However, further investigation was required to validate this model. 40 3.4 Activity loss due to T-cell presence in the culture The major contributor to activity loss in culture was proposed to be the presence of the T-cells. This hypothesis was confirmed with the experimental results obtained previously (Figure 20). The screening experiment indicated more than 85% activity loss with T-cell co-incubation. Thus, a follow-up experiment to validate this phenomenon was designed with 6 biological replicates under two different initial activity conditions (8 pL/cell, 25 pL/cell). Both average cell diameter and proliferation methods were implemented. However, the proliferation method was only used for 25 pL/cell condition. 3.4.1 Analysis of T-cell presence effect in activity loss by cell diameter method 3.4.1.1 Culture with initial activity of 8 pL/cell A trend similar to what was observed during the screening experiment (Figure 20) was observed for ‘no cell’ and ‘with cells’ conditions (Figure 22). In both experiments, an initial decline of remaining activity was observed from day 0 to day 3. However, from day 3 to day 5, an increase in the remaining activity was detected specifically in ‘no cells’ conditions. In the later experiments, the volume of no cell condition was measured and recorded. The figure above confirmed a significant loss of volume due to evaporation. On day 5, a 26% loss (1.7 mL vs. 2.3 mL) in volume was found compared to the expected value only due to sampling. Since evaporation concentrated the activator in media, the activity increased in the absence of cells. The medium conditions with cells had a decreasing activity at 15.8 %/day or 1.26 pL/cell-day. Interestingly, the screening experiment with 2 pL/cell initial activity decreased at 0.35 pL/cell-day, about a quarter of the rate for the 8 pL/cell condition, and that was -17.5 %/day for the 2 pL/cell condition. Thus, the percentage activity loss rates were similar despite the difference in initial activity. 41 Figure 22. Percentage remaining activity in supernatant and evaporation during culture. Eight pL/cell initial activity was implemented along with 6 biological replicates for the culturing and supernatant collection part of the experiment. A single assay donor was used for all standard curve and activity measurement. All experiments started with 500,000 cells/mL seeding concentration. For the assay, the Day 0, day 3 and day 5 supernatants were diluted using different dilution ratios so that the activity stayed within the assay standard curve range (0-2.5 pL/cell). The cell culture was performed in 6-well plates at 3 mL working volume. The volume measurements were performed in one ‘no cells’ well during one experiment. Figure 23. Cell-specific activator consumption rate for 8 pL/cell condition. Another direct evidence that showed activity loss due to T-cells was a lower remaining activity found with higher T-cell concentrations from day 3 to day 5 (Figure 23). Upon calculating the 42 cell-specific consumption rate, the rate decreased significantly as cell proliferation increased, potentially due to an activator concentration limitation. Thus, 25 pL/cell starting medium conditions were performed to investigate this further. 3.4.1.2 Culture with initial activity of 25 pL/cell Figure 24. Percentage remaining activity profile and evaporation measurement. The 25 pL/cell initial activity experiments were performed for 6 biological replicates. One assay donor was used for all standard curve and activity measurement. The cultures were started with 500,000 cells/mL, then the incubation was performed in 6-well plates at 3 mL working volume. The volume measurements were performed in two ‘no cells’ wells during 3 experiments. The trend for ‘with cells’ conditions was similar to 8 pL/cell conditions from day 0 to day 3 (Figure 22 and Figure 24). ‘With cells’ conditions had a sharp decline to, on average, below 75% remaining activity, which means a loss of 6.25 pL/cell of activity in the first three days, while 8 pL/cell conditions had a loss of 2 pL/cell (Figure 22). The reason for the difference in activity consumption was suspected to be that 25 pL/cell conditions were present in excess initially for cells to consume. An even sharper decline was found from day 3 to day 5 with the presence of T-cells. 25 pL/cell conditions had a greater activity loss, close to 50% or 12.5 pL/cell, while 8 pL/cell conditions showed a loss close to 25% or 2 pL/cell (Figure 22 and Figure 24). 43 Figure 25. Standard curves up to 2.5 pL/cell activity and cell-specific activator consumption rate. As for the ‘no cell’ conditions, a decline after day 3 was recorded, which contradicted the results from 8 pL/cell conditions. In this case, the dilution of supernatant caused the measurements to fall outside our standard curve range (0.25 to 2 pL/cell). Unlike the 8 pL/cell results (Figure 22 and Figure 23), where 0.8 pL/cell-day and 0.3 pL/cell-day decreases were measured for days 0-3 and 3-5, respectively, the 25 pL/cell cultures maintained 1.5 pL/cell-day decreases during both periods, and thus appeared not to drop to levels that limited the cell binding rates. Two potential reasons for the higher consumption rate are: (1) as initial activity increased to 25 pL/cell T-cells were more stimulated than they were at 8 pL/cell initial activity, such that the more activated cell metabolism consumed more activator, and/or (2) increased medium activator levels increased the consumption rate as activator concentration was not limiting. In conclusion, 8 pL/cell and 25 pL/cell initial activity conditions were tested in a total of 6 batches of experiments with 12 donors. In both conditions, the presence of T-cells in the culture significantly reduced the activity remaining after 5 days. For the ‘no cell’ conditions, 8 pL/cell and 25 pL/cell conditions had minor opposite trends at least in part due to varied culture medium evaporation. For the 25 pL/cell conditions, there was a greater rate of activator decrease than for the 8 pL/cell conditions. Thus, the activator availability in culture limited the rate of activity decrease, including from days 3-5 when a higher consumption rate was maintained for the 25 pL/cell condition. 44 3.4.2 Analysis of T-cell presence effect in activity loss by cell proliferation method The design of the activity assay contained two methods: cell diameter and cell proliferation. Although the cell proliferation method required more time, the dose response generated had a wider range as shown in figure 14. For the 25 pL/cell initial activity conditions, both cell diameter and proliferation methods were implemented to compare the results between the two methods. Figure 26. Standard curve generated from diameter (from Figure 25) and proliferation methods. The same assay donor was used for both cell diameter and cell proliferation methods. 3 standard curves were generated using 2 technical replicates each. 500,000 cells/mL initial seeding concentration was implemented using 24-well plate at 1 mL working volume. When comparing two standard curves (Figure 26), the proliferation method curve had decreased precision than the diameter method. Above a 1 pL/cell activator dose the difference between data points on the same activator dose was as large as 100%. On the other hand, most of the cell diameter results had far greater precision. One of the reasons the proliferation method results varied significantly is that the procedure for the proliferation method was more complex than the diameter methods. With more human intervention, it came with a higher chance of variability. 45 Figure 27. Comparison of the measured percentage remaining activity from two assay methods. Results of diameter methods were from Figure 22. 6 biological replicates were tested with initial activity of 25 pL/cell. Supernatants taken for two methods were each collected from the same donor during the same experiments but stored separately. Cell diameter took 48 hours to complete measurements and cell proliferation required 5 days of culture, with a volume dilution on day 3. All experiments started with 500,000 cells/mL seeding concentration. Despite the potential inaccuracy of the proliferation method, when the results from both methods were plotted on the same graph, the results were very similar (Figure 27). Thus, both methods demonstrated their ability to reflect the remaining activity of the supernatant, with the cell diameter method was preferred as it took less time and labour to analyze the samples and the standard curve points were far more closely replicated than the cell proliferation method. 3.4.3 Effect of cell phenotypes in activity loss One of the critical quality attributes in CAR T-cell therapy is cell phenotype, as certain phenotypes of T-cells are preferred. Rooted from this idea, an investigation of activity loss regarding T-cell phenotypes was proposed. Fortunately, CD4+ and CD8+ T-cells were available in the enriched form in the cell inventory. The primary focus for this side project was to determine if CD4+ and CD8+ T-cells resulted in different activity loss. Except for the T-cells used, the experimental setup was the same as the activity assay with 8 pL/cell initial activity experiments. Two technical replicates of CD4+ and CD8+ T-cells from the same donor replaced two biological replicates in previous experiments with 8 pL/cell initial activity. This setup eliminated the donor-to-donor variability and focused on the effect of phenotypes. 46 Figure 28. Cell growth profile and percentage remaining activity during culture for CD4+ and CD8+ T-cells. Two biological replicates per condition were implemented with 500,000 cells/mL seeding concentration. 6-well plates at 3 mL working volume were used for cell culture. One of the most distinctive differences between CD4+ and CD8+ T-cells was their proliferation profile (Figure 28). CD8+ T-cells had a much shorter lag phase before the massive cell growth; CD8+ T-cells reached around 1.5 * 106 cells/mL versus 0.5 * 106 cells/mL for CD4+ T-cells on day 3. This difference gave CD8+ T-cells an advantage in consuming and reducing activity from day 0 to day 3 but also limited its growth from day 3 to day 5 due to nutrient limitation. Both cell types had a sharp and continuous decline in remaining activity, with CD8+ T-cells having relatively higher activity loss on days 3 and 5. During 5 days of culture, the CD4+ condition had around 65 % activity loss, whereas the CD8+ condition resulted in 83 % loss in activity. The 18% difference mainly came from day 3, since CD8+ conditions had less than 45 % activity left, compared to 70 % with CD4+ conditions. However, less activity loss (28 %) was overserved from day 3 to day 5 for CD8+ conditions. 47 Figure 29. Correlation between cell concentration and percentage remaining activity on day 3 and day 5 based on different cell types and cell-specific activator consumption rate. The above graphs illustrate the relationship between cell concentration and the percentage remaining activity (Figure 29). On both graphs, it was clear that higher cell concentration resulted in higher activity loss. The discrepancies in activity loss between CD4+ and CD8+ cells were mainly due to the difference in cell growth profile other than the phenotype of T-cells consuming more activators per cell. Based on the cell-specific activator consumption rate, CD4+ and CD8+ T-cells had a similar rate for the first 3 days. However, as activity drained over time, both phenotypes of T-cells had a decrease in cell-specific consumption rate on day 5. The lower percentage remaining activity was correlated to the lower cell-specific activator consumption rate. The same observation was found during the 8 pL/cell initial activity assay experiment, where the activator was the limiting agent in the cell-specific activator consumption rate. 3.4.4 Matrix effect in the activity assay One of the biggest sources of error in assays was the matrix effect. The matrix effect could significantly interfere with the result in multiple ways. The significance of the matrix effect could be examined by diluting samples with multiple dilutions and comparing results. The matrix effect was considered significant when the t-test resulted in a significant difference. With the matrix effect, samples must be treated before assays. 48 Figure 30. No significant matrix effect was found. Two different dilution ratios for day 0 and day 3 supernatants plus day 5 diluted supernatant with added fresh activator for 8 pL/cell conditions. Due to the lower initial activity in 8 pL/cell, the higher dilution ratio of 1:8 dilution was used to prevent any points from falling out of the operational range of the activity assay. However, 1:8 dilution was still too high for day 5 supernatants as less than 1 pL/cell activity was left (Figure 22). An alternative way to counter this problem was adding a set amount of activator to the supernatant after dilution and comparing the theoretical value to the measured value. When a paired t-test was conducted using the assay results from days 0 and 3 samples, no significant differences were found between 1:6 and 1:8 dilution. Although no significant difference was found in the day 5 test, the measured average activity was lower than the theoretical average. One explanation for this observation was that the theoretical value was miscalculated due to the day 5 control supernatant falling below the measurable range. In this experiment, both supernatants were diluted using 1:4 dilution. The measured samples had 1 pL/cell fresh activity added to the supernatants. When calculating the theoretical value, the estimated activity from the theoretical samples was added with another 4 pL/cell to generate the theoretical value. The issue was that with a 4-time dilution, the day 5 supernatants were likely to be diluted to a level lower than 0.25 pL/cell, which could result in an inaccurate measurement. The estimation was usually higher than the actual value based on the standard curve. As a result, the average measured value was lower than the average theoretical value (Figure 30). Even with slightly inaccurate measurements, no statistical evidence showed that the matrix effect was significant. 49 Figure 31. Matrix effect test results for day 5 supernatants under 25 pL/cell conditions. Two dilution ratios were performed for the day 5 supernatant to examine the matrix effect. 6 biological replicates were included in the experiments. All experiments started with 500,000 cells/mL using 6-well plates at 3 mL working volume. Activity assay was performed using the same assay donor for all supernatants (*: P<0.05). Based on the test results for the matrix effect under the 4 pL/cell condition, days 0 and 3 were excluded since no significance was found. For the 25 pL/cell conditions, both 1:6 and 1:12 dilution ratio was tested. To reduce the variability from donors, results were compared with paired t-tests within each donor (Figure 31). Out of six donors, only one donor (donor 5) showed significant differences with P = 0.013, while donor 6, whose experiment was in the same batch, did not. Since other test results suggested nonsignificant differences, this standalone case was viewed as a donor-specific event or an operation error. To summarize, the matrix effect was not detected in day 0 and day 3 samples, whereas the potential matrix effect was detected on day 5 supernatant with nonsignificant differences for most of the tests. 3.4.5 Conclusion In conclusion, the validated major factor of activity loss during culture was the presence of T-cells under both 8 pL/cell and 25 pL/cell initial activity conditions with a total of 12 biological replicates. The phenomenon was tested with both the cell diameter and cell proliferation method. Although both methods provided comparable standard curves, the cell proliferation method 50 generated greater variability when compared to the cell diameter method. Evaporation was one of the major contributors to the inaccuracy of assay measurement, and as the initial activity increased, the effect became more substantial. The cell-specific activator consumption rate was limited by the amount of activity remaining: 8 pL/cell conditions had a lower average consumption rate at day 3-5 versus day 0-3, whereas 25 pL/cell conditions had a similar (or higher) average consumption rate at day 3-5. A negative correlation was found between cell concentration and percentage remaining activity for 8 pL/cell initial activity conditions but not 25 pL/cell conditions. 3.5 Cryopreservation of aliquot T-cells and multiple freeze-thaw cycle One of the most critical processes for the clinical samples we received from the CLIC-01 trial was to enrich the CD3+ T-cells and aliquot T-cells to several vials and then cryopreserve them. The rationale was that multiple types of analyses were proposed to assess these patient cells, but some of them could not be conducted simultaneously. Thus, aliquot and refreezing of the remaining T-cells were required for later use. The experiment started with three areas of interest: the feasibility of refreezing T-cells, the effect of aliquot cells in small volume and the effect of prolonged resting in toxic environments (10 % DMSO, room temperature). Driven by the results of refreezing cord blood, which demonstrated the feasibility of refreezing primary cells with relatively high recovery after several freeze-thaw cycles, the first experiment was proposed to examine if the knowledge can be transferred to T-cells[65], [87], [88]. 51 3.5.1 Effect of refreezing and thawing on T-cell recovery rate and proliferation Figure 32. Percentage recovery of refrozen cell thaw and cell proliferation comparison. Percentage recovery is calculated based on the number of viable cells recovered after the first thaw. Six biological replicates were tested. Cell proliferation was performed with 500,000 cells/mL initial seeding concentration using 6-well plate at 3 mL working volume. (*: P<0.05). Using 6 biological replicates, the recovery of the refrozen thaw conditions was recorded (Figure 32). The percentage recovery was calculated based on the viable cells after the first thaw. Thus, the results in the above graph illustrated the percentage of viable T-cells and their losses compared to the first thaw instead of what was labelled on the vial before the first thaw. Around 70 % to 100% of viable T-cells from the end of the first thaw were generally recovered after the refrozen and thaw process. These values matched the average fresh thaw recovery from previous experiments (~70 %). These data demonstrated the feasibility of refreezing T-cells with a relatively high recovery rate. Variances between each donor were more due to the biological differences between each donor as some T-cells survive better in freeze-thaw cycles than others. Cell proliferation was proposed to be analyzed after the thaw of both first and refrozen conditions. Due to the physical limitations that T-cells could change in their characteristics after resting, first thaw and refrozen thaw cell proliferation experiments were performed in separate batches, but media and soluble activators were from the same lot[91]. The major drawback of this setup was that inconsistencies between separate batches could lead to false conclusions. Judging from the fold expansion graph, refrozen thaw conditions had lower cell fold expansion across the board with the indicated significant differences and a P value less than 0.05 from the paired t-test. Lower cell proliferation could be the result of freeze-thaw cycle induced apoptosis, which could dramatically reduce the cell’s capability of propagation. Based on the results, the 52 conclusion was that refreezing T-cells did affect T-cells performance in cell growth, but the recovery of T-cells after multiple freeze-thaw cycles was acceptable. As long as the focus of the experiment was not on the results of cell growth profile. 3.5.2 Effect of time in 10% DMSO and aliquot volume on T-cells The first part of the investigation demonstrated the capability of recovering a sufficient amount of viable cells from the refrozen vials. Building on that foundation, other parameters were tested. Previous results from thawing cryopreserved cells, cells stored at higher concentrations had better recovery after thaw; and the patient samples were originally stored in around 20 * 106 cells/mL. Based on these inputs, 20 * 106 cells/mL cell concentration was chosen as the storage condition. However, this induced another question: Would T-cells survive when stored at small volume? To investigate this, a series of experiments using 50, 100 and 250 µL of aliquot volumes was proposed. These specific volumes were chosen to reflect the 1/20, 1/10 and 1/4 of the original volume. At the same time, since the enrichment of T-cells was a process that required time, the survivability of T-cells after exposure to 10% DMSO under room temperature was another challenge. Through the previous experiences of enriching T-cells, about 60 minutes of toxic exposure to DMSO was estimated. Thus, 5-minute control and 65-minute conditions were also implemented in the next experiment. Figure 33. Percentage recovery of aliquoted T-cells after the refrozen thaw. Four biological replicates were performed at varied aliquot volumes (50, 100 and 250 µL) and two different time periods in 10% DMSO at room temperature (5 and 65 minutes). Cell counts were performed using a hemacytometer with trypan blue. 53 With 4 biological replicates, a questionably high recovery was recorded with an average of above 100% recovery based on the fresh thaw (Figure 33). The potential cause for this unreasonable number might be how the experiment was set up. The leftovers after aliquot were used to obtain the first thaw cell concentration. This method created two potential problems: the homogeneity of the mix after the fresh thaw, which gave the same cell concentration for all aliquots. And rapid rehydration when the fresh thaw cell concentration was measured since no prior slow dilution was done before the counting. This could lead to dramatic cell losses and resulted in inaccurate cell concentration measurements. Overall, no statistically significant difference was found between different time or aliquot volume conditions. This confirmed that aliquot T-cells in small volumes were feasible, and T-cells could survive in 10% DMSO media under room temperature for more than one hour without significantly impacting recovery. Figure 34. Day 5 cell number fold expansion profile after the refreeze-thaw cycle. Culture started with 500,000 cells/mL using 6-well plates at 3 mL working volume. On day 3 of culture all wells were diluted to 100,000 cells/mL to reduce nutrient limitation, high lactate and low pH effect. Cell counts were taken using CEDEX. Another analysis carried out during the experiment was the cell proliferation comparison. From the first part of the experiment, we observed that cell proliferation can be significantly impacted (Figure 34). Although large error bars due to donor-to-donor variability were generated, which was expected, no statistically significant difference was observed between all conditions. These results illustrated that cell performance in terms of proliferation was not altered by the change in 54 aliquot volume or the time they spent in the 10% DMSO conditions. The aliquot volume can be as small as 1/20 of the original volume, and cell proliferation would have a similar outcome within the range of errors. 3.5.3 Analysis of multiple freeze-thaw impact on T-cell apoptosis One of the major challenges in cryopreserving primary cells was the induced cell apoptosis after the freeze-thaw cycle[68], [79]. This could be especially harmful to T-cells when multiple freeze-thaw cycles were performed. From the previous experiment results, a hypothesis was proposed where multiple freeze-thaw cycles could significantly reduce cell proliferation due to induced apoptosis. This time, apoptosis was checked on the fresh thaw and refrozen thaw conditions with two donors at day 0 and day 5 of culture, as well as comparing activated and non-activated T-cells up to day 3 of culture. To analyze apoptosis signals, flow cytometry was implemented in this experiment. Annex V was one of the common markers that indicates cell apoptosis. For both biological replicates, no dramatic difference was found, and both donors had relatively low apoptotic cell percentages. Based on these results, no significant damage was reflected on the T-cells during the refreezing-thaw process. However, this first experiment only illustrated T-cells at specific time points and one of the conditions T-cell had been activated and cultured for an extended period. In some reports, T-cells were found to build apoptosis signals 24 hours after the thaw, and these experimental results could potentially overlook this fact. Thus, using the same donor, a three-day culture experiment was done to analyze if refrozen cells show more apoptotic signals with or without activation. 55 Figure 35. Flow cytometry results for fresh thaw and refrozen thaw T-cell apoptosis marker at day 0 and day 5 of culture. Table 6. Summary of live apoptotic T-cells percentage in culture under different conditions. Time Fresh thaw Refrozen thaw Donor 1 Donor 2 Donor 1 Donor 2 Day 0 3.3% 1.5% 0.9% 1.5% Day 5 8.4% 6.1% 6.0% 5.3% 56 Figure 36. Percentage of live apoptotic T-cells in culture. Fresh thaw (after one freeze) and refrozen thaw (after freeze, thaw and refreeze) T-cells under two activation conditions (Activated vs. non-activated). Two biological replicates with samples taken and analyzed through flow cytometry every day. *: P < 0.05. The results from this experiment were unexpected and unveiled one of the secrets of induced apoptosis. The percentage apoptotic T-cells difference was not significant between refrozen and fresh thaw conditions on any day of the culture, under the same activation conditions (Figure 35). However, dramatic differences with statistical significance were observed between activated and non-activated cells, which was not observed during the last experiment (Figure 36). Low apoptotic T-cell percentages around 5% to 8% were recorded from the last experiment compared to 40% to 60% this time (Table 6). After investigation, the most plausible cause of this difference was the frequency and time of sampling. For this experiment, samples were taken every day from day 1 to day 3 instead of just day 5. This disturbed cell signalling during early activation stages and stressed T-cells with shear force due to multiple pipetting in order to reduce aggregates. This shear stress could damage the cell and induce cell apoptosis. At the end of the day, no significant difference was found between fresh thaw and refrozen thaw conditions from both experiments, and the percentage of live apoptotic T-cells remained low as long as standard culture protocols were followed. 3.5.4 Conclusion In conclusion, to prepare for the analysis and storage of CLIC-01 patient samples, a series of experiments were conducted to investigate the impact of multiple freeze-thaw cycles, time T- 57 cells spent in 10% DMSO at room temperature and aliquot volume on the recovery of T-cells and their proliferation. The results were promising as the refrozen-thaw conditions typically had 70% to 100% recovery based on the number of cells after the fresh thaw. However, T-cell function in terms of proliferation had been significantly affected. No statistically significant difference was observed after examining T-cell recovery and proliferation under three aliquot conditions and two lengths of time in 10% DMSO at room temperature. Thus, it was feasible to aliquot T-cells in small volumes as low as 1/20 of the original volume and rest the cells in toxic conditions for over an hour. Apoptosis due to multiple freeze-thaw cycles was not significant, and the percentage of apoptotic T-cells stayed low when standard culture protocols were executed. 58 Chapter 4: Conclusion In conclusion, the first functional assay utilizing average cell diameter to measure activity in media was developed to analyze the soluble activator percentage remaining profile during T-cell culture. Building on top of this assay, the hypothesis of three activity loss modes was proved and demonstrated through a series of experiments. Additionally, the feasibility of multiple freeze-thaw cycles on T-cell aliquots with small volume was determined to be applicable since relatively high recovery was recorded after refrozen-thaw, and no statistical significance was found for variables related to time in cryostorage media at room temperature or aliquot volume but variations between donors were recorded. T-cells, as an important defence line in the human body, can be categorized into many different types depending on their surface marker and primary function. Current research showed that common T-cell types are CD4+ and CD8+ T-cells, which represent helper and cytotoxic T-cells, respectively, and Memory T-cells. For T-cells to develop and mature from Hematopoietic stem cells, a series of selections and checkpoints T-cells must go through. Activation is required for T-cells to expand massively, and three signals are often required to activate T-cells properly. One of the applications of T-cells in the biomedical field is chimeric antigen receptor T-cell therapy, which has proven its effectiveness against cancers (leukemia, etc.). One of the factors that limit patients’ access to this therapy is the cost and availability in their region. By optimizing manufacturing processes and providing off-the-shelf options, industry could dramatically lower the financial burden and increase the availability of CAR T-cell therapy. To improve the manufacturing process, monitoring the culture process is key. Since activation is critical to T-cells’ growth and quality, a reliable activity assay is required to monitor the culture process. Immunoassays and biological assays are implemented as a means to qualify biological parameters. ELISA is one example of immunoassay often used to precisely measure the number of target proteins. However, despite the time required to develop a functional ELISA, the major disadvantage of ELISA is that it does not measure activity. To quantify activity, another correlation of activity and the number of target proteins are required. Biological assays, on the other hand, are cell-based assays that directly measure the effect of activity through the change 59 of the cells. Immune functional assays, lymphocytes proliferation test and T-cell activation assay are functional assays that use cells to reflect the change of input parameters. Building on top of these developed assays, we hypothesized that a functional assay using cell proliferation and average cell diameter could be designed to measure soluble activator activity level in culture. One of the benefits of soluble activator is that no downstream processing is required, which reduces the complexity of production. To quantify the activity, a new unit was defined as pL/cell, which refers to the volume of fresh soluble activator added per T-cell at the beginning of the culture. The first stage to validate the hypothesis is to confirm the response of cells when exposed to different activity level. Two publicly available soluble activators involved in this validation process were Human T Cell TransAct™ (Miltenyi Biotech) and ImmunoCult™ Human CD3/CD28/CD2 T Cell Activator (STEMCELL). These two activators are fundamentally different from each other in terms of their structure. If a dose-response can be reflected on both soluble activators, then the application of this assay could be universal. Since STEMCELL recommended 25 µL of soluble activator per 1 million cells/mL, 25 pL/cell is the recommended dose for STEMCELL activators. Similarly, 57 pL/cell for Miltenyi Biotech soluble activators. The dose response was successfully observed using both cell proliferation and average cell diameter method. The two methods used similar culture techniques where 5*105 cell/mL was seeded at the beginning of the culture, accompanied by 200 IU/mL of IL-2 and activators. The major differences were the time of sampling, culture length and the range of activity, that each method was able to respond to. Cell proliferation method had dose response of up to 12.5 pL/cell, and due to the matrix effect of nutrient limitation, high lactate and low pH under the proliferation methods, a volume dilution of 1:4 at day 3 was required. Cell counts were sampled on both day 3 and day 5 to calculate fold expansion of T-cells. Cell diameter method requires only one sampling at the end of the culture, and the culture length is 48 hours. The average cell diameter method had a dose response range of 0 to 2.5 pL/cell after 48 hours of culture for activators from both companies. Although the dose-response profile was different between two activators, the Miltenyi activator promoted T-cells to grow faster and bigger. In total, 8 biological replicates were examined using cell diameter method and a fitted curve with R2 of 60 0.87 was obtained. This demonstrated that within the range of error, the average cell diameter method was reliable. Therefore, the first hypothesis of using cell proliferation and cell diameter to analyze activity was supported. The second hypothesis was proposed to investigate the mystery of activity loss during culture, where three modes of activator loss were hypothesized: (1) Binding to plate surface, (2) thermal degradation, (3) binding to or internalized by T-cells. To investigate these modes together, a screening experiment was conducted to isolate these variables and compare the results. Three conditions of culture were: 4 °C, 37 °C and 37 °C with T-cells. The results had shown that the presence of T-cells had the most effect on activator loss. However, it remained unclear whether binding to cell surface or internalization was the major contributor. Binding to the plate surface and thermal degradation were all minor contributors to the activity loss during culture. Since thermal degradation had higher losses than binding to plate surface, further investigation was conducted. Thermal degradation required time to occur; thus, in this experiment, soluble activators were stored in the incubator at 37 °C with 5% CO2 for up to 8 weeks. This way, activity loss overtime profile can be generated. The experiments were performed using average cell diameter methods. Results obtained from the cell diameter experiments showed an exponential decay of y =102.6 ∗ 𝑒−0.051𝑋 − 2.6 with R2 = 0.89 for STEMCELL activator. Based on the results, thermal degradation would not have a significant impact in culture up to 2 weeks as only a 10% loss of the activity was found, and the estimated half-life is 14 weeks. The percentage remaining activity profile was not linear. This means activators in media incubated at 37 °C with 5% CO2 had more advanced degradation model other than a simple constant decrease. However, further studies are required to validate the new model. Overall, no drastic decrease in activity due to thermal degradation was observed at the 2-week time point, which is the average culture time for CAR T-cell manufacturing. As demonstrated in the screening experiment, the presence of T-cells acted as the major contributor to activity loss during culture. To further investigate this phenomenon, a series of 61 experiments using cell proliferation and cell diameter methods were performed. Two different initial activity were implemented: 8 pL/cell and 25 pL/cell. Due to the higher dilution ratio, only 25 pL/cell conditions implemented the cell proliferation method. With 6 biological replicates, in 8 pL/cell conditions, a linear decrease of activity was observed with a coefficient of –15.75 %/day or -1.26 pL/cell-day due to the presence of T-cells. When comparing the cell-specific activator consumption rate between day 0-3 and day 3-5, statistical significance was found. This indicates that activator consumption was limited by the remaining activator concentration since day 3-5 consumption rate was dramatically lower than day 0-3, although day 3-5 had higher T-cell concentration. Evaporation was the main cause of the percentage remaining activity increasing from day 3 to day 5 under “no cell” conditions, as losing 26% working volume condensed the activator in the media. To reduce the remaining activity limitation effect, 25 pL/cell initial activity was tested. As a result, a non-linear curve of percentage remaining activity under “with cells” conditions were recorded, where day 3 to day 5 had a sharper decline than day 0 to day 3. According to the results, on average, 25 % of activity was lost from day 0 to day 3 and close to 50% of the activity loss was made from day 3 to day 5. This result agreed with the plot showing cell-specific activator consumption rate where day 0-3 had similar or lower rate than day 3-5. These phenomena indicated that T-cells were the major contributor to the loss of activity during culture in both 8 and 25 pL/cell conditions. Additionally, activator concentration/availability was a limiting factor in the consumption of activator. Higher initial activity at 25 pL/cell allowed higher dilution of samples at day 5 with the diluted activity above 0.25 pL/cell. Based on 3 technical replicates, cell proliferation and cell diameter had similar standard curves, with proliferation method had worse precision. The percentage remaining activity profiles were similar between two methods, with a slight difference in day 5 “no cell” conditions. This was due to the volume dilution in the proliferation method, which allowed this method to have a higher range of operation. As cell proliferation method requires more time and steps, it is recommended to adapt the cell diameter method to the manufacturing process since “no cell” conditions are not critical in CAR T-cell production and medical bioprocessing is time sensitive. 62 T-cells are categorized into different types based on their surface marker; each type would have different characteristics. During the experiment, CD4+ and CD8+ cells were compared in their ability to consume activators. The results showed that no significant difference was found in cell-specific consumption rate. The major difference in percentage remaining activity was driven by the fact that CD8+ T-cells propagated faster than CD4+ T-cells. For manufacturers targeting a specific ratio of different types of T-cells, the activity loss at day 3 would change proportionally to the ratio of different types of T-cells, but if the culture lasted for more than 5 days, the remaining activity would be similar. One of the challenges in biological assay is the matrix effect in samples; thus, it is critical to examine if the matrix effect could significantly affect the assay. Both 8 pL/cell and 25 pL/cell conditions were implemented, and no significant matrix effect was observed across all data except for one donor. These results showed that as long as the dilution ratio is above 1:6, the matrix effect will not significantly affect the results. After receiving them, the CLIC-01 trial samples required secondary processing to enrich CAR T-cells and T-cells for later analyses. These patient cells will go through multiple freeze-thaw cycles as well as an enrichment process. Therefore, three possible challenges needed to be resolved: (1) feasibility of T-cells enduring multiple freeze-thaw cycles, (2) effect of T-cells cryopreserved in small aliquots, (3) effect of time spent in toxic cryostorage media at room temperature. From the experimental results of 6 biological replicates, over 70% of T-cells were recovered after they had been refrozen and thawed, which is similar to the recovery of fresh thaw from previous experiments. However, freeze-thaw cycles affected (lower) T-cells’ proliferation with significant differences in fold expansion between the fresh thaw and refrozen thaw. Meanwhile, no statistical significance was recorded across the board on all volume conditions (1/20, 1/10 and 1/4 of the original volume) and two lengths of time (5 and 65 minutes) T-cells spent in cryostorage media. Based on these results, it is acceptable to process the patient samples and refreeze the aliquots for later experiments, as well as any future project involving multiple freeze-thaw cycles of T-cell aliquots. Finally, to investigate the lowered cell proliferation after multiple freeze-thaw cycles, apoptosis was analyzed since freeze-thaw cycles had been reported to increase apoptosis. However, apoptosis was not significant after multiple freeze-thaw cycles, and the percentage of apoptotic T-cells was low after culture for a few days. 63 Overall, CAR T-cell therapy has been an emerging field in treating cancers, and the ongoing number of trials has grown exponentially. The development of this activity assay provided a new tool for academia and industry to monitor the activity of the culture over the course of CAR T-cell expansion, which helps optimize the manufacturing processes. The advantage of this activity assay was that it was designed to directly measure the activity in the culture media at any time point with relatively fast and reliable results (48 hours) and simple procedure. The biggest finding in this project was that the major contributor to activity loss had been identified, which is the presence of T-cells. The effect of thermal degradation is minor as long as the culture length is within 2 weeks. However, there are some limitations to this assay. First, multiple dilution ratio is required if the activity at the time of sample is completely unknown, and no estimation can be made based on previous experiences. Secondly, this functional assay was designed with measuring soluble activators in media in mind. Thus, activity using the beads system may result in inaccurate results. Thirdly, this assay can only be used for T-cell or CAR T-cell analysis in enriched form; other cell types, as well as PBMCs may result in inaccurate test results. Fourthly, at the current state of the assay, it was unable to distinguish the major contributor of activity loss between binding to the cell surface and internalization of activator. Finally, due to the nature of donor-to-donor variability, results could not be comparable unless both the standard curves and test results were done using the same donor. For future studies, several ideas have been proposed and documented. One of the limitations of this project is that it was unable to distinguish between activator binding to cell surface and internalized by cells. Upon further investigation, one possible way to unveil the fact is to use transmission electron microscopy with tagged activators. This way, we could obtain an image of the distribution of the activators if they are attached to the cell surface or inside the cells. It may be that some of the activity loss resulted from proteases secreted by the T-cells degrading the activator. To investigate this, the supernatant can be collected (clarified of cells), and then incubated for more days to determine if the activity decrease continues at a higher rate than could be explained by thermal degradation. One of the challenges this project encountered was that donor-to-donor variability prevented standard curve interpolation between different assay donors. Only a finite number of T-cells can be enriched from each buffy coat; therefore, it is 64 inevitable to require a new standard curve as the assay donor changes. If a T-cell cell line can be developed to mimic the characteristics of inactivated T-cells, this cell line can be widely adopted as a standard for assays using T-cells. This will also enable cross-experiment comparisons of activity results without the need for normalization. The standard curve can be used consistently and standardized throughout every batch of CAR T-cell manufacturing. With the incorporation of the above-mentioned potential research areas, the boundary of CAR T-cell manufacturing and immunology could move outward another step. 65 Bibliography [1] R. S. Sauls, C. McCausland, and B. N. Taylor, “Histology, T-Cell Lymphocyte,” in StatPearls, Treasure Island (FL): StatPearls Publishing, 2023. Accessed: May 24, 2023. [Online]. Available: http://www.ncbi.nlm.nih.gov/books/NBK535433/ [2] B. Alberts, A. Johnson, J. Lewis, M. Raff, K. Roberts, and P. Walter, “Helper T Cells and Lymphocyte Activation,” in Molecular Biology of the Cell. 4th edition, Garland Science, 2002. Accessed: May 25, 2023. [Online]. Available: https://www.ncbi.nlm.nih.gov/books/NBK26827/ [3] J. Charles A Janeway, P. Travers, M. Walport, and M. J. Shlomchik, “T cell-mediated cytotoxicity,” in Immunobiology: The Immune System in Health and Disease. 5th edition, Garland Science, 2001. Accessed: May 25, 2023. [Online]. Available: https://www.ncbi.nlm.nih.gov/books/NBK27101/ [4] D. L. Farber, N. A. Yudanin, and N. P. Restifo, “Human memory T cells: generation, compartmentalization and homeostasis,” Nat. Rev. Immunol., vol. 14, no. 1, pp. 24–35, Jan. 2014, doi: 10.1038/nri3567. [5] Q. Liu, Z. Sun, and L. Chen, “Memory T cells: strategies for optimizing tumor immunotherapy,” Protein Cell, vol. 11, no. 8, pp. 549–564, Aug. 2020, doi: 10.1007/s13238-020-00707-9. [6] K. D. Omilusik and A. W. Goldrath, “Remembering to remember: T cell memory maintenance and plasticity,” Curr. Opin. Immunol., vol. 58, pp. 89–97, Jun. 2019, doi: 10.1016/j.coi.2019.04.009. [7] B. V. Kumar, T. Connors, and D. L. Farber, “Human T cell development, localization, and function throughout life,” Immunity, vol. 48, no. 2, pp. 202–213, Feb. 2018, doi: 10.1016/j.immuni.2018.01.007. [8] D. A. Horwitz, T. M. Fahmy, C. A. Piccirillo, and A. L. Cava, “Rebalancing Immune Homeostasis to Treat Autoimmune Diseases,” Trends Immunol., vol. 40, no. 10, pp. 888–908, Oct. 2019, doi: 10.1016/j.it.2019.08.003. [9] J. Charles A Janeway, P. Travers, M. Walport, and M. J. Shlomchik, “Principles of innate and adaptive immunity,” in Immunobiology: The Immune System in Health and Disease. 5th edition, Garland Science, 2001. Accessed: May 24, 2023. [Online]. Available: https://www.ncbi.nlm.nih.gov/books/NBK27090/ [10] H. T. Petrie, “Role of thymic organ structure and stromal composition in steady-state postnatal T-cell production,” Immunol. Rev., vol. 189, no. 1, pp. 8–20, 2002, doi: 10.1034/j.1600-065X.2002.18902.x. [11] G. Anderson and E. J. Jenkinson, “Lymphostromal interactions in thymic development and function,” Nat. Rev. Immunol., vol. 1, no. 1, Art. no. 1, Oct. 2001, doi: 10.1038/35095500. [12] J. C. Zúñiga-Pflücker, “T-cell development made simple,” Nat. Rev. Immunol., vol. 4, no. 1, Art. no. 1, Jan. 2004, doi: 10.1038/nri1257. [13] P. P. Parham Peter, The Immune System, 4th ed. New York: W.W. Norton & Company, 2014. doi: 10.1201/9781317511571. [14] C. Hong, M. Luckey, and J.-H. Park, “Intrathymic IL-7: The where, when, and why of IL-7 signaling during T cell development,” Semin. Immunol., vol. 24, no. 3, pp. 151–158, Jun. 2012, doi: 10.1016/j.smim.2012.02.002. 66 [15] A. Hamrouni, A. Aublin, P. Guillaume, and J. L. Maryanski, “T Cell Receptor Gene Rearrangement Lineage Analysis Reveals Clues for the Origin of Highly Restricted Antigen-specific Repertoires,” J. Exp. Med., vol. 197, no. 5, pp. 601–614, Feb. 2003, doi: 10.1084/jem.20021945. [16] J. Charles A Janeway, P. Travers, M. Walport, and M. J. Shlomchik, “T-cell receptor gene rearrangement,” in Immunobiology: The Immune System in Health and Disease. 5th edition, Garland Science, 2001. Accessed: May 26, 2023. [Online]. Available: https://www.ncbi.nlm.nih.gov/books/NBK27145/ [17] S. H. Kaufmann, “gamma/delta and other unconventional T lymphocytes: what do they see and what do they do?,” Proc. Natl. Acad. Sci., vol. 93, no. 6, pp. 2272–2279, Mar. 1996, doi: 10.1073/pnas.93.6.2272. [18] J. Wo, F. Zhang, Z. Li, C. Sun, W. Zhang, and G. Sun, “The Role of Gamma-Delta T Cells in Diseases of the Central Nervous System,” Front. Immunol., vol. 11, 2020, Accessed: May 26, 2023. [Online]. Available: https://www.frontiersin.org/articles/10.3389/fimmu.2020.580304 [19] A. Morath and W. W. Schamel, “αβ and γδ T cell receptors: Similar but different,” J. Leukoc. Biol., vol. 107, no. 6, pp. 1045–1055, Jun. 2020, doi: 10.1002/JLB.2MR1219-233R. [20] R. N. Germain, “T-cell development and the CD4–CD8 lineage decision,” Nat. Rev. Immunol., vol. 2, no. 5, Art. no. 5, May 2002, doi: 10.1038/nri798. [21] P. Borgulya, H. Kishi, U. Müller, J. Kirberg, and H. von Boehmer, “Development of the CD4 and CD8 lineage of T cells: instruction versus selection.,” EMBO J., vol. 10, no. 4, pp. 913–918, Apr. 1991. [22] L. Klein, B. Kyewski, P. M. Allen, and K. A. Hogquist, “Positive and negative selection of the T cell repertoire: what thymocytes see and don’t see,” Nat. Rev. Immunol., vol. 14, no. 6, pp. 377–391, Jun. 2014, doi: 10.1038/nri3667. [23] E. Palmer, “Negative selection — clearing out the bad apples from the T-cell repertoire,” Nat. Rev. Immunol., vol. 3, no. 5, Art. no. 5, May 2003, doi: 10.1038/nri1085. [24] L. Chopp, C. Redmond, J. J. O’Shea, and D. M. Schwartz, “From thymus to tissues and tumors: A review of T-cell biology,” J. Allergy Clin. Immunol., vol. 151, no. 1, pp. 81–97, Jan. 2023, doi: 10.1016/j.jaci.2022.10.011. [25] J. E. Smith-Garvin, G. A. Koretzky, and M. S. Jordan, “T Cell Activation,” Annu. Rev. Immunol., vol. 27, pp. 591–619, 2009, doi: 10.1146/annurev.immunol.021908.132706. [26] “T Cell Activation | Annual Review of Immunology.” https://www.annualreviews.org/doi/full/10.1146/annurev.immunol.021908.132706 (accessed May 26, 2023). [27] K. Shah, A. Al-Haidari, J. Sun, and J. U. Kazi, “T cell receptor (TCR) signaling in health and disease,” Signal Transduct. Target. Ther., vol. 6, no. 1, Art. no. 1, Dec. 2021, doi: 10.1038/s41392-021-00823-w. [28] N. Beyersdorf, T. Kerkau, and T. Hünig, “CD28 co-stimulation in T-cell homeostasis: a recent perspective,” ImmunoTargets Ther., vol. 4, pp. 111–122, May 2015, doi: 10.2147/ITT.S61647. [29] M. A. Linterman et al., “CD28 expression is required after T cell priming for helper T cell responses and protective immunity to infection,” eLife, vol. 3, p. e03180, Oct. 2014, doi: 10.7554/eLife.03180. 67 [30] A. Shahinian et al., “Differential T Cell Costimulatory Requirements in CD28-Deficient Mice,” Science, vol. 261, no. 5121, pp. 609–612, Jul. 1993, doi: 10.1126/science.7688139. [31] Y. Wu, C. Anasetti, and X.-Z. Yu, “Chapter 11 - T-Cell Costimulation and Coinhibition in Graft-Versus-Host Disease and Graft-Versus-Leukemia Effect,” in Immune Biology of Allogeneic Hematopoietic Stem Cell Transplantation (Second Edition), G. Socié, R. Zeiser, and B. R. Blazar, Eds., Academic Press, 2019, pp. 167–194. doi: 10.1016/B978-0-12-812630-1.00011-6. [32] J. M. Curtsinger and M. F. Mescher, “Inflammatory Cytokines as a Third Signal for T Cell Activation,” Curr. Opin. Immunol., vol. 22, no. 3, pp. 333–340, Jun. 2010, doi: 10.1016/j.coi.2010.02.013. [33] B. E. Freeman, E. Hammarlund, H.-P. Raué, and M. K. Slifka, “Regulation of innate CD8+ T-cell activation mediated by cytokines,” Proc. Natl. Acad. Sci., vol. 109, no. 25, pp. 9971–9976, Jun. 2012, doi: 10.1073/pnas.1203543109. [34] A. D. Waldman, J. M. Fritz, and M. J. Lenardo, “A guide to cancer immunotherapy: from T cell basic science to clinical practice,” Nat. Rev. Immunol., vol. 20, no. 11, Art. no. 11, Nov. 2020, doi: 10.1038/s41577-020-0306-5. [35] E. J. Wherry, “T cell exhaustion,” Nat. Immunol., vol. 12, no. 6, Art. no. 6, Jun. 2011, doi: 10.1038/ni.2035. [36] D. J. Gasper, M. M. Tejera, and M. Suresh, “CD4 T-Cell Memory Generation and Maintenance,” Crit. Rev. Immunol., vol. 34, no. 2, pp. 121–146, 2014. [37] M. D. Martin and V. P. Badovinac, “Defining Memory CD8 T Cell,” Front. Immunol., vol. 9, 2018, Accessed: May 26, 2023. [Online]. Available: https://www.frontiersin.org/articles/10.3389/fimmu.2018.02692 [38] P. Pandiyan, L. Zheng, S. Ishihara, J. Reed, and M. J. Lenardo, “CD4+CD25+Foxp3+ regulatory T cells induce cytokine deprivation–mediated apoptosis of effector CD4+ T cells,” Nat. Immunol., vol. 8, no. 12, Art. no. 12, Dec. 2007, doi: 10.1038/ni1536. [39] “Risk Factors: Age - NCI,” Apr. 29, 2015. https://www.cancer.gov/about-cancer/causes-prevention/risk/age (accessed Mar. 02, 2023). [40] “Leukemia - Cancer Stat Facts,” SEER. https://seer.cancer.gov/statfacts/html/leuks.html (accessed Mar. 02, 2023). [41] “Global Manufacturing of CAR T Cell Therapy - PMC.” https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5363291/ (accessed Mar. 02, 2023). [42] “Clinical development of CAR T cell therapy in China: 2020 update | Cellular & Molecular Immunology.” https://www.nature.com/articles/s41423-020-00555-x (accessed Mar. 02, 2023). [43] “Potential solutions for manufacture of CAR T cells in cancer immunotherapy | Nature Communications.” https://www.nature.com/articles/s41467-022-32866-0 (accessed Mar. 03, 2023). [44] “A Safety and Efficacy Study Evaluating CTX110 in Subjects With Relapsed or Refractory B-Cell Malignancies (CARBON) - NCI,” Jun. 23, 2016. https://www.cancer.gov/about-cancer/treatment/clinical-trials/search/v?id=NCT04035434 (accessed Mar. 02, 2023). [45] J.-R. Hwang, Y. Byeon, D. Kim, and S.-G. Park, “Recent insights of T cell receptor-mediated signaling pathways for T cell activation and development,” Exp. Mol. Med., vol. 52, no. 5, Art. no. 5, May 2020, doi: 10.1038/s12276-020-0435-8. 68 [46] B. Malissen and P. Bongrand, “Early T cell activation: integrating biochemical, structural, and biophysical cues,” Annu. Rev. Immunol., vol. 33, pp. 539–561, 2015, doi: 10.1146/annurev-immunol-032414-112158. [47] J. E. Smith-Garvin, G. A. Koretzky, and M. S. Jordan, “T Cell Activation,” Annu. Rev. Immunol., vol. 27, pp. 591–619, 2009, doi: 10.1146/annurev.immunol.021908.132706. [48] “Expamers: a new technology to control T cell activation | Scientific Reports.” https://www.nature.com/articles/s41598-020-74595-8 (accessed Mar. 03, 2023). [49] “The Power and the Promise of Restimulation-Induced Cell Death in Human Immune Diseases - PMC.” https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2907538/ (accessed Mar. 03, 2023). [50] N. Kekre et al., “CLIC-01: Manufacture and distribution of non-cryopreserved CAR-T cells for patients with CD19 positive hematologic malignancies,” Front. Immunol., vol. 13, 2022, Accessed: Mar. 05, 2023. [Online]. Available: https://www.frontiersin.org/articles/10.3389/fimmu.2022.1074740 [51] L. A. A. de Jong, D. R. A. Uges, J. P. Franke, and R. Bischoff, “Receptor–ligand binding assays: Technologies and Applications,” J. Chromatogr. B, vol. 829, no. 1, pp. 1–25, Dec. 2005, doi: 10.1016/j.jchromb.2005.10.002. [52] A. P. Mayer and C. S. Hottenstein, “Ligand-Binding Assay Development: What Do You Want to Measure Versus What You Are Measuring?,” AAPS J., vol. 18, no. 2, pp. 287–289, Dec. 2015, doi: 10.1208/s12248-015-9855-0. [53] M. Alhajj and A. Farhana, “Enzyme Linked Immunosorbent Assay,” in StatPearls, Treasure Island (FL): StatPearls Publishing, 2023. Accessed: May 28, 2023. [Online]. Available: http://www.ncbi.nlm.nih.gov/books/NBK555922/ [54] “Enzyme-linked immunosorbent assay (ELISA). Quantitative assay of immunoglobulin G - PubMed.” https://pubmed.ncbi.nlm.nih.gov/5135623/ (accessed Mar. 05, 2023). [55] J. C. Simpson, “Functional Assays,” in Encyclopedic Reference of Genomics and Proteomics in Molecular Medicine, Berlin, Heidelberg: Springer, 2006, pp. 617–620. doi: 10.1007/3-540-29623-9_3700. [56] P. K. Sen, “Biological Assay, Overview,” in Wiley StatsRef: Statistics Reference Online, John Wiley & Sons, Ltd, 2014. doi: 10.1002/9781118445112.stat07056. [57] N. Christofi, “BIOASSAYS | Microbial Tests,” in Encyclopedia of Analytical Science (Second Edition), P. Worsfold, A. Townshend, and C. Poole, Eds., Oxford: Elsevier, 2005, pp. 265–271. doi: 10.1016/B0-12-369397-7/00044-3. [58] C. S. Pierre et al., “A human tissue-based functional assay platform to evaluate the immune function impact of small molecule inhibitors that target the immune system,” PLOS ONE, vol. 12, no. 7, p. e0180870, Jul. 2017, doi: 10.1371/journal.pone.0180870. [59] N. Ganesan, S. Ronsmans, and P. Hoet, “Methods to Assess Proliferation of Stimulated Human Lymphocytes In Vitro: A Narrative Review,” Cells, vol. 12, no. 3, Art. no. 3, Jan. 2023, doi: 10.3390/cells12030386. [60] O. Rezahosseini et al., “Use of T Cell Mediated Immune Functional Assays for Adjustment of Immunosuppressive or Anti-infective Agents in Solid Organ Transplant Recipients: A Systematic Review,” Front. Immunol., vol. 11, p. 567715, Oct. 2020, doi: 10.3389/fimmu.2020.567715. 69 [61] N. T. Woods et al., “Functional assays provide a robust tool for the clinical annotation of genetic variants of uncertain significance,” Npj Genomic Med., vol. 1, no. 1, Art. no. 1, Mar. 2016, doi: 10.1038/npjgenmed.2016.1. [62] D. Di Blasi, I. Claessen, A. W. Turksma, J. van Beek, and A. ten Brinke, “Guidelines for analysis of low-frequency antigen-specific T cell results: Dye-based proliferation assay vs 3H-thymidine incorporation,” J. Immunol. Methods, vol. 487, p. 112907, Dec. 2020, doi: 10.1016/j.jim.2020.112907. [63] S. E. Hines, K. Pacheco, and L. A. Maier, “The role of lymphocyte proliferation tests in assessing occupational sensitization and disease,” Curr. Opin. Allergy Clin. Immunol., vol. 12, no. 2, pp. 102–110, Apr. 2012, doi: 10.1097/ACI.0b013e3283511396. [64] C. Cottle et al., “Impact of Cryopreservation and Freeze-Thawing on Therapeutic Properties of Mesenchymal Stromal/Stem Cells and Other Common Cellular Therapeutics,” Curr. Stem Cell Rep., vol. 8, no. 2, pp. 72–92, Jun. 2022, doi: 10.1007/s40778-022-00212-1. [65] G.-H. Kim et al., “High Integrity and Fidelity of Long-Term Cryopreserved Umbilical Cord Blood for Transplantation,” J. Clin. Med., vol. 10, no. 2, p. 293, Jan. 2021, doi: 10.3390/jcm10020293. [66] S. Yamanaka, “Pluripotent Stem Cell-Based Cell Therapy—Promise and Challenges,” Cell Stem Cell, vol. 27, no. 4, pp. 523–531, Oct. 2020, doi: 10.1016/j.stem.2020.09.014. [67] D. Ilic and C. Ogilvie, “Concise Review: Human Embryonic Stem Cells—What Have We Done? What Are We Doing? Where Are We Going?,” Stem Cells, vol. 35, no. 1, pp. 17–25, 2017, doi: 10.1002/stem.2450. [68] B. C. Heng et al., “Loss of viability during freeze-thaw of intact and adherent human embryonic stem cells with conventional slow-cooling protocols is predominantly due to apoptosis rather than cellular necrosis,” J. Biomed. Sci., vol. 13, no. 3, pp. 433–445, May 2006, doi: 10.1007/s11373-005-9051-9. [69] K. A. Murray and M. I. Gibson, “Chemical approaches to cryopreservation,” Nat. Rev. Chem., vol. 6, no. 8, Art. no. 8, Aug. 2022, doi: 10.1038/s41570-022-00407-4. [70] J. Baboo et al., “The Impact of Varying Cooling and Thawing Rates on the Quality of Cryopreserved Human Peripheral Blood T Cells,” Sci. Rep., vol. 9, no. 1, Art. no. 1, Mar. 2019, doi: 10.1038/s41598-019-39957-x. [71] D. Lysak et al., “Long-Term Cryopreservation Does Not Affect Quality of Peripheral Blood Stem Cell Grafts: A Comparative Study of Native, Short-Term and Long-Term Cryopreserved Haematopoietic Stem Cells,” Cell Transplant., vol. 30, p. 09636897211036004, Jan. 2021, doi: 10.1177/09636897211036004. [72] J. M. Baust, L. H. Campbell, and J. W. Harbell, “Best practices for cryopreserving, thawing, recovering, and assessing cells,” Vitro Cell. Dev. Biol. - Anim., vol. 53, no. 10, pp. 855–871, Dec. 2017, doi: 10.1007/s11626-017-0201-y. [73] Y. S. Heo et al., “‘Universal’ vitrification of cells by ultra-fast cooling,” Technology, vol. 3, no. 1, pp. 64–71, Mar. 2015, doi: 10.1142/S2339547815500053. [74] C. J. Hunt, “Cryopreservation: Vitrification and Controlled Rate Cooling,” in Stem Cell Banking: Concepts and Protocols, J. M. Crook and T. E. Ludwig, Eds., in Methods in Molecular Biology. New York, NY: Springer, 2017, pp. 41–77. doi: 10.1007/978-1-4939-6921-0_5. [75] J. Wang, G. Zhao, Z. Zhang, X. Xu, and X. He, “Magnetic induction heating of superparamagnetic nanoparticles during rewarming augments the recovery of hUCM-MSCs 70 cryopreserved by vitrification,” Acta Biomater., vol. 33, pp. 264–274, Mar. 2016, doi: 10.1016/j.actbio.2016.01.026. [76] J. G. Baust, K. K. Snyder, R. Van Buskirk, and J. M. Baust, “Integrating Molecular Control to Improve Cryopreservation Outcome,” Biopreservation Biobanking, vol. 15, no. 2, pp. 134–141, Apr. 2017, doi: 10.1089/bio.2016.0119. [77] S. R. Panch et al., “Effect of Cryopreservation on Autologous Chimeric Antigen Receptor T Cell Characteristics,” Mol. Ther., vol. 27, no. 7, pp. 1275–1285, Jul. 2019, doi: 10.1016/j.ymthe.2019.05.015. [78] J. G. Baust, D. Gao, and J. M. Baust, “Cryopreservation,” Organogenesis, vol. 5, no. 3, pp. 90–96, 2009. [79] J. M. Baust, Van Buskirk, and J. G. Baust, “Cell viability improves following inhibition of cryopreservation-induced apoptosis,” In Vitro Cell. Dev. Biol. Anim., vol. 36, no. 4, pp. 262–270, Apr. 2000, doi: 10.1290/1071-2690(2000)036<0262:cvifio>2.0.co;2. [80] P. J. Hanley, “Fresh versus Frozen: Effects of Cryopreservation on CAR T Cells,” Mol. Ther., vol. 27, no. 7, pp. 1213–1214, Jul. 2019, doi: 10.1016/j.ymthe.2019.06.001. [81] B. C. Heng, M. V. Clement, and T. Cao, “Caspase Inhibitor Z-VAD-FMK Enhances the Freeze-Thaw Survival Rate of Human Embryonic Stem Cells,” Biosci. Rep., vol. 27, no. 4, pp. 257–264, Oct. 2007, doi: 10.1007/s10540-007-9051-2. [82] Y. Luo, P. Wang, H. Liu, Z. Zhu, C. Li, and Y. Gao, “The state of T cells before cryopreservation: Effects on post-thaw proliferation and function,” Cryobiology, vol. 79, pp. 65–70, Dec. 2017, doi: 10.1016/j.cryobiol.2017.08.008. [83] B. Li et al., “Comprehensive evaluation of the effects of long-term cryopreservation on peripheral blood mononuclear cells using flow cytometry,” BMC Immunol., vol. 23, no. 1, p. 30, Jun. 2022, doi: 10.1186/s12865-022-00505-4. [84] A. Dreyzin et al., “Cryopreserved anti-CD22 and bispecific anti-CD19/22 CAR T cells are as effective as freshly infused cells,” Mol. Ther. - Methods Clin. Dev., vol. 28, pp. 51–61, Mar. 2023, doi: 10.1016/j.omtm.2022.12.004. [85] D. Kaiser et al., “Freezing Medium Containing 5% DMSO Enhances the Cell Viability and Recovery Rate After Cryopreservation of Regulatory T Cell Products ex vivo and in vivo,” Front. Cell Dev. Biol., vol. 9, 2021, Accessed: Jun. 23, 2023. [Online]. Available: https://www.frontiersin.org/articles/10.3389/fcell.2021.750286 [86] C. M. Hope et al., “Optimization of Blood Handling and Peripheral Blood Mononuclear Cell Cryopreservation of Low Cell Number Samples,” Int. J. Mol. Sci., vol. 22, no. 17, p. 9129, Aug. 2021, doi: 10.3390/ijms22179129. [87] M. Gunetti et al., “Refreezing of cord blood hematopoietic stem cells for allogenic transplantation: in vitro and in vivo validation of a clinical phase I/II protocol in European and Italian Good Manufacturing Practice conditions,” Exp. Hematol., vol. 36, no. 2, pp. 235–243, Feb. 2008, doi: 10.1016/j.exphem.2007.08.030. [88] Yu. A. Romanov, E. E. Balashova, N. E. Volgina, N. V. Kabaeva, T. N. Dugina, and G. T. Sukhikh, “Changes in Cell Composition of Umbilical Cord Blood and Functional Activity of Hematopoietic Stem Cells during Cryogenic Storage and Repeated Freezing/Thawing Cycles,” Bull. Exp. Biol. Med., vol. 160, no. 4, pp. 571–574, Feb. 2016, doi: 10.1007/s10517-016-3220-x. 71 [89] J. Wang, B. Yiu, J. Obermeyer, C. D. M. Filipe, J. D. Brennan, and R. Pelton, “Effects of temperature and relative humidity on the stability of paper-immobilized antibodies,” Biomacromolecules, vol. 13, no. 2, pp. 559–564, Feb. 2012, doi: 10.1021/bm2017405. [90] A. Grevys et al., “Antibody variable sequences have a pronounced effect on cellular transport and plasma half-life,” iScience, vol. 25, no. 2, p. 103746, Feb. 2022, doi: 10.1016/j.isci.2022.103746. [91] S. Kutscher et al., “Overnight Resting of PBMC Changes Functional Signatures of Antigen Specific T- Cell Responses: Impact for Immune Monitoring within Clinical Trials,” PLoS ONE, vol. 8, no. 10, 2013, doi: 10.1371/journal.pone.0076215. 72 Appendices Appendix A Sample calculations 1. Fold expansion: Fold expansion = [viable cell concentration][previous time point viable cell concentration][previous time point fold expansion] Fold expansion on day 5 = 4080000 𝑐𝑒𝑙𝑙𝑠/𝑚𝐿1180000 𝑐𝑒𝑙𝑙𝑠/𝑚𝐿∗ 2.368 = 8.152 2. Activity calculation: Activity = 𝑉𝑜𝑙𝑢𝑚𝑒 𝑜𝑓 𝑠𝑜𝑙𝑢𝑏𝑎𝑙𝑒 𝑎𝑐𝑡𝑖𝑣𝑎𝑡𝑜𝑟𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑒𝑙𝑙𝑠 Recommended activity by STEMCELL = 25 𝜇𝐿1000000 𝑐𝑒𝑙𝑙𝑠= 25 𝑝𝐿/𝑐𝑒𝑙𝑙 3. Cell counting using hemacytometer: Cell concentration = 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑒𝑙𝑙𝑠 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑠𝑞𝑢𝑎𝑟𝑒𝑠∗ 𝑑𝑖𝑙𝑢𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑖𝑜 ∗ 10000 Cell concentration of donor 1 at 50 µL aliquot = 1953 * 1 * 10000 = 650000 cells/mL 4. Recovery of the refrozen thaw: Recovery = 𝐶𝑜𝑛𝑐𝑒𝑛𝑡𝑟𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑣𝑖𝑎𝑏𝑙𝑒 𝑐𝑒𝑙𝑙𝑠 𝑎𝑓𝑡𝑒𝑟 𝑡ℎ𝑒 𝑟𝑒𝑓𝑟𝑜𝑧𝑒𝑛 𝑡ℎ𝑎𝑤𝐶𝑜𝑛𝑐𝑒𝑛𝑡𝑟𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑡ℎ𝑒 𝑣𝑖𝑎𝑏𝑙𝑒 𝑐𝑒𝑙𝑙𝑠 𝑎𝑓𝑡𝑒𝑟 𝑡ℎ𝑒 𝑓𝑖𝑟𝑠𝑡 𝑡ℎ𝑎𝑤∗ 100% Recovery of donor 1 at 50 µL aliquot = 650000 𝑐𝑒𝑙𝑙𝑠/𝑚𝐿653000 𝑐𝑒𝑙𝑙𝑠/𝑚𝐿∗ 100% = 99.5% 5. Activity estimation from cell diameter: Activity = 𝑓(𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑐𝑒𝑙𝑙 𝑑𝑖𝑎𝑚𝑒𝑡𝑒𝑟) ∗ 𝑑𝑖𝑙𝑢𝑡𝑖𝑜𝑛 f is a function of average cell diameter fitted to the standard curve Activity = (-163.4 + 62.29 * 8.21 -7.907*8.21^2 + 0.3365*8.21^3) pL/cell * 12 = 15.04 𝑝𝐿/𝑐𝑒𝑙𝑙 6. Percentage remaining activity: 73 Percentage remaining activity = 𝑒𝑠𝑡𝑖𝑚𝑎𝑡𝑒𝑑 𝑎𝑐𝑡𝑖𝑣𝑖𝑡𝑦𝐼𝑛𝑖𝑡𝑖𝑎𝑙 𝑎𝑐𝑡𝑖𝑣𝑖𝑡𝑦∗ 100% Percentage remaining activity = 15.04 𝑝𝐿/𝑐𝑒𝑙𝑙25 𝑝𝐿/𝑐𝑒𝑙𝑙∗ 100% = 60.2% 7. Cell specific activator consumption rate: Cell specific activator consumption rate = ∆𝐴𝑐𝑡𝑖𝑣𝑖𝑡𝑦 (𝑝𝐿𝑐𝑒𝑙𝑙)∗500000(𝑐𝑒𝑙𝑙𝑠𝑚𝐿)[𝑐𝑒𝑙𝑙]̅̅ ̅̅ ̅̅ ̅̅ (𝑐𝑒𝑙𝑙𝑠𝑚𝐿)∗∆𝑡𝑖𝑚𝑒 (𝑑𝑎𝑦) Cell specific activator consumption rate = (25−15.04)𝑝𝐿𝑐𝑒𝑙𝑙∗500000(𝑐𝑒𝑙𝑙𝑠𝑚𝐿)(500000+1960000)𝑐𝑒𝑙𝑙𝑠𝑚𝐿2∗3𝑑𝑎𝑦𝑠= 1.35𝑝𝐿𝑐𝑒𝑙𝑙∗𝑑𝑎𝑦 74 Appendix B Cell diameter distribution histogram of standard curve from CEDEX (screen shots) Figure 37. 0 pL/cell activator added. Figure 38. 0.25 pL/cell activator added. 75 Figure 39. 0.5 pL/cell activator added. Figure 40. 1 pL/cell activator added. 76 Figure 41. 1.5 pL/cell activator added. Figure 42. 2 pL/cell activator added. 77 Figure 43. 2.5 pL/cell activator added.
Thesis/Dissertation
eng
Biomedical Engineering
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Piret, James
Novel activity assay development for soluble T-cell activators in bioprocessing
Text