Medicine, Faculty of
Medicine, Department of
DSpace
UBCV
Ho, Chia Hao
Master of Science - MSc
University of British Columbia
The use of next-generation anti-androgens in the treatment of prostate cancer has led to an increase in therapy-induced neuroendocrine prostate cancer (t-NEPC). Recent studies have identified t-NEPC as a highly aggressive subtype of prostate cancer with poor survival rates. Our laboratory has recently demonstrated that the Lin28B, a core embryonic protein that suppresses the maturation process of the micro-RNA let-7, plays a crucial role in transforming adenocarcinoma prostate cancer (AdPC) into t-NEPC. Lin28B is an RNA-binding protein with two critical domains: the cold-shock domain (CSD) and the zinc-knuckle domain (ZKD). By utilizing both of CSD and ZKD domains, Lin28B protein can structurally binds to the microRNA let-7, which has been reported as a tumor suppressor and oncogene in NEPC, and inhibits its biosynthesis. Therefore, we hypothesize that blocking the interaction of CSD or ZKD with let-7 using a small molecule chemical may provide therapeutic opportunities to treat t-NEPC. In this study, we used a computer-aided drug design strategy to target Lin28B ZKD with small molecule inhibitors. We identified several inhibitors that effectively block Lin28B from binding to let-7 miRNA and restore let-7 biogenesis. Furthermore, we demonstrated that these inhibitors suppress the expression of stem-like pluripotency gene networks and neuroendocrine biomarkers. Lin28B inhibitors also reduces the expression of cancer stem cell surface markers such as CD44 and CD133. We also showed that these inhibitors suppress t-NEPC cell proliferation and clonogenic abilities. Overall, our study discovered several promising small molecules inhibitors of Lin28B that could be developed into potential drugs against NEPC.
DISCOVERY AND CHARACTERIZATION OF NOVEL LIN28 PROTEIN INHIBITORS SUPPRESS STEMNESS IN NEUROENDOCRINE PROSTATE CANCER by CHIA HAO HO B.Sc., University of Washington-Seattle, 2018 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Experimental Medicine) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) October 2023 © CHIA HAO HO, 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis entitled: DISCOVERY AND CHARACTERIZATION OF NOVEL LIN28 PROTEIN INHIBITORS SUPPRESS STEMNESS IN NEUROENDOCRINE PROSTATE CANCER Submitted by Chia Hao Ho in partial fulfillment of the requirements for the degree of Master of Science in Experimental Medicine Examining Committee: Xuesen Dong, Associate Professor, Urological Sciences, UBC Supervisor Artem Cherkasov, Professor, Urological Sciences, UBC Supervisory Committee Member Nada Lallous, Assistant Professor, Faculty of Medicine, UBC Supervisory Committee Member Colin Ross, Professor, Pharmaceutical Sciences, UBC Additional Examiner iii Abstract The use of next-generation anti-androgens in the treatment of prostate cancer has led to an increase in therapy-induced neuroendocrine prostate cancer (t-NEPC). Recent studies have identified t-NEPC as a highly aggressive subtype of prostate cancer with poor survival rates. Our laboratory has recently demonstrated that the Lin28B, a core embryonic protein that suppresses the maturation process of the micro-RNA let-7, plays a crucial role in transforming adenocarcinoma prostate cancer (AdPC) into t-NEPC. Lin28B is an RNA-binding protein with two critical domains: the cold-shock domain (CSD) and the zinc-knuckle domain (ZKD). By utilizing both of CSD and ZKD domains, Lin28B protein can structurally binds to the microRNA let-7, which has been reported as a tumor suppressor and oncogene in NEPC, and inhibits its biosynthesis. Therefore, we hypothesize that blocking the interaction of CSD or ZKD with let-7 using a small molecule chemical may provide therapeutic opportunities to treat t-NEPC. In this study, we used a computer-aided drug design strategy to target Lin28B ZKD with small molecule inhibitors. We identified several inhibitors that effectively block Lin28B from binding to let-7 miRNA and restore let-7 biogenesis. Furthermore, we demonstrated that these inhibitors suppress the expression of stem-like pluripotency gene networks and neuroendocrine biomarkers. Lin28B inhibitors also reduces the expression of cancer stem cell surface markers such as CD44 and CD133. We also showed that these inhibitors suppress t-NEPC cell proliferation and clonogenic abilities. Overall, our study discovered several promising small molecules inhibitors of Lin28B that could be developed into potential drugs against NEPC. iv Lay Summary According to cancer statistics, prostate cancer is the second most common cancer among males worldwide and the third leading cause of cancer-related deaths among Canadian males. Recent reports have revealed that after androgen deprivation therapy, tumors can recur and sometimes progress into an aggressive and lethal form called therapy-induced neuroendocrine prostate cancer (t-NEPC). Our lab has identified Lin28B as a key player in t-NEPC tumor development. Lin28B directly binds to the microRNA let-7d, which is an important cell differentiation regulator to protect the cell from uncontrolled growth, and downregulate it. This work reports on the design of small molecule inhibitors that interact with Lin28B and inhibit its binding to let-7d, thus restoring the microRNA expression level. We demonstrate that Lin28B inhibitors can slow t-NEPC tumor growth and are as such a potential therapeutic option for patients with lethal t-NEPC. v Preface Chapter 1: Figures 1.1 through 1.8 have been included with permission from the respective references. The introduction was initially drafted by me and received invaluable input from Dr. Lallous and Dr. Dong through continuous revisions. Chapter 2: The materials and methods detailed in this thesis were originated and compiled by me, and subsequently refined with the valuable insights of Dr. Lallous and Dr. Dong. The protein purification protocol was established by Dr. Lallous and Joseph. Additionally, Mariia Radaeva, from Dr. Cherkasov's lab, laid the foundation for the computer-aided drug discovery pipeline. All figures in this chapter were generated by me. Chapter 3, 4, 5, and the appendix: The computational work outlined in this thesis was executed by Mariia Radaeva. The experiment design, results, analysis, and figures were all curated and analyzed by me. Our collaborative effort resulted in the publication of our work (Ho, C. H., Radaeva, Xie, N., Zhang, S., Lee, J., Liu, L., Lallous, N., Cherkasov, A., & Dong, X. "Discovery of Novel Lin28 Inhibitors to Suppress Cancer Cell Stemness." Cancers, 14(22), 5687. 2022). In this publication, I generated the raw experimental data, conducted the analysis, and co-authored the draft with Mariia. Dr. Dong played a crucial role in experiment design, draft revision, and manuscript submission. Other members listed in the publication provided technical supports. vi Table of Contents Abstract ................................................................................................................................. iii Lay Summary ......................................................................................................................... iv Preface ................................................................................................................................... v Table of Contents ................................................................................................................... vi List of Tables ........................................................................................................................ viii List of Figures ......................................................................................................................... ix List of Abbreviations .............................................................................................................. xi Acknowledgements .............................................................................................................. xiv Dedication ........................................................................................................................... xvi Chapter 1: Introduction ........................................................................................................... 1 1.1 Prostate Cancer .......................................................................................................................... 1 1.1.1 Overview .............................................................................................................................................. 1 1.1.2 The Prostate ......................................................................................................................................... 1 1.1.3 Prostate cancer .......................................................................................................................................... 4 1.2 Castration Resistant Prostate Cancer (CRPC) .............................................................................. 7 1.3 Treatment-induced Neuroendocrine Prostate Cancer (t-NEPC) ................................................. 10 1.3.1 Clinical Difficulties associated with t-NEPC treatments ......................................................................... 12 1.3.2 T-NEPC tumor is derived from AdPC ....................................................................................................... 13 1.3.3 t-NEPC Cell Plasticity and Neuroendocrine Differentiation ................................................................... 14 1.4 Lin28B/let-7 Pathway ............................................................................................................... 19 1.4.1 Lin28B Gene and Protein Structure ......................................................................................................... 19 1.4.2 Lin28B Biological Function in Embryogenesis ......................................................................................... 22 1.4.3 Lin28B Stemness and Pluripotency ......................................................................................................... 24 1.4.4 Lin28-Mediated Metabolism ................................................................................................................... 25 1.4.5 MicroRNA ................................................................................................................................................. 26 1.4.6 Let-7 microRNA Family ............................................................................................................................ 28 1.5 Lin28B protein and Let-7 miRNA ............................................................................................... 31 1.5.1 Lin28B Block Biogenesis of Let-7 MicroRNA ........................................................................................... 31 1.5.2 Lin28B/Let-7 miRNA in Prostate Cancer ................................................................................................. 33 1.5.3 Lin28B Domain Structure and ZKD-Lin28B as a therapeutic Target in Cancer ....................................... 35 1.6 Hypothesis ............................................................................................................................... 36 Chapter 2: Materials and Methods ........................................................................................ 37 2.1 Cell Lines and Cell Culture Maintenance ................................................................................... 37 2.2 ZKD-Lin28B Inhibitors Drug Designed ....................................................................................... 37 2.3 Lin28B Protein Purification Process (In collaboration with Lallous lab) .................................... 38 2.3.1 Transformation of Lin28B into BL21 (DE3) ............................................................................................... 38 2.3.2 Protein Expression of Lin28B in BL21 (DE3) cells ..................................................................................... 39 vii 2.3.3 Protein Purification using Nickel-NTA column. ........................................................................................ 40 2.4 Fluorescence Polarization Assay ............................................................................................... 42 2.5 Electrophoretic Mobility Shift Assay (EMSA) ............................................................................ 49 2.6 Bio-Layer Interferometry Assay (BLI) ........................................................................................ 51 2.7 Real-time Quantitative Polymerase Chain Reactions (RT-qPCR) ................................................ 52 2.8 Flow Cytometry and Fluorescence-Activated Cell Sorting (FACS) .............................................. 55 2.9 Western Blot ............................................................................................................................ 57 2.10 Cell Proliferation Assay .......................................................................................................... 59 2.10.1 CellTiter 96® Aqueous One solution ....................................................................................................... 59 2.10.2 Incucyte® Cell Proliferation Assay .......................................................................................................... 60 2.11 Colony Formation Assay ......................................................................................................... 60 2.12 Microsomal and Solubility Assay ............................................................................................ 61 2.13 Statistics ................................................................................................................................ 62 Chapter 3: Result .................................................................................................................. 64 3.1 Identification of a Novel Docking Pocket for Lin28B Binders ..................................................... 64 3.2 Establishment of the Fluorescence Polarization Assay to Screen ZKD-Lin28B Inhibitors ............ 68 3.3 Established FP Assay on Raw Screening of Ln1 – Ln193, ZKD-Lin28B Protein Inhibitors. ............ 71 3.4 Electrophoresis Mobility Shift Assay (EMSA) and FP Titration Demonstrate ZKD-Lin28B Inhibitors Block the Interaction of ZKD-Lin28B and pre-let-7d. ....................................................................... 74 3.5 Bio-Layer Interferometry (BLI) Assays to Validate the Selected Inhibitors ................................. 77 3.6 Selected Lin28B Inhibitors Block Both Lin28A and Lin28B Protein Isoforms. ............................. 79 3.7 Selected ZKD-Lin28B Inhibitors Regulate the Let-7d Expression and Block Lin28B Functions in t-NEPC Cancer Cells. ......................................................................................................................... 81 3.8 Selected ZKD-Lin28B Inhibitors Regulate Cancer Stem-cell (CSC) and Neuroendocrine (NE) Biomarkers Expression in t-NEPC Cell Line. .................................................................................... 84 3.9 Selected ZKD-Lin28B Inhibitors Suppress the DuNE Cancer Cell Stemness Phenotypes. ............ 86 3.10 Solubility and Microsomal Stability of Selected Compounds ................................................... 90 Chapter 4: Discussion ............................................................................................................ 92 Chapter 5: Limitation and Future Direction ........................................................................... 95 References ............................................................................................................................ 96 Appendix: Supplementary Figures ....................................................................................... 135 viii List of Tables Table 1. 1 Alteration in gene expression (approximate %) in therapy-induced neuroendocrine prostate cancer (t-NEPC). ............................................................................................................. 12 Table 2. 1 Real time-qPCR Primer Information. ............................................................................ 54 Table 2. 2 Antibody List. ............................................................................................................... 58 Table 3. 1 Microsomal Stability and Solubility Assay of selected compounds. ............................ 91 ix List of Figures Figure 1. 1 The anatomy graphs of the location and the architecture blocks of the human prostate gland. ............................................................................................................................... 3 Figure 1. 2 Androgen receptor-dependent mechanisms of resistance in hormone-naive prostate cancer leading to castration-resistance. ......................................................................................... 8 Figure 1. 3 Mechanisms of neuroendocrine differentiation in response to androgen receptor pathway inhibitors. ....................................................................................................................... 15 Figure 1. 4 Schematic of human Lin28A and Lin28B proteins. ..................................................... 20 Figure 1. 5 The Lin28A and Lin28B/let-7 miRNA axis has important biological functions. ........... 24 Figure 1. 6 miRNA transcription and mechanism of action. ......................................................... 27 Figure 1. 7 Sequence comparison of let-7 family members across diverse animal species. ........ 30 Figure 1. 8 Lin28B/let-7 regulatory axis. ....................................................................................... 33 Figure 2. 1 FP assays demonstration of the binding of pre-let-7d-FAM probe with Lin28B protein and the FP signal changed due to the rotational speed difference. ............................................. 43 Figure 2. 2 Titration of the probe (pre-let-7d-FAM) with fixed concentration of protein (Lin28B 10 µM). ......................................................................................................................................... 45 Figure 2. 3 Titration of the protein (Lin28B) with fixed concentration of the probe (pre-let-7d-FAM 1nM). .................................................................................................................................... 46 Figure 2. 4 FP competition assay using the 1 nM of probe (pre-let-7d-FAM) with 10 µM of protein (Lin28B) and titrating with non-labeled probe (pre-let-7d). ............................................ 47 Figure 3. 1 Computer-aided drug design (CADD) of ZKD-Lin28B protein inhibitors. .................... 67 Figure 3. 2 Establishment of the Fluorescence Polarization Assay. .............................................. 70 x Figure 3. 3 Fluorescence Polarization Assay for Raw Inhibitors screening on Lin28B Protein. .... 73 Figure 3. 4 Direct binding assays and FP dose-dependent assays of the three selected compounds. .................................................................................................................................. 76 Figure 3. 5 Bio-laryer interferometry (BLI) assay of Ln115 with ZKD-Lin28B. ............................... 78 Figure 3. 6 Direct binding EMSA assays and FP dose-dependent assays of the three selected compounds. .................................................................................................................................. 80 Figure 3. 7 RT-qPCR on Ln7, Ln15, and Ln115 to restore miRNA let-7d expression levels and decrease expression of SOX2 and HMGA2 genes. ........................................................................ 83 Figure 3. 8 Potential ZKD-Lin28B inhibitors regulate cancer stem cell and neuroendocrine biomarkers in DUNE cell line. ....................................................................................................... 85 Figure 3. 9 The ZKD-Lin28B inhibitors suppress cancer stem cell phenotypes of cancer cells. .... 88 Figure S. 1 Establishment of the Fluorescence Polarization Assay using Lin28A protein. .......... 135 Figure S. 2 FP Titration Assay of the Potential Compounds. ...................................................... 136 Figure S. 3 EMSA assay of the non-selected compounds ........................................................... 137 Figure S. 4 Selected ZKD-Lin28B inhibitors regulate protein expression level of SOX2 and HMGA2. ...................................................................................................................................... 138 Figure S. 5 Colony Formation Assays on DuNE and DuNELin28BKO cell lines treated with selected inhibitors. ..................................................................................................................... 139 Figure S. 6 Final Purification of ZKD-Lin28B (15kDa) on the 18% SDS-PAGE. ............................. 141 Figure S. 7 Final Purification of Full-Length Lin28B (28kDa) on the 18% SDS-PAGE ................... 141 xi List of Abbreviations 6-FAM 7-AAD ABI 6-Carboxyfluorescein 7-Aminoactinomycin D Abiraterone AUA AUKRA American Urological Association Aurora Kinase-A AMA American Medical Association AR Androgen receptor ARPI Androgen receptor pathway inhibition ATCC CADD American Type Culture Collection Computer Aided Drug Design CCHC Cysteine cysteine histidine cysteine CHGA Chromogranin A CRPC Castration-resistant prostate cancer CRPC-Ad Castration-resistant prostate adenocarcinoma CSC Cancer stem cell CSD Cold shock domain CSS Charcoal stripped serum CZ Central zone DKO Double knockout DMEM DMRT DHT DHEA Dulbecco's Modified Eagle Medium Doublesex And Mab-3 Related Transcription Factor 1 Dihydrotesterone Dehydroepiandrosterone DTT Dithiothreitol EAU European Association of Urology EDTA Ethylenediaminetetraacetic acid EMT Epithelial-mesenchymal transition ESC Embryonic stem cell FACS Fluorescence-activated cell sorter FBS Fetal bovine serum FGF Fibroblast growth factor GEMM Genetically engineered mouse model GO GR Gene oncology Glucocorticoid Receptors GSEA Gene set enrichment analysis HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid IF Immunofluorescence IGF2 Insulin-like growth factor 2 xii iPSCs LBD Induced pluripotent stem cells Ligand binding domain LET-7 Lethal-7 LIN28A LIN-28 homolog A LIN28B LIN-28 homolog B MAPK Mitogen-activated protein kinase miRNA microRNA mRNA mTOR Messenger RNA Mechanistic Target Of Rapamycin Kinase NANOG Nanog Homeobox NCP Nucleocapsid protein NE NED Neuroendocrine Neuroendocrine differentiation NEdT Neuroendocrine transdifferentiation NEPC Neuroendocrine prostate cancer NLS Nuclear localization signal NoLS Nucleolar localization signal NTD N- terminal domain PCa Prostate cancer PSA PSC Prostate specific antigen Pluripotent Stem Cells PVDF Polyvinylidene difluoride qPCR Quantitative polymerase chain reaction RB1 Retinoblastoma 1 RNA Ribonucleic acid RPMI-1640 Roswell Park Memorial Institute 1640 SC Stem cell Spg-let-7 let-7 SPONGE SRY Sex determining region Y SYP Synaptophysin TBS-T Tris-buffered saline plus TWEEN-20 TKO Triple knockout TUT Terminal Uridyl Transferase t-NEPC Treatment-induced neuroendocrine prostate cancer TP53 Tumor protein 53 TUT4 Terminal uridyl transferase 4 TUT7 Terminal uridyl transferase 7 UGE UTR Urogenital Sinus Epithelium Untranslated Regtion VPC Vancouver Prostate Centre xiii WT Wild type xiv Acknowledgements First, I would like to give my best appreciation to my supervisor, Dr. Xuesen Dong, for helping me complete my graduate studies. Studying and experiencing this lab has been an unforgettable memory for me. Your mentorship and critical thinking advice have always been indispensable, and I appreciate all the challenges and thinking you have given me over the last three years. I learned a lot from you, especially the attitude of how to perform science and think as a research scientist. I could only have completed this project with help from Dr. Art Cherkasov and Dr. Nada Lallous, my supervisory committee members. Thank you for your advice, encouragement, and suggestions during my graduate study at the Vancouver Prostate Centre. Dr. Steven Pelech, whom I enrolled in his MEDI class, inspired me with different ideas relating to my project. Thank you so much for the opportunity of doing a rotation in your lab and join some exciting experiments with your team. I would also like to give a massive thanks to Mariia Radaeva from Dr. Art Cherkasov’s lab, who not only established the CADD pipeline to predict small molecule inhibitors but also helped me discover the potential drug candidates for my project and publications. I may not have finished this project without the assistance of Ms. Ning Xie, who provided so much insight into managing a good experiment technique. Mr. Joseph Lee helped me purify the protein samples for this project. Jessica Lovnicki and Ahn Lee trained me to learn and gain all the assays and protocols step by step and showed me the passionate attitude of doing science. Finally, Victor, I would like to thank you for being so lovely to me and providing me with so much help during these years. Without your support and encouragement, I could never complete this. xv I also want to thank my parents for giving me this opportunity to study abroad and for all of the encouragement and help you have provided. Thank you all. xvi Dedication Dreams and Dedication are a powerful combination You dream You plan You do And You succeed 1 Chapter 1: Introduction 1.1 Prostate Cancer 1.1.1 Overview Prostate cancer accounts for more than 20% of new cancer cases among men, making it a significant public health concern (1). It is the second leading cause of cancer-related deaths in men, responsible for 11% of deaths, only after lung and bronchus cancer. The number of cases is projected to increase from 24,000 in Canada in 2015 to 42,000 by 2032 due to the aging population (4). The introduction of prostate-specific antigen (PSA) testing in the United States in the 1990s led to a 40% decline in prostate cancer mortality rates between 1992 and 2007. However, over 10% of Canadian men are still expected to be diagnosed with prostate cancer in their lifetime, with direct medical costs estimated to be $9.76 billion (3). The financial burden and medical expense can adversely affect the quality of life of patients and their families. While advancements in diagnosis and treatment helped reduce mortality rates, the recurrence of prostate cancer tumors remains a significant challenge for modern medicine. Therefore, understanding the mechanisms of prostate cancer progression and the reasons for recurrence are crucial in developing new treatments for the patients (2). 1.1.2 The Prostate The human prostate gland, shaped like a walnut, develops from the embryonic urogenital sinus and primarily produces fluid containing different enzymes and proteins, including prostate-specific antigen (PSA), a protease that indicates prostate cancer risk (5). Prostate gland formation 2 begins with epithelial budding during embryogenesis (6). Figure 1.1 depicts the inside structure of the prostate gland and its various types of cells. It is believed that the initiation of sexual differentiation is regulated solely by the presence or absence of sex-determining region of the Y chromosome (SRY) (7). Experimental and clinical studies have reported that the SRY gene is the decision-making gene for the testis-determining factor (8,9). The urogenital ridges serve as the shared precursors for the urinary and genital systems. During human development, they emerge on the ventral surface of the cranial mesonephric in the fourth week post-fertilization. They are formed by intermediate mesoderm covered by coelomic epithelium. In the meantime, a pattern of gene expression that is listed in Table 3 of the "Sexual Differentiation" publication (Rey et al., 2020) participates in the development of the whole genital system, turning mesonephros into the gonadal ridge, which is the dividing point between the ovary or testis. After three weeks, the SRY gene expresses which turns the undifferentiated gonadal ridge into a testis in the XY embryo. The gonadal cells are separated into two compartments forming the testicular cords and the interstitial tissue. The testicular cords consist of somatic Sertoli cells and germ cells surrounded by a basal membrane and peritubular cells (7). Leydig cells inside the testis are responsible for testosterone production after the 9th week of gestation. Under the pulsatile control of pituitary luteinizing hormone, testosterone binds to the androgen receptor in Wolffian ducts and promotes the male gonaducts differentiation process (10-12). Testosterone is then converted into dihydrotestosterone (DHT) by the enzyme 5-alpha-reductase, which has a higher affinity to the androgen receptor, driving male differentiation of the urogenital sinus (UGS) and external genitalia (10,11). The development of the prostate can be divided into several stages. The first stage is the pre-bud stage of UGS, around 8-9 weeks of 3 human embryogenesis follow by the initial budding stage which occurs around 10-11 weeks, with the appearance of solid prostatic epithelial buds from the urogenital sinus epithelium (UGE). The third stage after the initial budding is the bud elongation, branching and canalization. These three steps are concurrent processes that take place over several weeks, commencing at approximately 12 weeks of gestation. Research indicates that ductal branching patterns vary among individual human prostatic "lobes." The final stage is the secretory cytodifferentiation, resulting in a well-formed prostate (12). The development of all prostate glands in various species depends on androgens and androgen receptors (AR) including human prostate gland. Studies have shown that the presence of AR in various stages of human prostatic development is crucial (13). Figure 1. 1 The anatomy graphs of the location and the architecture blocks of the human prostate gland. The Prostate gland has three different zones, central, transition, and peripheral zone. Histologically, it is comprised of luminal, basal, and few intermediate cells and neuroendocrine cells. The basement membrane separates the stromal cells and the epithelial surface. Reports stated that preneoplastic or neoplastic cellular transformation can initiate from either basal cell or luminal cells. Original drawing adapted from https://www.mdpi.com/2072-6694/12/9/2651/htm 4 1.1.3 Prostate cancer Prostate cancer has become a significant health concern for men worldwide, as discussed in the overview (14). The most common screening method for prostate cancer is the serum prostate-specific antigen (PSA) test. PSA, a glycoprotein produced in the prostate gland, is responsible for nourishing and transporting sperm. Early detection through PSA testing can lead to better treatment options and reduced overall mortality rates. However, there is ongoing debate regarding the benefits and harms of this screening method (15, 16). While there is no direct evidence that PSA screening significantly saves more lives among men, recent research has shown that overdiagnosis and overtreatment are prevalent outcomes (17-20). Although the relationship between prostate cancer mortality rates and PSA tests remains controversial, older men are at a higher risk of developing and progressing to aggressive forms of prostate cancer. Studies have shown that the incidence rate of prostate cancer increases with age, particularly after the age of 65 (21). However, most research focuses on men younger than 75 years, leading the US Preventive Services Task Force (USPSTF) to recommend against PSA screening for men aged 75 years or older (22). Race, geography, socioeconomic status, and ethnicity are all variables that can significantly impact prostate cancer outcomes. For example, African America men in the United States have higher incidence and mortality rates of prostate cancer than white males (23). Access to proper medical care is also a crucial factor that is widely affected by geography and socioeconomic stage (24). Additionally, having a family history of prostate cancer may increase an individual's chance of developing the disease, and the degree of relatedness can also affect the incidence rate (25-27). 5 Recently, dietary patterns were associated with cancer incidence due to changing lifestyles and improved economic status. The Western dietary pattern, characterized by high consumption of processed foods, meats, and fats, and low intake of fruits and vegetables, has been linked to a higher risk of cancer incidence (28). A case-control study identified that Western and Mediterranean dietary patterns have different impacts on the risk of prostate cancer, with the Mediterranean dietary style being more beneficial in reducing the risk (29). Another case-control study conducted in Argentina found that high adherence to traditional and carbohydrate-rich dietary would increase prostate cancer incidence, while diets rich in whole grains, non-starchy vegetables, and cheese diets were associated with a lower risk (30). However, further research is still needed to understand the pathways and mechanisms behind these specific foods and the development of prostate cancer. Prostate cancer cells have the remarkable ability to replicate without restriction, evade apoptosis mechanisms, attack surrounding tissues, and spread throughout the body without limitation. During the early stages of tumor development, there are usually no significant symptoms as the gland has not yet grown enough to cause discomfort. However, as the tumor grows, symptoms such as difficulty in urinating, blood in the urine, constant pain or stiffness (around the hip, back, and chest), and fatigue may appear (31). Nowadays, PSA tests and digital rectal examinations can detect early signs of prostate cancer (31, 33). Elevated PSA levels were previously hypothesized to result from the prostate gland's destruction, releasing PSA into circulation (33, 34). However, high PSA levels are not always indicative of prostate cancer development, as physical stress, localized infections, and other factors can also increase PSA levels in the circulation. In modern medications, if prostate cancer 6 is suspected, both the European Association of Urology (EAU) and the American Urological Association recommend a prostate biopsy for confirmation (33, 34). Instead of normal biopsy, liquid biopsies, which provide information about the tumor's immune response and gene expression profile, are becoming more common worldwide and offer less invasive alternatives to traditional biopsies (35). The Gleason grading system is a significant prognostic tool for determining therapy decisions (41). Several revisions to the Gleason system have been made in recent years to improve its prognostic value (36, 37). The International Society of Urological Pathology (ISUP) has proposed a new grading system that has been incorporated into the 2016 edition of the WHO classification of Tumors of the Urinary System and Male Genital Organs (36-38). The ISUP Grade Groups establish five distinct Grade Groups based on Gleason scores: Grade Group 1 (Gleason score 3+3=6) for well-differentiated, less aggressive, and slower-growing tumor tissue; Grade Group 2 and 3 (Gleason score 3+4 or 4+3=7) for moderately differentiated, moderately aggressive tumor tissue likely to grow but may not spread quickly; and Grade Group 4-6 (Gleason score 8-10) for poorly differentiated or undifferentiated, highly aggressive tumor tissue that is likely to grow faster and spread (39, 40). For the high-grade prostate cancer patients (Gleason score greater than or equal to 8), radiation therapy with neoadjuvant androgen deprivation therapy or radical prostatectomy with salvage radiation therapy is recommended by the American Medical Association (AMA) and the EAU (36, 43). The report suggested combining multiple therapies is more beneficial in the case of high-risk prostate cancer (41). Despite the success of surgery and radiation therapy in treating most localized prostate cancers, some patients will still develop advanced prostate cancer or more aggressive subtypes within five years of these procedures (44, 7 45). Increasing PSA levels, tumor growth, and cancer cell metastasis are signs of prostate cancer recurrence following radical prostatectomy. Androgen receptor pathway inhibition (ARPI) is the first-line treatment for locally advanced, chronic, and metastatic prostate cancer (36, 46-48). ARPI treatment directly inhibits the androgen synthesis and the androgen binding to the AR ligand-binding domain to achieve surgical or medicinal castration (49-52). Unfortunately, most patients with metastatic prostate cancer treated with ARPI will develop castration-resistant prostate cancer (CRPC) within two to three years (51). 1.2 Castration Resistant Prostate Cancer (CRPC) As previously discussed, patients receiving androgen receptor pathway inhibitor (ARPI) treatment will still experience tumour recurrence and progress to castration resistant prostate cancer (CRPC). The average survival time for patients with CRPC is between 18 to 24 months (53). Treatments of CRPC comprise anti-androgen drugs (e.g. enzalutamide (278), darolutamide (279), apalutamide (280), proxalutamide (281) and rezvilutamide (282)), androgen synthesis inhibitor (e.g. abiraterone (283), ketoconazole (284) and aminoglutethimide (285)), or chemotherapeutic drugs (e.g. docetaxel (286) and cabazitaxel (287)) (54,264). Furthermore, CRPC can either be driven by AR-dependent or AR-independent pathways (265). Almost all the mechanisms that 8 contribute to castration resistance are linked to AR or the androgen axis, as depicted in Figure 1.2. wtAR, wild-type androgen receptor; ARV, androgen receptor variant; mutAR, mutated androgen receptor; T, testosterone; DHT, dihydrotestosterone; SHGB, sex hormone binding globulin. Original figure adapted from Chandrasekar, T., Yang, J. C., Gao, A. C., & Evans, C. P. (2015). Mechanisms of resistance in castration-resistant prostate cancer (CRPC).https://doi.org/10.3978/j.issn.2223-4683.2015.05.02 Permission of republished from publisher. The first subset is the ligand-dependent pathway, where androgen deprivation therapy (ADT) reduces androgen levels but low androgen levels persist. Prostate cancer cells in this microenvironment become sensitive to low levels of androgens through either amplification of the AR signal (called the AR amplification pathway) (56) or mutation of the AR, which allows its Figure 1. 2 Androgen receptor-dependent mechanisms of resistance in hormone-naive prostate cancer leading to castration-resistance. 9 activation by molecules other than androgen (promiscuous pathway) (57, 58). This amplification enables CRPC to respond to low androgen levels and promotes tumour progression (57, 59). The second and the third subset are the ligand-independent pathway, where under normal conditions, the AR recruits a series of coregulators that either activate or repress transcriptional activity. These coregulators such as kinases, methylases, acetylases, ubiquitylating enzymes, RNA splicing regulators, and molecular chaperones may promote or inhibit the transcriptional machinery (60-62). Many of these coregulators interact with AR eventually but have an AR-independent effect. Moreover, CRPC reduces some expression level of repressor proteins (55), contributing to castration resistance regardless of the presence of ligands. Furthermore, a few in vitro studies and reports suggest that multiple growth factors, cytokines, and kinase pathways increase AR signalling in a ligand-independent manner, thereby contributing to the progression of castration resistance (63). Identifying and characterizing these ligand-independent pathways may help in developing additional targeted therapies. In the fourth subset, CRPC still develops despite castrate-levels of circulating androgens. However, studies have revealed that intra-tumoral levels of androgens in CRPC models are equivalent to or even higher than those found in eugonadal men, indicating the presence of alternative androgen production pathways (64-66). There may be an adrenal component to these findings, specifically the production of androgen precursors such as dehydroepiandrosterone (DHEA) and its sulphated derivative (DHEA-S), which use a “backdoor” pathway to convert DHEA into highly active DHT which will bind to AR and promote AR signaling (67). 10 Finally, the fifth subset pathway reports the identification of AR variants (AR-Vs) that lack the C-terminal ligand-binding-domain (LBD), resulting in constitutively active variants. The amplification of AR observed in CRPC might play a role in developing these splice variants (55). From a treatment perspective, the number of therapies available for patients with CRPC has increased, including new medications such as abiraterone (ABI), enzalutamide, and recently FDA approved apalutamide (68-70,280,288). For example, the overall survival rate of patients treated with apalutamide has improved significantly from 73.5% to 82.4% compared to placebo group (288). However, resistance still occurs due to heterogeneous molecular mechanisms, including AR bypass signalling or complete AR independence such neuroendocrine differentiation (NED) (71,72). NED has been identified as a trans-differentiation process which causes phenotypic change of the prostate cancer cells into neuroendocrine-like (NE-like) cells (73). NE-like cells lack the expression of AR and PSA and are resistant to ARPI treatments (273). So, the treatment pressure by AR pathway inhibitors can convert prostate cancer cells into AR-independent variants such as treatment-induced neuroendocrine prostate cancer (t-NEPC) (74). 1.3 Treatment-induced Neuroendocrine Prostate Cancer (t-NEPC) Although de novo NEPC is a rare variant of prostate cancer, accounting for only 0.5% to 2% of all cases (75), treatment-induced NEPC is still a significant clinical problem affecting 16-25% of patients with advanced-stage prostate cancer (76,77). It's important to note that t-NEPCs are distinct from de novo NEPCs, as patients with treatment-induced tumors typically have a history of typical prostate adenocarcinoma and have been treated with ARPI one or more times (78). While ADT remains the standard of care for metastatic prostate cancer, most patients 11 relapse to an advanced form of the disease under CRPC after the initial response to ADT has worn off (80,81). The discovery and development of enzalutamide and abiraterone have led to the next generation of ADT treatments. Long-term and repeated ADT treatments (such as androgen inhibitors, enzalutamide, and androgen synthesis inhibitors like abiraterone) have been shown to promote CRPC progression to neuroendocrine differentiation (NED), commonly known as CRPC-NE or t-NEPC (79,82,83). Moreover, genetic reprogramming and cell plasticity can promote neuroendocrine phenotypes that are resistant to ADT by promoting stem-like characteristics. Radiation therapy has also been reported to induce resistance to ADT and the differentiation of NE cells (84). Table 1.1 shows the extent to which gene expression is altered in t-NEPC (84). This genetic change will have a huge impact on clinical perspectives not only on diagnosis but also increase the difficulty of the drug development. Gene Case % Status v-myc avian myelocytomatosis viral related oncogene, Neuroblastoma-derived (MYCN) 40% Up-regulated Aurora Kinase A (AURKA) 40% Up-regulated Serine/arginine repetitive matrix 4 (SRRM4) ~50% Up-regulated 12 Gene Case % Status AKT Serine/Threonine Kinase 1 (AKT1) 28% Up-regulated CYCLIN D1 (CCND1) 88% Loss Retinoblastoma Protein 1(RB1) 70–90% Loss Phosphatase and tensin homolog (PTEN) 90% Loss Tumor suppressor protein p53 (TP53) 56–67% Loss or Mutation Table 1. 1 Alteration in gene expression (approximate %) in therapy-induced neuroendocrine prostate cancer (t-NEPC). Original table data acquired from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6826557/ 1.3.1 Clinical Difficulties associated with t-NEPC treatments Currently, the lack of a uniform consensus definition and universal biomarkers makes prognosis of the t-NEPC extremely hard. In order to validate the presence of t-NEPC in patients, analysis of tumor histological features and tissue biopsies to evaluate the expression of NE markers are needed. However, there are no guidelines or standards for when and where to do the biopsy on patients who are suspected to have t-NEPC (268). Additionally, t-NEPC has been 13 observed to have a high spreading rate in the patient's body, leading to a significant decrease in median survival time to 7 months upon confirmation of the diagnosis (268). The growing clinical burden of t-NEPC subtypes is partly due to the absence of a proper gold standard for screening them. NE markers, including synaptophysin (SYP), chromogranin A (CHGA), chromogranin B (CHGB), CD56, and neuron-specific enolase (NSE), are the only few biomarkers that are currently available for the early detection of NEPCs (86). A recent study found that positive expression of NE biomarkers was present in 90% of the t-NEPC cases. In conclusion, the existing clinical evidence and research indicate the need for more precise and efficient methods to diagnose t-NEPC and establish additional biomarkers for the AR/PSA negative subtype of prostate cancer, ultimately improving diagnostic capabilities. 1.3.2 T-NEPC tumor is derived from AdPC Although NEPC is known to originate from the prostate, the exact mechanism by which it develops is still unknown. Several hypotheses suggest that t-NEPC arises from benign prostatic neuroendocrine cells that acquire tumorigenic properties. Adenocarcinoma of the prostate cells can differentiate and become NEPC, leading to the development of t-NEPC tumors due to ADT or other hormonal treatments. T-NEPC can also acquire stem-like cell characteristics that enable cancer cells to maintain their ability to self-renew, invade, and resist apoptosis under multiple hormone-mediated therapies. This process, known as lineage plasticity, can facilitate the development of mechanisms of therapeutic resistance and tumor cell heterogeneity (88-92). 14 1.3.3 t-NEPC Cell Plasticity and Neuroendocrine Differentiation The phenomenon of lineage plasticity, which refers to cells’ capacity to shift from one predetermined developmental pathway to another, has been suggested as a potential contributor to intratumoral heterogeneity and tumor adaptation in the presence of unfavorable tumor microenvironments, such as exposure to targeted anticancer therapies (275). Researchers have reached a consensus that lineage plasticity contributes to the acquisition of the cancer stem cells (CSC) phenotype. While no direct evidence supports the hypothesis that NEPC arises from the expansion of resident CSCs or neuroendocrine cells within a heterogeneous tumour, recent studies have shown that acute ADT drives neuroendocrine trans-differentiation via a metastable stem-like state. Upon re-exposure to androgens, reprogrammed CSCs can return to an AR-driven state, highlighting the bidirectional plasticity of these cells (82). However, a recent study analyzing genetic cell lineage tracing - the gold standard for in vivo phenotypic analysis - reported that neuroendocrine differentiation may occur in prostate cancer through trans-differentiation of luminal tumour cells (92, 93) (Figure 1.3). Figure 1.3A demonstrates the effectiveness of ARPI treatment in the hierarchical model, where it successfully inhibits transformed luminal epithelial cells driven by AR, leading to a reduction in tumor size. Nevertheless, ARPI does not have the same inhibitory effect on AR-independent cells like cancer stem-like cells or neuroendocrine cells. This allows cancer stem-like cells to continue growing and differentiate into neuroendocrine cells. Another pathway involves normal neuroendocrine cells acquiring mutations and transforming into malignant NEPC. In Figure 1.3B, the dynamic transdifferentiation model illustrates that trans-differentiation takes place when cells undergo a partial epithelial-mesenchymal transition (EMT). This process can advance through transient pluripotent and stem-like states, eventually giving 15 rise to cancer stem cells (CSCs). The extent of adenocarcinoma to neuroendocrine trans-differentiation varies, indicated by red representing high levels of migration, invasion, and therapy resistance. Therefore, while the exact mechanism of NEPC emergence is not yet fully understood, it is clear that lineage plasticity plays a significant role in the development of NEPC. Figure 1. 3 Mechanisms of neuroendocrine differentiation in response to androgen receptor pathway inhibitors. (A) In the hierarchical model, tumors are heterogeneous, which means the tumor itself contains different mixture of cells whose stemness and/or proliferative ability varies. (B) Dynamic trans-differentiation model hypothesizes that under the pressure of ARPI therapy to the adenocarcinoma cells, tumor will be reprogrammed into neuroendocrine cells. Original figure adapted from: Davies, A. H., Beltran, H., & Zoubeidi, A. (2018). Cellular plasticity and the neuroendocrine phenotype in prostate cancer. Nature reviews. Urology, 15(5), 271–286. https://doi.org/10.1038/nrurol.2018.22 Permission of reuse gained from Nature Reviews. 16 Based on whole-genome sequencing, functional mutations in the retinoblastoma 1 (RB1) is 70-90%, and tumour protein 53 (TP53) genes are present in 56-67% of t-NEPC tumors, in contrast to 15-40% of CRPC-Ad tumors (89,94). Research suggests that cancer cells that lack RB1/TP53 can differentiate into various lineages. One genetically engineered mouse model for prostate cancer progression, known as TRAMP GEMM mice, illustrates the importance of these genes in the emergence of t-NEPC tumors (95). In TRAMP mice under castration conditions, the spontaneous development of prostate cancers closely mirrors the characteristics and progression of metastatic CRPC-Ad to t-NEPC, with TP53 and RB1 being inactivated (95,96,97). A recent study by Mu et al. showed that knocking down the RB1 and TP53 genes in the LNCaP AdPC cell line confers resistance against ARPI and promotes t-NEPC development through the activation of pluripotency genes such as SOX2 (98). SOX2 and Lin28B genes are putative developmental factors that play a crucial role in the self-renewal and pluripotency of embryonic stem cells. Furthermore, Mu et al. reported that certain transcription factors from the SOX family (e.g., SOX2, SOX9, and SOX11) are temporally regulated to promote cell lineage plasticity towards NE cell lineage fate and t-NEPC (98). The researchers found that using LNCaP/AR and CWR22Pc-EP cells, both cell lines expressing high levels of AR and PSA, with a combined TP53/RB1 shRNA knockdown will result a shift from AR-dependent luminal epithelial cells to AR-independent basal-like cells (98). A similar resistance mechanism is seen in PTEN/RB1/Trp53 triple knock-out (TKO) GEMMs (99). So, TP53 and RB1 loss of function confers resistance has been demonstrated. Together, these findings led to the development of a model of lineage plasticity, which proposes that prostate cancer cells undergo a process of differentiation and reprogramming into a stem-like 17 intermediate cell capable of differentiating into NE, basal, or mesenchymal lineages as needed (85). There is compelling evidence to support the hypothesis that epithelial plasticity contributes to the development of a neuroendocrine phenotype. First, numerous studies on prostate cancer cell lines and clinical samples have shown that inhibiting the AR pathway promotes epithelial-mesenchymal transition (EMT), the enrichment of CSC populations, and neuroendocrine differentiation (85, 100-105). Second, research suggests that transcription factors, signaling pathways, and cell surface receptors are responsible for defining epithelial plasticity and its link to the neuroendocrine phenotype. For example, the over-expression of SNAI1, an EMT transcription factor, in LNCaP cells results in the up-regulation of neuroendocrine lineage markers, such as CHGA and ENO2, and the cell will develop a neuronal-like morphology (106). Increased expression of SNAI1 is also observed in LNCap-C33 prostate cancer cell-line models, which are LNCaP cells with ADT (106), and the repression of SNAI1 via small interfering RNA (siRNA) can significantly reduce the expression of neuroendocrine markers (106). Several studies show that the upregulation of EMT transcription factors encoded by SNAI1 and ZEB1 also upregulates stem cell-associated genes (107). Clinical studies and research show that trans-differentiation of adenocarcinoma into neuroendocrine prostate cancer is due to EMT-like programmed mechanisms. Studies have demonstrated that IL-6 activates the STAT3 signaling pathway, which causes AR downregulation, endowing prostate cancer cells with stem-like attributes and EMT characteristics, and leading to the neuroendocrine differentiation process (67, 108-111). Conversely, inhibiting the IL-6/STAT3 activation signal using an IL-6 cytokine trap can decrease the number of CSCs (110), indicating that this pathway is essential in regulating the 18 plasticity phenotype of neuroendocrine prostate cancer. Additionally, the WNT-beta-catenin pathway, which is often activated in CRPC, can strengthen resistance to ADT and promote the neuroendocrine phenotype via the induction of CSCs (112-115). These studies demonstrate that cellular plasticity and neuroendocrine lineage switching are manipulated by complex gene expression network, redundant mechanisms that need more research. Distinct cell surface markers can differentiate CSCs from other cell types. For example, prostate CSCs have been shown to upregulate cell surface markers CD44 and CD133 (116). CD44+ cells derived from prostate cancer cell lines and tumour xenografts demonstrate enhanced tumorigenic and metastatic potential and increased expression of stemness genes and transcription factors, including OCT3/4, Bmi, and beta-catenin (117). Selective expression of CD44 and CD133 markers has also been linked to the neuroendocrine prostate cancer lineage. Studies using Du145 and PC3 prostate cancer lines have demonstrated that silencing the EMT transcription factor ZEB1 leads to reduced CD44/CD133 expression, while knocking down CDH1, which encodes the epithelial protein E-cadherin, increases their expression (118, 119). Furthermore, CD44 expression has been found to be highly concentrated in NSE-positive (NE-like) cells, indicating a connection between CSCs and neuroendocrine differentiation (120). The connection and association between CSCs, EMT, and neuroendocrine differentiation showed in the CSCs transplanted mice. Mice inoculated with CD44+CD24- CSCs isolated from Du145 cells developed mesenchymal-like tumours (which is a tumour subtype that contains a low level of E-cadherin expression and beta-catenin but has a high level of vimentin) with a high density of CHGA, one of the neuroendocrine markers (121). As mentioned in the previous idea, t-NEPC’s relationship with EMT CSCs have not been fully elucidated yet, and we need more research and 19 novel way to investigate the pathways to help with the treatment and target design. The previous publication from our lab recognized that the core pluripotency stem cell genes, Lin28 and SOX2, co-upregulated and contributed to t-NEPC differentiation. Especially, the Lin28B isoform along with Let-7 miRNA regulation axis in t-NEPC might be a potential therapeutic target for treatment (230). 1.4 Lin28B/let-7 Pathway 1.4.1 Lin28B Gene and Protein Structure As a highly conserved RNA-binding protein, Lin28 was initially discovered in Caenorhabditis elegans and Drosophila melanogaster. In all vertebrates, Lin28 has two homologs: Lin28 homolog A (Lin28A) and Lin28 homolog B (Lin28B) (122, 123). The human Lin28A gene, located on chromosome 1p36, encodes a 209 amino acid protein while the human Lin28B gene, is located on chromosome 6q21 encodes a longer 250 amino acid protein (124). Both Lin28A and Lin28B proteins are highly conserved in sequence among species and share a high degree of homology in the structural domains, as shown in Figure 1.4. 20 Figure 1. 4 Schematic of human Lin28A and Lin28B proteins. (A) Human Lin28A and Lin28B protein sequence alignment indicated the highly similarity of both cold-shock domain (CSD) and CCHC zing-knuckle domain (ZKD). (B) Lin28 gene is identified as proto-oncogene and encodes two distinct RNA binding regions, cold-shock domain (CSD) and CCHC zing-knuckle domain (ZKD). CSD found binds preferably to GNGAY RNA sequences while ZKD-1 and ZKD-2 likely to bind to RNA GGAG motif. Distinctively, Lin28B has nucleolar (NoLS) and nuclear localization (NLS) signal for being putative regulation gene. Original figure adapted from: Balzeau, J., Menezes, M. R., Cao, S., & Hagan, J. P. (2017). The LIN28/let-7 Pathway in Cancer. Frontiers in genetics, 8, 31. https://doi.org/10.3389/fgene.2017.00031 One unique characteristic of the Lin28 protein is that it contains both the cold-shock domain (CSD) and two cysteine-cysteine-histidine-cysteine zinc-knuckle domains, which are capable of binding to RNA (122,125,126). Cold shock domain-containing proteins regulate ribosomal translation, messenger RNA stability, degradation of RNA, transcription, and 21 termination of RNA processes by binding to single-stranded nucleic acids. The primary function of the zinc-knuckle domains, which were first found to be present in the nucleocapsid protein (NCP) of HIV-1, is to increase the binding specificity and enzymatic activity of the Lin28B protein. Nucleolar localization signals (NoLS) are found between the cold-shock domain and zinc-knuckle domains of Lin28B, in addition to a nuclear localization signal (NLS) at its C-terminus (128). Lin28 is predominantly expressed in male testis, female placenta, and primarily expressed in undifferentiated pluripotent cell types throughout their lifetimes (129). Cytoplasmic expression of Lin28 and its association with various organelles, such as ribosomes and stress granules, have been observed (130). Although the molecular function of Lin28 is not well understood, evidence suggests that it is associated with translating mRNA in pluripotent mammalian cells. Lin28 is found in RNase-sensitive complexes with poly(A)-binding protein and polysomal fractions of sucrose gradients. When cells encounter stress, Lin28A/B are transported and located to stress granules, which contain vital mRNA for cell regeneration (133). While several different studies have shown that in neuroblastoma and hepatocellular carcinoma, Lin28B is shuttled into the nucleus in a cell cycle-dependent manner (125,128-131). The subcellular localization of Lin28B is cell-cycle dependent, where it is predominantly expressed in the cytoplasm of G1 phase cells and the nucleus of S and G2 phase cells (132). A previous publication from our lab specifically discussed the role of Lin28B in neuroendocrine prostate cancer (NEPC). The cell lysis fragmentation combined with immunoblotting assays confirmed that Lin28B protein was localized and overexpressed in the cytoplasm (85). Lin28 proteins expression can thus have an impact on cell cycle, stress responses, and relates to RNA binding and cell survival. 22 1.4.2 Lin28B Biological Function in Embryogenesis Lin28A and Lin28B, are RNA-binding proteins that play critical roles in a variety of developmental processes such as skeletal myogenesis, neural development, and germ cell differentiation, as well as metabolic processes such as insulin sensitivity and glucose tolerance (134-138). Lin28 is particularly important for embryonic stem cell pluripotency, as it can reprogram differentiated cells into pluripotent stem cells in combination with NANOG, OCT4, and SOX2 (139). A Lin28 homolog (Lin28A/B) is expressed during development by various animals including mice (122). Reports demonstrated that mouse Lin28 is highly expressed in embryonic stem (ES) cells and embryonic carcinoma (EC) cells, but not in a range of differentiated cell types, such as fibroblasts and neurons. Lin28 expression is common during mammalian development, but its absence from some differentiated cells raises the question of how broadly it is expressed and how temporally it is regulated. Lin28 is regulated by various factors, including microRNAs, transcription factors, and signaling pathways which plays a critical role in controlling cell differentiation timings (140). The same study showed that Lin28B expression level could correlate to the embryogenesis process in mice. In the two-cell stage of embryogenesis, by embryonic day 6, Lin28B is expressed throughout the entire embryo and expressed all over the extra-embryonic tissue (140). However, a significant decrease in expression level of Lin28B occurs at embryonic days 17.5 (140). This decline in Lin28B expression occurs simultaneously with the onset of meiotic germ cell differentiation, and it remains low throughout embryonic development (141). By the time the embryo is developed completely, progenitor cells have differentiated, and Lin28B 23 expression is now restricted to a subset of epithelial cells, including those of the bronchi, lungs, kidney, cardiac muscle cells, myocardium, and neuroepithelium (140). In order to understand the physiological function of the Lin28 gene in mammals, the Daley Lab created mice with gene knockouts for both Lin28A and Lin28B (144). They found that during the perinatal period, Lin28A null mice die, while Lin28B knockout mice develop postnatal growth defects only in males. Double knockouts result in embryonic lethality by day 13, suggesting that these proteins are functionally crucial during embryo development (144). In conclusion, Lin28A and Lin28B expression is primarily restricted to embryonic development in mammals (125). It has also been observed that Lin28A/B levels of expression are remarkably reduced during differentiation, along with an increase expression in let-7 microRNAs (145). Regarding the subcellular localization of Lin28B, there are divergent opinions. One study demonstrated that Lin28B has distinct nucleolar and nuclear localization signals (128), whereas other studies resulted in Lin28B being predominantly cytoplasmic and suggesting that it might enter the nucleus in a cell-cycle-dependent manner (125, 131, 132). In neuroendocrine prostate cancer cell line, Lin28B expressed as a cytoplasmic protein (85). Further research still needs to determine the exact subcellular location of human Lin28B, which may vary depending on the cell type. However, reports demonstrated that Lin28 plays a crucial role in maintaining pluripotency by inhibiting the let-7 microRNA, which promotes the self-renewal properties of undifferentiated cells, and potentially contributes the stemness characteristics to tumors. (142, 170). 24 1.4.3 Lin28B Stemness and Pluripotency Lin28B promotes the generation of human induced pluripotent stem cells (iPSCs) (139, 146, 147). Inhibition of the let-7 mechanism by Lin28B promotes de-differentiation of cells during reprogramming, which is essential for the generation of iPSCs (142). Additionally, overexpression of Lin28B in mice has been shown to increase tissue regeneration rates, indicating that Lin28B-mediated control of stem cells and transit-amplifying populations is crucial for tissue regeneration (148). Manipulation of the Lin28B/Let-7 axis can therefore be utilized to control the differentiation or dedifferentiation of ESCs, this axis is major contribution to maintain the pluripotency of the cells (124). Figure 1.5 shows how the Lin28/let-7 axis regulates and affects the expression levels, thereby influencing cellular behaviors. Figure 1. 5 The Lin28A and Lin28B/let-7 miRNA axis has important biological functions. In undifferentiated cells, Lin28A and Lin28B expression is high, preventing let-7 microRNA biogenesis. The loss of expression of Lin28 gene results in a proliferation of mature let-7 microRNAs that negatively regulate expression of Lin28 as differentiation progresses. LIN28A/B is responsible for the generation of pluripotency, self-renewal, differentiation and/or cellular transformation during cellular transformation, wound healing (mostly in young mammals), and during the generation of iPSCs. Original figure adapted from: Balzeau, J., Menezes, M. R., Cao, S., & Hagan, J. P. (2017). The LIN28/let-7 Pathway in Cancer. Frontiers in genetics, 8, 31. https://doi.org/10.3389/fgene.2017.00031 Reproduction of this figure is permitted by Publisher. 25 1.4.4 Lin28-Mediated Metabolism It is increasingly recognized that metabolic diseases and malignancies have overlapping biological pathways and mechanisms. First, the metabolic properties of pluripotent stem cells (PSCs) are unique (149). In the case of somatic cell reprogramming, the cellular metabolism is reset to a state of low oxidative phosphorylation and high glycolysis. However, the mechanism of oxidative phosphorylation repression has not been fully understood. Furthermore, the maintenance of pluripotency and histone methylation of PSCs is facilitated by one-carbon metabolism, which provides cells with the necessary building blocks for DNA synthesis, methylation, and other biosynthetic processes to help PSCs maintaining pluripotency and regulating cell fate decisions (150,151,152). Additionally, both mouse and human PSCs are highly oxidative in a “naive” state, as opposed to “primed” cells (153,154,155), and Lin28 is expressed at significantly lower levels in naive states versus primed states (156,162). A number of factors are unknown regarding the role that Lin28 plays in determining whether pluripotent cells will develop into naive or primed phenotypes and their metabolic capabilities. It has been reported that Lin28 regulates glucose metabolism using let-7 dependent mTOR signaling pathway (138). In the Zhu’s group publication, they developed an inducible Lin28 overexpression transgenic mouse model (iLin28 Tg) to monitor if the Lin28 expression level correlates to the glucose metabolism (138). The conclusion is that overexpressed Lin28A showed increasing activity of the glucose metabolism and insulin sensitivity and protected mice to against diabetes when fed with high fat diet during aging. On the other hand, knockdown Lin28A and Lin28B or overexpressed of let-7 can result in dwarfism and intolerance of glucose. Furthermore, in Frost and Olson research data demonstrated that overexpression of let-7 in mice can impaired glucose tolerance and 26 reduced insulin secretion in pancreas; let-7 also mediated different metabolic pathways including mTOR, Igf1r, Insr, and Irs2 (290). More and more work started to focus on the relevance of metabolic regulation pathway of Lin28 and let-7, there is a publication suggested that Lin28/let-7 axis could relate to neural differentiation which could potentially benefit for the NEPC research (138, 291). 1.4.5 MicroRNA microRNAs, in this study, let-7 families demonstrate strong inhibition characteristics of tumour growth (277). MicroRNAs (miRNAs), which are short (22 nucleotides) post-transcriptional regulators of gene expression, play a critical role in a wide range of diseases including cancer (162). In fact, a systematic review has demonstrated that miRNA expression levels can serve as a predictor of clinical outcomes, such as overall survival, disease-free survival, and response to treatment in various cancer types (163). The process of miRNA production involves the cleavage of primary miRNAs (pri-miRs) by the enzyme RNAseIII Dorsha into stem-looped precursors (pre-miRs) in the nucleus. Once transported into the cytoplasm, pre-miRs are further cleaved by the RNAseIII enzyme, Dicer, into mature and function miRNAs. Typically, miRNAs inhibit mRNA expression by binding to the mRNA's 3' untranslated regions (3' UTRs) (165), although they may also interact with other regions such as 5' UTRs, coding sequences, and gene promoters (166). The article explains that miRNAs can bind to the 3’UTR of target mRNAs, leading to the recruitment of miRNA-recruiting RNA-induced silencing complexes (RISC) proteins (164). RISC proteins primarily induce mRNA degradation through 3' UTR binding (164), although miRNAs have also been shown to activate gene expression under certain conditions (167). MiRNAs shuttle 27 between subcellular compartments to control rates of translation and transcription and regulate a variety of biological processes essential for normal animal development (168). The current understanding of miRNA expression and function in various aspects of placental development, including trophoblast differentiation, angiogenesis, and immune regulation (169). Aberrant miRNA expression has been associated with human diseases and cancers (170, 171), and miRNAs are secreted into extracellular fluids, serving as cancer biomarkers and signaling molecules for cell-to-cell communication (172-174). So, miRNAs have been evaluated as cancer biomarkers and are being taken more seriously as potential targets for cancer treatment. In our focus, miRNA let-7 is the most reported and the major target for us to develop neuroendocrine prostate cancer treatments. Figure 1.6 provides a visual representation of how miRNAs regulate the mRNA degradation. Figure 1. 6 miRNA transcription and mechanism of action. 28 RNA polymerase II transcribes pri-miRNA and Drosha RNase III processed pri-miRNA into pre-miRNA. Exportin-5 protein on the nucleus transports pre-miRNA to cytosol then processed by Dicer, another RNase III. Mature miRNA form RISC complex to bind to the target mRNA to repress or cleavage them. Original figure adapted from: Magri, F., Vanoli, F., & Corti, S. (2018). miRNA in spinal muscular atrophy pathogenesis and therapy. Journal of cellular and molecular medicine, 22(2), 755–767. https://doi.org/10.1111/jcmm.13450 Permission and license to use can be found in https://creativecommons.org/licenses/by/3.0/ 1.4.6 Let-7 microRNA Family The Let-7 miRNA family was first identified in C.elegans as a heterochronic gene (182). At larval three stages, let-7 expression was detected and peaked at larval 4 stage (182,183), which means let-7 is an essential factor during the transition from larval stage 4 to the adult stage (182). As the larval cells failed to differentiate and exit the cell cycle, abnormal cell division and alae formation were observed in the let-7 mutants. After a bursting vulva, the larval cells eventually die. The miRNA was named lethal-7 (let-7) based on its lethal phenotype. miRNAs can bind to multiple sites on the same mRNA or to multiple mRNAs, allowing for complex regulatory networks, additionally, seed regions in miRNAs, which are highly conserved sequences of nucleotides that are involved in the initial recognition and binding of target mRNAs (184). In humans, 12 members of the let-7 family (let-7a-1, 7a-2, 7a-3, 7b, 7c, 7d, 7e, 7f-1, 7f-2, 7g, 7i, and mir-98) are expressed (181,185). These miRNAs are members of the same family, and their seed sequences contain the same region of nucleotides 2 to 8, which appears to be important for target recognition (184, 186). Additionally, this suggests that at least some of the targets and functions of the members of the let-7 family are similar (187). Later research demonstrated that let-7 functions in humans are very similar to those in nematodes, indicating that it is both biologically conserved and has a crucial function (180). Numerous studies have demonstrated let-7 miRNAs critical role in organism development and metabolism (188). Let-7 29 miRNA is expressed and its peak during the late stages of embryonic development in mammals, inducing cell differentiation and managing the cell-cycles (189). The let-7 family has been implicated in the negative regulation of proliferation rates and induction of differentiation in hematopoietic stem cells and progenitor cells (190). These findings indicate that let-7 miRNA function promotes terminal differentiation in development and serves as the tumour suppressor. Thus, restoring let-7 miRNA levels in cancer cells becomes a potential approach to halt tumour proliferating. Figure 1.7a shows the sequence comparison of let-7 family members across diverse animal species. Figure 1.7b shows the sequence alignment of let-7 family members in human. 30 Figure 1. 7 Sequence comparison of let-7 family members across diverse animal species. (A) C. elegans (cel), D. melanogaster (dme), X. tropicalis (xtr), D. rerio (dre), G. gallus (gga), C. familiaris (cfa), M. musculus (mmu), and H. sapiens (hsa) all possess the consensus mature let-7 (let-7a) sequence of ‘UGAGGUAGUAGGUUGUAUAGUU’. The seed sequence is indicated as a yellow box. Consensus mature sequences are placed at the top of the box, where only perfectly aligned sequences are capitalized. (B) Sequence alignment of the mature forms of human let-7 family members (upper panel). Dark blue box represents percentage identity over 70%, whereas light blue box indicates percentage of over 50%. Consensus mature sequences are placed at the top of the box, where only perfectly aligned sequences are capitalized. Consensus sequences of the mature human let-7 family members, as assessed by MEME (http://meme-suite.org, bottom panel) 31 Original figure adapted from: Lee, H., Han, S., Kwon, C.S. et al. Biogenesis and regulation of the let-7 miRNAs and their functional implications. Protein Cell 7, 100–113 (2016). https://doi.org/10.1007/s13238-015-0212-y This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/) 1.5 Lin28B protein and Let-7 miRNA 1.5.1 Lin28B Block Biogenesis of Let-7 MicroRNA The Lin28 protein has been extensively studied for its role in selectively inhibiting Let-7 biogenesis. This inhibitory characteristic guides the tumour to grow uncontrollably. Various human malignancies, such as ovarian and hepatocellular carcinomas and Wilm's tumours, overexpress Lin28 (193,125). In 2008, several reports demonstrated that Lin28 suppresses let-7 maturation in mammalian cells and specifically targets the Drosha stage (194,195,196). It was found that Lin28 interacts directly with the let-7 precursors (pri- and pre), which counteracts the Dicer and Drosha-dependent maturation pathways. Lin28 also interacts with the conserved terminal loop of the pre-let-7 family for its inhibition. Moreover, the Lin28/let-7 feedback loop plays a critical role in controlling cancer stem cell differentiation and development (194-196). The study by Van Wynsberghe et al. showed that let-7 in C. elegans plays an essential regulator to ensure the development from larval stage to adult stage (187). Expand this basic knowledge from the C. elegans study, further investigations showed that Lin28 binds to pri-let-7 in the nuclear compartment of human embryonic stem cells and co-transcriptional interactions between Lin28 and pri-let-7 prevent Drosha-mediated maturation (197). The binding of Lin28 to pre-let-7 induces a conformational change within the Dicer processing site of pre-let-7 that 32 facilitates the unwinding of its double-stranded region, leading to inhibition of let-7 maturation (198). The mechanism described in this study sheds light on how Lin28 targets and counteracts let-7 maturation. Lin28B is known to bind to pre-let-7 in the cytoplasm, thus preventing its processing by Dicer. In addition, Lin28B is a catalyst for the oligo-uridylation and degradation of pre-let-7 through the action of terminal uridyl transferase 4 and 7 (TUT4, TUT7) (199,200). When the expression of Lin28B is turned off during differentiation, Pri-let-7 is cleaved and subsequently moved to the cytoplasm by Drosha (201). Then, with the assistance of TUT4, TUT7, and TUT2, Dicer creates single-stranded mature let-7 miRNA (201). The Let-7 system is designed to silence the expression of proto-oncogenes such as Ras, c-Myc, HMGA2, cell cycle progression factors including Cyclin D1, Cyclin D3, CDK4, components of the insulin-PI3K-mTOR pathway, as well as the Lin28B gene itself (201). Previous lab member Jessica Lovnicki described how Lin28B blocks let-7 biogenesis by binding to pri-let-7 or pre-let-7 (85). This, in turn, inhibits Drosha and Dicer microprocessor from processing and maturing the let-7. Figure 1.8 shows that increased expression of Lin28B can transform differentiated cells into undifferentiated cells. The Lin28B protein inhibits the maturation of Let-7 by binding to pre-let-7 and recruiting TUT4/TUT7 oligo-uridylation proteins, resulting in degradation. Figure 1.8 illustrates how the Lin28B/let-7 axis in the nucleus and cytosol regulates cell fate. 33 Figure 1. 8 Lin28B/let-7 regulatory axis. Original figure pathway adapted from Mayr, F., & Heinemann, U. (2013). Mechanisms of Lin28-mediated miRNA and mRNA regulation--a structural and functional perspective. International journal of molecular sciences, 14(8), 16532–16553. https://doi.org/10.3390/ijms140816532 Permission to use and reproduce is gained by the publisher. 1.5.2 Lin28B/Let-7 miRNA in Prostate Cancer The expression and role of the Lin28B/let-7 pathway in neuroendocrine prostate cancer is an area that has not been studied detaily, but our research group believes this pathway is important because we observed the overexpression in neuroendocrine prostate cancer tumour 34 environment, and knocked down Lin28B seems to dramatically inhibit the tumorigenesis and xenograft growth (230). Lin28A and Lin28B expression have been detected in several prostate cancer cell lines, including PC3, Du145, C4-2B, LNCaP, and VCaP, but not in normal prostate tissues (145, 201, 202-204). In the PC3 cell line and DuNE, a t-NEPC cell line developed as a model in our lab, Lin28B expression has been detected (203). However, there is some disagreement about which let-7 miRNA is repressed by Lin28B in prostate cancer, although all studies suggest that Lin28B functions through Let-7. For example, when Lin28B expression is increased in Du145 cells, Albino et al. (206) observed a reduction in the expression of let-7b and prime-let-7b, while Kang et al. (203) and Kong et al. (205) found that overexpression of Lin28B decreased the expression of all members of the let-7 miRNA family in PC3 cells. Additionally, Yu et al. (271) reported a decrease in let-7a and let-7c in Du145 cells, while Nadiminty et al. (204) found a decrease in let-7c in C4-2B cells. Compelling evidence indicates that downregulation of Lin28B significantly impairs prostate cancer growth and stemness and prevents the transition from prostate adenocarcinoma to the highly morbid t-NEPC (85, 204, 207). High levels of Lin28B have also been shown to enhance the expression of androgen receptor, which is the main driver of prostate cancer (204). Importantly, Lin28B overexpression has been linked to high tumorigenic and metastatic ability of prostate cancer. Despite the known difficulties in targeting RNA-binding proteins, Lin28B has been proposed as a promising therapeutic target for cancer treatment (208, 209). 35 1.5.3 Lin28B Domain Structure and ZKD-Lin28B as a therapeutic Target in Cancer To have further understanding of how Lin28B block the miRNA let-7 biogenesis, structure study is critical to facilitate our hypothesis. Lin28B has two domains: the cold-shock domain (CSD), which binds to the GNGAY motif of let-7 miRNA and the zinc-knuckle domain (ZKD), which has been shown to bind to the GGAG motif of let-7 (201). Additionally, it has been suggested that the pre-let-7 molecule first binds to the CSD, which then causes the pre-miRNA conformational change, leading Lin28B ZKD to bind to the GGAG motif (201). An enzyme called TUTase is recruited by the GGAG-motif, which is responsible for stabilizing the Lin28B-pre-let-7 complex (210). Upon uridine addition to the 3' end of pre-miRNA, TUTase causes degradation of pre-miRNA. According to a study in which pre-let-7 binding and downstream effects upon Lin28B mutagenesis were examined, ZKD-GGAG interactions are more essential for the functional effects of Lin28B and degradation of let-7 (212). These studies show that inhibiting Lin28B and restoring let-7 levels will negatively affect the growth of tumor cells. Several studies have attempted to identify small molecules capable of blocking the degradation induced by Lin28B (217,231). There is evidence that some of the identified small molecules are active in protein-based assays and cell-based tests. Unfortunately, their activity was either modest or coupled with toxicity, leaving the studies to serve as a proof-of-principle for targeting Lin28B. We designed novel inhibitors for ZKD-Lin28B using computational tools such as virtual screening, pharmacophore modeling, then selected potent chemicals by using fluorescence polarization assay, electrophoresis mobility assay, real-time qPCR, western blot, proliferation assay, and colony formation assay. 36 1.6 Hypothesis Based on previous publications from our lab, we have demonstrated that Lin28B/let-7 pathway is playing a critical role for the development of NEPC. In t-NEPC, we observed high expression of Lin28B and low expression of let-7, especially let-7d. Moreover, Lin28B protein has been shown to promote NEPC proliferation and the trans-differentiation process. We have gathered evidence that the zinc-knuckle domain (ZKD) in Lin28B plays the most critical role in degrading the let-7 miRNA family. Therefore, we hypothesize that small molecules that block the interaction between ZKD Lin28B and let-7d miRNA will restore mature let-7d expression. Furthermore, we anticipate that ZKD Lin28B inhibitors can inhibit the expression of neuroendocrine and stem-cell markers, downregulate let-7 dependent stem-like pluripotency gene, reduce the tumor growth rate, and lower the colony formation ability. In order to investigate this hypothesis, we will pursue the following aims: Aim 1: Perform virtual screening using CADD pipeline, and in vitro binding assays to screen the potential ZKD-Lin28B inhibitors. Aim 2: Select the most promising ZKD-Lin28B inhibitors identified in Aim 1 and compare their potency with reported Lin28B inhibitors using in vitro assays. Aim 3: Validate the efficacy of the most potent ZKD-Lin28B inhibitor identified in Aim 2 using cell assays. 37 Chapter 2: Materials and Methods 2.1 Cell Lines and Cell Culture Maintenance Human prostate cancer adenocarcinoma (PCa) cell line Du145 and human ovarian cancer cell line IGROV1 were purchased from American Type Culture Collection (ATCC; Manassas, VA, USA). Embryonic kidney cell line 293T were kindly provided by Dr. Ralph Buttyan (293T) from the Vancouver Prostate Centre (VPC; Vancouver, BC, Canada). The DuNE cell models, along with their control cells, were previously established by our lab group (213-215). The DuNE cell line was established using lentiviral expression vectors (pFUGWBW) encoding Flag-SRRM4, which regulates alternative splicing programs to drive neuroendocrine prostate cancer, and an empty control vector, which were transduced into target Du145 cells (215). The transduced cells were then selected with blasticidin (Gibco Life Technologies), and the expression of SRRM4 was confirmed using real-time qPCR and immunoblotting (Western Blot) assays (213-215). Du145, DuNE, IGROV1 and 293T cells were cultured in Dulbecco’s Modified Eagle Medium, high glucose/L-glutamine (DMEM; Hyclone, Logan, UT, USA) with 10% fetal bovine serum (FBS; Gibico, Waltham, MA, USA). All cell lines were incubated in a 5% CO2 cell incubator at 37°C. The cell lines were tested for mycoplasma contamination weekly and were not maintained for more than two months, 15 passages for repeat assays. 2.2 ZKD-Lin28B Inhibitors Drug Designed ZKD-Lin28B inhibitors drug discovery pipeline CADD was established by Mariia Radaeva and described detail in “THE USE OF COMPUTER-AIDED DRUG DESIGN METHODOLOGY TO 38 TARGET DNA-PROTEIN, RNA-PROTEIN AND PROTEIN-PROTEIN INTERACTIONS IMPLICATED IN CANCER” (289). Binding site identification was performed in MOE software using SiteFinder tool (217). All the protein structures used for docking and molecular dynamics were prepared using Protein Preparation Wizard from Schrödinger (218). The preparation included hydrogen bond assignment (using PROPKA with pH of 7.0), minimization with OPLS3e force field (with heavy atoms constrained to 0.30Å RMSD) and addition of the missing side chains. Ligand preparation was performed using Omega toolkit and included canonization of SMILES, ligand tautomerization and conformer generation (219). DeepDocking was performed with default parameters as described in Gentile et al (2020) (220). Redocking with GlideSP (218) was performed with default parameters; docking grids were calculated with the grid generation software from Schrodinger. FRED docking was performed with default parameters. Distances between docking poses were generated using MOE software (217). ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties were calculated using SwissADME software (221). 2.3 Lin28B Protein Purification Process (In collaboration with Lallous lab) 2.3.1 Transformation of Lin28B into BL21 (DE3) One Shot TM BL21 (DE3) were purchased from Thermo Fisher (MAN0000662). BL21 (DE3) competent E. coli cells are high efficiency cells for wide variety of applications such as transformation and routine protein expression. A tube of 50 µL BL21 (DE3) competent cells was thawed on ice for 10 minutes. 50 ng of target plasmid DNA (PET28 His-tag containing either ZKD- 39 Lin28B or Full length Lin28B made by Ning Xie) were added to the competent cells. The mixture was placed on ice for 30 minutes, followed by heat shock exactly at 42°C in a water bath for exactly 45 seconds. After heat shock, the tube was placed on ice for 5 minutes and 250 µL of room temperature super optimal broth with catabolite repression medium (SOC) were then added to the mixture. The tube was then placed in a shaking incubator at 37°C and 250 rpm for 1 hour. Afterward, 100 µL of the mixture were spread onto a pre-warmed kanamycin selection plate and incubated overnight at 37°C. 2.3.2 Protein Expression of Lin28B in BL21 (DE3) cells To express Lin28B protein, a single colony was selected using a pipetting tip and resuspended in a 5 mL liquid Lysogeny broth (LB) culture containing kanamycin at a concentration of 100 µg/mL. The bacteria culture was incubated overnight at 37°C with shaking at 225 rpm. After overnight incubation, a 50 mL flask containing LB liquid with kanamycin (100 µg/mL) was prepared, with 1 mL of LB/antibiotic saved for blanking. Each 50 mL flask was inoculated with 1 mL of the overnight culture, and the culture was shaken at 37°C at 225 rpm until the OD 500 reaches 0.5-0.7 (the incubation takes about 3-4 hours). A sample was taken by spinning down 200 µL of culture in a 1.5 mL Eppendorf tube to obtain a pellet before induction. The big flask was induced with 1 mM IPTG (Isopropyl β-D-1-thiogalactopyranoside) (Invitrogen; Cat. 15529019) and incubated for 5 hours at 37°C with shaking, after which the protein expression was checked by SDS-page. For larger expression and induction scales, a 1 L liquid LB medium with 100 µg/mL kanamycin was inoculated with 20 mL of overnight culture to make up 2% volume (20 mL:1L). 40 2.3.3 Protein Purification using Nickel-NTA column. Purification Buffers Composition: 1. 500 mL Buffer A - 20 mM Tris-HCl, pH8.0 - 500 mM NaCl - 5% Glycerol - 10 µM ZnSO4 - 5 mM beta-mercaptoethanol - 0.1 mM PMSF 2. Lysis Buffer - 100 mL of Buffer A + 3 mM beta-mercaptoethanol + 2 mM PMSF + 4 PIC (Roche EDTA free Protease inhibitor cocktail) 3. 500 mL Buffer B - 20 mM Tris-HCl, pH8.0 - 500 mM NaCl - 5% Glycerol - 300 mM Imidazole - 10 µM ZnSO4 - 5 mM beta-mercaptoethanol - 0.1 mM PMSF 4. 100 mL Buffer C - Mix 90 mL Buffer A with 10 mL Buffer B 5. 1 L Dialysis Buffer - 20 mM Tris-HCl, pH8.0 - 500 mM NaCl - 10 µM ZnSO4 - 5 mM beta-mercaptoethanol - 0.1 mM PMSF 6. 500 mL Gel Filtration Buffer - 20 mM Tris-HCl, pH8.0 - 150 mM NaCl 41 - 10 µM ZnSO4 - 0.2 mM TCEP - 0.1 mM PMSF Supplementary Figure 5.1 and 5.2 demonstrated the purification results of ZKD-Lin28B and FL-Lin28B proteins. Protocol for Lin28B protein purification was established by Joseph Lee (Lallous Lab). Lysis of the cell pellet: BL21 (DE3) cells were harvested and centrifuged for 20 minutes at 4000 rpm at 4°C. The cells were then kept at 4°C throughout the lysis process. The cells were resuspended in 20 mL of cold lysis buffer and transferred to a 100 mL beaker along with 2 µg/mL protease inhibitor cocktail (Roche) and lysozyme to a final concentration of 1 mg/mL. The cells were gently mixed and kept on ice for 30 minutes before sonication. Sonication was performed on ice for 7.5 minutes using a sonicator with an amplification of 20%, 30 seconds on and 30 seconds off. The sonicated lysate was then transferred to a centrifuge tube and centrifuged for 45 minutes at 10,000 rpm. The supernatant was filtered into a clean 50 mL Falcon tube using a 0.4 µm syringe filter. Immobilized Metal Affinity Chromatography (IMAC): For IMAC , 5 mL of nickel-nitrilotriacetic acid (Ni-NTA) agarose resin (Qiagen) was first washed with 50 mL then twice with 10 mL of Buffer A. The supernatant from previous step was incubated with the resin for 1 hour at 4°C under agitation. The mixture was then applied into an empty gravity column, and the flow through was collected. The resin was next washed with 50 mL of Buffer A (W1) and 100 mL of Buffer C (W2a and W2b). Finally, the protein of interest was eluted from the column by washing 4 times 5 mL each of Buffer B (E1 – E4). The concentration of each elution sample was determined using Bradford method. 42 Dialysis (7000 kDa, cellulose membrane): For dialysis, the dialysis tubing was rinsed with water and then soaked in dialysis buffer (listed below). Elution fractions from the affinity chromatography step containing proteins according to the Bradford were pooled and transferred to the dialysis bag and dialyzed overnight at 4°C with stirring. The next day, the sample was transferred into a Falcon tube, and a 30 µL sample was taken for SDS-PAGE. Size exclusion chromatography (s75 10/300 GL Column): The dialyzed sample was centrifuged at 13,000 rpm at 4°C for 10 minutes to remove any precipitates and then injected onto a size exclusion chromatography column pre-equilibrated with gel filtration buffer. An 18% SDS-PAGE was then performed to confirm the purity of the protein sample. 2.4 Fluorescence Polarization Assay The fluorescence polarization (FP) assay is a commonly used technique in biochemical and drug discovery research to measure the binding of small molecules to proteins. The basic principle of FP assay is that the fluorescence polarization of a labeled molecule changes upon binding to its target protein. The light source emits multidirectional light waves initially, named depolarized light. After the depolarized light passes through the polarizer, it becomes polarized light (one directional light wave). Moreover, when the polarized light hits the molecule which is rotating rapidly, it will result depolarized light (low FP signal). If the polarized light hits the molecule which bound to bigger molecule rotating slower, it results in higher polarized light (high FP signal). This change in FP can be used to calculate the binding affinity of the small molecule to 43 its target protein. In this study, we used as a probe the per-let-7d miRNA labeled with 6-FAM fluorophore at 3’(synthesized by Integrated DNA Technologies; sequence details are described below). We used Lin28B as target proteins. To measure FP signal, we used a polarimeter that measures the ratio of emitted polarized to depolarized light. When a fluorescent molecule such as pre-let-7d-FAM in our case, is excited by polarized light, it emits light in a polarized orientation. If the molecule is free in solution, it will rotate rapidly and emit depolarized light (lower FP signal). However, if it is bound to the target protein (e.g Lin28B), its rotational motion is restricted and emits more polarized light (higher FP signal) (272). Figure 2.1 illustrates the principle of FP assays on pre-let-7d and Lin28B protein (262). Figure 2. 1 FP assays demonstration of the binding of pre-let-7d-FAM probe with Lin28B protein and the FP signal changed due to the rotational speed difference. To confirm the binding of pre-let-7d-FAM to Lin28B protein (both ZKD-Lin28B and FL-Lin28B FP assays were performed, we used Lin28B in the following paragraphs), we used Tecan InfiniteTM F500 plate reader to measure fluorescence polarization (Invitrogen). We ordered from Integrated DNA technologies the probe pre-let-7d-FAM with fluorophore tagged on 3’ end. We also ordered the same pre-let-7d sequence without fluorophore tagged as a control: Rapid rotation Low FP signalFree pre-let-7d probeFAM FAMBound Pre-let-7dprobeSlow rotation High FP signalLinker ZKD-Lin28BCSD-Lin28B 44 Pre-let-7d with FAM tagged: UUAGGGCACGAGAUUUUGCCCACAAGGAGUU–FAM. Pre-let-7d with no FAM tagged: UAGGGCACGAGAUUUUGCCCACAAGGAGUU. To ensure that the FP assay works, we included 3 control experiments: We first checked the binding of pre-let-7d-FAM to Lin28B protein. We thus used increasing concentrations of pre-let-7d-FAM probe in the presence of a fixed amount of Lin28B protein indicated a decreased in FP signal. To do so, we used 384-well black polystyrene microplates (Corning, Cat. 3573) to evaluate the direct binding between pre-let-7d-FAM probe and purified Lin28B protein. We added 10 µM of Lin28B per well, then titrated the tagged probe to cover the following range: 1, 2, 5, 10, 20, 50, 100, 200, 500, 1000, 2000, 5000, 10000 and 50000 nM per well in FP buffer (50 mM HEPES buffer pH 8.0, 500 mM NaCl, 250 mM imidazole, 10 mM b-mercaptoethanol, 5% glycerol). We prepared in 1.5 mL Eppendorf tubes 100 µL of each reaction (for triplicates). We gently mixed the solution by pipetting and incubated the tubes in the dark for 15 minutes at room temperature. We then transferred 30 µL to each well of a 384-well black flat-bottom plate (Corning, #3573). Noted that if the mixing process exceeds 20 minutes, the probe signal would start to decrease. Before reading the FP signal, we centrifuged the plate at 1000 rpm for 1 minute to ensure that all the liquid is at the bottom of the well. We used the following parameters at the TECAN500 to read FP signal: EX/EM 485/535, mirror selection-auto, G-Factor=1.000, number of flashes=60 and 45 settle time=70ms, signal gain – optimal. The demonstration of titration of the probe illustrated in Figure 2.2. The second control of the FP experiment is to titrate Lin28B protein into a fixed concentration of pre-let-7d. We thus used 1 nM of pre-let-7d-FAM concentration of 1 nM. This concentration was determined by Experiment 1 to have the lowest pre-let-7d-FAM probe concentration while yielding the highest fluorescence polarization (FP) signal. We titrated the concentration of Lin28B protein to cover the following range: 1, 2, 5, 10, 20, 50, 100, 200, 500, 1000, 2000, 5000, 10000, and 50000 nM per well. The first tube contained only FP buffer for the background signal. The second tube contained only pre-let-7d-FAM probe (1 nM) with FP buffer for the baseline signal. The third tube contained the highest Lin28B protein concentration (10 µM), and 1 nM of pre-let-7d-FAM, serving as the positive control (obtained the highest FP signal for calibration). Every subsequent tube added 1 nM of the pre-let-7d-FAM probe per well with a titration of Lin28B protein from 1 nM to Log [probe concentration] FP Readout (mP) Low High Low High Figure 2. 2 Titration of the probe (pre-let-7d-FAM) with fixed concentration of protein (Lin28B 10 µM). 46 50000 nM. The total solution volume was 100 µL for triplicates, and 30 µL of liquid was added to each well. The mixing solution step remained the same as the first step FP experiment, replaced the titration with Lin28B protein instead of the pre-let-7d-FAM probe. Example of protein titration figure demonstrated in Figure 2.3. Figure 2. 3 Titration of the protein (Lin28B) with fixed concentration of the probe (pre-let-7d-FAM 1nM). Once the two previous control experiments were done and we confirmed that pre-let-7d-FAM probe and the Lin28B protein interact together, we performed a competition FP assay using non-labelled pre-let-7d probe as a positive control to compete out the pre-let-7d-FAM probe specifically from Lin28B miRNA binding pocket. We thus used 10 µM Lin28B protein and 1 nM pre-let-7d-FAM probe as determined from previous experiments. We then titrated the concentration of the non-labeled probe pre-let-7d to cover the following range: 1, 2, 5, 10, 20, 50, 100, 200, 500, 1000, 2000, 5000, 10000 nM per well. Log [concentration] 0 1 2 3 4 550100150200250300 FP Readout (mP) Low High Low High Log [protein concentration] 47 Preparation of the first and the second tube remained the same. The third tube contained the positive control, which was 10 µM of the Lin28B protein and 1 nM of pre-let-7d-FAM mixture with FP buffer (Acquired from previous first and second FP experiment). After the positive control tube, added 10 µM of Lin28B protein and 1 nM of the pre-let-7d-FAM probe along with the calculated titration of pre-let-7d compete probe. The total solution volume was 100 µL for triplicates, and each well would have 30 µL of liquid. Solution mixing step remained the same as previous two FP experiments. Moreover, parameter and sample preparation stayed the same. Competition assay figure demonstrated in Figure 2.4. After conducting all three control experiments and established the experimental parameters for the competition assay, we were ready to screen for small molecule inhibitors that interfere with the interaction between Lin28b and pre-let-7d-FAM,. Compounds Ln1 to Ln193 FP Readout (mP) Log [concentration] IC50=238.8nM 0 1 2 3 4 550100150200250Low High Low High Log [non-labeled probe concentration] Figure 2. 4 FP competition assay using the 1 nM of probe (pre-let-7d-FAM) with 10 µM of protein (Lin28B) and titrating with non-labeled probe (pre-let-7d). 48 were identified by CADD pipeline and selected to purchase. The compounds prepared in 100% DMSO at 50 mM, dilution based on chemicals molecular weight provided by the company. These compounds were first screened at a single concentration (50 µM) in FP competition assay. The first, second and third tube in FP competition assay remained the same as described before. The fourth and fifth tubes contained 10 µM of Lin28B protein, 1 nM of the pre-let-7d-FAM probe, FP buffer, and 50 µM of reported Lin28B inhibitors 1632 (236) and Li71 (222), whose signal served as the cutoff to select more potent Lin28B inhibitors from Ln1-Ln193. After the fifth tube, 10 µM of Lin28B protein and 1 nM of pre-let-7d-FAM probe were added to each tube along with the FP buffer and 50 µM of the inhibitors. The total solution volume was 100 µL for triplicates, and 30 µL of liquid was dispensed to each well before reading the plate. The FP raw screening experiment design including solution mixing and sample preparation was remained identical and mentioned in the previous FP experiments. All the parameters remained the same as well. After the raw screening, potential inhibitors were compared to published Lin28B inhibitors, Li71 and 1632. Inhibitors that had better the inhibition of Li71 and 1632 were then subjected to the compound titration FP assay, following the same process as experiment 1 and experiment 2 titration design. The selected Lin28B inhibitors were titrated from 1 nM to 100 µM and added the mixture contained with 10 µM of Lin28B protein and 1 nM pre-let-7d-FAM to complete the inhibition curves and further selected better inhibitor compounds. To calculate fluorescence polarization signal, we used the following equation: 𝑃 = 𝐹!"##"$$%$ − 𝐹!%#!%&'()*$"#𝐹!"##"$$%$ + 𝐹!%#!%&'()*$"# 49 P is the fluorescence polarization reading, Fparallel is the fluorescence intensity acquired from the parallel excitation plane, and Fperpendicular is the fluorescence intensity acquired from the perpendicular direction of the excitation plane. The total fluorescence intensity is estimated using this equation: 𝐹 = 𝐹!"#"$$%$ + 2𝐹!%#!%&'()*$"# After accumulating all the raw FP signal data from the TECAN 500 FP results, data was transferred to the Prism 8.0 (GraphPad) to generate the normalized curves and plot with the IC50 concentration in the competition assay. All FP data were repeated at least three times (n=3) to get biological replicates. 2.5 Electrophoretic Mobility Shift Assay (EMSA) To validate the identified if the inhibitors were specifically bound to ZKD-Lin28B to truly interfere with the binding of miRNA pre-let-7d to ZKD-Lin28B protein, we also evaluated them in an electrophoretic mobility shift assay (EMSA). We designed an miRNA probe pre-let-7d labelled with an IRDye800CWN fluorophore at the 5’ end and purchased them from IDT (5’IRD800CWN-UUAGGGCAGAGAUUUUGCCCACAAGGAGU ). This designed miRNA sequence required annealing by heating to a specific temperature as instructed by the company. To set up the labelled miRNA pre-let-7d probe, a PCR machine was used to heat it at 95°C for 3 minutes. The miRNA was then left on ice to slowly cool down and form the proper structure after heating and cooling properly. The first step was preparing 1X TBE buffer containing 89mM of Tris, 89mM of Boric acid, 2mM of EDTA. Second, SDS-free gel casting equipment was used to prepare an 8% native EMSA 50 gel. 2.7 mL of 29:1 polyacrylamide-Bis, 6.3 mL of ddH2O, 1 mL of 5X TBE buffer, 100 µL of 20% APS, and 10 µL of TEMED were mixed in a 50 mL tube. The liquid mixture was then poured into the gel cast and a 10-well comb was inserted. After the gel was made, it was stored in a 4°C fridge for 2 hours before running. To prepare the samples, a set of 1.5 mL Eppendorf tubes was used. The first tube contained 1 µL of 10 µM ZKD-Lin28B protein, 2 µL of 10 nM pre-let-7d-IR800CWN probe, 15 µL of ddH2O, and 2 µL of 20 mM HEPES buffer (NaOH pH 7.4, 2 mM DTT, 3 mM MgCl2, 0.05% NP-40, Protease inhibitor 1X, 0.2 µg BSA) without any ZKD-Lin28B inhibitors. The second tube was prepared with only 1 µL of 10 nM pre-let-7d-IR800CWN probe, 17 µL of ddH2O, and 2 µL of 20 mM HEPES buffer. The third tube was mixed with 1 µL of 10 µM ZKD-Lin28B protein, 2 µL of 10 nM pre-let-7d-IR800CWN probe, 15 µL of ddH2O, 2 µL of 20 mM HEPES buffer, and 1 µL of 100nM pre-let-7d (non-labelled) miRNA oligo as a competitor to show the band shifting up. The remaining tubes were used to conduct the titration of selected ZKD-Lin28B protein inhibitors from the FP assay. The contents of each tube included 1 µL of 10 µM ZKD-Lin28B protein, 2 µL of 10 nM pre-let-7d-IR800CWN probe, 13 µL of ddH2O, 2 µL of 20 mM HEPES buffer, and 2 µL of the desired concentration of ZKD-Lin28B protein inhibitors. The selected ZKD-Lin28B protein inhibitors were titrated at concentrations of 100, 200, 400, 600, 800, and 1000 µM. To prepare the samples, the reagents were added in a specific order: first water, then 20 mM HEPES buffer, followed by ZKD-Lin28B protein inhibitors, and finally ZKD-Lin28B protein. The samples were incubated at room temperature for 10 minutes, followed by the addition of pre-let-7d-IR800CWN probe and another 10-minute incubation at room temperature in the dark. 51 After incubation, 5 µL of loading dye, consisting of 0.1 M Tris-HCl pH 7.4, 0.1% bromophenol blue, 0.1% NP-40, and 50% glycerol, was added to each tube, and the samples were loaded onto a gel. The gel was run at 100V for 30-90 minutes in a non-denaturing buffer (0.5X TBE buffer) placed in the icebox and covered with a sheet to prevent light exposure. The running was stopped when the loading dye reached 70% of the gel. The glass was then removed, and the samples were imaged using the Li-Cor Odyssey 9120 Infrared Imaging. 2.6 Bio-Layer Interferometry Assay (BLI) BLI assays were conducted to quantify the direct and reversible interactions between small molecules and Lin28B protein. The OctetRED instrument (ForteBio, Bohemia, NY, USA) was utilized for this purpose. We followed the same protocol that we previously published by our group (230). Lin28B with a His-tag and Avi-Tag sequence (GLNDIFEAQKIEWHE) at its N-terminus was expressed and biotinylated in E. coli competent cells (BL21). Super-streptavidin sensors were employed and incubated with purified ZKD-Lin28B protein (50 µg/mL) at room temperature for 1 hour. Subsequently, the sensors were blocked with biocytin (10µg/mL), washed and immersed in wells containing increasing concentrations of the selected inhibitors. Buffer composition was 20 mM N-2-hydroxyethylpiperazine-N0-2-ethanesulfonic acid (HEPES), 150 mM NaCl, 500 µM tris-(2-carboxyethyl) phosphine (TCEP), and 1% of dimethylsulfoxide (DMSO). The association between ZKD-Lin28B and inhibitors was measured for 200-seconds and the dissociate was measured for 100-seconds in assay buffer. Data analysis was performed using the OctetRED software (ForteBio, Bohemia, NY, USA). 52 2.7 Real-time Quantitative Polymerase Chain Reactions (RT-qPCR) Real-time quantitative polymerase chain reaction (RT-qPCR), also known as quantitative reverse transcription PCR, is used to measure the amount of a specific RNA molecule in each sample. RT-qPCR combines the principles of reverse transcription (RT) and PCR to amplify and quantify RNA. In this study, relative gene expression levels of cell lines, DuNE, DuNE Lin28BKO, and IGROV1, were analyzed using RT-qPCR methods. The process involved three main steps: RNA extraction, reverse transcription, and RT-qPCR. RNA Extraction: RNA extraction was performed according to the manufacturer's protocol using TRIzol® (Ambion; Waltham, MA, USA). According to our lab protocol, 1 mL of TRIzol® reagent per well was added to a 6-well plate with around 80-90% cell confluence. The TRIzol® reagent was homogenized with the cells using a pipette, and after 5 minutes of incubation, the cell lysate and TRIzol® mixture were transferred to a 1.5 mL Eppendorf tube. The mixture was homogenized by flipping the tube upside down for 30 times and then incubating it at room temperature for 5 minutes. Then, 200 µL of chloroform (MAN0016835, InvitrogenTM) was added to the tube, which was shaken and reversed by hand for 30 seconds. After incubating at room temperature for 5 minutes, cell lysates were centrifuged at 12,000 g for 15 minutes at 4°C. The upper aqueous phase was transferred to a new 1.5 mL tube without disturbing the interphase or lower phase. After transferring the aqueous layer to new tubes, 500 µL of 100% isopropanol was added and shaken by hand for 30 seconds. The solution was then incubated at room temperature for another 10 minutes before centrifuging at 12,000 g for 10 minutes at 4°C. After centrifugation, the supernatant was carefully removed and the RNA pellet stayed at the bottom of the tube. Next, a new 1.5 mL tube was prepared and filled with 500 µL of 70% ethanol. The RNA pellet was 53 carefully washed with 500 µL of 70% ethanol and transferred to another tube pre-filled with 500 µL 70% ethanol. The tubes were then centrifuged at 8000 g for 5 minutes at 4°C, and most of the ethanol was removed from the tubes after the centrifugation. After the ethanol was removed, the RNA pellet was allowed to air dry for 10 minutes by putting tubes upside down on a clean paper until the pellet became transparent. Then, 20 µL of RNase-free water was added to each Eppendorf tube to dissolve the RNA pellet, followed by incubation for 10 minutes at 65°C. The RNA concentration was measured using the NanoDrop2000 machine and application. RNA quality (260/280 > 1.9 and 260/230 > 2.0) was ensured before proceeding with the reverse transcription. Reverse Transcription Step: 2 µg of total RNA was measured and mixed with 1 µL of 10X DNase Reaction Buffer (ThermoFisher; Waltham, MA, USA), 1 µL of DNase I Amp Grade reagent (Ambion; Waltham, MA, USA), and RNase-free water to create a total volume of 10 µL. This mixture was incubated at room temperature for 15 minutes, followed by the addition of 1 µL of EDTA and incubation in a PCR machine for 10 minutes at 65°C. After DNase I treatment, 1 µL of 10mM dNTP mix (Ambion; Waltham, MA, USA) and 1 µL of 10 µM Random Hexamers were added to the mixture, which was then incubated at 65°C for 5 minutes. When reverse transcribing miRNA samples, a designed 10 µM stem-loop primer was used instead of random hexamers. Next, a master mix containing 4 µL of 5X First Strand Buffer (Invitrogen; Waltham, MA, USA), 2 µL of 0.1M dithiothreitol (DTT) (Invitrogen; Waltham, MA, USA), and 0.5 µL of double-distilled water (ddH2O) was added to the solution to establish the cDNA sample for RT-qPCR. The resulting cDNA could be used immediately or stored at -20°C for future use. 54 Real-Time qPCR: Following the creation of the cDNA library, reactions were prepared using the SYBR® Green reaction mix (Roche; Basel, Switzerland) according to the company's protocols. Real-time qPCR was performed using an ABI ViiA7 machine (Applied Biosystems; Burlington, ON, Canada) with a 384-well plate. The default cycle settings on the machine consisted of 2 minutes at 50°C and 10 minutes at 95°C, followed by 40 cycles of 15 seconds at 95°C and 1 minute at 60°C. For miRNA, the housekeeping gene U6 was used, and for gene expression levels, the housekeeping gene GAPDH was used for relative quantification. Additionally, ΔΔCt values were calculated to compare different genes of interest. The real-time qPCR procedures were tested with at least three technical replicates and three independent biological replicates. Table 2.1 lists primer information. Table 2. 1 Real time-qPCR Primer Information. Primer Name Forward Primer Sequence (5’-3’) Reverse Primer Sequence (5’- 3’) ALDH1A2 TTGCAGGGCGTCATCAAAAC ACACTCCAATGGGTTCATGTC ASCL1 CCCAAGCAAGTCAAGCGACA AAGCCGCTGAAGTTGAGCC CDK1 CCAGATGGCTCTAACCTCAGT AACTTCCACGAAAAAGAGGCTT CHGA TAAAGGGGATACCGAGGTGATG TCGGAGTGTCTCAAAACATTCC CHGB CGAGGGGAAGATAGCAGTGAA CAGCATGTGTTTCCGATCTGG FOXC1 TGTTCGAGTCACAGAGGATCG ACAGTCGTAGACGAAAGCTCC FOXD3 TCACGCACCAATTCTAACGC CACGGCTTGCTTACTGAAGG GAPDH GGACCTGACCTGCCGTCTAGAA GGTGTCGCTGTTGAAGTCAGA G HEY1 GTTCGGCTCTAGGTTCCATGT CGTCGGCGCTTCTCAATTATTC 55 HMGA2 AGTCCCTCTAAAGCAGCTCAAAAG GCCATTTCCTAGGTCTGCCTC ID4 GGCCACTCAAGCAGCATTTG TCTGGTTGCCTGGTTAGGAC IGF2BP1 GGCCATCGAGAATTGTTGCAG CCAGGGATCAGGTGAGACTG LIN28B TGTAGTCTACCTCCTCAGCCAA ATTCTGCTTCCTGTCTTCCCTG miR-let-7d CCAGCTGGGAGAGGTAGTAGGT TGC CTGGTGTCGTGGAGTCGGCAA TT SCGN GGCCATTTCTGAGGCTAAACT GGGCTCCTGTTTTACTAACATCA SIX2 AAGGCACACTACATCGAGGC CACGCTGCGACTCTTTTCC SOX2 GCCGAGTGGAAACTTTTGTCG GGCAGCGTGTACTTATCCTTCT SYP TTAGTTGGGGACTACTCCTCG GGCCCTTTGTTATTCTCTCGGTA SYT4 ATGGGATACCCTACACCCAAAT TCCCGAGAGAGGAATTAGAACTT U6 GCTTCGGCAGCACATATACTAAAAT CGCTTCACGAATTTGCGTGTCAT Primer Name Stem Loop Primer Sequence (5’-3’) miR-let-7d CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGAACTATGC U6 CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGAAAAATATG 2.8 Flow Cytometry and Fluorescence-Activated Cell Sorting (FACS) Flow cytometry was used to analyze and compare the surface protein expression level before and after the treatment of cells with selected inhibitors. To detach cells from 10.0 cm non-coated plates, 3.0 mL of 1 mM ethylenediaminetetraacetic acid (EDTA, Sigma-Aldrich; St. Louis, MI, USA) was added to each dish and incubated for 2 minutes at 37°C. Cell counting was performed using a TC20™ Automated Cell 56 Counter (Bio-Rad Laboratories; Hercules, CA, USA) to ensure that each 1.5 mL Eppendorf tube had 1.0x106 cells/mL. Eppendorf tubes were labeled as unstained control, isotype control (one tube with all isotypes), positive control(s) (one tube for each fluorophore), and 7-Aminoactinomycin D (7-AAD). To prepare the CD44 (Invitrogen, Cat. 14-0441-82) and CD133 (Invitrogen, Cat. 14-1331-82) solution at a concentration of 500 nM, the primary antibody was diluted in binding buffer (20 mM PBS + HEPES + 2% FBS) instead of PBS. DuNE cells were harvested and seeded into FACS tubes at a density of 1.0x106 cells/mL. The tubes were then spun at 1300 rpm for 4 minutes, and the supernatant was removed. The cells were resuspended in 1 mL of CD44/CD133 solution and binding buffer. Four sets of samples were prepared: DuNE cells alone, DuNE cells with CD44/CD133 but no stain, DuNE cells without CD44/CD133 but with stain, and DuNE cells with CD44/CD133 and the stain. The cells were incubated at room temperature for 1 hour, followed by centrifugation at 1300 rpm for 4 minutes to pellet the cells at the bottom of the FACS tubes. The supernatant was removed, and the cells were washed with binding buffer three times. To remove the binding buffer between washes, the cell pellet was pipetted until homogenized, and the cells were spun down at 1300 rpm for 4 minutes. The cells were then stained with 1 mL of Mouse anti Rat kappa Light chain secondary antibody – PE (Invitrogen, Cat. SA5-10182) with the binding buffer on ice for 1 hour in the dark. The secondary antibody was diluted to a final concentration of 1 µg/mL. The cells were again centrifuged at 1300 rpm for 4 minutes to pellet the cells at the bottom of the FACS tubes, and the supernatant was removed before washing the cells three times with binding buffer. The cells were resuspended in 500 µL to 1 mL of FACS buffer and analyzed using a FACSCanto II flow cytometer (BD Biosciences). FlowJo 57 software (TreeStar; Woodburn, OR, USA) was used to analyze the data. Each experiment was performed in triplicates, and three independent experiments were conducted. 2.9 Western Blot Western blot assay was performed to semi-quantified and compare the protein expression difference between neuroendocrine (NE) and cancer stem cell (CSC) markers. Cells were removed from a 5% CO2 incubator and washed with cold-PBS before being transferred to 1.5 mL Eppendorf tubes. The cells were then centrifuged at 8000 g for 3 minutes at 4°C. The PBS was removed, and the cells were lysed by adding cell-lysis buffer containing 50 mM Tris-HCL (pH 8.0), 150 mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, and 0.1% sodium dodecyl sulphate (SDS) with proteinase and phosphatase inhibitors from Roche. The cells were sonicated for 30 cycles using a sonication machine (VPC provided) with settings of 10 seconds on and 10 seconds off. The lysate was then centrifuged at 12,000 g for 10 minutes at 4°C, and the supernatant was collected for protein concentration measurement using the Pierce BCA Protein Assay Kit (ThermoFisher Scientific; Mississauga, ON, Canada) following the company's protocol. After the protein concentration measurement, each well on the western SDS gel was loaded with the same amount of total protein (30-60 µg), mixed with the 4X SDS loading buffer (CSH) and boiled for 5 minutes at 95°C. An 8-15% SDS polyacrylamide gel was run using 110 voltages, depends on the molecular weight of the proteins, and the electrophoresis was performed to separate the proteins. Once the loading dye ran to the bottom of the gel, the proteins were transferred to a polyvinylidene difluoride (PVDF) membrane (Millipore; Bedford, MA, USA) using two different methods. The first method used semi-dry transfer with 25 V at 58 room temperature for 45-60 minutes with the Trans-Blot® SD Semi-Dry Transfer Cell (Bio-rad). The second method used a wet transfer cassette with a consistent 220 mA for 60 minutes at 4°C. Following the transfer process, membranes were blocked by Odyssey Blocking Buffer PBS for at least 1 hour before incubating with a primary antibody at room temperature. The membranes were then immunoblotted with specific primary antibodies (1:500 or 1:1000 dilution depending on the manufacturer's instructions in Odyssey Blocking Buffer PBS) overnight at 4°C on a shaker. The membranes were washed three times for 10 minutes each using TBS-T containing Tris-buffered saline mixed with TWEEN-20 buffer. Next, the membranes were incubated with secondary antibodies (Rabbit/Mouse/Rat IgG Polyclonal Antibody IRDye® 680RD, LI-COR Biosciences; Lincoln, NE, USA) at a dilution of 1:5000-1:10000 for 1 hour at room temperature in a sealed dark box. After removing the secondary antibody incubation, the membranes were kept in a dark environment while washing with TBS-T three times for 10 minutes at room temperature. Finally, the membranes were scanned using the ImageStudio® Odyssey Densitometry and a specific analysis application provided by Vancouver Prostate Centre. Table 2.2 provides all the antibody information. Table 2. 2 Antibody List. Antibody Vendor Catalogue Number Application Dilution CD44 eBioscience 14-0441-82 WB, FC, IF 1:500 CD133 eBioscience 14-1331-82 WB, FC, IF 1:500 beta-Actin Santa Cruz sc-1615 WB, IF 1:1000 N-Cadherin Santa Cruz Sc-7870 WB 1:1000 Lin28B Abcam Ab71415 WB 1:1000 SYP Santa Cruz Sc-17750 WB, IF 1:1000 59 SOX2 Cell Signaling 3579S WB 1:1000 Vinculin Sigma Aldrich V9131-2ML WB 1:1000 *FC = Flow Cytometry *IF = Immunofluorescence *WB = Western Blot 2.10 Cell Proliferation Assay 2.10.1 CellTiter 96® Aqueous One solution Cell proliferation assays were performed to examine the impact of our selected Lin28B inhibitors have better inhibition effect onthe neuroendocrine prostate cancer proliferation rate. The CellTiter 96 Aqueous One kit (Promega Corporation) was used to perform a cell viability assay following the manufacturer’s protocol. Proliferation rates were measured at an optical density (OD) of 490nm every other day for 5 days post-seeding on a 96-well plate (Invitrogen). An additional set of wells was prepared with medium only to subtract the background. The cells were then incubated in a 37°C 5% CO2 incubator for the desired period of treatment, followed by the addition of 20 µL of solution reagent containing a tetrazolium compound [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium, inner salt; MTS] and electron coupling reagent (phenazine ethosulfate; PES) into each well using a multichannel pipette. Viable cells formed a coloured formazan product, and the plate was incubated for 2 hours at 37°C. The plate was then read at an absorbance of 490 nm using the Microplate Spectrophotometer (EPOCH, BioTek). Each experiment contained at least three technical replicates, and the proliferation data were generated by performing three independent experimental repeats. 60 2.10.2 Incucyte® Cell Proliferation Assay The Incucyte® cell proliferation assay was performed using the IncuCyte® S3 Live-Cell Analysis System (Satorius). Cells were harvested and resuspended at a concentration of 2x104 cells/mL in growth medium. An optimized number of cells (t-NEPC cell line DUNE in 4000 cells) were seeded onto a 96-well plate (Invitrogen) in 50 µL/well and incubated overnight in a 37°C incubator with 5% CO2 to allow attachment to the plate surface. The following day, another 50 µL of medium, along with the calculated concentration of ZKD-Lin28B inhibitors, was added to each well, and the plate was immediately read in the IncuCyte® machine to obtain the day 0 reading. The plate was then read every 12 or 24 hours, depending on the experimental design, and the IncuCyte® software was used to analyze the plate after each reading to calculate changes in cell population. After 5 days of reading, the cell confluence analyzed data was exported as raw data and normalized with Day 0 to obtain the cell proliferation data. Each experiment contained at least three technical replicates, and three independent experiment repeats were performed to generate the proliferation data. 2.11 Colony Formation Assay The principle of colony formation assay is to assess the ability of individual cancer cells to grow and form 3D colonies under treatment and treatment-free condition. For colony formation assays, 2000 cells of DUNE and DUNELin28BKO were seeded in 0.7% soft agar with a 1% soft agar bottom base coating. The 1% agar (DNA grade) and 0.7% agar were warmed with a microwave and placed in a 40°C water bath to slowly cool down. 2X DMEM + 20% FBS was also prepared in the biosafety cabinet and placed in the 40°C water bath. Equal amounts 61 of 2X media and 1% agar were mixed to give a final 0.5% agar + 1X DMEM + 10% FBS, which was then allowed to set in the plate in the biosafety cabinet. The cells were resuspended in 2X DMEM + 20% FBS medium and gently mixed with an equal volume of 0.7% agar. The cells were then plated on top of the base agar and 1 mL media was added to prevent the plate from drying. On the second day, the media was changed with media containing chemicals with desired concentration and stained with crystal violet after 10-14 days, depends on the colonies size. The entire well was imaged by stitching 5X field images together, a feature on the Zeiss AxioObserver Z1 microscope. Colony numbers were counted according to their diameter (>100 µm or 100–300 µm and >300 µm). Three technical replicates and three independent biological replicates were performed. 2.12 Microsomal and Solubility Assay Solubility: A solubility assay was performed to determine the solubility of certain compounds in a particular solution, and further identified suitable formulations for further testing or modification. The compounds being tested were prepared as stock solutions of 50 mM in dimethyl sulfoxide (DMSO) and then diluted 50-fold in methanol (MeOH), Dulbecco’s Modified Eagle Medium (DMEM) with 5% charcoal-stripped serum (CSS) from Sigma-Aldrich (media), and phosphate-buffered saline (PBS). The resulting mixtures were vortexed at room temperature for 1 hour at 800 rpm, and then centrifuged at 20,000 g for 5 minutes. The saturated supernatants were diluted 40-fold in acetonitrile, and their solubility was determined using LC/MS/MS. 62 Microsomal: Microsomal assay was performed to assess the metabolism and potential toxicity of drug candidates. Using subcellular structures derived from cells that contain drug-metabolizing enzymes, to simulate the metabolic reactions that occur in the human body. The mouse liver microsomal system (Xenotech, M1000) enriched with nicotinamide adenine dinucleotide phosphate and NADPH (BD Biosciences, San Jose, USA) was used to carry out the in vitro microsomal stability assay. Compounds ZKD-Lin28B inhibitors were used at a concentration of 1 µM and incubated with a reaction mixture containing liver microsomal proteins (0.15 mg/mL) in 100 mM potassium phosphate buffer (pH 7.4). The reaction was initiated using NADPH and then incubated at 37°C for different time points, with the timer set precisely. At each time point, one tube of reaction aliquot was taken and quenched with three volumes of acetonitrile containing 0.05% formic acid. The samples were vortexed and then centrifuged at 16,000 rpm for 10 minutes at 4°C to pellet any solids. The supernatants were collected and analyzed by LC/MS/MS to determine the remaining percentage and the half-life (t=1/2). The compound peaks were integrated, and the resulting AUC values and time points were fit to a one-phase decay equation. The activity of the microsomes of the assay was confirmed using imipramine as a positive control with a t=1/2 of 24 minutes (216). 2.13 Statistics Statistical analyses were carried out using GraphPad Prism (version 8). All results are expressed as the mean ± SD. One-way ANOVA or unpaired Student’s t-tests were carried out to determine differences between groups. The correlation between two expression groups was measured by Pearson’s r correlation coefficient. The level of significance was set at P < 0.05. In 63 figures, P < 0.05, P < 0.01, P < 0.001, and P < 0.0001 are denoted as *, **, ***, and **** respectively. 64 Chapter 3: Result 3.1 Identification of a Novel Docking Pocket for Lin28B Binders The first crucial step in finding Lin28B inhibitors is determining which domain to target. Since Lin28B has both CSD and ZKD domains, both domains are potential targets as they help the protein to adopt a favorable structure for pre-let-7 miRNA binding (Figure 3.1A). However, we chose in this study to target ZKD based for the following reasons: Firstly, previous research has demonstrated that ZKD is the most crucial domain for recruiting TUTases for oligouridylation of let-7 precursors (212). Secondly, another study has identified ZKD as a potential therapeutic target for Lin28-driven diseases and has also reported an inhibitor that inhibits Lin28 activity (222). Thirdly, the GGAG motif that is present in all let-7 members, except for one, binds to a pocket in the ZKD domain (209). Deleting the GGAG motif demonstrated that the ZKD-GGAG binding is functionally essential for suppressing let-7 maturation (209). Furthermore, the specificity of the ZKD binding was demonstrated by measuring the dissociation constant of various analogs of GGAG (226). Substituting the first and second Gs to A led to a 4-to-13-fold reduction in overall let-7 binding affinity, suggesting that these nucleotides are necessary to form critical contacts with the protein. The recruitment of TUTase, which is essential for the inhibition of Dicer processing, occurs through recognition of GGAG (227). In contrast, CSD accommodates a highly variable structure of let-7 miRNA, and the pocket presented within that domain appears unfavorably flexible for small molecule binding (201). Therefore, we used the crystal structure of the Lin28A protein (PDB:5UDZ) (228) as both Lin28A and Lin28B share the same amino acid sequence for this area and conducted a 65 computational search for plausible drug-binding sites on the surface of both ZKD and found that indeed the ZKD pocket where the GGAG-motif of pre-let7 binds, scored at the top of potential druggable sites. We thus visually examined the binding pocket and found that it is large enough to accommodate small molecules and deep enough to provide potential for strong ligand binding (262). We used our previously reported computer-aided Drug Design (CADD) pipeline to perform an initial virtual screening of 1 billion compounds from the Enamine library database using our in-house developed DeepDocking tool (220) coupled with Glide docking software (218) (Figure 3.1B). DeepDocking utilizes machine-learning docking score prediction to expedite screening large compound libraries (Figure 3.1C). We sampled the entire ZINC20 database (247) for docking and used docking scores to train models and predict the compounds that were not docked. This allowed our computational model to exclude the prediction of poor-binding molecules. The top 18 million compounds that highly scored using DeepDocking software, were then redocked with Glide docking software, resulting in 1 million compounds that were retained (Figure 3.1B). We calculated the spatial difference between the docking poses produced by FRED software (OEDocking by OpenEye) (248) after redocking the 1 million compounds with FRED. We removed compounds with significantly different docking poses (RMSD >2Å) and retained about 275,000 compounds that were then subjected to ADMET filtering to eliminate potentially toxic compounds (262). Furthermore, we screened the remaining library for molecules that could mimic the GGAG motif and ZKD-Lin28B interaction. We postulated that an active compound should form similar contacts with Lin28 residues as the native ligand, i.e., the GGAG motif. We performed a 66 30ns molecular dynamics simulation of the protein-RNA complex to identify which residues contributed most to the binding of ZKD-Lin28 and GGAG motif. We observed that amino acid residues Lys159, Lys160, His162, and Val171 formed the most stable and robust bonds with the ribonucleotides (Figure 3.1D and Figure 3.1E). Therefore, these residues were selected as pharmacophore features, i.e., requirements to act as hydrogen donors or acceptors. The developed pharmacophore features were then used to filter the remaining 275,000 compounds, resulting in around 150,000 compounds. The substantial retention indicated that docking had already top-ranked the compounds that formed stable bonds with these residues. We performed additional scoring with MOE SVL scripts (e.g., number of hydrogen bonds, number of rings, IogP) to guide expert selection of the compounds. Finally, the top 163 compounds were purchased for experimental validation. All content in this section, including descriptions and figures, was initially made by Chia-Hao Ho and Mariia Radaeva. Permission to use and reproduce this content was obtained from the original authors (262). 67 Figure 3. 1 Computer-aided drug design (CADD) of ZKD-Lin28B protein inhibitors. (A) Cold shock domain (CSD) in green and zinc knuckle domain (ZKD) in blue connected in bi-partite manner by pre-let-7 (white ribbon). (B) The CADD pipeline employed to find 163 potential ZKD-Lin28B protein inhibitors. (C) DeepDocking workflow. (D) Interaction of ZKD-Lin28B protein and two let-7 nucleotides (first guanine and the adenosine of the GGAG motif). The residues that form hydrogen bonds (in red dotted lines) used for pharmacophore features are in red boxes. (E) Lin28B – let-7 nucleotides (first G and A) contacts timeline over the 30 nanosecond MD simulation. The residues forming most stable contacts are in red boxes. B CD EAFigure 1. Computer-aided drug design (CADD) of ZKD-Lin28B protein inhibitors. A) Cold shock domain (CSD) in purple and zinc knuckle domain (ZKD) in orange connected in bi-partite manner by pre-l t-7 (whit ribbon). The GGAG motif is highlighted in blue and the surface of the proposed binding pocket is colored in green. B) The CADD pipeline employed to find 163 potential ZKD-Lin28B protein inhibitors. C) DeepDocking workflow. First, for each molecule in the database molecular descriptors are calculated. These descriptors are then used to cluster molecules. Second, molecules are sampled from clusters and docked into the target protein. Third, the derived docking scores and corresponding molecular descriptors are used to build machine learning models that predict docking scores of undocked compounds. With each iteration, docking Tyr140Asn141His148Ala149Lys150Cys152Leu154Gln157Pro158Lys159Lys160Cys161His162Met179Val171Ala1720 5 10 15 20 25 30Time (nanoseconds) 68 3.2 Establishment of the Fluorescence Polarization Assay to Screen ZKD-Lin28B Inhibitors Fluorescence polarization (FP) has been widely used to measure protein-nucleic acid interactions (223,224). In RNA-binding protein research, the FP assay is especially useful for developing or screening small molecule drugs that can disrupt RNA-protein binding. It provides real-time data in a short amount of time and can help determine if the inhibitors bind to the target protein (ZKD-Lin28B). We used a fluorophore-tagged miRNA probe (pre-let-7d) to measure its binding to ZKD-Lin28B. When the pre-let-7d binds to the Lin28B protein, the resulting complex is large and rotates slowly, causing high polarized light emission. If potential inhibitors interact with the binding pocket and compete with the tagged probe, the free tagged probe is released into the solution and causes non-polarized light emission, resulting in a low FP signal. To develop an FP assay for small molecules screening, we first purified recombinant Lin28B ZKD domain (ZKD-Lin28B). The Lin28B construct was expressed using BL21 (DE3) bacterial competent cells and purified using the Nickel-NTA purification process described in Method 2.3.3. We designed a human miRNA pre-let-7d probe labeled with fluorescein amidites (FAM) on the 3-prime region (IDT). We chose pre-let-7d as its expression level is the most decreased among pre-let family members in the t-NEPC (230). Additionally, introducing let-7d mimic decreased HMGA2 expression, an identified oncoprotein, in the DuNE cell after eliminating by using spg-let-7d (85). Moreover, let-7d has been recognized as a prominent prognostic and predictive marker in various cancer types (224). Importantly, pre-let-7 possesses the GGAG motif essential for binding to our selected target region on ZKD (211). Therefore, the pre-let-7 probe would effectively act as a competitor for the designed inhibitors. Based on the above information and published results, 69 our design of pre-let-7d RNA oligonucleotides will likely have a high-affinity score and interact with ZKD-Lin28B protein. We first titrated the pre-let-7d-FAM probe (1nM-50µM) with a fixed concentration of ZKD-Lin28B protein (10µM) (Figure 3.2B). As the probe concentration increased, the FP signal dropped, indicating more of the free probe was rotating in the solution and thus confirming the direct binding of the protein and the labelled nucleotides. Next we titrated Lin28B protein (1nM to 50µM) into a fixed concentration of 1nM of the pre-let-7d-FAM probe. As we increased the protein concentration, the FP signal increased, indicating more protein-RNA binding had occurred in the solution and fewer free rotating probes were detected (Figure 3.2C). These FP assay experiments confirmed that 10 µM of Lin28B protein and 1 nM of the pre-let-7d-FAM probe are the best concentrations for maximizing the FP signal. We thus performed using these concentrations, a competition assay that measured the competitive binding of an unlabeled oligonucleotide with the protein. We titrated unlabeled pre-let-7d probe into 10µM of ZKD Lin28B protein and 1nM pre-let-7d-FAM. As we increased the unlabeled probe concentration, it competed out the labelled probe and replaced it into the ZKD-Lin28B binding pocket. A decrease in FP signal output was demonstrated since more free labelled probes rotated, causing more depolarized light to be detected (Figure 3.2D). With the dose-dependent of FP results, indicated that our established FP assay is suitable for quantifying our Lin28B-Let-7 binding events. Both short ZKD-Lin28B protein and FL-Lin28B protein (Figure 3.2B-D) FP results demonstrated that our FP assay is valid for screening inhibitors on such interactions. The same procedure was performed with Lin28A protein, both full-length and ZKD domain, and similar results were obtained (Figure S1). 70 Figure 3. 2 Establishment of the Fluorescence Polarization Assay. (A) Graphical representation of FP assay principle. As the labelled probe floats freely in the solution, it rotates more rapidly producing lower FP signal. In contrast, when the labelled probe binds to the protein, it rotates slower and produces higher FP signal. (B) 10 µM of protein with pre-let-7d-FAM titration (9 replicates). Top: ZKD-Lin28B protein; Bottom: FL-Lin28B protein. X-axis represents log of concentration in nM, Y-axis represents FP signal mP readout from the TECAN 500 machine. (C) 1 nM of pre-let-7d-FAM with Lin28B protein titration (9 replicates). Top: ZKD-Lin28B protein; Bottom: FL-Lin28B protein. (D) Competition assay using non-labeled pre-let-7d-FAM probe (9 replicates). Top: ZKD-Lin28B protein; Bottom: FL-Lin28B protein. 71 3.3 Established FP Assay on Raw Screening of Ln1 – Ln193, ZKD-Lin28B Protein Inhibitors. To screen the compounds selected through the CADD pipeline Ln1-Ln193 (total 163 molecules), we prepared them at 1 mM in 100% DMSO. We screened all the molecules at 20µM and considered as potential candidates molecules that showed at least 60% inhibition at this concentration (Figure 3.3). Preparation of potential inhibitors and FP was described in material and methods 2.3.3. In the FP raw screening experiment design, higher the FP remaining signal means lower the inhibition percentage. So, we screened for the compounds that had the lowest FP remaining signal which meant the compounds had the highest inhibition ability in the Lin28B-Let-7 interaction. Li71 and 1632, reported Lin28B inhibitors, were included in this experiment design and used as standards to select compounds that had better inhibition. Our positive control was Lin28B with labeled pre-let-7d having 100% of FP remaining signal (0% inhibition). Negative control was unlabeled pre-let-7d competed out the labeled pre-let-7d resulting in 0% of FP remaining signal (100% inhibition). With 40% FP remaining signal (60% inhibition) cut-off, we screened out 15 active compounds, achieving a hit rate of 9% (15/163) (Figure 3.3A). Compounds that passed this initial FP raw screening assay were selected for FP titration analysis and electrophoresis mobility shift assay (EMSA). We further tested these 163 compounds with the same setup but using full-length Lin28B protein. We observed that none of the compounds passed the threshold of 60% inhibition (Figure 3.3B). 72 Interestingly, the reported inhibitors of CSD, Li71, and 1632 (binding domain undefined) showed remarkably low inhibitions in the ZKD-Lin28B assay of just around 30% and 20% inhibition, respectively, while some compounds as Ln7, Ln15, and Ln115 demonstrated about 50% , 50%, and 20% inhibition in FP signals, respectively. These results suggest that the identified ZKD-Lin28B inhibitors can be sufficient to interrupt the binding between ZKD-Lin28B and pre-let-7d, consistent with our rational drug design using the CADD pipeline model. 73 Figure 3. 3 Fluorescence Polarization Assay for Raw Inhibitors screening on Lin28B Protein. (A) Raw screening of 163 compounds was performed using FP assay on ZKD-Lin28B. (B) FL-Lin28B protein FP screen for 163 compounds. X-axis represents 20µM of the treatment of each chemical (Ln1-Ln193), while Y-axis represents the percentage of binding left after the treatment of compounds. Positive control (P-Ctrl) contained Lin28B protein with pre-let-7d-FAM and the reaction buffer. Negative control (N-Ctrl) contained Lin28B protein with pre-let-7d-FAM and pre-let-7d probe and the FP buffer. Li71 and compound 1632 were reported Lin28B inhibitors and were used as positive controls. Compounds with an average remaining fluorescence below 40% were consider as potential candidates for Lin28B protein inhibitors. 74 3.4 Electrophoresis Mobility Shift Assay (EMSA) and FP Titration Demonstrate ZKD-Lin28B Inhibitors Block the Interaction of ZKD-Lin28B and pre-let-7d. To validate the identified molecules, we used Electrophoresis mobility shift assay (EMSA) that uses band shift on the gel to measure the affinity of protein-nucleic acid interactions (234, 235). We performed EMSA to determine whether the compounds interfere with ZKD-Lin28B protein binding to the miRNA. We used the same miRNA sequence (pre-let-7d) to design the EMSA probe, but this time, the oligo probe was labeled with the IRDye800CWN fluorophore. when IRDye800-pre-let-7d probe is unbound, it small molecular weight makes it run to the bottom of the gel along with the EMSA loading dye. However, when IRDye800-pre-let-7d probe is bound to ZKD-Lin28B protein, the molecular weight of the complex is larger, and thus the the probe bands is shifted to the upper part of the gel and is clearly separted from the free probe band. We observed robust inhibition effects from Li71, Ln7, Ln15, and Ln115 but not 1632. While our selected Ln7 compound only showed band shifting at concentrations ≥ 1000 µM, Ln15 showed potent inhibition of the ZKD-Lin28B and pre-let-7d complex at 400 µM, and Ln115 demonstrated strong efficacy, blocking the interaction at 800 µM (Figure 3.4A). Despite detecting a dose-dependent inhibition of ZKD-let-7d in the remaining 8 molecules by FP assays (Figure S2), we were not seeing this inhibition effect disrupting the binding event in the EMSA assay. Most likely due to the lower sensitivity of the EMSA (Figure S3). To compare inhibitors selected from the raw screening and EMSA assay, we performed an FP titration assay. The results showed that compounds Ln7, Ln15, and Ln115 had IC50s of approximately 45 µM, 9 µM, and 21 µM, respectively (Figure 3.4B). In contrast, the reported 75 inhibitor, positive control Li71, had an IC50 of 55 µM, and compound 1632 only achieved around 50% inhibition. By combining EMSA and FP titration, we not only demonstrated the chemical interference of ZKD-Lin28B/pre-let-7d binding and the dose-dependent effect but also gained more information about potential inhibitors such as Ln7, Ln15, and Ln115, which are the three lead inhibitors for further cell biological assays. FP and EMSA results indicated that the three selected lead compounds, Ln7, Ln15, and Ln115, disrupted ZKD-Lin28B and pre-let-7d interactions. Ln135 Ln135 Ln135 Ln135 Ln135 Ln135 Ln135 Ln135 Ln135 Ln135 Ln135 Ln135 Ln135 Ln135 Ln135 Ln135 76 Figure 3. 4 Direct binding assays and FP dose-dependent assays of the three selected compounds. (A) The setup contained 0.5 µM of ZKD-Lin28B protein with 10 nM of the IR800CWN-pre-let-7d probe. The "Pre-let-7d Comp" refers to the non-labeled probe competitor. The positive control included only the IR800CWN-Pre-let-7d probe, while the negative control contained both the labeled probe (IR800CWN-pre-let-7d) and ZKD-Lin28B protein. The "Comp" band corresponds to the competition setup where both labeled (IR800CWN-pre-let-7d) and unlabeled probes (pre-let-7d) were present together with the ZKD-Lin28B protein. The numbers represent chemical concentrations in µM. (B) Dose-dependent effect of selected hit compounds in FP titration: The dose-dependent effect of selected hit compounds was tested in FP titration (1 nM-100 µM) with 10 µM ZKD-Lin28B and 1 nM of pre-let-7d-FAM. 77 3.5 Bio-Layer Interferometry (BLI) Assays to Validate the Selected Inhibitors After EMSA and titration of FP assays, we also used biolayer interferometry assay (BLI) to validate that the chemicals directly bind to the ZKD domain of Lin28B in a reversible and dose-dependent manner. First, we attached the biotinylated Avi-tagged purified protein, ZKD-Lin28B, to the streptavidin biosensors. Then, we dipped the sensor plates into wells containing increasing concentrations of Ln7, Ln15, or Ln115 and generated the KD value for analysis. Only Ln115 demonstrated excellent binding and reliable curves, showing an estimated KD of 60 ± 4 µM (Figure 3.5A). While Ln7 did not show the binding event on the BLI assay, Ln15 did not produce solid BLI curves and signals despite several optimizations and trials. Nevertheless, the combination of three different techniques, FP, EMSA, and BLI, supports our conclusion that Ln7, Ln15, and Ln115 are potential ZKD-Lin28B inhibitors that can prevent the interaction. Three chemical structures are shown in Figure 3.5B. 78 Figure 3. 5 Bio-laryer interferometry (BLI) assay of Ln115 with ZKD-Lin28B. (A) Bio-layer interferometry (BLI) assays were performed using 0-25 µM of Ln115 compound with ZKD-Lin28B-Avi tagged. (B) Three potential inhibitors structures of the lead selected compounds, Ln7, Ln15, and Ln115. 79 3.6 Selected Lin28B Inhibitors Block Both Lin28A and Lin28B Protein Isoforms. It has been reported that Lin28A and Lin28B have minor differences in their amino acid sequences. Therefore, we hypothesized that it is highly possible that Lin28B inhibitors can also block Lin28A isoforms. This could expand the usage of Lin28 inhibitors to treat various types of tumors that are driven by the Lin28 pathway. We performed EMSA assays using ZKD-Lin28A purified protein and our selected inhibitors, Ln7, Ln15, and Ln115 (Figure 3.6A). The inhibition results showed that Li71 and Ln15 inhibited at around 200-600 µM. However, 1632, Ln7, and Ln115 did not have any inhibitory effect even at a high concentration of 1200 µM. In contrast, FP titration using ZKD-Lin28A protein demonstrated that Ln7, Ln15, and Ln115 had a dose-dependent suppression of FP signals (Figure 3.6B). To confirm that our three lead inhibitors can block Lin28A activity and help restore the Let-7d expression level, we conducted RT-qPCR using the IGROV1 cell model, which only expresses Lin28A but not Lin28B protein (263). We observed that all three lead compounds and positive control Li71 and 1632 upregulated the miRNA let-7d expression levels (Figure 3.7C). Ln15 had the most potent inhibition effect and induced a 10-fold upregulation of let-7d. All inhibitors were shown to suppress the expression of SOX2 and HMGA2 levels as well. Combining the EMSA, FP, and RT-qPCR data, we have concluded that the newly discovered Lin28B inhibitors can block the activity of both Lin28A and Lin28B protein isoforms. 80 Figure 3. 6 Direct binding EMSA assays and FP dose-dependent assays of the three selected compounds. (A) The setup consisted of 0.5 µM of ZKD-Lin28A protein with 10 nM of the IR800CWN-pre-let-7d probe. The "Pre-let-7d Comp" refers to the non-labeled probe competitor was added to compete out pre-let-7d probe. The positive control included only the IR800CWN-Pre-let-7d probe, while the negative control contained both the labeled probe (IR800CWN-pre-let-7d) and ZKD-Lin28A protein. The "pre-let-7d Comp" band corresponds to the competition setup where both labeled (IR800CWN-pre-let-7d) and unlabeled probes (pre-let-7d) were present together with the ZKD-Lin28A protein. The numbers represent chemical titrations in µM. (B) Dose-dependent effect of selected hit compounds in FP titration: The dose-dependent effect of selected hit compounds was tested in FP titration (1 nM-100 µM) with 10 µM ZKD-Lin28A and 1 nM of pre-let-7d-FAM. 81 3.7 Selected ZKD-Lin28B Inhibitors Regulate the Let-7d Expression and Block Lin28B Functions in t-NEPC Cancer Cells. We next tested if the observed inhibition of pre-let7 binding to Lin28B translates into an increase of let-7 maturation. We thus measured the expression levels of let-7 in DuNE cell lines using RT-qPCR. We observed a 6 to 7-fold increase in the expression of mature let-7d in the DuNE cell line when treated with 20 µM of Ln7, Ln15, and Ln115 compounds (Figure 3.7A). Furthermore, after 48 hours of treatment, these chemicals showed no significant toxicity on DuNE Lin28BKO cells, excluding any off-target effect of the compounds (Figure 3.7B). The control compound Li71 produced a 5-fold increase, while 1632 did not affect the expression of mature let-7. Thus, Ln7, Ln15, Ln115 and Li71 induced the expression of mature let-7d levels by approximately 5-8 folds in the RT-qPCR analysis. Consistently, we tested the expression of Lin28B/let-7 pathway-regulated genes, namely HMGA2 and SOX2 (Figure 3.7). These genes are critical hubs in the stem-like pluripotency gene network as they activate oncogenic pathways, including MAPK/ERK, TGFß/Smad, PI3K/AKT/mTOR, NFkß, and STAT3 (237-239). Previous studies from our lab confirmed that the downregulation of let-7 leads to a increase in SOX2 and HMGA2 expressions (230). Indeed, Ln7, Ln15, and Ln115 treatment reduced the levels of SOX2 transcripts by approximately 60% (Figure 3.7). HMGA2 expression decreased by approximately 60% (±3%) and 40% (±5%) upon treatment with upon treatment with Ln15 and Ln115, respectively. Compound Li71 reduced the expression of HMGA2 and SOX2 by 40% ± 5%. These results indicate that blocking the binding of Lin28B to the pre-let-7d by our identified Ln7, Ln15, and Ln115 compounds, result in an increased 82 maturation of let-7d and subsequently a downregulation of reported oncogenes such as SOX2 and HMGA2 in neuroendocrine prostate cancer cells. To exclude off-target effect, we used the DuNELin28BKO cell line and observed minimal or no impact on the expression of Let-7d, HMGA2, and SOX2 (Figure 3.7B). In addition, supplementary figure S4 demonstrated the inhibitors treatment reduced the protein expression of HMGA2 and SOX2. 83 Figure 3. 7 RT-qPCR on Ln7, Ln15, and Ln115 to restore miRNA let-7d expression levels and decrease expression of SOX2 and HMGA2 genes. (A) RNA expression levels of let-7d, SOX2 and HMGA2 in DuNE cell line after inhibitors treatments. (B) RNA expression levels of let-7d, SOX2 and HMGA2 in DuNELin28BKO cell line after inhibitors treatments. (C) RNA expression levels of let-7d, SOX2, and HMGA2 in IGROV1(Lin28A) cell line after inhibitors treatments. All results were analyzed after 48 hours of 20 µM inhibitors treatments. X-axis represents treatment of different compounds, while Y-axis represents relative gene expression in fold-change (n=9 replicates). Three biological replicates were performed, and all results are presented as mean ± SD. Statistical analyses were performed with P≤0.05-(*), P≤0.01-(**),P≤ 0.001-(***). 84 3.8 Selected ZKD-Lin28B Inhibitors Regulate Cancer Stem-cell (CSC) and Neuroendocrine (NE) Biomarkers Expression in t-NEPC Cell Line. Four genes - OCT4, SOX2, NANOG, and Lin28A/B - are known to reprogram somatic cells to pluripotent stem cells, and they are also considered biomarkers of cancer stem cells (CSCs) in tumors that develop treatment resistance (240-244). Our previous studies have shown that cancer stem cell markers and neuroendocrine (NE) markers decrease expression upon knocking out Lin28B in the t-NEPC cell model (230). Therefore, we conducted experiments to determine whether our selected Lin28B inhibitors could regulate the expression of both CSC markers and NE biomarkers in our DUNE cell model. Using real-time qPCR, we assessed the expression of a set of CSC markers including IGF2BP1, CDH2, FOXD3, HEY1, ALDH1A2, CDK6, FOXC1, SIX2, and ID4 in our established DUNE cell line (230). Treatment with our selected inhibitors led to a significant reduction in the expression of all CSC markers (Figure 3.8A). Notably, Ln115 was able to suppress the expression levels of CDH2 and FOXD3 by up to 90%. In contrast, previously reported inhibitors, Li71 and 1632, showed only mild or no suppression effects on CSC markers. We also evaluated the expression levels of NE markers including ASCL1, CHGB, SCGN, SYP, and SYT4. These NE markers were significantly reduced in the DuNELin28BKO cell model as well since knockout Lin28B in the NE cells would reduce NE markers expression (230). Treatment with our selected compounds resulted in the most significant suppression of SCGN, ASCL1, SYP, and SYT4 markers (Figure 3.8B). Li71 and 1632, our control molecules, produced a lesser suppression effect on the expression of all NE markers. 85 Figure 3. 8 Potential ZKD-Lin28B inhibitors regulate cancer stem cell and neuroendocrine biomarkers in DUNE cell line. (A) Real-time PCR measured the mRNA levels of cancer stem cell (CSC) markers and (B) neuroendocrine (NE) markers in DuNE cell line expression. All measurements were taken after 48 hours of 20µM chemical treatments. Three biological replicates were performed, and all results are presented as mean ± SD. Statistical analyses were performed with P≤0.05-(*), P≤0.01-(**), P≤ 0.001-(***). 86 3.9 Selected ZKD-Lin28B Inhibitors Suppress the DuNE Cancer Cell Stemness Phenotypes. We conducted experiments to investigate the effect of our selected Lin28B inhibitors on cancer stem-cell surface markers, CD133 and CD44, using flow cytometry (FACS) in DuNE Lin28BKO and DuNE cell lines. CD133 and CD44 are associated with therapy resistance in various cancers, including prostate cancer (245,246). We observed a shift in CD133 and CD44 expression in DuNE cells and confirmed that neuroendocrine characteristics affected CSC surface markers expression (Figure 3.9A). Treatment with three potential ZKD-Lin28B inhibitors in DuNE cells resulted in decreased CD44 and CD133 protein expression levels compared to the control (Figure 3.9A). We also measured the protein levels of CD44, CD133, and SYP (a NE biomarker) using an immunoblotting assay. The levels of CD44, CD133, and SYP were significantly reduced in cells treated with Ln15 and Ln115 compared to cells treated with reference compounds Li71 and 1632. Furthermore, the level of CD44 protein in Ln115-treated DuNE cells was similar to that in DuNE Lin28BKO cells (Figure 3.9B). Next, we conducted a cell proliferation assay mainly on DuNE and DuNELin28BKO cell lines. All three selected inhibitors suppressed proliferation by up to 80%, but the DuNELin28BKO cells were not affected, confirming that the inhibition effects only targeted Lin28 proteins. In addition, the IGROV1 cell line, which expressed Lin28A only, showed inhibitory effects using the three selected compounds compared to the vehicle (Figure 3.9C). Finally, we performed colony formation assays to assess the suppression of the selected Lin28 protein inhibitors on self-renewal and cancer stemness of DuNE cells. The clonogenic assay allowed us to estimate the levels of malignancy and reproductive viability (248). The DuNE cell 87 line treated with 20µM of the selected chemicals produced fewer colonies than the DuNE cell line treated with vehicle, Li71 and 1632 treated, and the effect was particularly notable in Ln15-treated cells (Figure 3.9D and Figure S5). 88 Figure 3. 9 The ZKD-Lin28B inhibitors suppress cancer stem cell phenotypes of cancer cells. (A) FACS analysis using of CD44-APC and CD133-PE fluorescence antibodies collected CSC cell populations from DuNE and DuNELin28BKO cell lines with Vehicle or 20 µM of selected inhibitors Ln7, Ln15, and Ln115 for 48 hours treatments. (B) Lin28B, SYP, CD44, and CD133 immunoblotting assays (triplicates performed). Beta-actin (ß-actin) serves as loading control and Lin28B immunoblotting confirms the DuNELin28BKO cell lines. (C) Cell proliferation assays were measured in the presence of 20 µM of Ln7, Ln15, and Ln115 on DuNE, DuNELin28BKO and IGROV1 cells for every 48 hours from Day0 to Day5. (D) Quantification of colony formation assays (colonies > 100 µM were counted). Ln7, Ln15, and Ln115 at 20 µM concentration treatment after 89 24 hours of the cell seed and colonies counted at Day 12. Three biological replicates were performed, and all results are presented as mean ± SD. Statistical analyses were performed with P≤0.05-(*), P≤0.01-(**), P≤ 0.001-(***). 90 3.10 Solubility and Microsomal Stability of Selected Compounds Metabolic stability assays are widely used in drug development to guide structural modifications, predict in vivo performance, develop structure-metabolic stability relationships, and select compounds for animal trials. However, these methods are frequently developed and validated using commercially available drugs. Despite the differences between commercial and drug discovery compounds, many drug discovery compounds have high lipophilicity, high molecular weight, and low solubility (253). It is recommended that drug discovery compounds have a solubility greater than 60 ug/mL (254). To evaluate the metabolic stability of our hit compounds, we performed microsomal stability assays using intrinsic clearance rate (µL/min/mg protein) to compare different compounds. In humans, a low intrinsic clearance rate indicates a compound with high clearance (<8.6 µL/min/mg), whereas a high intrinsic clearance rate indicates a compound with low clearance (>47.0 µL/min/mg). We aimed to identify hit compounds with both low clearance rate, high solubility, and long half-life. Combined with FP, EMSA, RT-qPCR, and cell-based assays we most focusing on comparing Ln7, Ln15, and Ln115 to other 8 compounds were stood out from FP raw screening (Table 3.1). Notably, Ln15 had the lowest clearance rate and the highest solubility in PBS and FBS/Media, suggesting it may be a promising candidate for further development and animal studies. These findings suggest that both Ln15 and Ln115 are stable and soluble enough to reach therapeutic concentrations in the bloodstream. 91 Compounds Microsomal stability Solubility Half Life (min) Clearance (μl/min/mg) PBS (μl) FBS/Media (μl) LN7 51 45 210 644 LN15 346 7 1155 1073 LN27 40 60 46 311 LN115 476 5 365 990 LN121 54 43 268 987 LN135 186 13 16 531 LN162 29 84 88 1245 LN184 93 25 32 802 LN188 421 6 637 997 LN189 2 777 41 1173 LN193 539 4 410 77 Impiramine 21 125 Table 3. 1 Microsomal Stability and Solubility Assay of selected compounds. 92 Chapter 4: Discussion In this study, we report the discovery of a series of small molecule inhibitors of ZKD-Lin28B that prevent the degradation of pre-let-7d binding to the miRNA. These compounds successfully restored the expression level of mature let-7d miRNA in our t-NEPC cell model, DuNE. As a result, we observed downregulation of a set of let-7 dependent cancer-stem-cell (CSC) genes and neuroendocrine markers (NE) in the studied cancer models. These findings are consistent with our previous work that showed that the t-NEPC Lin28BKO cell line expressed significantly fewer stem-like and NE markers (85). Furthermore, DuNE cells, after being treated with the selected inhibitors, showed significantly reduced levels of SOX2 and HMGA2, which are oncogenes regulating pluripotency and fostering the development of treatment resistance (238,239). This effect was similar to our previous publication on Lin28B, where we re-introduced the let-7d mimic back to let-7d eliminated DuNE cells (230). We also found that the clonogenicity and self-renewal abilities of cancer stem cells treated with our lead inhibitors were significantly diminished. Overall, our results suggest a reduction in the stemness phenotype in response to the treatments. As stemness potential promotes cancer recurrence, proliferation, metastasis, and treatment resistance (247), these findings highlight the importance of targeting Lin28 protein for therapeutic modulation. This study provides evidence for the feasibility of therapeutic modulation of Lin28 protein. A growing body of research highlights the significance of Lin28 in various diseases (207). The Lin28/let-7 regulatory pathway serves as a central hub, presenting a unique opportunity to modulate the expression of a multitude of oncogenes that regulate different types of cancer. For 93 example, our study demonstrated that Ln7 and Ln115 significantly reduce the expression of CDH2, a gene that encodes for cadherin 2 protein. CDH2 has been associated with the progression of castration-resistant prostate cancer (257) and the epithelial-mesenchymal transition in non-small cell lung cancer (258). We also evaluated the effectiveness of our selected inhibitors, Ln7, Ln15, and Ln115, on the IGROV1 cell line, which has high expression of Lin28A protein. The results show that our designed inhibitors restore the expression of mature let-7d miRNA in the Lin28A cell line. Therefore, our developed lead inhibitors could be used as a starting point for the development of therapeutic options for Lin28-dependent conditions. The lack of defined binding sites and generally disordered structures of RNA-binding proteins makes them difficult to target with small molecules (259). However, our study contradicts this notion and demonstrates that targeting RNA-binding proteins can have potential therapeutic effects on our neuroendocrine prostate cancer cell model. An essential aspect of our study was the use of computer-aided drug discovery (CADD) techniques to overcome these limitations. We used a computational model to analyze the Lin28 protein surface and identify possible binding pockets for small molecule drugs. Additionally, we employed DeepDocking, a novel machine-learning tool, to screen an ultra-large compound library. Since such a vast chemical space was covered, there was a high possibility of finding effective inhibitors, as the library of experimentally tested compounds was as focused as possible. Indeed, the initial FP assay hit rate was 9% (15 hits out of 163 tested) compared to high-throughput (HT) screenings of non-focused libraries. For instance, HT FP screens on Lin28 protein yielded 0.01% (14/16,000) (236), 0.05% (53/101,017) (222), and 2.3% (64/2,768) (260) hit rates, which are significantly lower than our model's hit rate. Most importantly, our inhibitors 94 demonstrate a better inhibitory effect than the hits from the previously reported two Lin28 inhibitors (1632 and Li71, respectively). In our latest publication about this study (268), we also showed minimal cytotoxicity to cells by using a cell toxicity assay that measures the lactate dehydrogenase (LDH) release in the cancer cell-cultured media in the supplementary figures 4. The cell-based assays showed colony formation and proliferation with minimal cytotoxicity results (Figure 3.9). Therefore, this study supports our previous conclusion that structure-based drug discovery can target proteins that are conventionally considered undruggable (262). 95 Chapter 5: Limitation and Future Direction The study is limited by the fact that only a few in vitro NEPC cell lines were used to study molecular biology and signalling pathways. Additionally, understanding the molecular mechanisms of t-NEPC development requires recognition that the transition from AdPC to t-NEPC is a chronic process involving several intermediate phenotypes and molecular processes (214). Despite identifying the genomic underpinnings of the disease, comprehensively understanding it is near impossible due to the crucial role of epigenetic modifications and microenvironmental factors in lineage plasticity and differentiation (214). Given the heterogeneity of patient samples collected, many complex mechanisms are involved in the development of t-NEPC, and tracking disease progression is challenging due to the short survival time after diagnosis. Secondly, animal studies have not been conducted, which is critical to developing inhibitors for the next step. Lastly, structural modifications of chemicals can further improve them, reducing the concentration required for all assays. Moreover, this study demonstrated the Lin28A inhibition effect of our selected inhibitors, indicating that different cancers might benefit from these Lin28 inhibitors. Further testing with downstream gene regulations is planned for the future. 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For the probe titration assay, 10 µM of Lin28A protein was applied, and pre-let-7d-FAM probe concentrations were titrated from 1 nM to 100 µM. For the protein titration assay, 1 nM of pre-let-7d-FAM probe was used, and Lin28A proteins were titrated from 1 nM to 50 µM in both ZKD and full-length forms. In the competition assay, pre-let-7d non-labelled probe concentrations ranging from 1 nM to 50 µM were used with 10 µM of Lin28A protein and 1 nM of pre-let-7d-FAM labelled probe. Each FP assay was conducted with n=9 replicates. 136 Figure S. 2 FP Titration Assay of the Potential Compounds. To identify potential inhibitors of ZKD-Lin28B, 10 µM of the protein was incubated with different raw screening compounds at concentrations ranging from 0 µM to 500 µM. The FP readout signals were measured, calibrated, and plotted relative to the vehicle treatment. 137 Figure S. 3 EMSA assay of the non-selected compounds The setup contained 0.5 µM of ZKD-Lin28B protein with 10 nM of the IR800CWN-pre-let-7d probe. The "ZKD+Pre-let-7d+competition” refers to the non-labeled probe competitor adding to the mixture. The positive control included only the IR800CWN-Pre-let-7d probe, while the negative control contained both the labeled probe (IR800CWN-pre-let-7d) and ZKD-Lin28B protein. The "Competition" showing band which corresponds to the competition setup where both labeled (IR800CWN-pre-let-7d) and unlabeled probes (pre-let-7d) were present together with the ZKD-Lin28B protein. The numbers represent chemical concentrations in µM. 138 Figure S. 4 Selected ZKD-Lin28B inhibitors regulate protein expression level of SOX2 and HMGA2. DuNE cells were treated with 20 µM of Li71, 1632, Ln7, Ln15, and Ln115 for 24 hours. Protein lysates were collected and immunoblotted with antibodies against Vinculin (loading control), SOX2, and HMGA2. Western blot results showed that the selected inhibitors regulated the protein expression levels of SOX2 and HMGA2. 139 Figure S. 5 Colony Formation Assays on DuNE and DuNELin28BKO cell lines treated with selected inhibitors. (A) DuNE cells were seeded at 500 cells per well in 6-well plates. After 24 hours, selected compounds were added at a total chemical concentration of 60 µM, which was diluted with media to 20 µM per well. The medium was changed every 120 hours with the chemicals for a total of 14 days. After 14 days, colonies were stained with 0.005% crystal violet for 2 hours. The 140 colony sizes were analyzed using ImageJ software and the number of colonies formed was calculated. Colonies with a size of 50 µm or larger were counted. The experiment was performed with n=3 replicates. (B) DuNELin28BKO cells were seeded at 500 cells per well in 6-well plates. After 24 hours, selected compounds were added at a total chemical concentration of 60 µM, which was diluted with media to 20 µM per well. The medium was changed every 120 hours with the chemicals for a total of 14 days. After 14 days, colonies were stained with 0.005% crystal violet for 2 hours. The colony sizes were analyzed using ImageJ software and the number of colonies formed was calculated. Colonies with a size of 50 µm or larger were counted. The experiment was performed with n=3 replicates. 141 Figure S. 6 Final Purification of ZKD-Lin28B (15kDa) on the 18% SDS-PAGE. Figure S. 7 Final Purification of Full-Length Lin28B (28kDa) on the 18% SDS-PAGE
Thesis/Dissertation
eng
Experimental Medicine
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Dong, Xuesen
Discovery and characterization of novel LIN28 protein inhibitors suppress stemness in neuroendocrine prostate cancer
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