(Title of the Thesis)*

Home , Glutamine

TARGETING PROSTATE CANCER

BY SMALL MOLECULES

JIAN ZHANG

Submitted in partial fulfillment of the requirements

For the degree of Doctor of Philosophy

Dissertation Adviser: Dr. Andrei Gudkov

Department of Biochemistry

CASE WESTERN RESERVE UNIVERSITY

May, 2011

CASE WESTERN RESERVE UNIVERSITY

SCHOOL OF GRADUATE STUDIES

We hereby approve the dissertation of

Jian Zhang

candidate for the Doctor of Philosophy degree *.

(signed) David Samols (chair of the committee)

Andrei V. Gudkov

Donal S. Luse

Hung-Ying Kao

Julia V. Kichina

Warren D. Heston

(date) August 24, 2010

*We also certify that written approval has been obtained for any proprietary material contained therein.

ii Table of Contents

List of Tables ...... vi List of Figures ...... vii Acknowledgements ...... ix List of Abbreviations ...... x Abstract ...... xiv Chapter 1. Introduction ...... 1 1.1. The Prostate and Prostate Cancer ...... 1 1.1.1. Prostate ...... 1 1.1.2. Androgen Receptor ...... 5 1.1.3. Prostate Cancer ...... 9 1.2. Treatment of Prostate Cancer ...... 11 1.2.1. Hormone Therapy ...... 14 1.2.2. AR in CRPCa from Hormone Therapy ...... 18 1.2.3. Palliative Therapies ...... 21 1.3. Experimental Plan and General Strategy of Studies ...... 24 1.4. Preliminary Data 1: Screening of Small Molecule Library ...... 29 1.4.1. Rationale and Approach ...... 29 1.4.2. High Throughput Screening ...... 32 1.4.3. Long-term Survival Assay ...... 38 1.4.4. Summary...... 41 1.5. Preliminary Data 2: In Vivo Evaluation Therapeutic Efficiency of 5582 ...... 42 Chapter 2. Materials and Methods ...... 44 2.1. Material ...... 44 2.1.1. Cell Lines...... 44 2.1.2. Chemicals ...... 47 2.1.3. Plasmids ...... 48 2.1.4. PCR Primers ...... 49 2.1.5. Solutions ...... 49

iii 2.2. Method ...... 53 2.2.1. Cell Survival Assay ...... 53 2.2.2. Flow Cytometric Assay ...... 54 2.2.3. Hybridization Assays...... 55 2.2.4. Immunostaining ...... 56 2.2.5. Nucleic Acids Preparation ...... 57 2.2.6. Polymerase Chain Reaction (PCR) ...... 59 2.2.7. Transfection ...... 61 2.2.8. Reporter Assay ...... 62 2.2.9. RNA Interference Analysis ...... 63 2.2.10. Western blotting Analysis ...... 63 2.2.11. Lentivirus Viral Transduction ...... 64 2.2.12. In vivo Evaluation Therapeutic Potential of ARKILs ...... 65 Chapter 3. Approaching Mechanisms of the Hits Specific Cytotoxicity ...... 67 3.1. Hypothesis, Rationale and Approaches ...... 67 3.2. Characterization of the Hits by Cytotoxicity Assay ...... 69 3.3. Mechanism of Prostate Cell Death ...... 76 3.4. Are AR Involved in the Isolated Hits Cytotoxicity? ...... 79 3.4.1. Effect of the Hits on AR Transactivation Function in Sensitive PCa Cells .... 79 3.4.2. Do the Isolated Compounds Affect AR Protein Abundance? ...... 85 3.4.3. The Isolated Hits were Named as ARKILs ...... 87 3.5. Is AR a Potential Target of the Isolated Hits ...... 89 3.5.1. Potential mechanism of ARKILs...... 89 3.5.2. Is Translocation of AR Affected by ARKILs? ...... 91 3.5.3. Do ARKILs Influence the Stability of AR and AR mRNA? ...... 94 3.5.4. Is AR Itself Related to ARKILs Toxicity? ...... 97 3.5.5. Summary of the AR Biased Investigations ...... 100 3.6. Identification and Characterization of ARKIL Resistant Variants of 22Rv1 ...... 102 3.6.1. Isolation of Resistant Variants...... 102 3.6.2. Are Resistant Variants Cross-Resistant to ALL ARKILs? ...... 109 3.6.3. Non-involvement of Multidrug Resistance Transporters ...... 116

iv 3.6.4. Characterization of ARKIL Resistance in AKRVs...... 120 3.7. Summary ...... 130 Chapter 4. Investigating Potential Target of ARKILs ...... 130 4.1 Gene Profiling Analysis on AKRVs and Parental 22Rv1 cells ...... 131 4.1.1 Hypothesis and Background ...... 131 4.1.2 Annotated DEGs from Microarray Analysis ...... 134 4.1.3 Validation of c-Maf Involvement in ARKIL-3 toxicity ...... 143 4.2 DEGs Validation by shRNA Library High Throughput Screening ...... 155 4.3 Summary ...... 159 Chapter 5. In vivo Evaluation of Therapeutic Potential ...... 160 5.1. Pilot Toxicity Assessment of ARKILS ...... 160 5.2. Evaluation of in vivo Efficacy of ARKIL-3 ...... 165 5.3. Summary ...... 168 Chapter 6. Conclusions and Discussion ...... 169 6.1. Conclusions ...... 169 6.2. Discussion ...... 171 6.3. Working Model ...... 180 Biobliography ...... 182

v List of Tables

Table 1-1. Treatments for prostate cancer ...... 12 Table 2-1. Cell lines ...... 45 Table 2-2. Recipe of medium I - RPMI ...... 46 Table 2-3. Recipe of medium II - DMEM ...... 47 Table 2-4. Chemicals ...... 47 Table 2-5. Expressing construct ...... 48 Table 2-6. Lentiviral packaging system ...... 48 Table 2-7. Primers for AR investigation ...... 49 Table 2-8. Methylene blue methanol (MBM) solution ...... 49 Table 2-9. Propidium iodide DNA staining buffer (3 μM) ...... 50 Table 2-10. MOPS Buffer Recipe (10x) ...... 50 Table 2-11. Nucleic acid transfer buffer (20 x SSC) ...... 50 Table 2-12. HEPES lysis buffer (stock 10 ml, 4°C)...... 51 Table 2-13. Running buffer (10 x) ...... 51 Table 2-14. Running buffer (1 x) ...... 51 Table 2-15. Transferring buffer ...... 51 Table 2-16. Blocking buffer ...... 51 Table 2-17. PBST buffer ...... 52 Table 2-18. Stripping buffer ...... 52 Table 2-19. Antibody ...... 52 Table 3-1. Name of the isolated hits ...... 88 Table 3-2. ARKIL resistant variants selection ...... 106 Table 3-3. SNP genotyping analysis of PCa cells ...... 106 Table 4-1. Upregulated DEGs in AK3RVs ...... 136 Table 4-2. Annotated upregulated DEGs in AK3RVs ...... 137 Table 4-3. Downregulated DEGs in AK3RVs ...... 139 Table 4-4. shRNA constructs for AKIL targets validation ...... 157

vi List of Figures

Figure 1-1. The anatomy of the prostate gland and the regulation of androgenesis ...... 3 Figure 1-2. Androgens in human steroidogenesis ...... 4 Figure 1-3. Human androgen receptors ...... 7 Figure 1-4. Action of androgen receptor in prostate cells ...... 8 Figure 1-5. Mechanism of androgen independence and therapies for prostate cancer .... 20 Figure 1-6. Outline of experimental plan and general strategy ...... 26 Figure 1-7. Principles of cell-based readout system for the screening ...... 31 Figure 1-8. The secondary screening of the primary hits ...... 36 Figure 1-9. Multi-doses response assay in secondary screening ...... 37 Figure 1-10. Long-term survival assay of secondary hits toxicity in diverse cell lines ... 40 Figure 1-11. Tumor inhibition of 5582 by i.v. injection (Narizhneva et al., 2009) ...... 43 Figure 3-1. Cytotoxic assay of 5314 in diverse cell lines or tissues ...... 72 Figure 3-2. Cytotoxic assay of 5582 in diverse cell lines or tissues ...... 73 Figure 3-3. Cytotoxic assay of 6061 in diverse cell lines or tissues ...... 74 Figure 3-4. Cytotoxic assay of 6137 in diverse cell lines or tissues ...... 75 Figure 3-5. FACS analysis of apoptotic cells in the selected hits treatment ...... 77 Figure 3-6. The selected hits inducing apoptotic PARP cleavage ...... 78 Figure 3-7. Scheme of AR translocation and ARE luciferase reporter ...... 82 Figure 3-8. AR transcriptional activity in the hits dose- and time-dependent assay ...... 83 Figure 3-9. AR transcriptional activity in R1881 dose-dependent assay of the hits ...... 84 Figure 3-10. AR expression was inhibited by 5314 and 5582 in 22Rv1 ...... 86 Figure 3-11. Potential targets of ARKILs in PCa cells ...... 90 Figure 3-12. ARKIL-3 did not inhibit R1881 induced AR translocation ...... 92 Figure 3-13. ARKIL-8 did not inhibit R1881 induced AR translocation ...... 93 Figure 3-14. Stability assay of AR in 22Rv1 with ARKIL-3 ...... 96 Figure 3-15. Overexpression of AR did not lower drug toxicity towards 22Rv1 cells ... 99 Figure 3-16. Summary of the investigated ARKILs potential targets ...... 101 Figure 3-17. Scheme of selection for resistant variants of 22Rv1to ARKILs ...... 104 Figure 3-18. PARP cleavage induced by ARKILs ...... 107

vii Figure 3-19. Cytotoxic assay of resistant variants of ARKILs ...... 108 Figure 3-20. Potential mechanism for cross-resistance of RVs ...... 111 Figure 3-21. ARKIL-1 cytotoxic assay of resistant variants for cross-resistance ...... 112 Figure 3-22. ARKIL-3 cytotoxic assay of resistant variants for cross-resistance ...... 113 Figure 3-23. ARKIL-7 cytotoxic assay of resistant variants for cross-resistance ...... 114 Figure 3-24. ARKIL-8 cytotoxic assay of resistant variants for cross-resistance ...... 115 Figure 3-25. Multidrug resistance hypothesis for AKRVs ...... 118 Figure 3-26. Multidrug resistant assay of ARKILs’ resistant variants ...... 119 Figure 3-27. AR transcriptional activity following ARKILs dose-dependent assay ..... 121 Figure 3-28. AR transcriptional activity following androgen time-dependent assay .... 122 Figure 3-29. AR transcriptional activity following androgen dose-dependent assay .... 123 Figure 3-30. AR expression was not inhibited by ARKILs in AKRVs ...... 126 Figure 3-31. Knockdown AR in AKRVs by siAR ...... 129 Figure 4-1. Hypothesized model of resistance mechanism in AKRVs ...... 133 Figure 4-2. Upregulated DEGs in AK3RVs ...... 135 Figure 4-3. Downregulated DEGs in AK3RVs ...... 138 Figure 4-4. Validation of c-Maf expression in AK3RVs ...... 146 Figure 4-5. Cytotoxicity assay for c-Maf overexpressed 22Rv1 cells ...... 149 Figure 4-6. Cytotoxicity assay for siMaf knockdown AK3R4 cells ...... 150 Figure 4-7. Promoter regulation analysis on the promoter of c-Maf ...... 154 Figure 4-8. Knockdown candidate DEGs by shRNAs ...... 158 Figure 5-1. Effect of ARKILS on mouse weight ...... 161 Figure 5-2. Cytotoxic Assay of Cell Lines...... 164 Figure 5-3. Xenografts with ARKIL-3 treatment via i.p. administration ...... 167 Figure 6-1. The approach of anti-PCa screening in the project ...... 176 Figure 6-2. Current model and proposed mechanism of ARKILs anti-PCa activity ..... 181

viii Acknowledgements

First and foremost, I would like to express my heartfelt gratitude to my advisor - Andrei V.

Gudkov. This work could not be achieved without his amazing mentoring, great support and constant encouragement, especially always positive feedback to my always negative results.

Having such a wonderful mentor would be a biggest fortune in my whole life. I also want to thank my supervisor – Julia V. Kichina. She gave me much help and support in every step of the experiments. I'd like to thank Dr. Catherine Burkhart. This dissertation would not be finished without her generous and professional help.

I would like to thank my committee members, Dr. David Samols, Dr. Donal S. Luse, Dr. Hung-

Ying Kao, and Dr. Warren D. Heston for their advising and support all along.

I would like to thank all people who helped to make this dissertation possible. I also want to thank each member of Dr. Gudkov’s lab, past and present, for their scientific and personal support. I would like to expend my thanks to my friends and colleagues at Case Western Reserve

University, Roswell Park Cancer Institute, Cleveland Clinic Foundation, Tartis Inc and Cleveland

Biolab Inc..

At last, I am forever indebted to my family for their unconditional love and encouragement. In particular, thanks my wife, Yue, for her endless support and caring.

ix List of Abbreviations

ARKIL androgen receptor inhibitor killing 5AR 5α-reductase ADPCa androgen dependent PCa AF activation function AIPCa androgen independent PCa AMACR α-methylacyl-CoA racemase ARE androgen response element ARΔLBD AR mutant without ligand-binding domain ATCC American Type Culture Collection ATP adenosine triphosphate bp base pair BPH benign prostate hyperplasia cDNA complimentary DNA CRPCa castration refractory PCa CSS charcoal-stripped serum Ct threshold cycle number CYP19 aromatase DBD DNA binding domain DHEA dehydroepiandrosterone DHT dihydrotestosterone DMEM Dulbecco/Vogt modified Eagle's Harry Eagle medium DMSO dimethyl sulfoxide DNA deoxyribonucleic acid dNTP deoxyribonucleotide triphosphate Dox doxorubicin DRE digital rectal examination dsDNA double strand DNA

x ECAD E-cadherin EDTA ethylenediaminetetraacetic acid EGF epidermal growth factor EGF epidermal growth factor EPCA early prostate cancer antigen EZH2 enhancer of zeste homolog 2 FBS fetal bovine serum FDA food and drug administration FITC fluorescein isothiocyanate FSH follicle-stimulating hormone GFP green fluorescent protein GnRH gonadotropin-hormone-releasing hormone hK2 human kallikrein-related peptidase 2 HMEC Human mammary epithelial cells HPA axis hypothalamic-pituitary-adrenal axis hr hour HRP horseradish peroxidase HSD3B 3β-hydroxysteroid dehydrogenase HSDB17B testosterone by 17-beta-hydroxysteroid dehydrogenase HSP heat shock proteins HTS high throughput screening IGF insulin-like growth factor IL6 interleukin-6 Kb kilo bases kg kilogram KGF keratinocyte growth factor LBD ligand androgens binding domain LH luteinizing hormone LHRH the luteinizing-hormone-releasing hormone

xi MAKP mitogen activated protein kinase Mb mega bases MBM methylene blue methanol solution mg milligram µg microgram min minute ml milliliter µl microliter mRNA messenger RNA NCI National Cancer Institute ng nanogram NKE normal kidney epithelial cells NP-40 Nonident P-40 NTD N-terminal domain NTP nucleotide triphosphate PAGE polyacrylamide gel electrophoresis PBS phosphate-buffered saline PCa prostate cancer PCR polymerase chain reaction PSA Prostate-specific antigen PSCA prostate stem cell antigen PSMA prostate-specific membrane antigen Puro puromycin RNA ribonucleic acid RNAi RNA interference rpm revolutions per minute RPMI Roswell Park Memorial Institute medium 1640 RT reverse transcription RT room temperature

xii RTK receptor tyrosine kinase RT-PCR reverse transcriptase polymerase chain reaction SAR Structure-activity relationship SDS sodium dodecyl sulfate sec second shRNA short hairpin RNA siRNA small interference RNA SMSC Small Molecule Screening Core SNP single nucleotide polymorphism T testosterone TGF-β transforming growth factor β TK promoter thymidine kinase promoter U unit uPA urokinase plasminogen activator uPAR urokinase plasminogen activator receptor

xiii Targeting Prostate Cancer by Small Molecules

Abstract

by JIAN ZHANG

Prostate cancer (PCa) is the most common malignant tumor and one of the most frequent causes of mortality for men in the US. This project is focused on exploration of the idea of “anti-tissue therapy”, which involves the identification and use of compounds that can selectively eliminate cells of prostate origin. The feasibility of this approach is justified by the success of anti-androgen therapy, which targets all cells of prostate lineage.

Unfortunately, androgen ablation therapy is effective only at early stages of the disease and results in the development of hormone-independent tumors that are practically insensitive to available therapies. By screening diverse chemical libraries a series of compounds were identified that belonged to five structural classes, which are specifically toxic towards androgen receptor (AR) expressing PCa cells, particularly 22Rv1 cells. In particular, these compounds, designated ARKILs, demonstrated extremely strong selective toxicity to 22Rv1 cells that involved cell cycle arrest and apoptosis. ARKILs have no effect on the stability of AR protein or AR mRNA. In addition, they do not block

AR translocation into the nucleus. However, they clearly inhibit AR mediated transcription. The degree of resistance of the isolated 22Rv1 cell variants to ARKILs was comparable to that of non-prostate origin cells. Moreover, the variants selected with a

xiv single ARKIL were cross-resistant to all others. This cross-resistance does not appear to be mediated by ATP-dependent multidrug resistance (MDR) transporters (P-gp/MRPs).

ARKILs are likely to target one common mechanism that is important to survival of

22Rv1 cells. siRNA against AR did not sensitize resistant variants (AKRVs) to ARKILs, suggesting that the target is not AR itself. However, mechanism(s) of action of ARKILS may involve a component(s) of the AR signalling pathway.

The therapeutic potential of ARKILs against PCa was evaluated with 22Rv1 xenografts in nude mice. ARKIL-3 showed modest, but statistically insignificant, inhibition of

22Rv1 xenograft tumors but may yield promising efficacy in following future optimization. ARKIL-8 is able to block growth of and even kill PCa tumors. Therefore,

ARKILs, as represented by ARKIL-3 and ARKIL-8, have potential for development into therapeutic agents against PCa.

xv Chapter 1. Introduction

1.1. The Prostate and Prostate Cancer

1.1.1. Prostate

The prostate gland is an exocrine gland of the male mammalian reproductive system

(Figure 1-1) (Susan Standring, 2009). The prostate gland produces the fluid components needed to support and transport sperm. The tissue of the prostate is made up of both epithelial and stromal cells. Normal prostatic epithelial cells include luminal secretory, basal and neuroendocrine cells (Liu and True, 2002). The differentiation and proliferation of the prostatic epitheliums mainly depends on a steroid hormone (Huggins and Hodges,

1941). The steroid hormone is androgen (also called androgenic hormone or testoid), a word derived from the Greek andros, man, and gennan, to produce, which was first discovered in 1936 (Nelson and Gallagher, 1936). Androgens (Figure 1-2) are the most important steroids in man for regulating the normal development and maintenance of male reproductive tissues (the testis and prostate) and male secondary sex characteristics

(Mooradian et al., 1987). As the original anabolic steroids, androgens are also the precursor of all female sex hormones, estrogens (Figure 1-2). The synthesis of testosterone, the primary and most well-known androgen, occurs in response to follicle- stimulating hormone (FSH) and luteinizing hormone (LH) from the pituitary gland

(Kalra, 1985), whose release is triggered by luteinizing-hormone-releasing hormone

(LHRH, also known as gonadotropin-hormone-releasing hormone, GnRH) from the hypothalamus (Figure 1-1). Testosterone is principally secreted into the bloodstream by

1 the testes of males (other small amounts from the adrenal glands) in mammals.

Dihydrotestosterone (DHT), which is formed by the reduction of testosterone by 5α- reductase, is the principle androgen in prostate epithelial cells (Bruchovsky and Wilson,

1968). Testosterone has physiological effects on body composition whereas DHT is mainly required for the development of the prostate (Fizazi et al., 2010; Miller, 2009;

Morley, 2000).

2 www.cancer.gov

Figure 1-1. The anatomy of the prostate gland and the regulation of androgenesis The anatomy picture of the prostate gland (left) was obtained from the NCI website and cropped for illustration. The prostate gland is an exocrine gland of the male mammalian reproductive system. The function of the prostate is regulated by androgens. The primary androgen, testosterone, is secreted from the testes. The secretion of androgens is regulated by neuroendocrine signals. HPA axis: hypothalamic-pituitary-adrenal axis; LHRH: the luteinizing-hormone-releasing hormone; FSH: follicle-stimulating hormone; LH: luteinizing hormone; T: testosterone.

Figure 1-2. Androgens in human steroidogenesis All steroid hormones are synthesized from the basic substrate cholesterol. In standard androgenesis, dihydrotestosterone (DHT) is converted from the testes derived testosterone by 5α-reductase (5AR). Prostate cells can also convert adrenal derived steroids (androstenediol and dehydroepiandrosterone (DHEA)) to testosterone by 17-beta-hydroxysteroid dehydrogenase (HSDB17B) and 3β-hydroxysteroid dehydrogenase (HSD3B2). In estrogenesis, estrogens (estrone, estrdiol, and estriol) are converted from androstenedione and testosterone by aromatase (CYP19).

4 1.1.2. Androgen Receptor

Androgens exert their effects through the androgen-androgen receptor (AR) signaling pathway (Lindzey et al., 1994; Roy et al., 1998). AR is the most important factor in the androgen-AR signaling pathway for prostate (Culig and Bartsch, 2006; Edwards and

Bartlett, 2005; Zhu and Kyprianou, 2008). AR (NR3C4) is a member of the steroid receptor subfamily of nuclear hormone receptors (Lu et al., 2006) . AR has three major domains: 1) the N-terminal domain (NTD), which includes the transcriptional activation function (AF)-1, 2) DNA binding domain (DBD) and 3) the C-terminal domain that contains both the ligand (androgens) binding domain (LBD) and AF-2 co-activator binding surface (Bain et al., 2007; Dehm and Tindall, 2007) (Figure 1-3). Inactive AR is bound to heat shock proteins (HSPs). In the absence of HSPs, AR will be degraded

(Heinlein and Chang, 2004; Neckers and Ivy, 2003; Pratt and Toft, 1997). AR is activated by androgen binding, which causes its release from HSPs in the cytoplasm where it then translocates into the nucleus with AR coregulators (Heemers and Tindall, 2007; Lindzey et al., 1994; Mooradian et al., 1987; Rahman et al., 2004) (Figure 1-4). As a transcription factor, AR mediates physiological effects of androgens by modulating androgen- responsive genes via binding to androgen-responsive elements (AREs) in the promoters of target genes (Lindzey et al., 1994; Mooradian et al., 1987). AR is also important in integrating signals through central pathways for proliferation and differentiation of prostate epithelial cells (Burd et al., 2006; So et al., 2003). Although there is no strong evidence indicating that increased androgen stimulation of the AR alone can significantly promote carcinogenesis of the prostate (Hsing, 2001), the functional AR is an important mediator of prostate adenocarcinoma progression (Chen et al., 2004; English et al., 1989;

5 Heinlein and Chang, 2004; Ruizeveld de Winter et al., 1994). For example, an increase in the expression level of prostate specific antigen (PSA) is observed in all prostate cancer

(PCa) patients. PSA is tightly regulated by AR. The castration resistant PCa (CRPCa) patients often receive extended hormone therapies to block AR signaling again, which indicates that the development of CRPCa is strongly associated with the androgen-AR signaling pathway axis. Even in androgen independent PCa (AIPCa) cell lines (such as

22Rv1), which can grow without androgens, the androgen-AR signaling pathway still participates in cell proliferation (Belandia et al., 2005; Hartel et al., 2003; Lin et al.,

1999; Sramkoski et al., 1999). Many studies indicate that AR function is still important for androgen-insensitive PCa cell survival after castration and for the progression of

CRPCa tumors (Burnstein, 2005; Steven, 2002). Indeed, siRNA knockdown of AR expression suppresses the growth of both androgen-dependent and -independent PCa cells (Tararova et al., 2007). Moreover, mutations in the AR gene frequently occur in PCa patients, indicating that AR mutations may be functionally important. Such mutations usually resume or boost AR activity, suggesting that AR signaling (with or without androgen-activation) is crucial for PCa cell growth. Thus, AR is still a promising candidate for therapeutic treatment of PCa (Figure 1-5). Hence, nowadays hormone therapies mainly focus on the androgen-AR signaling pathway.

Figure 1-3. Human androgen receptors The human AR contains three domains: 1) the N-terminal domain (NTD), which includes the transcriptional activation function (AF)-1, 2) DNA binding domain (DBD) and 3) the C- terminal domain, which contains both the ligand (androgens) binding domain (LBD) and the AF-2 co-activator binding surface. 22Rv1 cells have two AR alleles, a mutant AR with duplicate exon3, and a mutant AR (ARΔLBD) that has lost ligand-binding domain.

Figure 1-4. Action of androgen receptor in prostate cells AR is stabilized by binding to HSPs. Free testosterone from the blood stream enters prostate cells and is reduced by 5α-reductase to dihydrotestosterone (DHT). AR is activated by androgens and dimerizes. Activated AR together with AR coregulators translocates into the nucleus and binds to androgen response elements (AREs) in the promoters of target genes.

8 1.1.3. Prostate Cancer

Prostate cancer (PCa) is the most frequent neoplastic disease in men and the second leading cause of cancer-related deaths (Jemal et al., 2005). In the United States, an estimated 217,730 (192,280 in 2009) men are projected to be newly diagnosed and about

32,050 (27,360 in 2009) men will die from PCa in 2010 (Jemal et al., 2005; NCI, 2008).

With advanced understanding of prostate anatomy and improved approaches, the mortality rate of PCa has decreased from 31% in 1970s to 25% currently (Horner MJ,

2009). Several risk factors may contribute to PCa, such as age >65, family history, race, certain prostate changes (high-grade prostatic intraepithelial neoplasia) (Joniau et al.

2005; Partin 2002; Weiss 2001). Some genetic alterations are also associated with PCa, such as amplified Myc, Bcl-2 overexpression, translocated ETV1 and ERG1, loss or mutated tumor suppressing genes (PTEN, Rb, p53, etc.), hypersensitive or mutated AR, and so on (Nieto et al., 2007).

Because the symptoms of PCa may not be obvious, the most common detection methods are digital rectal exam (DRE) and a blood test for prostate-specific antigen (PSA). First identified in the late 1970s (Wang et al., 1979), PSA has been used to monitor and screen for early detection and diagnosis PCa. It detects 90% of early-stage PCa (Carroll et al.,

2001a; De Angelis et al., 2007) and is also useful for PCa staging and post-treatment follow up (Carroll et al., 2001b). However, the PSA test is not specific for PCa. A high

PSA level is also commonly associated with benign prostate hypertrophy (BPH) or prostatitis (Armitage et al., 1988; Nickel, 2008). Abnormal PSA test results are usually further diagnosed by transrectal ultrasound or biopsy. Recently, new bio-markers have

9 been found that are more specific for PCa (Eddy et al., 2007; Hansel et al., 2007). For example, detection of early prostate cancer antigen (EPCA)-2 has 94% specificity for

PCa (Eddy et al. 2007). Some other biomarkers, which human kallikrein-related peptidase 2 (hK2), α-methylacyl-CoA racemase (AMACR), insulin-like growth factors

(IGFs) and binding proteins, urokinase plasminogen activator (uPA) and receptor

(uPAR), transforming growth factor β1 (TGF-β1), interleukin-6 ligand and receptor, enhancer of zeste homolog 2 (EZH2), E-cadherin (ECAD), prostate stem cell antigen

(PSCA), prostate-specific membrane antigen (PSMA), chromogranin A, hepsin,

TMPRSS2:ERG and TMPRSS2:ETV1 gene fusion and Ki-67 have also been found

(Bickers and Aukim-Hastie, 2009).

10 1.2. Treatment of Prostate Cancer

Treatment for PCa consists of single or combination therapeutic options (Table 1-1), including watchful waiting, surgery, radiation therapy, hormone (androgen) therapy, and chemotherapy (NCI, 2008). Since PCa is usually an indolent disease, some older patients or those with other serious health problems may benefit from watching waiting rather than surgery or more aggressive therapy (Bill-Axelson et al., 2008; Bill-Axelson et al.,

2005; Holmberg et al., 2002; Johansson et al., 2009; Klotz, 2007). For early stage, localized PCa, surgery (cryosurgery, prostatectomy, and robotic prostatectomy) and radiotherapy (brachytherapy and radiation therapy) are usually the main therapeutic methods (Brandeis et al., 2000; Jani and Hellman, 2003; Rosenberg and Eschenbach,

1990). When these therapies fail, the next step is hormone therapy. Hormone therapy involves the reduction of activity of steroid-steroid receptor signaling pathway. Androgen withdrawal is usually used against local advanced and metastatic PCa. Because prostate as a tissue is not necessary for viability, androgen ablation (surgical castration and medical castration), which specifically eliminates testosterone or suppresses androgen, has been the predominant therapeutic intervention for prostate tumor therapy for over 70 years (Grayhack et al., 1987; Huggins and Hodges, 1941). Some other therapies have also been introduced into PCa as palliative therapies, including chemotherapy, molecular targeted therapy, and immunotherapy.

ine

Tumor growing Tumor Metastasis pain pelvic Moderate ur in Blood swelling Scrotal urgency urinary Mild Impotence complications Surgical Impotence Incontinence complications Surgical Impotence Incontinence loss Blood

             

Risk

term term

free free

May benefit waiting watchful from Limited on long clinical results; But promising. Recurrence success rates 90% over Comparable traditional retropubic procedures as

Advantage

nder 10 nder

Low Gleason Low levels PSA Low tumors Nonpalpable patient Older problem health Other cancer Localized cancer Recurrent 6 under scores Gleason u levels Psa For healthy patients younger Cancer only gland in prostate

          

Patient Profile Patient

o o

small small

via

laparoscope laparoscope

Carefully Carefully monitoring the without cancer other aggressive therapy, surveillance active called also Minimally invasive procedure via needles to send freezing gases t the cryotherapy prostate, also called Removing the surrounding cancerous tissue prostate surgical by incisions in abdomen and or perineum, or incisions Prostatectomy Robotic

Treatments for prostate cancer cancer prostate for Treatments

Treatment Description Treatment

. . 1

- Robotic

1 Cryosurgery Prostatectomy Watchful Waiting Prostatectomy

Surgery

Table Table

RH)

Impotence gain Weight flashes Hot Fatigue mass muscle of Loss Hormone (LH “flare” urine the in Blood burning Scrotal Incontinence Impotence Tiredness Diarrhea irritation Skin stomach Upset Frequent or urination burning Nausea loss Hair Vomiting sores Mouth

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Risk

e e

fre

Not Not destroy cancer but enhancing treatments. other Recurrence survival rates of 77 to 93% Success rates 85% over Relieve pain and slow tumorgrowth

Advantage

Before, Before, during, or after other treatment. PCa Healthy patients PCa localized with For good patients younger health Advanced stages ofPCa

   

Patient Profile Patient

(continued). (continued).

ation ation at PCa cells, also

Description

Suppressing, Suppressing, blocking, or androgens eliminating by castration to surgical slow the prostate growth tumor’s or medical Low or high dose HDR) seeds implanted radiation in the prostate in (LDR or therapy radiation invasive Minimally External radi called EBRT (electron beam therapy) radiation PCa to targeted molecules Small

Treatments for prostate cancer cancer prostate for Treatments

Treatment

. 1 - Radiation Hormone Brachytherapy Therapy Chemotherapy Therapy

Table 1 Table Radiation Therapy

13 1.2.1. Hormone Therapy

The loss of androgen signals causes dramatic and rapid changes in the prostate that lead to massive apoptosis of prostate epithelial cells (English et al., 1989; Kyprianou and

Isaacs, 1988). These hormone therapies include bilateral orchiectomy, LHRH agonists/diethylstilbestrol (DES), antiandrogens, and anti-extragonadal androgenesis.

LHRH agonists/diethylstilbestrol (DES) and anti-extragonadal androgenesis are central and peripheral inhibitors of androgen synthesis (Figure 1-5). Although rapidly eliminating androgens from circulation by surgical castration is a mainstay of treatment for PCa, psychological stress (expectation on quality of life) may lead patients to look for pharmaceutical alternatives. Medical castration avoids physical removal of the testes by eliminating androgen signaling with hormones or drugs. Secretion of hormones is under the delicate control of the hypothalamic-pituitary-adrenal (HPA) axis (Figure 1-1). DES

(a form of estrogen) inhibits release of LHRH from the hypothalamus. LHRH agonists

(Leuprolide, goserlin, histrelin, triptorelin, etc.) break the subtle equilibrium of the neuroendocrine system, thus shutting down synthesis of the hormones that control production of testosterone in the testes. Antiandrogens (flutamide, bicalutamide, and nilutamide) inhibit tumor cell growth by directly occupying and antagonizing the ligand binding domain of the AR, which prevents DHT binding and activation of AR.

Antiandrogens can be divided into steroidal androgen antagonists and non-steroidal AR inhibitors. The use of these antiandrogens to enhance responses to androgen ablation therapy or to treat androgen-independent disease is not encouraging. Not only are there significant side effects, but patients usually acquire resistance to these drugs. For example, the most effective non-steroidal antagonist of AR, casodex (bicalutamide),

14 which is the current “gold standard” of AR inhibitors, is the only FDA approved AR inhibitor and is effective in castration resistant PCa (CRPCa) patients. The interaction between casodex and the AR ligand-binding domain (LBD), which blocks AR activity, eventually causes drug resistant mutations in that domain (Bohl et al., 2005; Yoshida et al., 2005). When this happens, casodex switches from an antagonist of wild type AR to an agonist of these AR mutants, inducing their activity (Hara et al., 2003; Taplin et al.,

1999). Moreover, 5-30% of circulating androgens (androstenedione, dehydroepiandrosterone (DHEA), and DHEA sulfate) are synthesized by the adrenal gland. These adrenal androgens activate AR signaling by acting as precursors of DHT or agonists of mutated AR (Figure 1-5). The anti-extragonadal androgenesis agents

(ketoconazole, aminoglutethimide, abiraterone acetate) suppress synthesis of steroids thereby reducing the level of DHT. However, almost all antiandrogen compounds eventually promote the appearance of androgen-insensitive PCa by causing agonistic rather than antagonist effects.

As shown in (Figure 1-5) the potential mechanisms of androgen independence include the hypersensitive pathway, the promiscuous pathway, the outlaw pathway, and the bypass pathway, which are closely related to AR signaling pathway. These pathways explain how cancer cells (may not be limited to only PCa cells, but rather all kinds of malignant cells) evolve alternative signaling pathways to overcome unfavorable situations, particularly those that influence proliferation. As shown in Figure 1-5, PCa cells may use one or a combination of several of these pathways to escape the effects of therapy. These four pathways are not the only possibilities enabling cancer cells to survive androgen ablation. For example, a recent study demonstrated that CRPCa may

15 arise from of small fraction of a cancer stem cell subpopulation (Collins et al., 2005).

Epigenetic alterations of PCa cells may also contribute to aberrant growth (Li et al.,

2005).

Since early stages of primary or metastatic PCa are androgen dependent PCa (ADPCa), most patients initially respond to standard androgen ablation and the PCa can be effectively controlled or progression even stopped for a long period of time (Brawer,

2006; Eisenberger et al., 1998; Grayhack et al., 1987; McLeod, 2003; Rosenberg and

Eschenbach, 1990). However, such treatments provide only a temporary relief and rarely result in a complete cure. Regardless of the aggressive pharmacological methods employed, the development of CRPCa from ADPCa can only be delayed but not stopped.

Consequently, PCa relapses with malignant CRPCa in 13-18 months after hormone therapy has been completed (Harris and Reese, 2001; Horner MJ, 2009; NCI, 2008). The advanced disease is usually named androgen independent PCa (AIPCa), because the relapse appears to have eliminated androgen signaling through AR. However, more and more results show that androgen signaling is still active in AIPCa (Feldman and Feldman,

2001). Thus, “androgen independent” PCa is actually “castration independent” PCa

(castration refractory PCa, CRPCa). Moreover, “castration resistance” usually also means acquisition of “drug-resistance” to cytotoxic agents at the same time. This may be the reason why the treatment for CRPCa is still a challenge for patients and oncologists. The relapse of CRPCa requires additional regimens. Therefore, effective therapies for CRPCa patients may require accurately targeted therapy to some specific characteristic of the cancer cells of prostate origin. Since growth and/or survival of the PCa cells heavily rely

16 on the androgen-AR signaling pathway, inhibition of androgen-AR signaling may be the key component for future hormone therapies.

17 1.2.2. AR in CRPCa from Hormone Therapy

Comprehensive investigations into the role of AR in the progression of CRPCa indicate that androgen independence of PCa is not related to inactivation of AR signaling. On the contrary, PCa cells develop different mechanisms to maintain a constitutively active androgen pathway, regardless of any hormone disruption. In fact, AR is involved in several mechanisms accounting for the development of androgen independence (Feldman and Feldman, 2001; Heinlein and Chang, 2004; Pienta and Smith, 2005) (Figure 1-5).

One mechanism is the hypersensitive pathway that makes PCa cells have increased sensitivity to very low levels of androgens. Although androgen castration or androgen antagonists deplete the majority of androgens, tumor cells strive for proliferation by higher expression of AR (e.g. AR amplification), increased stability of AR or enhanced localization of AR. For example, with dramatically reduced serum testosterone, an increase in 5-alpha-reductase enzyme activity enhances the local concentration of androgen by increasing the conversion of testosterone to DHT (Russell and Wilson,

1994).

A second mechanism is the promiscuous pathway, which acquires aberrantly activated androgen signaling from pseudo-androgens, androgen antagonists and corticosteroids by mutated AR or altered AR coregulators, such as ARAs, TIF2, GSN, and SRC1. For example, the ligand binding domain deletion mutant (ARΔLBD) in 22Rv1 cells allows the AR to retain the ability to bind androgen responsive elements (ARE) of DNA even without binding ligand (Tepper et al., 2002). A third possible mechanism is called the outlaw pathway. In androgen non-responsive cells, AR can be activated in the absence

18 of androgens by growth factors, such as insulin-like growth factor-1 (IGF-1), keratinocyte growth factor (KGF), and epidermal growth factor (EGF) (Culig et al.,

1994); and/or activation of receptor tyrosine kinase (RTKs)/mitogen activated protein kinase (MAKP)/Akt pathways (Taplin et al., 1999; Taplin et al., 1995; Veldscholte et al.,

1990; Zhao et al., 2000). On the bypass pathway, the AR pathways could be substituted with a complementary or alternative pathway (Bcl-2/Bcl-xL) (Colombel et al., 1993;

Furuya et al., 1996; Gleave et al., 1999; Liu et al., 1996).

The above discussion indicates the insufficient efficacy of current anti-CRPCa drugs.

Current therapies for advanced PCa are mainly focused on either exhausting androgens from the body or inhibiting AR function. It is clear that new drugs that efficiently eliminate CRPCa cells with no or little toxicity to other tissues are urgently needed to treat this disease. There are two new antiandrogens under clinical development,

MDV3100 and RD162 (Medivation). These drugs, which are derived from the non- steroidal agonist RU59063, are small molecule antagonists of AR with ~5 times higher affinity than casodex (Chen et al., 2004; Narizhneva et al., 2009). MDV3100 has shown promising anti-PCa activity in Phase I/II clinical trials with advanced CRPCa. An inhibitor of extra-testicular androgen synthesis, abiraterone acetate (Cougar Biotech) is a small molecule inhibitor of cytochrome P17 (CYP17), which can reduce both adrenal and intratumoral androgen production. BMS-641988 (Bristol-Myers Squibb) is an improved casodex-like inhibitor that is currently in a Phase I study for patients with CRPCa.

However, the history of casodex indicates that the new compounds will have a similar destination - eventual acquisition of drug resistant mutations of AR (Bohl et al., 2005).

Figure 1-5. Mechanism of androgen independence and therapies for prostate cancer The synthesis of testosterone (T) occurs in response to signals from the hypothalamus (luteinizing-hormone-releasing hormone (LHRH)) to the pituitary gland, which releases follicle-stimulating hormone (FSH) and luteinizing hormone (LH). the adrenal gland, which releases adrenocorticotropic hormone (ACTH). Serum testosterone (ST) is principally secreted to bloodstream by the testes. Small amounts of serum androgens (SA) are secreted from the adrenal gland. Dihydrotestosterone (DHT) is converted from cellular testosterone by 5α- reductase, and activated AR pathway. The potential mechanisms of androgen independence are the hypersensitive pathway, promiscuous pathway, outlaw pathway, bypass pathway and cancer stem cells (○1 to ○5 ). Current therapies for PCa are LHRH analogs and diethylstilbestrol (DES), orchiectomy, anti-androgenesis in serum, antiandrogens, targeting AR/AR coregulators, targeting other signaling pathways, chemotherapy, epigenetic approaches, and vaccine (○A to ○I ) (Collins et al., 2005; Colombel et al., 1993; Culig et al., 1994; Feldman and Feldman, 2001; Furuya et al., 1996; Gleave et al., 1999; Heinlein and Chang, 2004; Li et al., 2005; Liu et al., 1996; Pienta and Smith, 2005; Russell and Wilson, 1994; Taplin et al., 1999; Taplin et al., 1995; Tepper et al., 2002; Veldscholte et al., 1990; Zhao et al., 2000).

20 1.2.3. Palliative Therapies

Chemotherapy. There are three general classes of chemotherapy agents used to treat

PCa: microtubule stabilizing agents, interchelating agents, and alkylating compounds.

Microtubules are essential for cell mitosis, which is especially important for the uncontrolled cell division of PCa. Taxanes (docetaxel, paclitaxel, etc.) are a class of drugs that promote and stabilize polymerization of microtubules, thus disrupting normal microtubule function, which leads to apoptosis (Orr et al., 2003). Clinical studies

(TAX237 and SWOG9916) with docetaxel have demonstrated the palliative benefits of chemotherapy regimens (Petrylak et al., 2004; Tannock et al., 2004). More effective chemotherapies have been investigated, including cabazitaxel, mitoxantrone, satraplatin, vinorelbine, patupilone, and ixabepilone (Fizazi et al., 2010). Another class of compounds, anthracyclines (daunorubcin, doxorubicin, and epirubicin) inhibit DNA and

RNA synthesis by interchelating into base pairs of DNA causing free radical-induced

DNA damage (Chen et al., 2007). Mitoxantrone (anthracenedione), a similar anthracycline, has been used as a palliative agent in advanced PCa clinical studies for a very long time (Huggins and Hodges, 1941; Tannock et al., 1996). The alkylating compound, estramustine, which is usually used as an adjuvant in docetaxel regimens, is specifically used for patients with advanced metastatic PCa (Petrylak et al., 1999b;

Petrylak et al., 2004; Savarese et al., 2001; Sinibaldi et al., 2002; Tannock et al., 2004).

Molecular Targeted Therapy. Recently advance in the understanding PCa potentiates some specific biological targets for PCa therapy. These targets may benefit PCa patients have been treated include specific signaling components that modulate AR signaling,

21 growth factors/receptors, signaling transduction, apoptosis, and angiogenesis in PCa growth (Antonarakis et al., 2010; Heath and Carducci, 2006; Ramsay and Leung, 2009).

Scientists are making great effort to identify new molecular targets for PCa treatment.

Some novel agents that are currently being studied in PCa include IGF-1R inhibitors

(monoclonal antibodies and small molecule TKIs); antisense oligonucleotide against clusterin (OGX-011, OncoGeneX); mTOR inhibitors,(the rapamycin analog everolimus,

Novartis), temsirolimus (Wyeth); angiogenesis inhibitors (bevacizumab (Genentech and

Roche), aflibercept (VEGF Trap, Sanofi-Aventis and Regenron); sunitinib (SU11248,

Pfizer Inc.), thalidomide and lenalidomide) and histone deacetylase (HDAC) inhibitors

(trichostatin A, vorinostat (Merck), and panobinostat (Novartis)). Recently, new potential targets in PCa have been reported, which include cyclooxegenase-2 (Smith et al., 2006), various tyrosine kinases (Blackledge, 2003), Stat-3 and Stat-5 (Ahonen et al., 2003;

Weerasinghe et al., 2008).

Immunotherapy. Vaccines against PCa have also been developed and studied in clinical trials (Antonarakis and Drake, 2010; Drake, 2010; Gray et al., 2009; Kantoff et al., 2010;

Risk and Corman, 2009).

However, none of the above mentioned therapies (i.e. chemotherapy, molecular target therapy and immunotherapy) is not effective in preventing the relapse of PCa, which often recurs as localized advanced or metastatic PCa. For example, conventional chemotherapy is generally ineffective against castration refractory PCa (CRPCa, hormone therapy) due to high resistance of the relapsed tissue cells against anticancer drugs (Gulley and Dahut, 2004; Smith, 1999). Even docetaxel, a major new compound

22 that has shown promise for the long-term survival of PCa patients, failed to evoke even a partial response in 60-83% of patients in Phase II trials (Friedland et al., 1999; Petrylak et al., 1999a; Savarese et al., 2001). Thus, conventional chemotherapy is of little use for

CRPCa patients (Chin et al., 2010; Gulley and Dahut, 2004). So far, the most useful of therapy is hormone therapy. However, the failure of androgen-deprivation therapies for advanced PCa has people to look for alternate therapies that are more effective.

Currently, over 200 novel therapies for PCa are being tested and are in various stages of development. Many of these are promising but were not curative. Therefore, there is an urgent need for newer therapies with improved safety, specificity and efficacies.

1.3. Experimental Plan and General Strategy of Studies

The underlying hypothesis behind this study postulates the existence of cellular factors that are essential for the viability of cells of the prostate lineage, which can serve as targets for small molecules. Compounds targeting such factors are expected to have anticancer (prostate specific) activity. The feasibility of this model is supported by the success of androgen ablation therapy targeting and inhibiting the androgen receptor- ligand interaction, which is essential for the viability of cells of prostate origin regardless of whether they are transformed or not.

Different approaches could be used for the identification of such targets. For our approach, the selection of small molecules is based on selective toxicity to cells of prostate origin. If isolated, such molecules are expected to become research tools driving the investigation towards their targets via analysis of their mechanism of action. This approach has several advantages. 1) It is unbiased since it is not based on a biochemical assay focused on specific cellular factors but on a cell response thereby closely mimicking the ultimate therapeutic application (elimination of cells of prostate lineage from the PCa patient). 2) It allows the pursuit of two simultaneous parallel lines of study after the compounds with the desirable properties are isolated (Figure 1-6): one aimed at development of an anticancer drug(s) and the other – at understanding the mechanism of action and identification of the target. Although these lines of work are technically independent, they may likely cross-fertilize each other. In fact, comparison of the properties of compounds differing in the scale of their anti-prostate activity may facilitate defining specific cellular mechanisms that mediate their therapeutic effect and expedite

target identification. Conversely, deciphering the mechanism of action and identification of molecular targets may help rationalizing optimization of small molecules based on functional and structural considerations.

Our approach involved the following steps. First, small molecules were isolated in a cell- based readout that involves comparison of relative toxicity of a single concentration of chemicals in the library to two cell lines: one of a prostate and one of a non-prostate origin. Primary hits, which demonstrate high selectivity in their toxicity to prostate cells, were confirmed in secondary assays, involving determination of dose dependence of the response followed by secondary screening in a panel of cell lines representing a variety of tissues, including multiple prostate-derived cells. Hits retaining prostate specificity in their toxicity after this step were selected for detailed analysis and prioritized according to their specificity, activity and stability. Pilot in vivo experiments were done with metabolically stable compounds, in which their toxicity and anticancer effect against xenografts of human prostate-derived tumors grown in mice were assessed. However, demonstration of in vivo activity at this stage was not considered an essential milestone since more pharmacological optimization steps are typically needed to reach desirable in vivo properties.

Figure 1-6. Outline of experimental plan and general strategy Detailed explanations can be found in the text. SAR: Structure-Activity Relationship.

After isolation and confirmation of advanced hits, the work was split into parallel lines.

One of them, as mentioned above, included a series of developmental steps known as

“hit-to-lead optimization”. In this arm of study, a consequent series of focused libraries of structural analogues are generated around selected candidates followed by their experimental analysis for activity, specificity, solubility and stability. Further steps involve analysis of metabolism, biodistribution, establishment of formulation and optimal treatment protocols - all necessary steps to complete full-scale preclinical analysis enabling the filing of an application to the FDA to obtain Investigation of New Drug status for clinical trials. This direction of research is done within an industrial entity and outside the scope of the present work.

A second line of study, which formed the substance of the present thesis, was aimed at uncovering the molecular mechanisms of anti-prostate toxicity of isolated compounds with an attempt to identify their target(s). The flow of research is shown in the highlighted area in Figure 1-6. Candidate compounds (hits) were assessed for their relative toxicity in a panel of prostate-specific lines and the results were analyzed taking into consideration the known properties of these cell lines with an expectation to come up with a testable hypothesis regarding their mechanism(s) of action. In addition, the molecules were characterized with respect to their mechanism(s) of anti-prostate activity to determine the mechanism of growth inhibition/death, including cell cycle arrest, senescence, apoptosis, necrosis or autophagy. These data are expected to narrow down the options for the next experimental steps. For example, if the relative toxicity of some of the identified hits were found to be more pronounced towards those prostate-derived cells that are known to express androgen receptor, then logically the compounds would

be analyzed for their effect on AR, including its expression, stability, activity and intracellular localization in order to define the specific part of AR signaling affected by the hits. In parallel, a series of unbiased approaches were also considered. For instance, a series of cell variants selected for resistance to the selected hits were isolated.

Presumably, the resistance was due to specific alterations in expression of the target(s) or with altered accessibility of the compounds (e.g., expressing multidrug resistant pumps).

The first possibility may provide valuable information about the mechanism(s) of drug action, while the latter may provide important information that may be unrelated to the mechanism of action. In this case, ways to overcome these mechanisms must be considered, for example, using functional genomics approaches (shRNA libraries, etc.) to target these cellular factors that may modulate a sensitive phenotype. The information generated within these studies for each of the selected hits was analyzed to understand whether these compounds had the same or different mechanisms. This step involved testing patterns of cross-resistance of cell variants selected for survival in the presence of each individual hit. Altogether, this set of approaches was expected to provide an insight into the mechanism of selective toxicity of the compounds for prostate-derived cells.

In the following chapters, the experimental results generated according to this plan are described as well as the conclusions that were made based on those experimental results

(Figure 1-6).

1.4. Preliminary Data 1: Screening of Small Molecule Library

1.4.1. Rationale and Approach

The major goal of the screening was to identify compounds that had highly selective toxicity against prostate epithelia. If such molecules were isolated, the compounds would be used as tools for the discovery of new prostate cancer treatment targets. There are two major methods for the discovery of new pharmacological agents: rational design of the candidate compounds and functional selection from a chemical collection. Although the first approach appears highly attractive, its feasibility for the given task is questionable.

Knowledge about relevant targets in PCa are scarce, so there would be a lengthy process of identification and validation of such targets before the rational design of corresponding pharmacological modulators could occur. Due to the high urgency and limited prior knowledge, functional screening of chemical libraries provided an attractive alternative.

In fact, several chemical screenings previously performed in our lab resulted in the compounds that protect normal cells from p53-mediated apoptosis or reversed drug resistance associated with multidrug transporters (Burkhart et al., 2009; Gudkov and

Komarova, 2003; Kondratov et al., 2001).

The screening consisted of three steps: primary screening, secondary screening, and long- term survival assays (Figure 1-7A). The primary and secondary screenings were conducted by Dr. Julia Kichina whereas subsequent testing and characterization of validated hits were performed as part of the thesis research presented here. In the primary screening, library compounds (10 µM) were simultaneously tested against the prostate cancer cell line 22Rv1, which is an androgen-independent cell line, and UISO-Mel-7

(Mel-7), a human melanoma cell line, which served as a specificity control. Those compounds that differentially inhibited the growth of 22Rv1 compared to Mel-7 (>30% stronger effect against 22Rv1), were considered as the hits for further characterization.

During secondary screening, the focus was on determining the prostate specificity of the hits. In primary screening, the hits showed preferential toxicity to 22Rv1. However, it was possible that this toxicity was specific for 22Rv1 cells and not to prostate cells in general. Similarly, the lack of toxicity to Mel-7 cells could have been specific for that cell line and not to all non-prostate cells. Therefore, the toxicity of the first round hits was tested against a panel of cell lines of various origins (multiple PCa cell lines, multiple non-prostate cancer cell lines) during secondary screening. The results for the toxicity of hits against the panel of prostate and non-prostate cell lines of various tissue origins enabled us to filter out hits that were generally toxic. Validated hits, i.e. those that demonstrated specific toxicity to a panel of prostate cells and not to non-prostate cells, were named ARKILs (compounds which exhibit toxicity towards AR expressing PCa cell lines). After completion of the first few steps of the screening process, the bulk of the true anti-CRPCa candidates were isolated.

To summarize, the HTS screening for prostate specific compounds included a three-step process: 1) primary screening to identify hits, 2) secondary screening against a small panel of prostate and non-prostate cells at 3 doses to validate the hits and 3) long-term survival assays.

Figure 1-7. Principles of cell-based readout system for the screening A. The filtering stages for hits, including the numbers of compounds that passed throughput each screening step. The primary screening was carried out in 96-well plates with a DIVERSet small molecule library. B. The assay used in primary and secondary screening. Details were described in the chapter of Material and Method.

1.4.2. High Throughput Screening

Primary Screening

The DIVERSet library used for the screening of prostate-specific small molecules was a carefully selected diverse collection of 34,000+ hand-synthesized chemical compounds for HTS. These drug-like small molecules were rationally pre-selected for maximum pharmacophore diversity for initial screening. The compounds were stored as 10 mM in dimethyl sulfoxide (DMSO) solution in -30 °C.

Primary screening was performed using a survival-based quantitatively comparative screening consisting of the human androgen independent PCa cell line 22Rv1 and human melanoma cell line Mel-7 as a specificity control. Cells were plated at 10% confluency and incubated overnight. Library compounds were added to cells the next day to a final concentration of 10 µM. The concentration of 10 µM was based on our lab’s experience, which has indicated that this concentration would yield pharmacological meaningful data without inhibiting all cell growth in general. After 48 hours, cells were fixed and stained with methylene blue methanol solution (MBM; Ch2.1). The plates were washed with distilled water and air-dried. Methylene blue was extracted by adding 100 µl/well 3% hydrochloric acid (HCl) into dried wells. The level of staining was determined by

3 measuring the absorbance at 595 nm (A595) on the Victor plate reader (PerkinElmer

Inc.). With this assay, the absorbance is proportional to the number of cells remaining in the well at the time of staining. The survival ratio of each compound for each cell line, which is the ratio of the A595 for a compound to that of the DMSO (vehicle) control, was calculated. In particular, there were two tiers of hits from primary screening: Tier 1- a

compound’s survival ratio for 22Rv1 is <30% and that for Mel-7 is >70%; Tier 2- a compound’s survival ratio for 22Rv1 is between 30% and 70% as well as the differential ratio between Mel-7 and 22Rv1 is more than 30%. According to the screening criteria,

~200 primary hits were isolated.

Secondary Screening

In a survival-based screening, it is typical to get quite a large number of false-positive hits during the primary screening. Based on our lab experience, the “true hits” that are confirmed later usually comprise less than 20% of initially selected hits. Moreover, the objective was not just to find something toxic to 22Rv1 cells, but something that would be toxic to multiple prostate cells and, most importantly, not to non-prostate cells. Thus, the candidates were passed through a strict filter of secondary screening: they had to be toxic to cells of prostate origin and not to multiple non-prostate controls.

The secondary screening was carried out essentially under the same conditions used for the primary screening using multiple doses (Figure 1-9). The additional PCa cell lines tested in the secondary screening included CWR22R, LNCaP, C4-2, DU145, and PC3.

These cell lines have been well characterized as androgen responsive (LNCaP) or CRPCa

(CWR22R, C4-2, DU145, and PC3) cells. PC3 and DU145 have completely lost AR expression and express human prostate tumor markers, such as PSA and PSMA expression. Cell lines 22Rv1, CWR22R, LNCaP and C4-2 have an active AR signaling pathway. C4-2 cells were isolated from a xenograft of LNCaP cells grown in castrated

hosts (Gregory et al., 1998; Wu et al., 1994). 22Rv1 and CWR22R were derivatives of xenograft tumor CWR22 cells grown in castrated hosts (Wainstein et al., 1994). The collection of non-prostate cancer cell lines used to determine prostate specificity included fibrosarcoma HT1080, osteosarcoma Saos2, breast cancer MCF7, non-small cell lung carcinoma H1299, renal carcinoma ACHN, colon cancer HCT116, and melanoma UISO-

Mel-7. As a result, the majority of candidates did not pass the secondary filter for prostate specificity: they were toxic to lines of non-prostate origin or insufficiently toxic to

22Rv1. Some compounds were toxic only to 22Rv1 and CWR22. Since the compounds of this class had hardly any effect on all other cells, this specificity was interesting enough for further characterization in case the compounds targeted a specific type of

PCa, which was represented by 22Rv1.

Based on secondary screening, nine candidate hits survived the PCa specificity filter.

These hits belong to five distinct chemical classes. Four hits showed unique structures.

Five others shared a similar structure and a similar toxicity profile. Those five were grouped together into one structural class. The best candidate of each class was selected for further characterization since according to drug characteristics, such as logP, H bond acceptors, H bond donors and molecular weight (Lipinski et al., 2001), all five compounds appear to be promising for further development. None of the discovered hits has been previously recognized as chemotherapeutic agents. In later tests, one representative member from each group was used. The hits showed highly specific toxicity against 22Rv1 and CWR22R (derived from same PCa xenograft cultured in parallel in our lab for a long period), and some of the hits also demonstrated moderately potent toxicity for LNCaP and C4-2 cells (Figure 1-8). The PCa cell lines specific

toxicity was confirmed in multi-doses cytotoxic assay (Figure 1-9). Since 22Rv1,

CWR22R, LNCaP and C4-2 cells express AR; Due to product limitations for 5715, whose specific toxicity was not as strong as the others, only four hits, 5314, 5582, 6061, and 6137 were used in the following experiments.

Figure 1-8. The secondary screening of the primary hits A. Five candidates selected from primary hits were representative of five classes of compounds that showed specific toxicity to PCa cells. The toxicity assay of the hits were measured under the same conditions used in the primary screening (10 µM, 48 hours treatment). The hits exhibit specific toxicity toward AR expressing PCa cells while little toxicity for other cell types. B. The expression of AR in PCa cell lines.

Figure 1-9. Multi-doses response assay in secondary screening The cytotoxicity assay of the candidate cell lines was measured under the same conditions used for the previous secondary screening with multiple doses of the hits (48 hours treatment). The hits exhibit specific toxicity toward AR expressing PCa cells while little toxicity for other cell types.

1.4.3. Long-term Survival Assay

The cytotoxicity of the selected hits may be due to either true cell death or growth arrest.

However, true inhibition of viability can only be identified over a relatively long period.

Hence, the hits that survived secondary screening were further verified using a long-term survival assay with 22Rv1, DU145, and Mel-7 cells treated with various concentrations of the different hits. The concentrations of the hits were selected between the IC50 and

IC90 of 22Rv1 as determined from short term cytotoxicity assays such that at least dozens of colonies of 22Rv1 survived after 3 to 4 weeks of treatment with the hits.

In the long-term survival assay, the cells (100,000 for sensitive 22Rv1 cells, 400 for resistant DU145 and Mel-7 cells) were plated in 100 mm dishes and treated with the hits.

Then, fresh medium with the hits was added and changed every other day. When colonies formed (more than 50 cells per colony) in treated 22Rv1 and all of DU145 and Mel-7 plates, cells were fixed and stained with MBM solution. The number of colonies was counted and the survival fraction was calculated relative to the respective DMSO treated control. The untreated 22Rv1 plates reached monolayer confluence after about two weeks. Therefore, the number of “colonies” could not be precisely calculated. Based on my experience of plating efficiency, 1/10 of the original number of 105 cells produced colonies of untreated 22Rv1. The candidate compounds completely inhibited the growth of 22Rv1 cells in the absence of a significant growth suppressive effect on DU145 and

Mel-7 cells (Figure 1-10A). The hits’ toxicity towards 22Rv1 cells was confirmed by subsequent survival assays (Figure 1-10B). 22Rv1 cells (1x106 per plate, which allowed a monolayer formed after about 10 days incubation in untreated plates) were plated in 100

mm dishes and treated for different lengths of time with various concentrations of

ARKILs. After 10 days, cells were fixed and stained by MBM solution. 1 µM of 6137 and 5582 completely killed 22Rv1 cells. 0.1 µM of 5314 and 5582 killed the majority of plated cells. 10 µM of 6061 also showed great inhibition of 22Rv1 cells.

Figure 1-10. Long-term survival assay of secondary hits toxicity in diverse cell lines A. 22Rv1 cells were (1x105 cells per 100 mm dish) plated and cultured in different concentration of the secondary hits (Table 3-2). Resistant cell lines, DU145 and Mel-7 (400 cells per 100 mm dish) were tested as controls. Fresh medium with compounds was changed every other day. When colonies formed (more than 50 cells per colonies), cells were fixed and stained with MBM solution. The number of colonies was counted, and the survival ratio was calculated relative to a respective DMSO treated control. B. 22Rv1 cells were (1x106 cells per 100 mm dish) plated and cultured in different concentrations of the hits as indicated in the figure. Cells were incubated with the hits for 2 weeks. Cells were fixed and stained by MBM solution. 40

1.4.4. Summary

Five classes of small molecules, which are selectively toxic towards AR expressing PCa cells, particularly 22Rv1 cells, were isolated after the screening a 34,000 small molecule library. None of the compounds were selectively toxic for all prostate cancer-derived cells. Four best candidates (5314, 5582, 6061, and 6137) were used in mechanistic studies. Hereby, the proposed hypothesis of mechanistic studies is that the isolated hits are effective against certain specific subtype of PCa and can be used as tools for identification of novel anti-PCa treatment targets.

1.5. Preliminary Data 2: In Vivo Evaluation Therapeutic Efficiency of 5582

Demonstration of in vivo activity at this stage was not considered an essential milestone since more pharmacological optimization steps hadn’t been done. But, to determine the potential of the secondary hits as anti-PCa therapy, the biological activity of the hits must be evaluated in vivo. In independent studies conducted by Dr. Gurova’s group, the efficacy of 5582 was evaluated (Narizhneva et al., 2009). The anti-tumor activity of 5582 in mice was determined according to an IACUC-approved protocol (Roswell Park Cancer

Institute, RPCI). For this experiment, immunodeficient athymic nude mice (n= 10 per treatment group) were used to grow the human prostate tumor-derived CRPCa cell line,

22Rv1, as subcutaneous (s.c.) xenografts (one tumor per mouse), followed by daily intravenous (i.v.) administration of 5582. The dosage of 5582 was 18 mg/kg/day. Five daily injections of 5582 suppressed the growth of 22Rv1 tumors (Figure 1-11) without any noticeable adverse side effects as assessed by evaluating mouse weight and condition over the course of the study as well as necropsy at completion. Among 10 mice treated with 5582, tumors completely disappeared in 2 mice, regressed in 1 mouse and did not change in size in 5 mice (i.e. stable disease). In contrast, 9 out of 10 control animals displayed progressively growing tumors. The results of this efficacy study indicate that

5582 is generally non-toxic, yet blocks the growth of CRPCa tumors. Therefore, 5582 is a candidate for the development of therapeutic agents against PCa.

In vivo experimental result of 5582 enforced the hypothesis that the isolated hits have potential for development into therapeutic agents against PCa.

Figure 1-11. Tumor inhibition of 5582 by i.v. injection (Narizhneva et al., 2009) 10 nude mice were i.v. administrated with five daily injections of 5582 at a dosage of 18 mg/kg/day. PBS was used as the vehicle in the control group of mice. 5582 exhibited anti- tumors potential. Asterisks (*) are placed under the means of measurement which are statistically different from the control group by a ANOVA test (p < 0.05). Error bars are standard deviation between the size of tumors within a given treatment group.

Chapter 2. Materials and Methods

2.1. Material

2.1.1. Cell Lines

Cell lines were obtained from laboratory stocks or purchased from ATCC (American

Type Culture Collection) (Table 2-1). PCa cell lines, ACHN, RCC45, NKE, WI138 cells were maintained in RPMI supplemented with 10% fetal bovine serum (FBS), 0.1 mM non-essential amino acids, 1mM sodium pyruvate, 10 mM HEPES, 55 nM β- mercaptoethanol, and antibiotics (penicillin and streptomycin) (Table 2-2). HEMC cells were maintained in HuMEC medium (Invitrogen Inc). MCF10A cells was maintained in

DMEM/F12 supplemented with 25% horse serum, 20 ng/ml EGF, 0.5 mg/ml hydrocortisone, 100 ng/ml cholera toxin, 10 μg/ml insulin, and antibiotics (Table 2-3).

Retrovirus packaging cell line phoenix-eco and lentivirus packaging cell line 293FT were maintained in DMEM supplemented with 10% FBS, 6 mM L-glutamine and antibiotics

(Table 2-3). All other cell lines were maintained in Dulbecco’s modified Eagle’s medium

(DMEM) supplemented with 10% FBS and antibiotics (Table 2-3).

Table 2-1. Cell lines Source Name Species Disease Primary Site* Metastatic Site**

22Rv1 human prostate ⁄ carcinoma

CWR22R human prostate ⁄ carcinoma LNCaP human prostate lymph node carcinoma

C4-2 human prostate ⁄ carcinoma DU145 human prostate brain carcinoma

PC-3 human prostate bone adenocarcinoma

Prostate cancer cancer Prostate lines cell

adenocarcinoma, renal ACHN human kidney ⁄ cell B16 Mouse skin ⁄ melanoma HCT116 human colon ⁄ carcinoma, colorectal Hela human cervix ⁄ adenocarcinoma HT-1080 human connective tissue ⁄ fibrosarcoma MCF7 human mammary gland pleural effusion adenocarcinoma

carcinoma, large cell NCI-H1299 human lung lymph node neuroendocrine RCC45 human renal ⁄ carcinoma Saos-2 human bone ⁄ osteosarcoma UISO-Mel-6 human skin ⁄ melanoma

UISO-Mel-7 human skin ⁄ melanoma Cancer cell lines cell Cancer

HMEC human mammary gland ⁄ epithelial

MCF10A human mammary gland ⁄ epithelial NKE human kidney ⁄ epithelial NMuMG mouse mammary gland ⁄ epithelial

WI138 human fetal lung ⁄ fibroblast Normal cells Normal * Cell lines known to be from primary sites are noted. ** Cell lines known to be from metastasis sites are noted.

Table 2-2. Recipe of medium I - RPMI RPMI RPMI with 2 mM L-glutamine 500 ml FBS 10% Penicillin 100 U/ml Strepmycin 100 µg/ml HEPES (100x) 5 ml Sodium pyruvate (100 mM) 5 ml non essential amino acids 5 ml β-mercaptoethanol 500 µl

RPMI-CSS RPMI without L-glutamine and phenol red 500 ml Charcoal stripped serum (CSS, heat-inactivated) 10% Penicillin 100 U/ml Strepmycin 100 µg/ml HEPES (100x) 5 ml Sodium pyruvate (100 mM) 5 ml non essential amino acids 5 ml β-mercaptoethanol 500 µl

Table 2-3. Recipe of medium II - DMEM DMEM DMEM with 2 mM L-glutamine 500 ml FBS 10% Penicillin 100 U/ml Strepmycin 100 µg/ml

DMEM with high L-glutamine (6 mM) DMEM with 2 mM L-glutamine 500 ml FBS 10% L-glutamine 4 mM Penicillin 100 U/ml Strepmycin 100 µg/ml

DMEM/F12 DMEM/F12 500 ml Horse Serum 5% EGF 20 ng/ml Hydrocortisone 0.5 mg/ml Cholera Toxin 100 ng/ml Insulin 10 μg/ml Penicillin 100 U/ml Strepmycin 100 µg/ml

2.1.2. Chemicals

Table 2-4. Chemicals

Name Stock concentration Sources ARKIL compounds 10 mM ChemBridge Doxorubicin 10 mM Sigma-Aldrich Cycloheximide 1 mg/ml Sigma-Aldrich Actinomycin D 10 mg/ml Sigma-Aldrich α-Amanin 10 mg/ml Sigma-Aldrich R1881 (methyltrienolone ) 1 mM PerkinElmer

2.1.3. Plasmids

The following expression plasmids were used in the study (Table 2-5). A full-length AR cDNA construct (pTVZ-hAR) and a GFP control construct (pTVZ-GFP) (kindly provided by Dr. Katerina Gurova, Roswell Park Cancer Institute, NY) were used in AR overexpression experiments. The pARE-Luc luciferase reporter construct (provided by

Dr. Gurova) was designed to measure AR transcriptional activity and contained triplicate

AREs followed by the minimal rat probasin gene promoter (min pr), luciferase and poly

A with flanking regions (Figure 4-2B). The lentiviral plasmids pLSL-shAR and shGFP were designed to target AR and GFP, respectively (provided by Dr. Gurova). The pLSLPw lentiviral packaging system was kindly provided by Dr. Peter Chumakov

(Lerner institute, CCF, OH)

Table 2-5. Expressing construct Construct Backbone Insert pTVZ-hAR pTVZ3-CMV human wild type AR protein pTVZ-GFP pTVZ3-CMV GFP protein pARE-Luc pcDNA3.1 3x ARE pLSL-shAR6 pLSL shRNA of AR pLSL-shGFP pLSL shRNA of shGFP

Table 2-6. Lentiviral packaging system Construct Backbone Insert pLSL-GAG1 pLSLPw encode GAG protein pLSL-VSV-G pLSLPw encode VSV-G protein pLSL-Rev2 pLSLPw encode Rev protein

2.1.4. PCR Primers

The primers for AR were designed to detect the sequences from exon 2 and exon 3 (AR1s and AR1as) and from exon2 to exon4 (AR2s and AR2as). The primers for GAPDH were used as an internal control.

Table 2-7. Primers for AR investigation Name Sequence AR1s 5'-TGTGGAGATGAAGCTTCTGGGTGT-3' AR1as 5'-ACACTGTCAGCTTCTGGGTTGTCT-3' AR2s 5'-GCGCCAGCAGAAATGATTGCACTA-3' AR2as 5'-TAGAGAGCAAGGCTGCAAAGGAGT-3' cmafs1571 5'-TGCACTTCGACGACCGCTTCTC-3' Scmafas1938 5'-GGTGGCTAGCTGGAATCGCG-3' MafpromoterS3SacI 5'-CGACGAGCTCAATCAAGGAGAAGAGGAGG-3' MafpromoterS2SacI 5'-CGACGAGCTCCTGCCACGATCAAGTCCGA-3' MafpromoterS1SacI 5'-CGACGAGCTCAGGCGAATTCACAATCCTGG-3' mafpromoterASBglII 5'-ATGCAGATCTAATAGCGAAGTCCTGGGGAA-3' GAPDHs 5'-GGCTCTCCAGAACATCATCCCTGC-3' GAPDHas 5'-GGGTGTCGCTGTTGAAGTCAGAGG-3'

2.1.5. Solutions

Cell Fixation and Staining

Table 2-8. Methylene blue methanol (MBM) solution

Methylene blue 0.5% Methanol 50% Adjust volume to 1 liter with Milli-Q (MQ) water

DNA staining in Flow Cytometric Assay

Table 2-9. Propidium iodide DNA staining buffer (3 μM) 1.5 mM propidium iodide (Invitrogen, #P3566) 3 µM 20 mg/ml RNase A (Invitrogen, #12091-021) 0.02 mg/ml 1 M Tris∙Cl (pH 7.4) 100 mM NaCl 150 mM CaCl2 1 mM MgCl2 0.5 mM Nonidet P-40 0.1% Dilute in ultraPURE water and store at 4 °C. Keep from light.

Northern Hybridization

Table 2-10. MOPS Buffer Recipe (10x) 0.4 M 3-[N-Morpholino] propanesulfonic acid, pH 7.0 (MOPS-free 41.2 g acid, MW = 209.27)

0.1 M Sodium Acetate, 3-hydrate (NaOAc-3H2O, MW = 136.08) 10.9 g 10 mM EDTA (pH 8.0) 3.7 g to 800 ml MQ water and stir until completely dissolved; adjust pH to 7.0 with NaOH (prepared in nuclease free distilled water) Adjust volume to 1 liter with MQ water Autoclave to sterilize; stored at room temperature protected from light.

Table 2-11. Nucleic acid transfer buffer (20 x SSC)

Tri-sodium Citrate 88.23 g Sodium chloride (NaCl) 175.32 g Add approximately 800 ml of distilled water. Mix to dissolve Check the pH is 7–8. Make up to a final volume of 1000 ml Store at room temperature for up to 3 months

Western blotting

Table 2-12. HEPES lysis buffer (stock 10 ml, 4°C)

HEPES 20 mM NaCl 150 mM Nonidet P-40 1% EDTA 1 mM Adjust volume to 10 ml with MQ water Protease inhibitor cocktail (PIC, Sigma-Aldrich, #P8340)* 1:1000 *Add PIC to HEPES solution before use

Table 2-13. Running buffer (10 x)

Tris∙Cl 30 g Glycine 144 g Adjust volume to 1 liter with MQ water

Table 2-14. Running buffer (1 x)

10 x running buffer 100 ml 10% SDS 10 ml Adjust volume to 1 liter with MQ water

Table 2-15. Transferring buffer 10 x running buffer 100 ml Methanol 50 ml Adjust volume to 500 ml with MQ water.

Table 2-16. Blocking buffer

5% (W/V) non-fat milk in PBST buffer

Table 2-17. PBST buffer

10 x non sterile PBS 100 ml Tween-20 1 ml Adjust volume to 1 liter with MQ water

Table 2-18. Stripping buffer

β-mercaptoethanol (14 M) 71 µl 10% SDS 2 ml 1 M Tris-Cl (pH6.8) 625 µl Adjust volume to 10 ml with MQ water

Table 2-19. Antibody Name Antigen Resource AR (N-20) N-terminal of AR Santa Cruz Biotech AR (C-19) C-terminal of AR Santa Cruz Biotech AR N-terminal of AR BD Biosciences β-actin-peroxidase N-terminal of β-actin Sigma-Aldrich

Alexa Fluor® 594 IgG heavy chains and light chains Invitrogen donkey anti-Rabbit IgG

2.2. Method

2.2.1. Cell Survival Assay

Methylene blue assay for growth inhibition/cytotoxicity

This survival based assay was performed in 96-well plates for primary and secondary screening. Cells were plated at 10% cell density and incubated overnight. Compounds were added to cells the next day. After 48-72 hours, cells were fixed and stained with methylene blue methanol (MBM) solution (Table 2-8) followed by drying. Methylene blue was extracted by adding 100 µl/well 3% hydrochloric acid (HCl) into the dried wells. The amount of dye eluted from each well was determined by measuring the

3 absorbance at 595 nm (A595) on a Victor Plate Reader (PerkinElmer Inc.). The relative survival ratio of each well was calculated by comparing the (A595) of a treated well with that of an untreated control well.

For dose dependent cytotoxic assay, cells were plated in 96 wells plates and incubated overnight in a 37 °C tissue culture incubator. Serial dilutions of ARKILs were applied to cells in triplicate for each cell line. Cells were fixed and stained by MBM after 72 hours treatment. The plates were washed with distilled water and air-dried. The MBM of each well was extracted from fixed cells by 3% HCl and the A595 was measured using the

Victor3 plate reader. The relative survival ratio was calculated by comparing treated wells with control untreated wells as described above. To represent the data, concentration- response curves were plotted using OriginLab.8.1 (OriginLab Corp., Northampton MA).

Clonogenic survival

Cells were plated in 100 mm dishes and treated with varying concentrations of compounds. Then media containing fresh compound was changed every other day. When colonies (>50 cells in one colony) formed, cells were fixed and stained with MBM. The number of colonies was counted, and the relative survival ratio of each sample was calculated by comparing the number of colonies for the ARKIL-treated sample with that of the untreated control

2.2.2. Flow Cytometric Assay

22Rv1 cells (106) were plated in 60 mm dishes and then treated with ARKILs for 24 hr.

The collected cells were washed with PBS and fixed with 70% ethanol for 30 min at 4

°C. The fixed cells were washed with 0.5% BSA in PBS and then stained by propidium iodide (PI) DNA staining buffer (Table 2-9) for 30 min at 4 °C. After brief centrifugation, the supernant was removed. The stained cells were resuspended in 1 ml fresh PI DNA staining buffer and transferred to Falcon tubes (BD Biosciences, #352235, with 35 µm cell strainer caps) to prepare a single-cell suspension. The PI stained cells were analyzed using the FACscan flow cytometer (BD Biosciences). CellQuest Acquisition and

Analysis Software (BD Biosciences) was used to quantify approximately 1x105 cells per sample.

2.2.3. Hybridization Assays

Northern Blotting Assay

Total RNA samples (2µg/sample) were mixed with Northern Max-Gly sample loading buffer (Ambion, AM8551) and incubated for 30 minutes at 50 °C. RNA samples were separated in 1% formaldehyde denaturing agarose gels and blotted onto Hybond-N nylon membrane (GE Healthcare). Probe, a fragment of c-Maf (AF055376) from 2625 bp to

3162bp, was synthesized from a PCR reaction on sequence-verified pBabe-c-Maf construct. The probe was labeled with α-32P-dCTP (3000 Ci/mmol, GE Healthcare) using the Megaprime DNA labeling system (GE Healthcare, #RPN1604) and random priming protocol. Hybridization was performed using ExpressHyb Hybridization solution (Clontech). After washing, radioactivity on the membrane was detected by

HyBlot CL autoradiography film (Denville Scientific, # E3018).The results were normalized by GAPDH. All hybridizations were repeated at least twice on independently prepared membranes.

Southern Blotting Assay

Genomic DNA samples (5µg/sample) were digested by Hind III overnight. DNA samples were separated in 1.5% agarose gels and blotted onto Hybond-N nylon membrane (GE Healthcare). Probe, a fragment of c-Maf (AF055376) from 2625 bp to

3162bp, was synthesized from a PCR reaction on sequence-verified pBabe-c-Maf construct. The probe was labeled with α-32P-dCTP (3000 Ci/mmol, GE Healthcare)

using the Megaprime DNA labeling system (GE Healthcare, #RPN1604) and random priming protocol. Hybridization was performed using ExpressHyb Hybridization solution (Clontech). After washing, radioactivity on the membrane was detected by

HyBlot CL autoradiography film (Denville Scientific, # E3018).The results were normalized by GAPDH. All hybridizations were repeated at least twice on independently prepared membranes. This work is finished by help of Dr. Tanaka in Cleveland Clinic

Foundation (CCF).

2.2.4. Immunostaining

Cells were plated in 35 mm dishes for the experiments. Before fixation, cells were washed with PBS and then fixed by formaldehyde/zinc fixative (Electron Microscopy

Sciences, #15675-04) for 1 min. The dishes were washed with PBS three times for 30 min. The blocking buffer, 5% BSA (Sigma-Aldrich, #A3059-10G) in PBS, was applied to the cells for 30 min at room temperature. Primary antibody was diluted in PBS (1:250) and applied to cells for 2 hr at room temperature followed by three PBS washes for a total of 30 min. The secondary antibody was conjugated to ALEXA dye (Alexa Fluor® 594 donkey anti-Rabbit IgG, Table 2-19) in blocking buffer (1% BSA in PBS buffer) was incubated with cells for 1 hr at room temperature. The nuclei were stained with 1 µg/ml

Hoechst 33342 (Invitrogen, #H3570) for 10 min at room temperature, followed by three

PBS washes for a total of 30 min. The 25 mm cover slips (Fisher Scientific, #12-545-

102) were mounted with Fluoromount-G mounting medium (SouthernBiotech, #0100-01)

onto the dishes. Images of cells were taken were taken using an Axio Observer A1 (Carl

Zeiss MicroImaging).

2.2.5. Nucleic Acids Preparation

Genomic DNA Preparation

Cultured cells were trypsinized and then centrifuged for 5 min at 300 x g. Genomic DNA was extracted using the DNeasy Blood & Tissue Kit (QIAGEN #69506) according to the manufacturer’s instructions. The DNA was eluted in 200 µl Ultrapure™ distilled water

(DNase and RNase free water, GIBCO #10977-015). The absorbance of A260 and A280 of the eluted DNA samples were measured using a spectrometer (Beckman Coulter DU800).

The concentration of the DNA was calculated based on the absorbance (optical density,

OD) of A260, 1 of OD corresponds to a concentration of 50 μg/ml for double-stranded

DNA. A 260/280 ratio of ~1.8 was considered pure. The genomic DNA samples were stored in -20 °C.

Total RNA Preparation

Total RNA was extracted using the TRIzol reagent (Invitrogen, #15596-026) according to the manufacturer’s instructions. RNA pellets were dissolved in ultraPURE™ distilled water (DNase and RNase free water, GIBCO #10977-015). A260 and A280 of diluted RNA were measured using a spectrometer. The concentration of the RNA was calculated based

on the absorbance of A260, 1 of OD corresponds to a concentration of 40 μg/ml for single- stranded RNA. For a pure RNA sample, the ratio of A260/A280 should be around 2. Total

RNA samples were stored in -80 °C.

Plasmid Preparation

Small-scale plasmid preparation. Individual bacterial colonies were inoculated into 4 ml of growth medium containing antibiotics (100 µg/ml ampicillin, 25 μg/ml kanamycin or

25 μg/ml chloramphenicol). Bacterial cells were shaken vigorously overnight at 37 °C and then pelleted by centrifugation at 13,200 rpm at room temperature using a tabletop microcentrifuge. DNA was purified using the QIAprep Spin Miniprep Kit (QIAGEN,

#27106) according to the manufacturer’s protocol. The purified DNA was dissolved in ultraPURE distilled water. The absorbance of A260 and A280 of the eluted DNA samples were measured using a spectrometer (Beckman Coulter DU800). The concentration of the

DNA was calculated as described above. The genomic DNA samples were stored in -20

°C.

Large-scale plasmid preparation. Bacterial cells were inoculated into 3 ml growth medium and then incubated at 37 °C for more than 6 hours with shaking. One ml of this culture was diluted into 250 ml growth medium containing antibiotics (100 µg/ml ampicillin, or 25 μg/ml kanamycin, or 25 μg/ml chloramphenicol). The bacterial cells were harvested by centrifugation at 6,000 g for 15 min at 4 °C. The purification of DNA

was done using the QIAGEN Plasmid Maxi Kit (QIAGEN, #12165). The DNA was dissolved in ultraPURE distilled water. The absorbance measured and concentration of the DNA calculated as described above. The DNA samples were stored in -20 °C.

2.2.6. Polymerase Chain Reaction (PCR)

PCR amplification

To generate DNA fragments for cloning, PCR reactions using AccuPrime Pfx DNA polymerase (Invitrogen, #12344-032) were set up as follows:

1x Pfx mix buffer 1x Primer S* 0.25 µM Primer AS* 0.25 µM Template DNA 100 ng Pfx DNA polymerase 1.25 U Adjust volume to 50 µl with MQ water * The sense (S) and antisense (AS) primers were prepared in 50 µM.

The PCR running program was:

Initial denature 95 °C 120 sec Amplification denature 95 °C 15 sec Annealing X* °C, 30 sec Extension 68 °C Y**s Repeated for 30 cycles Final extension 68 °C for 3 min * The annealing temperature X °C is decided by Tm of primers. ** The extension time Y seconds is decided by the length of template DNA.

The PCR reaction was carried out in a DNA Engine Dyad Peltier Thermal Cycler (Bio- Rad).

Reverse Transcription (RT)-PCR assay

Total RNA was isolated from cells as described above. The first-strand cDNA was synthesized from 2 µg of total RNA using the SuperScript III First-Strand Synthesis

System (Invitrogen, #18080-051). The total RNA was mixed with 1 µl of 50ng/µl random hexamer primers and 1 µl of 10 mM dNTP mix, and diluted in ultraPURE distilled water to 10 µl. The RNA/primer mixture was denatured at 65 °C for 5 min, and then chilled on ice. The mixture was gently mixed with 10 µl cDNA synthesis mix which includes 2 μl of 10X RT buffer, 4 µl of 25 mM MgCl2, 2 µl of 0.1 M DTT, 1 µl of 40

U/µl RNaseOUT, and 1 µl of 200 U/µl SuperScript III reverse transcriptase. The random hexamer primers were annealed to total RNA at 25 °C for 10 min. The reverse transcription was carried out at 50 °C for 50 min and terminated at 85 °C for 5 min. The cDNA in 1 µl of the reverse transcription mixture was then used as template for PCR.

The PCR was carried out as described above. The primers for PCR were as shown in

(Table 2-7). The number of PCR cycles was based on the abundance of the detecting gene.

Real time RT-PCR assay

Real-time PCR was performed using an Applied Biosystems HT7900 Fast Real-Time

PCR system. The 10 µl PCR reaction included 0.32 µl cDNA, 1x TaqMan Universal

PCR master mix (Applied Biosystems, #4304437), and 0.5 µl of primers and probe mix of the TaqMan Gene Expression Assay (Applied Biosystems, #Hs00907242_m1) for AR.

The TaqMan Gene Expression assay for 18S rRNA (Applied Biosystems,

#Hs99999901_s1) was used as an internal control. The reaction was incubated in a 96- well plate at 95 °C for 10 min followed by 40 cycles of 95 °C for 15 s and 60 °C for 1 min. The threshold cycle (Ct) data was determined using the default threshold setting.

The Ct is defined as the fractional cycle number at which the florescence passes a fixed threshold. The “delta-delta Ct method” was used for comparing relative expression results between treatments in real-time PCR (Livak and Schmittgen, 2001).

2.2.7. Transfection

Cells were plated and incubated overnight. Plasmid constructs or control vector were transfected together with an internal control plasmid, which was used to control the experiment for transfection efficiency (transient transfection) or for selection of transfected clones (stable transfection), using Lipofectamine Transfection Reagent

(Invitrogen, #18324-012) and PLUS Reagent (Invitrogen, #11514-015) according to the manufacture’s instructions. Transfection medium (DMEM with FBS only) was replaced with fresh regular medium after three hours. For transient transfections, the transfected cells were used in the experiments after 24 to 48 hours. For stable transfections, the transfected cells were selected in the presence of the antibodies (G418, or puromycin).

2.2.8. Reporter Assay

Luciferase Reporter Assay

Luciferase reporter assays were conducted with two different protocols: transient transfection and stable transfection. For transient transfection, cells were transfected with the pARE-Luc plasmid. Luciferase reporter activity was measured at 48 hr using the

Luciferase Assay System according to the manufacturer’s protocol (Promega, #E1500).

The luciferase activity (light unit, LU) was determined by measuring the fluorescence of each sample with a luminometer (Promega, # E6501). The relative luciferase activity

(relative light unit, RLU) of the treated cells was normalized to the LU of untreated control. Each experiment was repeated three times independently. For stable transfection, the ARE-Luc reporter construct was integrated into the genome of cell lines by transfection of cells with pARE-Luc followed by selection using 500 µg/ml geneticin

(Invitrogen, # 11811-023).

Dual-luciferase reporter assay

The firefly luciferase reporter (pGL3) and its constructs (pGL3-s1, pGL3-s2 and pGL-s2) were transiently co-transfected with the internal control renilla luciferase reporter (pRL-

TK) into cells. (Table 2-5) The activities of both luciferases were measured by the Dual-

Luciferase Reporter Assay System (Promega, #E1910) as described in the provided manufacturer’s instructions. The luciferase activity (LU) was measured as described

above. The difference between the firefly luciferase activity and renilla luciferase activity of each sample was calculated by comparing the ratio of LUfirefly/LUrenilla.

2.2.9. RNA Interference Analysis

In RNA interference (RNAi) analysis, ON-TARGETplus siRNA SMARTpool of AR, negative control siRNA, and positive control siRNA were purchased from Dharmacon.

ON-TARGETplus siRNA SMARTpool of c-maf is a mixture of four siRNAs targeting one gene. Negative control siCONTROL Non-Targeting Pool is comprised of four siCONTROL Non-Targeting siRNAs. Each individual siRNA within this pool was characterized by genome-wide microarray analysis and found to have minimal off-target signatures. As the positive control of transfection efficiency, siGLO RISC-Free siRNA was co-transfected with functional siRNA. The siGLO RISC-Free siRNA does not interfere with target gene silencing with active siRNA.

2.2.10. Western blotting Analysis

Cells were lysed in HEPES lysis buffer (Table 2-12). After a 10 min incubation on ice, the lysates were vortexed for 30 sec, three times. The supernatants were obtained by high speed centrifugation for 5 min. Protein concentrations were determined with protein assay dye reagent concentrate (Bio-Rad, #500-0006). 20 - 50 µg protein samples were mixed with laemmli sample buffer (Bio-Rad, #161-0737) and denatured in boiling water

for 5 minutes. The samples were separated by 4-20% Tris-HCl precast gels (Bio-Rad,

Criterion Precast Gels) and then transferred to PVDF membrane (Millipore,

#IPVH00010). Membranes were washed briefly and blocked with gentle agitation for 30 min in blocking buffer (Table 2-16). Blocked membranes were incubated with primary antibodies (Table 2-19) diluted in blocking buffer for 2 hour at room temperature or overnight at 4 °C. The membranes were washed three times in PBST buffer (Table 2-17) for 10 min each. The blots were then incubated with the secondary antibodies conjugated with HRP (horseradish peroxidase, 1:10000 dilution) for 1 hr at room temperature in

PBST buffer followed by three washes with PBST. Signals were detected using the chemiluminescent Rodeo ECL western detection reagents (USB, #72550) followed by exposure to HyBlot CL autoradiography film (Denville Scientific, # E3018) and development.

2.2.11. Lentivirus Viral Transduction

293FT cells were transfected with lentiviral construct (pTVZ-hAR, pTVZ-ARmut, pTVZ-

GFP, pLSL-shAR6, pLSL-shGFP) (Table 2-5), together with 3-plasmid lentiviral packaging system (pLSL-GAG, pLSL-VSV-g, and pLSL-Rev2) as described above

(Table 2-6). Supernatants were collected and filtered with 0.22 µm sterile syringe filter

(VWR, #366756) 48h and 72h post transfection. Target cells were infected with the filtered virus-containing supernatants in the presence of 4 µg/ml polybrene (Sigma,

#H9268). If necessary, stable transduction of a construct was selected with selective marker for antibody resistance.

2.2.12. In vivo Evaluation Therapeutic Potential of ARKILs

Pilot toxicity assessment of ARKILS

The toxicity assessment of ARKILs was carried out according to an IACUC-approved protocol (Cleveland Clinic Foundation, CCF). The experiment was performed using outbred 8 week old NIH Swiss male mice from Harlan (Indianapolis, IN), 2 mice per group. The dose of each compound was based on by previous results (Narizhneva et al.,

2009). The compounds were injected intraperitoneally (i.p.) in 50% DMSO. The mice were observed for weight loss and any other abnormal effects for three weeks. The control group of mice received the same volume of DMSO.

Evaluation of in vivo efficacy of ARKIL-3

Testing of the anti-tumor effect of ARKIL-3 in mice was done according to an IACUC- approved protocol (Cleveland Clinic Foundation, CCF) in 8 weeks old male NCI athymic nude mice from Harlan (Indianapolis, IN). For the 22Rv1 xenograft model, 106 22Rv1 cells were injected subcutaneously (s.c.) in two sites of each mouse in PBS. When visible tumors were evident, they were measured using a digital caliper. Tumor volume was calculated according to the formula: Volume = (Length x Width2)/2. Treatment was started when the tumor grew to a size of at least 40 mm3. ARKIL-3 were diluted in 50%

DMSO and delivered i.p. once a day for 5 days. Five mice per group were used. Mice

were monitored daily and tumors were measured every day. Mice were euthanized according to institutional regulations when the size of tumor reached 1,000 mm3.

Comparison of the tumor growth in control and treated mice was done using ANOVA test.

66 Chapter 3. Approaching Mechanisms of the Hits Specific Cytotoxicity

3.1. Hypothesis, Rationale and Approaches

The hypothesis of the mechanistic studies is that the isolated hits are effective against certain specific subtype of PCa and can be used as tools for identification of novel anti-PCa treatment targets. The assessment of the specific toxicity of the hits was evaluated in dose-response cytotoxicity assays against a broader panel of cancer cell lines and normal tissue cells. The evaluation would confirm the anti-PCa specificity of the hits, although the isolated hits already exhibit pretty specific cytotoxicity in many assays with various cell lines in previous screenings.

These additional assays will give a clear indication of how selective the compounds were for PCa cells. The following investigations on the hits inducing growth inhibition/cell death of PCa were expected to narrow down the options for the next experimental steps.

Testable hypotheses for mechanistic studies include biased (AR related) and unbiased approaches. From the results of the primary data, as well as the importance of AR, it is likely that the mechanism(s) involving the activity of the different hits centers around the AR and its signalling pathway since the compounds, in general, specifically affect PCa cell lines that express

AR. The activity of AR is important for viability of PCa cells, hence, an alteration of AR or its signaling pathway is likely be one of the potential targets for the hits toxicity. The AR signaling pathway is a key component of prostate epithelia. As such, alterations in normal signalling through this pathway would be expected to have detrimental effects. Therefore, investigating the influence of the hits on the AR may lead us to potential targets. Because of this, it is a high priority to examine AR behavior in response to the hits’ stress. An AR-responsive luciferase

reporter, which contains the AR regulatory element (ARE) is also available for monitoring AR activity changes. The expression of AR in 22Rv1 in the presence or absence of the hits are also measured and compared by western blotting. If alteration of AR activity and expression is confirmed, suggesting the involvement of AR in the hits sensitivity, we may able to identify potential targets of the hits by exploring the mechanism of the AR response.

In parallel, a series of unbiased approaches were also considered. Isolating resistant variants

(AKRVs) to the hits could be based on the following rationales: 1) isolated compounds may bind to specific cellular factors that are essential for cell viability and render these factors inactive; 2) increased expression of the compounds’ targets can result in resistance of the cells to these compounds; 3) cell variants resistant to the isolated hits may have altered expression (or stability) of the hits’ targets. In many cases, resistance of cells to cytotoxic compounds is associated with overexpression of the drug’s target genes. Many drugs were found based on this theory. For example, expression of dihydrofolate reductase (DHFR) can be competitively and reversibly repressed by methotrexate (Norris et al., 1996); the antimetabolite, N-phosphonacetyl-L-aspartate

(PALA) can inhibit its target enzyme CAD (carbamoyl-phosphate synthetase II, aspartate transcarbamylase, dihydroorotase) by several different mechanisms (Stark, 1993). Hence, new potential drugs can be identified by finding the druggable target genes. The cytotoxic compounds can alter these genes (upregulated or downregulated) in AKRVs of the target organism. The

AKRVs may develop similar mechanisms against the hits. Resistance may be similar to that observed in the development of CRPCa where several hormone resistant pathways are elevated that affect the activity of AR.

The selected AKRVs would also been used in other unbiased methods for the mechanistic studies. Exploring gene profiles between 22Rv1 and the AKRVs by mRNA microarray analysis may reveal the altered genes which contribute to resistance of the

AKRVs. Introducing shRNA constructs from shRNA library may inference sensitivity of cells (22Rv1 or AKRVs). By validating the transduced shRNA constructs may give us hints for the mechanism of the isolated hit.

All in all, it is expected that mechanistic studies on AR in 22Rv1 cells and AKRVs may reveal the potential targets of the isolated compounds.

3.2. Characterization of the Hits by Cytotoxicity Assay

Survival based 72h cytotoxicity dose-dependent assays for the hits were performed as described in Methods with a full concentration range of the hit doses (0.2 ~ 50 µM) using a large panel of prostate and non-prostate cancer cells as well as representatives of normal tissue. These cell lines included: 1) PCa cell lines- 22Rv1, LNCaP, C4-2,

DU145, and PC3; 2) non-prostate cancer cell lines- ACHN, RCC45 (kidney), H1299

(lung), HCT116 (colon), Mel-7 (skin), and 3) normal tissue cells- mouse myoblast

(C2C12), human mammary epithelial cells (HEMC), normal kidney epithelium (NKE),

normal murine mammary gland cells (NMuMG) and human fibroblasts (WI138). Some hits exhibited specific toxicity to 22Rv1 cells without obvious toxicity toward other cells.

5314 exhibited an specific cytotoxicity towards 22Rv1 cells but had no obvious effect on all other tested cancer cell lines or normal tissue cells (Figure 3-1). 5582 displayed in a similar pattern of toxicity as 6137, however, it was even more toxic to 22Rv1 cells

(Figure 3-2). 6061 showed strong cytotoxicity in 22Rv1, a mild one on LNCaP, and little effect on the other PCa cells tested. 6061 is toxic to non-PCa cancer cell at very high concentrations while showing almost no toxicity toward normal tissue cells (Figure 3-3).

6137 was extremely toxic to 22Rv1 cells (IC50, ~0.4 µM) and showed significantly toxicity toward LNCaP (IC50, ~4 µM). In contrast, toxicity was only observed in non-

PCa and normal cells at much higher concentrations (~6-16 fold less sensitive than

LNCaP and ~16-36 fold less sensitive than 22Rv1) (Figure 3-4). The pattern of specificity of the different hits was confirmed against an additional panel of non-PCa cells, including Saos2, Be2C, and MCF10A (data not shown). From the compiled data of these dose-response cytotoxicity assays, the hits, particularly 6061, 6137, and 5582, have a stronger effect against AR-expressing prostate cells (22Rv1 and/or LNCaP) than non- prostate cancer cells with the strongest effect observed in 22 Rv1 cells (Figure 3-2,

Figure 3-3, Figure 3-4). All in all, the hits were more toxic to 22Rv1 and, to a lesser extent, to LNCaP compared to non-PCa cancer cells and normal cells. This indicates that the identification of molecules, that are selective to a certain population of PCa (AR positive), can be achieved. And thus, the hits can be used as research tools for the mechanistic studies.

Figure 3-1. Cytotoxic assay of 5314 in diverse cell lines or tissues Cells were plated in 96 wells plates and incubated overnight in a 37 °C tissue culture incubator. A series of concentrations of 5314 was applied to cells in triplicate for each cell line. Cells were fixed and stained by MBM after 72 hour treatment. The plates were washed with distilled water and dried in air. The MBM of each well was extracted from fixed cells 3 with 3% HCl and measured at A595 in a PerkinElmer Vicotr plate reader. The survival ratio was calculated by comparing cell numbers in treated wells with control untreated samples. The curve of survival ratio was plotted by Originlab8.1.

Figure 3-2. Cytotoxic assay of 5582 in diverse cell lines or tissues Cells were plated in 96 wells plates and incubated overnight in a 37 °C tissue culture incubator. A series of concentrations of 5582 was applied to cells in triplicate for each cell line. Cells were fixed and stained by MBM after 72 hour treatment. The plates were washed with distilled water and dried in air. The MBM of each well was extracted from fixed cells 3 with 3% HCl and measured at A595 in a PerkinElmer Vicotr plate reader. The survival ratio was calculated by comparing cell numbers in treated wells with control untreated samples. The curve of survival ratio was plotted by Originlab8.1.

Figure 3-3. Cytotoxic assay of 6061 in diverse cell lines or tissues Cells were plated in 96 wells plates and incubated overnight in a 37 °C tissue culture incubator. A series of concentrations of 6061 was applied to cells in triplicate for each cell line. Cells were fixed and stained by MBM after 72 hour treatment. The plates were washed with distilled water and dried in air. The MBM of each well was extracted from fixed cells 3 with 3% HCl and measured at A595 in a PerkinElmer Vicotr plate reader. The survival ratio was calculated by comparing cell numbers in treated wells with control untreated samples. The curve of survival ratio was plotted by Originlab8.1.

Figure 3-4. Cytotoxic assay of 6137 in diverse cell lines or tissues Cells were plated in 96 wells plates and incubated overnight in a 37 °C tissue culture incubator. A series of concentrations of 6137 was applied to cells in triplicate for each cell line. Cells were fixed and stained by MBM after 72 hour treatment. The plates were washed with distilled water and dried in air. The MBM of each well was extracted from fixed cells 3 with 3% HCl and measured at A595 in a PerkinElmer Vicotr plate reader. The survival ratio was calculated by comparing cell numbers in treated wells with control untreated samples. The curve of survival ratio was plotted by Originlab8.1.

3.3. Mechanism of Prostate Cell Death

It is well known that inhibition of AR can induce apoptosis of prostate cells (Grossmann et al., 2001; Olsen et al., 1998). As a first approach to identify the mechanism underlying the selected hits-medicate cell death, the apoptotic cells (sub-G1) can be separated from normal cell cycle population by their lower DNA content (PI staining) in flow cytometry analysis (Ormerod et al., 1992; Schmid et al., 1994). The induction of apoptosis by the hits was confirmed by cell cycle analysis, which showed that the percentage of cells in the sub-G1 population increased with increasing concentrations of the compounds

(Figure 3-5). The apoptotic cells were ~4% with 1 µM 5314, ~5% with 1 µM 5582, ~1% with 10 µM 6061, and ~3% with 2 µM with 6137 after 24 hours treatment., The apoptosis was further confirmed by PARP1 cleavage, which was used as a marker for apoptosis

(Gottesman et al., 2002). PARP cleavage was monitored with a PARP antibody by western blotting analysis. The antibody specifically recognizes the 89 kDa fragment of the cleaved PARP and the uncleaved 116 kDa PARP. In these experiments, 22Rv1 cells and insensitive control Mel-7 cells were treated with the hits for 48 hours that is long enough for apoptosis induced PARP1 cleavage and the cleavage was evaluated by western blotting using the anti-PARP antibody. As illustrated in Figure 3-6, the hits induce apoptosis in 22Rv1 cells but not in Mel-7.

The induction of apoptosis by the isolated hits brought the next question was how the apoptosis was induced by the hits? Together with the results of dose-dependent cytotoxicity assays we hypothesized that the isolated hits affected function of AR expressing PCa cells via AR signaling pathway.

Figure 3-5. FACS analysis of apoptotic cells in the selected hits treatment 22Rv1 cells were treated with various concentrations of the hits for 24 hours. The induced apoptosis of 22Rv1 cells was analyzed by PI staining as described in Chapter 2. The fraction of sub-G1 increased with increasing the hit concentration.

Figure 3-6. The selected hits inducing apoptotic PARP cleavage 22Rv1 and Mel-7 cells were treated with the selected hits (as indicated concentration above) for 48 hours. The apoptotic cells were evaluated by western blot with anti-PARP antibody. The hits showed strong induction of apoptosis on 22Rv1 cells but not on Mel-7 cells.

3.4. Are AR Involved in the Isolated Hits Cytotoxicity?

3.4.1. Effect of the Hits on AR Transactivation Function in Sensitive PCa

Cells

Only AR expressing PCa cells were sensitive to the hits indicated the possibility of AR involvement in the hits toxicity. AR, as one of most important transcriptional factor in

PCa cells, regulates many downstream genes (Figure 3-7A). To investigated the hypothesis that the isolated hits affected function of AR expressing PCa cells via AR signaling pathway, the AR transcriptional activity was measured by the pARE-Luc luciferase reporter construct (Figure 3-7B), which was stably transfected into 22Rv1 cells and selected with geneticin. A scheme of the experiment is presented in Figure 3-7B. The ability of AR luciferase reporter to respond to the synthetic androgen methyltrienolone

(R1881) (PerkinElmer, #NLP005005MG) in 22Rv1 was confirmed. R1881 is commonly used in investigation of androgen-AR interaction in vitro (Vittek et al., 1985; ZAVA et al., 1979). The concentration of R1881 was 10 nM which is enough to activate AR luciferase reporter.

Since FBS contains testosterone the endogenous AR of 22Rv1 is always active in regular

RPMI-FBS medium. The experiments were therefore performed in RPMI-CSS medium, which is filtered through charcoal to remove non-polar material such as progesterone, cortisol and testosterone. To remove the influence of previously active AR induced by

FBS-testosterone on luciferase reporter activity, the cells were incubated in RPMI-CSS for 48 hours before the experiments.

To investigate the influence of the hits, the suitable time and dose of the hits treatment was determined in several rounds of dose- and time- dependent assays of the hits with

R1881. In the dose-dependent assays, the cells transfected with pARE-Luc plasmid and selected with geneticin for stable ARE luciferase reporter expressing cells. After a 48 hour incubation with RPMI-CSS medium, cells were plated in 96 wells plates with 10 fold serial dilution of the hits in RPMI-CSS medium for 18 hours (decided with the results of time-dependent assays). The AR transcriptional activity was measured by luciferase activity after treatment of the hits. All hits showed inhibition of AR transcriptional activity in 22Rv1 cells with 5582 having the strongest effect (Figure

3-8A). The concentrations (which allowed no more than 25% cells survival after 18 hour treatment) for the following assay was also decided with the dose-dependent assay result.

The treatment time was decided in time-dependent assays (Figure 3-8B). AR reporter activity was measured until 32 hours with the hits in a R1881 time-dependent assay. One parallel set of samples was fixed by MBM as a control at the same time. The MBM stained and fixed cells showed there was little cell death during the 32 hours of the hits treatment. 5582 inhibited AR transcriptional activity of 22Rv1 cells within 8 hours. In contrast, 6061 and 5314 inhibited AR transcriptional activity of 22Rv1 cells 12 ~ 16 hours after exposure (Figure 3-8B). Hence 18 hour treatment of the hits was chosen, which can induce AR luciferase reporter with little induction of cell death (Figure 3-8C).

Under conditions decided above, the isolated hits exhibited a strong inhibition on the transactivation capacity of AR in 22Rv1 cells (Figure 3-9). The AR transcriptional activity in 22Rv1 cells was suppressed by the hits to 25% that of the untreated cells.

In Figure 3-8C, the cells (22Rv1/ARE-Luc) was treated with 5314 (1 µM) and 5582 (0.5

µM). The AR reporter activity was measured at 12, 24, and 36 hours. A parallel set of plates was treated in a similar manner and stained with methylene blue to ensure that any decrease in reporter activity was due to actual inhibition of AR activity and not due to cell death (Figure 3-8C, right panel). Both 5314 and 5582 significantly inhibited AR activity by 24 hours (Figure 3-8C, left panel). Luciferase activity was reduced after 24 hour exposure to 5314 or 5582 in 22Rv1/ARE-Luc cells indicating that the hits could suppress AR transcriptional activity in these cells. Moreover, the loss of AR activity in

22Rv1 may be associated with apoptosis induced by the isolated hits.

Figure 3-7. Scheme of AR translocation and ARE luciferase reporter A. Androgen activated AR is released from heat shock proteins. Dimer of active ARs translocate into nucleus with AR coregulators. Active AR complex binds to AR response element (ARE) in the promoter of regulated genes. B. Experimental scheme using stably transfected 22Rv1/ARE-Luc cells. The ARE-Luciferase reporter has three copies of the ARE linked to a minimal rat probasin gene promoter (Tararova et al., 2007).

C Figure 3-8. AR transcriptional activity in the hits dose- and time-dependent assay The cells with ARE luciferase reporter were plated in 96 wells plates as described previously. The AR transcriptional activity was measured and calculated by luciferase assay. A. The luciferase activity was measured and normalized to MBM fixed and stained parallel plates. The hits showed strong inhibition on AR transcriptional activity of 22Rv1. B. The cells were treated with 10 nM R1881 and the hits every other 4 hours until 32 hours. The AR transcriptional activity of 22Rv1 was suppressed by the hits after 8 to 16 hours compared with untreated cells. C. AR activity of 22Rv1 in 24 hours after treatment with 5314 and 5582 as determined by luciferase reporter assay. Parallel treatment fixed and stained by MBM as a viability control (right).RFU: relative fluorescence unit; RS: relative survival ratio.

Figure 3-9. AR transcriptional activity in R1881 dose-dependent assay of the hits The cells were incubated with 10 fold serial dilution of R1881 together with the hits for 18 hours. The AR transcriptional activity of 22Rv1 was suppressed by the hits to 25% that of untreated cells.

3.4.2. Do the Isolated Compounds Affect AR Protein Abundance?

It is well known that inhibition of AR induces apoptosis of prostate cells (Grossmann et al., 2001; Olsen et al., 1998). Therefore, the induction of apoptosis by the hits may be due to the modulation of the AR signaling pathway. Because the massive cell death (~ >75%) of 22Rv1 in response to the hits treatment usually occurred within 48 hours, 22Rv1 cells were treated with increasing doses of each of the hits for 48h and then the lysates from treated cells analyzed by western blotting using an AR-specific antibody (Santa Cruz,

#sc-816).. The housekeeping gene β-actin (Sigma-Aldrich, #A3854) was used as a loading control. The expression of AR was strongly suppressed by all hits (Figure 3-10).

As mentioned in the Introduction, 22Rv1 cells have a mutant AR allele (ARΔLBD) that has lost the ligand-binding domain. Interestingly, both AR (larger band, with duplicated

Exon 3) and AR∆LBD (smaller band) in 22Rv1 are sensitive to the hits. This indicates that the sensitivity of 22Rv1 cells to the isolated hits may be due to downregulation of

AR. Moreover, similar downregulation of AR by the hits was not observed in other PCa cells (LNCaP and C4-2, data not shown). AR expression of LNCaP (androgen dependent) and C4-2 (androgen independent) was not affected by the hits indicating that it is not AR alone that is involved in the cytotoxic activity of ARKILs in 22Rv1. The non-response of

AR in LNCaP and C4-2 may partially explain why they are resistant to the isolated hits.

Figure 3-10. AR expression was inhibited by 5314 and 5582 in 22Rv1 A. 22Rv1 cells were treated by the hits for 48 hours. Lysates were collected and run on western blots with anti-AR serum. Note that 22Rv1 express two AR alleles (arrows)

3.4.3. The Isolated Hits were Named as ARKILs

All isolated hits inhibit activity of AR in 22Rv1 cells and lead to downregulation of AR, indicating that AR is a potential target of the isolated hits. Based on these properties, we named them ARKILs (Androgen Receptor KILlers). As indicated in 5314 was named as ARKIL-3; 5582 was named as ARKIL-8; 6061 was named as ARKIL-1; 6137 was named as ARKIL-7 (Table

3-1).

The previous experiments proofed the hypothesis that the isolated hits affected function of AR expressing PCa cells via AR signaling pathway. Thus, ARKILs can be used as tools for identification of novel anti-PCa treatment targets. We explored the possibility that AR, or factors involved in control of AR signaling pathway, are potential targets of ARKILs in following experiments.

Table 3-1. Name of the isolated hits ID Name 5314 ARKIL-3 5582 ARKIL-8 6061 ARKIL-1 6137 ARKIL-7

3.5. Is AR a Potential Target of the Isolated Hits

3.5.1. Potential mechanism of ARKILs

The inhibition of AR activity indicates that AR may be the potential target of ARKILs. There are several possibilities for inhibition of AR activity by ARKILs. As indicated in Figure 3-11,

ARKILs may suppress AR transcription or translation, block AR nuclear translocation, disturb stability of AR mRNA or protein, or influence AR transcription or translation. The other possibility is that AR is not direct target of ARKILs. ARKILs disturb some unknown factors involved in AR signaling pathway, thus lead to inhibition of AR activity. Since the influence on

AR happened as early as 8 hours, there is a little chance that ARKILs affected AR translation. We focused on other possibilities.

Figure 3-11. Potential targets of ARKILs in PCa cells To understand the mechanism by which ARKILs affect AR levels, several directions were explored: DNA level (genomics), RNA level (transcription or mRNA stability), protein level (translation or protein stability), or transcriptional activity of AR. AR may also be regulated by unknown factors Thus far, all that is known about ARKILs is that they inhibit growth of 22Rv1 cells in an AR dependent manner.

3.5.2. Is Translocation of AR Affected by ARKILs?

As a transcriptional factor, AR translocate into nuclei to exert its function (Figure 1-4,

Figure 3-7). Since the inhibition on AR function happened as early as 8 hours to 16 hours, it is possible that ARKILs interfere with nuclear translocation of AR thereby inhibiting AR function. To investigate this hypothesis, 22Rv1 cells were pretreated with

ARKIL-3 or ARKIL-8 for 12 hours followed by 10 nM R1881 in the presence or absence of ARKL-3 or ARKIL-8 for another 2 hours and then analyzed by immunofluorescence staining for AR as described in the Materials and Methods. As AR is functional in 22Rv1

CRPCa cells, it was not surprising that AR translocation was induced by R1881 (Figure

3-12, Figure 3-13). The ligand dependent translocation was not blocked by ARKIL-3 or

ARKIL-8.

Figure 3-12. ARKIL-3 did not inhibit R1881 induced AR translocation Translocation of AR was immunostained with anti-AR antiserum to analyze its subcellular localization. Cells were plated on 35 mm dishes for the experiments. The cells were pretreated with ARKIL-3 for 12 hours, followed by 10 nM R1881 (together with ARKIL-3) treatment for another 2 hours. The immunostain of AR was conducted as described in chapter 2. R1881 induced AR translocation in 2 hours, however, ARKIL-3 did not inhibit R1881 induced AR translocation.

Figure 3-13. ARKIL-8 did not inhibit R1881 induced AR translocation Translocation of AR was immunostained with anti-AR antiserum to analyze its subcellular localization. Cells were plated on 35 mm dishes for the experiments. The cells were pretreated with ARKIL-3 for 12 hours, followed by 10 nM R1881 (together with ARKIL-3) treatment for another 2 hours. The immunostain of AR was conducted as described in chapter 2. R1881 induced AR translocation in 2 hours, however, ARKIL-3 did not inhibit R1881 induced AR translocation.

3.5.3. Do ARKILs Influence the Stability of AR and AR mRNA?

Does ARKIL-3 affect the Stability of AR protein?

Western blotting demonstrated decreased AR abundance following treatment of 22Rv1 cells with each of the four studied ARKILs. One possible explanation for this is that

ARKILs inhibit the stability of AR. To test this hypothesis, cycloheximide (CHX) was used during the incubation of cells with ARKIL-3. CHX inhibits protein biosynthesis in eukaryotic organisms by blocking translational elongation (Kominek, 1975). If new protein synthesis is stopped by CHX, any influence of ARKILs on stability can be measured. Combining CHX and ARKILs allows one to determine whether the half-life of

AR is affected by ARKIL-3. As shown in Figure 3-14A, however, there was no difference in the half-life of AR protein in the presence of ARKIL-3 alone compared to

ARKIL-3 plus CHX. Therefore, ARKILs, (at least ARKIL-3), do not affect AR protein stability.

Does ARKIL-3 affect the stability of AR mRNA?

Since stability of AR was not affected by ARKIL-3 at the protein level, it is possible that this molecule inhibits the transcription of AR mRNA or reduces the stability of this mRNA. Therefore, the stability of AR mRNA in 22Rv1 cells was checked by using the highly effective transcription inhibitors actinomycin D (ActD, data not shown) and α- amanitin (α-Ama). -Amanitin interacts with RNA polymerase II (RNAP II) (Kedinger et al., 1970; Lindell et al., 1970), and RNAP III (Weinmann et al., 1974) to block the

incorporation of new ribonucleotides into nascent RNA chains. In contrast, actinomycin

D inhibits RNAP I by preventing the progression of RNA polymerases along the DNA template (de Mercoyrol et al., 1989; Perry and Kelley, 1970; Sobell, 1985). By treating cells with ARKIL-3 in the presence of these inhibitors, we will determine whether

ARKIL-3 affects AR mRNA half-life. The results of these experiments showed that the stability of AR mRNA was not affected by ARKIL-3 (Figure 3-14B).

Moreover, there was no difference in the stability of AR mRNA in 22Rv1 cells incubated with the transcription inhibitors in the presence or absence of ARKIL-3, there was also no obvious decrease in AR mRNA levels 24 hour treatment with ARKIL-3. Therefore, it is not possible that ARKIL-3 inhibits the activity of transcription factors responsible for

AR expression.

Figure 3-14. Stability assay of AR in 22Rv1 with ARKIL-3 A, cells were pretreated with 20 µg/ml cycloheximide (CHX) 30 minutes before 1 µM ARKIL-3 was added into the medium. Cell lysates were collected at 0, 6, 24, 48, 72 hours. The stability of AR was analyzed by western blot using anti AR antiserum. B. cells were pretreated 50 µg/ml α-amanitin (α-Ama) 30 minutes before 10 µM of ARKIL-3 was added into the medium. Total RNA extracts were prepared as described in chapter 2 using primers for AR mRNA or 18s rRNA. Real time PCR was performed as described in chapter 2. 18s rRNA was used as internal control. The relative expression level of AR mRNA was calculated based on the level of 18s rRNA.

3.5.4. Is AR Itself Related to ARKILs Toxicity?

Technical limitations prevent further investigation on how ARKILs interacted with AR activity, however, the relationship between AR activity and ARKILs could be explored from AR itself. It is attractive to suggest that the dose dependent suppression of AR levels in 22Rv1 cells is related to the mechanism underlying ARKIL toxicity, an effect of some ARKILs on the viability of other PCa cells in which AR is less downregulated (data not shown) indicates that toxicity cannot be solely related to this mechanism. To explore the association of AR and apoptosis induced by ARKILs, 22Rv1 cells were transduced with wild type AR. As mentioned in the Introduction, some druggable targets can overexpress themselves to overcome the attack from a compound. If AR is the “target”, overexpression of AR may overcome apoptotic signals induced by ARKILs. In other words, if loss of AR activity as a result of ARKIL treatment is the cause of apoptosis, then overriding the downregulation of AR may decrease sensitivity of 22Rv1 cells to

ARKILs. Alternatively, if apoptosis is the cause of AR downregulation, overexpression of AR will not stop ARKIL induced apoptosis. To test this, a wild type AR expressing construct, pTVZ-hAR, and a control construct, pTVZ-GFP were transiently transfected into 22Rv1 cells. The transfection efficiency was determined by the level of GFP expression at 48 hours. The transfected cells were plated into 96 wells plate and incubated with RPMI-CSS medium for cytotoxicity assays and incubated overnight. The cells were subsequently treated by ARKILs with or without DHT (1 nM) for 72 hours.

The IC50s of each treatment were calculated and compared (Figure 3-15). As shown by western blotting, both endogenous and exogenous ARs were slightly induced by DHT.

Transfected cells greatly overexpressed wild type AR. Unfortunately, such

overexpression of AR did not result in complete resistance for 22Rv1 cells. Instead, DHT induced a slightly increased resistance in 22Rv1 cells. This result suggests that it is not active AR itself that directly contributes to the resistance. In other words, AR is not a direct target of ARKILs. Nevertheless, the AR signaling pathway in general appears to be involved in the resistance.

Figure 3-15. Overexpression of AR did not lower drug toxicity towards 22Rv1 cells 22Rv1 cells were transiently transfected with the wild type AR expressing construct, pTVZ- hAR, or the control construct, pTVZ-GFP. A. After a 48 hour incubation, transfected cells were plated in 96 wells plates for cytotoxicity assays with ARKILs and 1 nM of DHT in triplicate. The cells were fixed and stained after 72 hours. The DHT induced cells showed an increased resistance, whereas overexpression of AR did not contribute to the resistance of these cells. B. Overexpression of transfected AR was confirmed by western blotting of cell lysates with anti AR antiserum.

3.5.5. Summary of the AR Biased Investigations

We found ARKILs inhibit AR transcriptional activity and reduce abundance of AR. We excluded that the change on AR was not from compromising several aspects: translocation, stability of mRNA or protein, translation, transcription. It is still unknown factors which involved in inhibition of AR activity (Figure 3-16A). From the experiments, we learned that the earliest comprise is AR activity (as early as ~7 hours),

Induction of apoptosis by ARKILs happened after 24 hours, however the influence on

AR protein (after 36 hours) and mRNA (48 hours) was far later (Figure 3-16B). These results indicated AR may not be the direct target, however AR signaling pathway is closely involved in ARKILs toxicity. The unknown factor should be a part of AR signaling pathway.

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Figure 3-16. Summary of the investigated ARKILs potential targets Details were described in text. A. The figure showed green checks for the excluded potential targets of ARKILs. B. The timeline was based on the components related to AR with ARKILs treatment.

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3.6. Identification and Characterization of ARKIL Resistant

Variants of 22Rv1

3.6.1. Isolation of Resistant Variants

For exploring the unknown factors, unbiased methods would be used as described in the

Introduction. The unbiased investigation is based on the hypothesis that drug resistant cells are likely to acquire alterations in structure, expression or regulation of the drug target. There are a lot of successful examples. For instance, example 1): resistance to

PALA is associated with overexpression of CAD gene encoding PALA target (Stark,

1993); example 2): resistance to methotrexate is associated with overexpression of

DHFR, the methotrexate target (Norris et al., 1996); example 3): resistance to androgen ablation is associated with mutations in androgen receptor; example 4): resistance to kinase inhibitors is associated with mutations in the target enzyme.

Generation and analysis of 22Rv1 resistant variants to ARKILs was an executable way for the investigation. Presumably, the resistance was due to specific alterations in expression of the target(s) or with altered accessibility of the compounds (e.g., expressing multidrug resistant pumps). One of potential problem is drug resistance may be the result of overexpression of multidrug transporters and therefore has nothing to do with the target.

The Approach is selecting ARKIL-resistant variants and comparing them with parental cells and with each other (Figure 3-17A). By selecting spontaneous mutated 22Rv1 cells which are resistant to ARKILs, exploring the mechanism of resistance may help us

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understand the potential mechanisms of action of ARKILs. The differences found between AKRVs and parental 22Rv1 cells are likely to be associated with ARKIL resistance. The number of distinct resistant phenotypes correspond to the number of targets.

Since spontaneous mutations only occur at a low rate, it is likely that they would not be identified in the common, short-term cytotoxicity assay. Therefore, to obtain such mutants, it was necessary to treat a large number of sensitive cells with the different

ARKILs over a long period. Since the spontaneous mutation rate of the human genome is

~2 x10-6 per genome per generation (Drake et al., 1998; Natarajan et al., 2003), 22Rv1 cells were treated with the highest concentration of the different ARKILs that allowed several colonies to survive amongst a million starting cells (Figure 3-17B). The survivors could contain spontaneously modified genes that contributed to their resistance. During this process, 22Rv1 cells were treated in the continuous presence of the chosen ARKIL concentration with fresh ARKILs being added every other day to ensure that “active”

ARKILs were always present (Table 3-2). After about 20 days of constant treatment with

ARKILs, resistant colonies (>50 cells per clone) formed, which were picked for each

ARKIL treatment (Table 3-2). A similar selection was then repeated and 5 resistant colonies for each ARKIL treatment were isolated in the 2nd round independent selection.

The success of the 2nd round of selection demonstrated the feasibility of the clonal selection. The similar selection rates in both rounds of selection suggest that the AKRVs are derived from a spontaneously modified subpopulation. The selected AKRVs are important research tools for understanding the potential mechanisms of action of these molecules. From this point onward, ARKIL resistant variants are referred to as AK#RV#.

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Figure 3-17. Scheme of selection for resistant variants of 22Rv1to ARKILs Detail was described in the text.

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The independently isolated AKRVs for each class of ARKILs were checked for detailed characterization. The resistance of these AKRVs to the different ARKILs was confirmed using the standard short-term cytotoxic assay (Figure 3-19). Most of AK1RVs and

AK3RVs exhibited more than 70% survival at the highest concentration of ARKILs

(except AK1R1, 61.8%, and AK3R6, 54.8%), compared with only ~18% survival of the parental 22Rv1 cells. Four of AK7RVs showed a similar level of resistance (more than

67.7%), which was close to the level of resistance observed with DU145 (68.1%) and

Mel-7 (76.3%), two cell lines that were inherently resistant to this molecule. In contrast, only ~15% of the parental 22Rv1 cells survived at the same compared concentrations of

ARKIL-7. Resistance of the AK8RVs ranged from 37.1% to 84.6% with the best

AK8RVs being >6-fold less sensitive to 3 µM ARKIL-8 than the parental 22Rv1 cells

(5.76%). This level of resistance of the AK8RVs is comparable to that of inherently non- sensitive cell lines. SNP assays have ruled out the possibility of other origins were contaminating the original population (Table 3-3). We conclude that we have successfully isolated a minor subpopulation of 22Rv1 cells that are spontaneously resistant to ARKILs. The resistance of these subpopulations is significantly greater than that of 22Rv1 cells. The AKRVs are as resistant as the control non-sensitive DU145 and

Mel-7 cells. Thus, neither of these ARKILs could induce apoptosis in the AKRVs (Figure

3-18).

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Table 3-2. ARKIL resistant variants selection

Concentration for Isolated Clones Number ARKIL Selection 1st round selection 2nd round selection ARKIL-1 25 μM 7 5 ARKIL-3 0.1 μM 7 5 ARKIL-7 5 μM 6 5 ARKIL-8 2 μM 6 5

Table 3-3. SNP genotyping analysis of PCa cells

Genotype

Cell line

rs556997 rs556997 rs477841 rs12855486 rs544823 rs682767 rs17622124 rs592885 rs693442 rs1413251 rs17485827 rs9513877

rs7335296

22Rv1 T G C C C C G CA G C C A

CWR22R T G C C C C G CA G C C A

AK3R4 T G C C C C G CA G C C A

Genotype

Cell line

s9302001

rs17678261 rs601605 rs17583059 rs682666 r rs17466684 rs6313 rs3816995 rs6136667 rs34004464

rs8922

22Rv1 GT A A T T CT G T G G DEL

CWR22R GT A A T T CT G T G G DEL

AK3R4 GT A A T T CT G T G G DEL

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Figure 3-18. PARP cleavage induced by ARKILs A panel of RVs was treated with either ARKIL-3 or ARKIL-8 for 48 hours and then PARP1 cleavage was detected by western blotting with an anti-PARP antibody. Cells were treated with ARKIL-3 (5 µM) or ARKIL-8 (3 µM) for 48 hours. Lysates were analyzed by western blotting with anti-PARP antiserum. Housekeeping protein β-actin was used as an internal control. 22Rv1 cells were used as an ARKIL sensitive control; Mel-7 cells were used as an ARKIL positive control.

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Figure 3-19. Cytotoxic assay of resistant variants of ARKILs RVs’ cells were plated in 96 wells plates and incubated overnight in 37 °C. A series concentrations of ARKILs were applied to the cells in triplicates for each cell line. Cells were fixed and stained by MBM after 72 hours of treatment. The survival ratio was calculated by comparing treated wells with control untreated wells. Parental 22Rv1 cells were used as a negative sensitive control, DU145 and Mel-7 cells were used as resistant controls.

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3.6.2. Are Resistant Variants Cross-Resistant to ALL ARKILs?

The impressive resistance of AKRVs demonstrated in the cytotoxic assays (Figure 3-19) indicates that the AKRVs are resistant to the ARKIL that was used for selection. One way to investigate whether the different ARKILs share the same or similar targets is to test the cross-resistance profile of the panel of AKRVs to the 4 ARKILs. If there is no such cross-resistance for resistant variants to the individual ARKILs, then the targets of the different ARKILs are likely to be distinct (Figure 3-20, Option 1). If the cross- resistance was observed, it is likely that all the ARKILs share a common mechanism of action (e.g. then affect the same signalling pathway, perhaps by targeting the same component) (Figure 3-20, Option 2). Three resistant variants for each ARKIL were randomly chosen for this analysis and treated with each of the ARKILs in a dose- dependent cytotoxic assay (Figure 3-21 ~ Figure 3-24). Although the level of resistance varied in different AKRVs for different ARKILs, the trends showed a somewhat global resistance (>2 fold compared to 22Rv1 cells) in all ARKIL treatments. For ARKIL-8 treated AR1RVs and AR7RVs, several of the AKRVs were sensitive to ARKIL-8 as survival was dose-dependent response curve. The other ARKILs did not show the same cross-resistance. This indicates that AKRVs may have acquired similar, but not necessarily identical, mechanisms of resistant to ARKILs and that ARKILs may share similar but not necessarily identical targets (i.e. affect the same signalling pathway, such as that involving AR).

As we learned from the development of CRPCa, it is possible that different therapies promote PCa cells to develop different resistance mechanisms against castration.

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Whatever methods (mutated, amplified, or directly activated AR, and so on) the cells use, some of the mechanisms (such as hypersensitive, promiscuous, and outlaw pathway) require active AR to achieve androgen independence. Likewise, the resistance of AR to

ARKILs may be due to one key genetic modification. This modification may be in AR or in a gene involved in the AR signalling pathway. However, before this hypothesis could be explored, it is important to determine whether the ARKILs resistance might be related to classical resistance mechanisms, such as those involving multidrug transporters (e.g. P- glycoprotein and multidrug-resistance associated protein 1 (MRP1)), which cause resistance by pumping agents out of cells thereby keeping intracellular drug concentrations too low to be cytotoxic (Hipfner et al., 1999). This mechanism is a very common cause of anticancer agents losing activity in the clinic (Borst et al., 2000;

Burkhart et al., 2009; Gudkov, 1987; Thomas and Coley, 2003).

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Figure 3-20. Potential mechanism for cross-resistance of RVs Details were described in text.

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Figure 3-21. ARKIL-1 cytotoxic assay of resistant variants for cross-resistance RVs’ cells were plated in 96 wells plates and incubated overnight at 37 °C. A series concentrations of ARKIL-1 were applied to the cells in triplicates. Cells were fixed and stained by MBM after 72 hours of treatment. The plates were washed with distilled water and dried. The MBM in each well was extracted from fixed cells in 3% HCl and OD was measured at 595 nm in a PerkinElmer Vicotr3 plate reader. The survival ratio was calculated by comparing treated wells with control untreated wells. Parental 22Rv1 cells were used as a sensitive control.

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Figure 3-22. ARKIL-3 cytotoxic assay of resistant variants for cross-resistance RVs’ cells were plated in 96 wells plates and incubated overnight at 37 °C. A series concentrations of ARKIL-3 were applied to the cells in triplicates. Cells were fixed and stained by MBM after 72 hours of treatment. The plates were washed with distilled water and dried. The MBM in each well was extracted from fixed cells in 3% HCl and OD was measured at 595 nm in a PerkinElmer Vicotr3 plate reader. The survival ratio was calculated by comparing treated wells with control untreated wells. Parental 22Rv1 cells were used as a sensitive control.

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Figure 3-23. ARKIL-7 cytotoxic assay of resistant variants for cross-resistance RVs’ cells were plated in 96 wells plates and incubated overnight at 37 °C. A series concentrations of ARKIL-7 were applied to the cells in triplicates. Cells were fixed and stained by MBM after 72 hours of treatment. The plates were washed with distilled water and dried. The MBM in each well was extracted from fixed cells in 3% HCl and OD was measured at 595 nm in a PerkinElmer Vicotr3 plate reader. The survival ratio was calculated by comparing treated wells with control untreated wells. Parental 22Rv1 cells were used as a sensitive control.

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Figure 3-24. ARKIL-8 cytotoxic assay of resistant variants for cross-resistance RVs’ cells were plated in 96 wells plates and incubated overnight at 37 °C. A series of concentrations of ARKIL-8 were applied to the cells in triplicates. Cells were fixed and stained by MBM after 72 hours of treatment. The plates were washed with distilled water and dried. The MBM in each well was extracted from fixed cells in 3% HCl and OD was measured at 595 nm in a PerkinElmer Vicotr3 plate reader. The survival ratio was calculated by comparing treated wells with control untreated wells. Parental 22Rv1 cells were used as a sensitive control.

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3.6.3. Non-involvement of Multidrug Resistance Transporters

Multidrug resistance (MDR) is the principle mechanism of cancer resistance to a wide variety of chemotherapy drugs (Persidis, 1999). One of the major mechanisms of MDR is overexpression of MDR transporters, which are ATP-dependent efflux pumps that extrude lipophilic drugs (especially anti-neoplastic agents) from cancer cells (Chernova et al., 1987; Gottesman et al., 2002; Kondratov et al., 2001). Thus, the cross-resistance of the ARKILs in the AKRVs may be explained by the selection of multidrug resistant variants that overexpress one of the multidrug transporters (Figure 3-25). Therefore, the resistance of the AKRVs to doxorubicin (DOX), which is a common substrate for the major classes of MDR transporters (such as, p-glycoprotein (P-gp) and multidrug resistant proteins (MRPs)), was evaluated. The known MDR transporter inhibitors, reserpine and verapamil were included as control. DOX is a commonly used drug in cancer chemotherapy that intercalates into DNA. Bona fide MDR cells (MCF7/VP cells that overexpress MRP1 (Diah et al., 2001; Vickers et al., 1988)) were used as a positive control in these studies. With 10 µM reserpine or verapamil, DOX killed 42% or 27% of

MCF7/VP cells (Figure 3-26). Survival ratios of prostate cells in DOX treatment were similar with or without reserpine or verapamil (data not shown). The MDR inhibitors could not sensitized the AKRVs to ARKILs indicating that the ARKIL resistance in

AKRVs was not due to MDR (Figure 3-26). The AKRVs did not show resistance to other common anticancer agents (vincristine, cisplatin, etc.) either (data not shown).

Another possible reason for resistance is that the AKRVs may specifically develop mutated MDR transporters to accommodate ARKILs. This mutation could be specific for

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ARKILs and not cause resistance to other anticancer agents. If such a mutation occurred, then the combination of reserpine or verapamil with ARKILs might make AKRVs again sensitive against ARKILs. However, cytotoxicity assays for ARKILs in the presence of

MDR reversal agents failed to overcome the ARKIL resistance (Figure 3-26). Therefore, it is unlikely that this mechanism of resistance is active in the AKRVs. ARKILs are likely to be directed against common targets.

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Figure 3-25. Multidrug resistance hypothesis for AKRVs Details were described in text.

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Figure 3-26. Multidrug resistant assay of ARKILs’ resistant variants 22Rv1, RVs, and MCF7/VP cells were plated in 96 wells plates in triplicates and incubated overnight at 37 °C. Cells were treated with doxorubicin (0.3 mg/ml) and reserpine (0.01 mM) or verapamil (0.01 mM) as indicated. Cells were fixed and stained by MBM after 48 hours of treatment. The plates were washed with distilled water and dried. The MBM in each well was extracted from fixed cells with 3% HCl and OD measured at 595 nm in a PerkinElmer Vicotr3 plate reader. The survival ratio was calculated by comparing treated wells with control untreated wells. MCF7/VP cells were used as MDR positive control.

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3.6.4. Characterization of ARKIL Resistance in AKRVs.

Susceptibility of AR transcriptional activity to ARKILs in AKRVs

Did the AKRVs carry on the AR sensitivity of 22Rv1 to ARKILs? To answer this question, AR transcriptional activity was measured using the pARE-Luc luciferase reporter transfected into the AKRVs. We used previously decided conditions which were used for 22Rv1 cells. In ARKILs dose-dependent assay, the AKRVs selected with AR luciferase reporter kept constant activity with ARKILs treatment (Figure 3-27). ARKILs could not inhibit AR activity of the AKRVs in time-dependent assay, not like that of

22Rv1 in previous experiments (Figure 3-28). In R1881 dose-dependent assay with

ARKILs treatment, AR transcriptional activity of the AKRVs was induced by R1881 15 times (AK1R7) to 80 times (AK3R4) compared to only ~5 times in untreated 22Rv1 cells

(Figure 3-29). The reduction in luciferase activity in 22Rv1 but not AKRVs indicates that

ARKILs can only suppress AR transcriptional activity in 22Rv1 cells. Moreover, the AR activity in response to R1881 was strongly increased in the AKRVs, which was also confirmed by R1881 dose- and time-dependent assays (Figure 3-28, Figure 3-29).

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Figure 3-27. AR transcriptional activity following ARKILs dose-dependent assay Cells transfected with pARE-Luc plasmid and selected with geneticin for stable ARE luciferase reporter expressing cells. After 48 hour incubation with RPMI-CSS medium, cells were plated in 96 wells plates with 10 fold serial dilutions of ARKILs in RPMI-CSS medium for 18 hours. The luciferase activity was measured and normalized to MBM fixed and stained parallel plates. The ARKILs showed strong inhibition on AR transcriptional activity of 22Rv1.

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Figure 3-28. AR transcriptional activity following androgen time-dependent assay Cells with ARE luciferase reporter were plated in 96 wells plates as described previously. The cells were incubated with 10 nM R1881 together with ARKILs for up to 32 hours treatment. The AR transcriptional activity was measured and calculated based on luciferase assay as described above. The 22Rv1 panel is was same as Figure 3-8B.

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Figure 3-29. AR transcriptional activity following androgen dose-dependent assay Cells with ARE luciferase reporter were plated in 96 wells plates as described previously. The cells were incubated with 10 fold serial dilutions of R1881 together with ARKILs for 18 hours. The AR transcriptional activity was measured and calculated based on luciferase assay as described above. The AR transcriptional activity of 22Rv1 was suppressed by ARKILs about 5 times lower than untreated cells. The 22Rv1 panel is same as Figure 3-8A.

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Effect of ARKILs on AR protein abundance in AKRVs

Studies presented earlier demonstrated that ARKILs cause decreased AR expression and loss of AR protein in 22Rv1 cells. However ARKILs showed little influence on AR activity in AKRVs in previous experiments. Therefore, the effect of ARKILs on AR levels in AKRVs was questionable and should be evaluated as part of the mechanistic studies of ARKILs. In this experiment, lysates of the AKRVs were collected after

ARKIL-3 treatment and then analyzed in western blotting assay. As shown in Figure

3-30A, AR in the tested AKRVs displayed different extents of stability to ARKIL-3 treatment. The ARs of AK3R4 were almost intact even with 15 µM ARKIL-3, the upper band of ARs (with one duplicated exon3) in AK3R1 was barely influenced by ARKIL-3 whereas the bottom band of AR (AR∆LBD) was still sensitive. The stability of AR to

ARKIL-3 was also true for other AKRVs in different extents. The RV isolated from

ARKIL-1 treatment, AK1R2, showed wild type level of AR on a concentration of

ARKIL-3 as high as 5 µM. The RV isolated from ARKIL-7 treatment, AK7R7, also showed a mild resistance to ARKIL-3. This AR resistance to ARKIL-3 is common in all

AKRVs (data not shown). The cross-resistance of the AKRVs also indicates reduced AR sensitivity in AKRVs may be common in all AKRVs to other ARKILs. Two AK3RVs

(AK3R1 and AK3R4) were treated with the other three ARKILs (Figure 3-30). The abundance of the full length allele AR of AK3R4 was not affected by the compounds, and the AR∆LBD allele of AK3R1 showed less resistance to ARKILs than the full length allele (Figure 3-30). Such downregulation of the short AR allele was common in all

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AKRVs (data not shown). Why there was such difference is still unknown and investigation of the reason is out of this study.

Taken together, these data implied that suppression of AR abundance by ARKIL-3 or

ARKIL-8 (other ARKILs results were not shown here) in RVs was attenuated. This indicates that the sensitivity of 22Rv1 cells to ARKILs cloud result from downregulation of AR protein levels. However, similar downregulation of AR protein levels was not observed in other PCa cells (LNCaP and C4-2) that were sensitive to ARKILs to some degree (e.g. ARKIL-8), indicating that the effects on AR itself are not the only mechanism by which ARKILs can kill 22Rv1.

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Figure 3-30. AR expression was not inhibited by ARKILs in AKRVs 22Rv1 and AK3RVs cells were treated by ARKILs for 48 hours. Lysates were collected and analyzed by western blotting with anti AR antiserum.

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Does AR contribute to ARKIL resistance of the AKRVs?

If ARKILs target abundance of AR, the AKRVs may overcome the toxicity of ARKILs with increased AR abundance. Hence, reducing AR levels in AKRVs by siRNA followed by assessing sensitivity to ARKILs may reveal whether AR contributes to ARKIL resistance of the AKRVs. In order to address this more thoroughly, AR knockdown experiments were performed in AKRVs. If downregulation of AR levels by siRNA in the

AKRVs leads to sensitization of the AKRVs to ARKILs, it would mean that the resistance of the AKRVs is strongly related to the AR abundance, in particular the restoration of AR levels in these cells. This would also suggest that loss of AR is a key component of ARKIL cytotoxicity in 22Rv1 cells. For these experiments, siRNAs specific to AR (smart pool siAR, Dharmacon) or control siRNAs (siCntl, Dharmacon) were transiently transfected into 22Rv1, Hela and AKRVs (two from each compound selection) cells. The efficiency of transfection was monitored using siGreen

(Dharmacon). After 48 hours, 1% of the transfected cells were plated in 60 mm dishes and incubated overnight. The remaining of cells were collected and analyzed by western blotting. The transfected AKRVs were treated with ARKILs for two weeks without passage. Suppression of AR by siAR was confirmed in western blotting assay (Figure

3-31A). The majority of AR expression was suppressed by siAR in both 22Rv1 and

AKRVs. Dr. Gurova’s group showed that the knockdown of AR in 22Rv1 arrested

22Rv1 cell growth (Tararova et al., 2007). To confirm this phenomenon, transfected

22Rv1 and Hela cells were left without any treatment. Hela cells were used as a negative control for the potential cell arrest by siAR. Suppression of growth of 22Rv1 cells was confirmed in this experiment (Figure 3-31B). Surprisingly, there was no such suppression

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of growth in AKRVs despite the dramatic decrease in AR levels (Figure 3-31C).

Therefore, growth arrest in AKRVs is not a direct consequence of compound regulation of AR. These data further suggest that the downregulation of AR may not be the mediator of ARKIL cytotoxicity but a consequence of the actual mechanism of action of these molecules. However, the mechanism still appears to be related to the AR signaling pathway.

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Figure 3-31. Knockdown AR in AKRVs by siAR A. 22Rv1 and AKRVs were transfected with siAR, or siCONTROL. After 72 hours, cells were collected and analyzed by western blotting. The AR was inhibited by siAR in all cells. B. 300 22Rv1 cells with siAR or siCntl were plated in 60 mm dishes. After a two week incubation, cells were fixed and stained by MBM. The siAR showed strong inhibition on cell growth of 22Rv1. C. 1% of the indicated transfected cells were plated in 60 mm dishes 48 hours after transfection. On the second day, AKRV cells were treated with different dilutions of ARKILs for two weeks. Knockdown of AR did not sensitize AKRVs to ARKILs.

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3.7. Summary

From the anti-PCa compounds screening, no compounds that were selectively toxic for all prostate cancer-derived cells were identified. Five classes of “hit” compounds (named ARKIL compounds) demonstrated selective toxicity for AR-expressing prostate cancer-derived cells. In particular, all ARKILs demonstrated extremely strong selective toxicity to 22Rv1 cells, which led to cell cycle arrest and apoptosis. AR mediated transcription was clearly inhibited by ARKILs.

However, ARKILs did not interfere with AR translocation into the nucleus. ARKILs suppressed

AR expression of 22Rv1 cells but not that of LNCaP or C4-2 cells. ARKILs have no effect on the stability of AR protein or AR mRNA.

Cell variants resistant to ARKILs were isolated. The degree of resistance of the isolated variants to ARKILs was comparable to that of non-prostate origin cells. Variants selected to each of the four ARKILs were cross-resistant to the others. This cross-resistance does not appear to be mediated by ATP-dependent MDR transporters (P-gp/MRPs). ARKILs cannot suppress AR transcriptional activity of AKRVs. ARKILs cannot fully suppress expression of AR in AKRVs.

ARKILs likely target one common mechanism that is important to survival of 22Rv1 cells. siRNA against AR did not sensitize AKRVs to ARKILs. Taken together, these data indicates that

AR itself is not directly involved in the resistance to ARKILs. However, signalling through the

AR pathway may be affected by ARKILs. AKRVs would be useful tools for unbiased mechanistic studies.

Chapter 4. Investigating Potential Target of ARKILs

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4.1 Gene Profiling Analysis on AKRVs and Parental 22Rv1 cells

4.1.1 Hypothesis and Background

In the previous chapter, AKRVs selected by long term treatment with ARKILs showed consistent and cross resistance to ARKILs. Thus, AKRVs could be great tools for exploring potential targets (or toxic mechanism). We hypothesized that alteration of a key factor gene X was a possible resistance mechanism in AKRVs (Figure 4-1). In this hypothesis, X is the primary factor driving resistance through the regulation of a secondary factor including gene A, B, C, Y, and also AR. There are two possibilities for alteration of gene X. One possibility is that upregulated X rescues AKRVs from the toxicity of ARKILs. The other possibility is that downregulated X relieves suppression of secondary factor genes. Among these genes, increased expression of the secondary factor gene Y is involved in AKRVs resistance to ARKILs. Hence, comparing differentially expressed genes (DEG) between AKRVs and parent sensitive 22Rv1 cells may reveal gene X as well as gene Y.

In order to identify DEGs, gene expression profiling of AK3RVs (AK3R1 AK3R2, and

AK3R4) and 22Rv1 cells were conducted via microarray total mRNA analysis.

Affymetrix largest gene chip U133 plus 2.0 (Affymetrix #900466), which can detect over

47,000 transcripts, was used as the microarray hybridization platform combined with computational analysis. By comparing gene expression profiles of the AK3RVs with that of the 22Rv1 cells, a series of DEGs commonly up- or down-regulated in these resistant variants compared to parental cells were identified (Figure 4-2, Figure 4-3). From this analysis, the common DEGs in all three AK3RVs included 28 increased (Table 4-1) and

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88 decreased transcripts (Table 4-3). To explore whether gene X was among these

DEGs, validation and functional confirmation of some DEGs were conducted.

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Figure 4-1. Hypothesized model of resistance mechanism in AKRVs This model hypothesized that there was a driving force, key factor gene X contributing to resistance to ARKILs in AKRVs. Upregulation or downregulation of gene X increases expression secondary genes including gene Y which is involved in resistance of AKRVs against ARKILs treatment.

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4.1.2 Annotated DEGs from Microarray Analysis

The raw data of each total mRNA sample was normalized and analyzed by a statistician (Table

4-1, Table 4-2). The expression of DEGs was plotted by fold change relative to that of control samples from 22Rv1 cells (Figure 4-2, Figure 4-3). The upregulated DEGs that were more than two fold increased (p<0.05) were selected and plotted (Figure 4-2). The upregulated DEG profiles of all AK3RVs tested showed a similar trend, which may indicate that these AK3RVs may share a common resistant mechanism. In addition, the downregulated DEGs with more than a two fold decrease (p<0.05) were selected and plotted (Figure 4-3). Unlike for the upregulated

DEGs, the downregulated DEG profiles from the AK3RVs didn’t show any consistent trends in all three AK3RVs. Therefore, it was less likely key factor X was one of the downregulated genes.

Thus, we focused on the upregulated DEGs common to all AK3RVs to determine whether there were involved in ARKIL resistance and, therefore, potential druggable targets. The upregulated genes were divided into different groups based on their annotated results, such as c-Maf, FN1

(fibronectin 1), PDM/LIZ, and so on (Table 4-2).

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Figure 4-2. Upregulated DEGs in AK3RVs The raw data obtained from microarray assay was normalized and analyzed. The upregulated DEGs with more than two folds change (p<0.05) relative to those of control DEGs of 22Rv1 cells were selected and plotted. The upregulated DEG profiles of AK3RVs showed similar trend, which may indicate that these AK3RVs share similar resistant mechanism.

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Table 4-1. Upregulated DEGs in AK3RVs Change (Fold) Genbank ID Genbank Description AK3R1 AK3R2 AK3R4 homo sapiens short form transcription factor c-Maf (c- AF055376 50.33 63.22 105.48 Maf ) mRNA, complete cds. X02761 16.37 32.92 8.31 humanmRNAfor fibronectin (fn precursor). homo sapiens fibronectin 1, mRNA (cdna clone BC005858 15.47 34.96 8.73 image:3506187), partial cds. homo sapiens cdna: flj23084 fis, clone lng06602, highly AK026737 15.22 32.69 9.20 similar to hsfib1 human mRNA for fibronectin (fn precursor). AF231124 14.10 25.84 13.88 homo sapiens testican-1 mRNA, complete cds. homo sapiens clone flc0562 pro2841 mRNA, complete AF130095 13.70 32.70 8.58 cds. homo sapiens transforming growth factor, beta 1 BC000125 12.81 18.20 14.91 (camurati-engelmann disease), mRNA (cdna clone mgc:3119 image:3351664), complete cds. AJ276395 7.63 27.48 4.52 homo sapiens mRNAfor msf-fn70 (fn gene). 7g91e06.x1 nci_cgap_co16 homo sapiens cDNA clone BF001670 6.51 4.01 3.05 image:3313858 3', mrna sequence. au151483 nt2rp2 homo sapiens cDNA clone AU151483 5.29 26.55 9.68 nt2rp2005327 3', mrna sequence. homo sapiens procollagen c-endopeptidase enhancer 2 NM_013363 4.90 5.38 13.51 (pcolce2), mRNA. wo96b08.x1 nci_cgap_kid11 homo sapiens cDNA clone AI928342 4.81 7.75 9.44 image:2463159 3', mrna sequence. NM_025080 4.60 9.20 9.73 homo sapiens asparaginase like 1 (asrgl1), mRNA. homo sapiens androgen-regulated serine protease tmprss2 AF270487 4.15 2.92 8.70 precursor (tmprss2) mRNA, complete cds. 7o46a11.x1 nci_cgap_kid11 homo sapiens cdna clone BG054550 3.97 16.18 3.81 image:3576885 3' similar to tr:o60705 o60705 lim protein. ; mRNA sequence. AK027217 3.62 13.82 3.85 homo sapiens cDNA: flj23564 fis, clone lng10773. homo sapiens cadherin 6, type 2, k-cadherin (fetal BC000019 3.15 20.79 6.09 kidney), mRNA (cdna clone mgc:1470 image:3506873), complete cds. 602017491f1 nci_cgap_brn64 homo sapiens cDNA clone BF344237 2.94 18.40 12.36 image:4152983 5', mRNAsequence. td14g10.x1 nci_cgap_co16 homo sapiens cDNA clone AI832249 2.93 8.83 11.89 image:2075682 3', mRNA sequence. homo sapiens monoamine oxidase a (maoa), nuclear gene NM_000240 2.74 3.75 2.51 encoding mitochondrial protein, mRNA. homo sapiens annexin a6 (anxa6), transcript variant 1, NM_001155 2.73 4.15 4.37 mRNA. homo sapiens lim protein (similar to rat protein kinase c- NM_006457 2.63 7.87 2.74 binding enigma) (lim), mRNA. homo sapiens mrna; cDNA dkfzp761p06121 (from clone AL390127 2.61 6.07 3.27 dkfzp761p06121). homo sapiens fatty acid binding protein 5 (psoriasis- NM_001444 2.47 2.84 3.31 associated) (fabp5), mRNA. yh15e02.s1soares infant brain 1nib homo sapiens cdna R61374 2.39 5.14 3.95 clone image:37665 3', mRNAsequence. homo sapiens monoamine oxidase a (maoa), nuclear gene NM_000240 2.38 3.69 2.43 encoding mitochondrial protein, mRNA. ol46a12.s1 soares_nfl_t_gbc_s1 homo sapiens cDNA AA923354 2.26 2.75 2.23 clone image:1526494 3', mRNAsequence.

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Table 4-2. Annotated upregulated DEGs in AK3RVs Genbank ID Gene Genbank ID Gene AF05T376 c-Maf AK026737 BC000125 BC005858 TGFβ1 AF231124 AF130095 FN1 BF344237 X02761 AU151483 Cadherin 6 AJ276395 BC000019 AF270487 ARSP AI832249 NM_001155 Anxa 6 NM_025080 R61374 HEY1 APG like 1 AI928342 NM_001444 LDLP AK027217 AL390127 BG054550 NM_000240 MAOA PDZ/LIM NM_006457 AA923354 AV715767 NM_013363 PCOLCE

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Figure 4-3. Downregulated DEGs in AK3RVs The raw data obtained from microarray assay was normalized and analyzed. The downregulated DEGs with more than a 2 fold decrease (p<0.05) relative to those of control DEGs of 22Rv1 cells were selected and plotted. The downregulated DEG profiles of AK3RVs didn’t showed consistent trend in all AK3RVs as showed in upregulated DEGs profiles. Hence, it would be less chance to find the key factor X in downregulated DEGs.

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Table 4-3. Downregulated DEGs in AK3RVs

Change (Folds) Genbank Genbank Description AK3R1 AK3R2 AK3R4 homo sapiens sema domain, immunoglobulin domain (ig), transmembrane domain (tm) and short NM_022367 -116.50 -88.00 -3.75 cytoplasmic domain, (semaphorin) 4a (sema4a), mRNA. nt99g05.s1 nci_cgap_alv1 homo sapiens cDNA AA640422 -77.25 -8.75 -20.50 clone image:1206680, mRNA sequence. homo sapiens mRNA; cDNA dkfzp586f1018 (from AL050090 -65.25 -5.00 -16.75 clone dkfzp586f1018). av691491gkc homo sapiens cDNA clone gkceeb10 AV691491 -32.50 -422.00 -2.00 5', mRNAsequence. homo sapiens glycoprotein hormones, alpha NM_000735 -25.50 -23.25 -17.75 polypeptide (cga), mRNA. av709406adc homo sapiens cdna clone adcahc11 5', AV709406 -24.50 -11.00 -2.67 mRNA sequence. AF052148 -19.25 -12.50 -8.25 homo sapiens clone 24507 mRNA sequence. hc97f08.x1 soares_nfl_t_gbc_s1 homo sapiens AW340486 -18.75 -2.25 -5.00 cDNA clone image:2907975 3', mRNA sequence. NM_001159 -16.50 -3.50 -2.50 homo sapiens aldehyde oxidase 1 (aox1), mRNA. yn84a12.s1soares adult brain n2b5hb55y homo H39185 -11.25 -8.50 -22.00 sapiens cDNA clone image:175102 3', mRNAsequence. homo sapiens histamine n-methyltransferase, BC005907 -10.75 -3.75 -3.50 transcript variant 2, mRNA (cDNA clone image:4249496), complete cds. homo sapiens chromosome 8 open reading frame 4 NM_020130 -9.25 -5.00 -41.75 (c8orf4), mRNA. homo sapiens cub domain-containing protein 1 NM_022842 -9.00 -5.25 -10.50 (cdcp1), transcript variant 1, mRNA. D16931 -8.50 -2.00 -12.25 human hepg2 3' region cDNA, clone hmd4b02. wi12a04.x1 nci_cgap_co16 homo sapiens cDNA AI738919 -8.50 -2.50 -6.75 clone image:2389998 3' similar to tr:o70264 o70264 ligand of numb-protein x ;, mRNA sequence. tq42g08.x1 nci_cgap_ut1 homo sapiens cDNA clone image:2211518 3' similar to tr:q63015 q63015 AI559190 -8.25 -3.25 -2.00 common salivary protein 1 precursor mRNA sequence. NM_017577 -7.50 -2.00 -13.25 AF116645 -7.00 -2.00 -9.00 homo sapiens pro1708 mRNA, complete cds. homo sapiens histamine n-methyltransferase (hnmt), NM_006895 -6.50 -6.00 -5.00 mRNA. homo sapiens glutaminyl-peptide cyclotransferase NM_012413 -6.33 -5.25 -2.67 (glutaminylcyclase) (qpct), mRNA. homo sapiens syndecan 4 (amphiglycan, ryudocan) NM_002999 -6.00 -8.50 -4.75 (sdc4), mRNA. wo31e07.x1 nci_cgap_gas4 homo sapiens cDNA AI925518 -5.75 -4.00 -29.75 clone image:2456964 3' similar to contains alu repetitive element;, mRNA sequence. homo sapiens mRNA; cDNA dkfzp434g0719 (from AL137725 -5.00 -9.75 -5.50 clone dkfzp434g0719); partial cds.

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Change (Folds) Genbank Genbank Description AK3R1 AK3R2 AK3R4 tx43a12.x1 nci_cgap_lu24 homo sapiens cDNA AI680986 -5.00 -8.25 -11.50 clone image:2272318 3', mRNA sequence. xn80a06.x1 soares_nfl_t_gbc_s1 homo sapiens AW263497 -5.00 -15.75 -8.75 cDNA clone image:2700754 3', mRNA sequence. homo sapiens cDNA flj12893 fis, clone AK022955 -4.75 -2.75 -14.75 nt2rp2004165. yj81a11.r1soares breast 2nbhbst homo sapiens R70320 -4.75 -6.00 -12.50 cDNA clone image:155132 5', mRNA sequence. BC037943 -4.50 -2.75 -22.75 homo sapiens cDNA clone image:5285657. homo sapiens mRNA; cDNA dkfzp564o1278 (from AL137517 -4.50 -6.00 -12.25 clone dkfzp564o1278). homo sapiens farnesoid-x-receptor beta splice AF478446 -4.25 -5.50 -3.00 variant 2 (nr1h4) mRNA, complete cds; alternatively spliced. homo sapiens bone marrow stromal cell antigen 2 NM_004335 -4.25 -9.75 -16.75 (bst2), mRNA. av691323gkc homo sapiens cDNA clone gkcewf11 AV691323 -4.25 -5.25 -25.00 5', mRNA sequence. homo sapiens mRNA for kiaa1568 protein, partial AB046788 -4.25 -2.75 -21.00 cds. au157303 place1 homo sapiens cDNA clone AU157303 -4.25 -9.25 -6.75 place1007150 3', mRNA sequence. homo sapiens tight junction protein 2 NM_004817 -4.00 -2.00 -4.25 (zonaoccludens 2) (tjp2), transcript variant 1, mRNA. homo sapiens bac clone gs1-99h8 from 12, AC004010 -4.00 -2.25 -2.00 complete sequence. homo sapiens mRNA; cDNA dkfzp434g0719 (from AL137725 -4.00 -9.25 -3.75 clone dkfzp434g0719); partial cds. qx65b04.x1 nci_cgap_gc4 homo sapiens cDNA AI365263 -3.75 -27.75 -2.33 clone image:2006191 3', mRNA sequence. human DNA sequence from clone rp4-761i2 on chromosome 6 contains a novel gene, the 3' end of AL136139 -3.50 -4.25 -3.25 the nedd9 gene for neural precursor cell expressed (developmentally down-regulated) 9 and three cpg islands, complete sequence. homo sapiens sry (sex determining region y)-box 9 NM_000346 -3.50 -7.00 -3.00 (campomelic dysplasia, autosomal sex-reversal) (sox9), mRNA. homo sapiens immunoglobulin superfamily, NM_153184 -3.25 -5.00 -2.75 member 4d (igsf4d), mRNA. homo sapiens protein tyrosine phosphatase, receptor NM_002844 -3.25 -2.50 -7.25 type, k (ptprk), mRNA. NM_031308 -3.25 -3.25 -2.67 homo sapiens epiplakin 1 (eppk1), mRNA. homo sapiens mitogen-activated protein kinase 13, BC000433 -3.25 -2.25 -2.50 mRNA (cDNA clone mgc:8364 image:2819932), complete cds. homo sapiens solute carrier family 2 (facilitated NM_030777 -3.25 -53.25 -2.75 glucose transporter), member 10 (slc2a10), mRNA. homo sapiens udpglycosyltransferase 2 family, NM_021139 -3.00 -119.75 -8.75 polypeptide b4 (ugt2b4), mRNA.

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Change (Folds) Genbank Genbank Description AK3R1 AK3R2 AK3R4 601483690f1 nih_mgc_69 homo sapiens cDNA BE620457 -3.00 -84.25 -3.75 clone image:3886055 5', mRNAsequence. L12468 -2.50 -3.00 -2.50 homo sapiens aminopeptidase a mrna, complete cds. av724323htb homo sapiens cDNA clone htbaye03 AV724323 -2.50 -2.00 -9.00 5', mRNA sequence. homo sapiens simple mRNA for small integral AB034747 -2.33 -14.50 -4.25 membrane protein of lysosome/late endosome, complete cds. X03363 -2.33 -3.00 -2.00 human c-erb-b-2 mRNA. homo sapiens platelet derived growth factor c NM_016205 -2.33 -3.25 -95.75 (pdgfc), mRNA. xf56c09.x1 nci_cgap_gas4 homo sapiens cDNA AW130600 -2.33 -4.25 -13.50 clone image:2622064 3', mRNA sequence. homo sapiens epithelial v-like antigen 1 (eva1) AF275945 -2.25 -2.00 -3.00 mRNA, complete cds. homo sapiens hyaluronan binding protein 2 (habp2), NM_004132 -2.25 -9.75 -8.25 mRNA. homo sapiens pou domain, class 4, transcription NM_004575 -2.25 -6.00 -31.00 factor 2 (pou4f2), mRNA. NM_017855 -2.25 -3.25 -30.50 homo sapiens apin protein (apin), mRNA. homo sapiens fzd8 mRNA for seven-transmembrane AB043703 -2.25 -2.75 -9.75 receptor frizzled-8, complete cds. xu08c06.x1 nci_cgap_co14 homo sapiens cDNA AW471145 -2.25 -3.50 -47.75 clone image:2799562 3' similar to contains alu repetitive element;, mRNA sequence. homo sapiens chromosome 9 open reading frame 66 NM_152569 -2.00 -4.50 -2.33 (c9orf66), mRNA. BC035922 -2.00 -2.25 -9.25 homo sapiens, clone image:5398658, mRNA. homo sapiens, clone image:3626122, mRNA, partial BC014056 -2.00 -7.25 -4.00 cds. 602520843f1 nih_mgc_20 homo sapiens cDNA BG475827 -2.00 -2.00 -15.75 clone image:4639114 5', mRNA sequence. homo sapiens brain abundant, membrane attached NM_006317 -2.00 -4.50 -19.75 signal protein 1 (basp1), mRNA. te30c10.x1 soares_nfl_t_gbc_s1 homo sapiens cDNA clone image:2087442 3' similar to AI382146 -2.00 -6.25 -2.25 sw:sox9_human p48436 sox-9 protein. ;containsalu repetitive element;, mRNA sequence. zd96a11.s1 soares_fetal_heart_nbhh19w homo W93728 -2.00 -4.00 -19.00 sapiens cdna clone image:357308 3', mRNA sequence. homo sapiens acid phosphatase, prostate (acpp), NM_001099 -2.00 -2.00 -3.00 mRNA. homo sapiens complement component 5 (c5), NM_001735 -2.00 -2.00 -4.00 mRNA. NM_013314 -2.00 -12.25 -11.50 homo sapiens b-cell linker (blnk), mRNA. homo sapiens connective tissue growth factor M92934 -2.00 -2.75 -78.25 mRNA, complete cds. no40b03.s1 nci_cgap_pr23 homo sapiens cDNA AA594937 -2.00 -4.50 -2.00 clone image:1103117 3', mRNA sequence.

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Change (Folds) Genbank Genbank Description AK3R1 AK3R2 AK3R4 homo sapiens cdna flj20263 fis, clone colf7804, AK000270 -2.00 -3.50 -2.00 highly similar to aj131693 homo sapiens mRNA for akap450 protein. homo sapiens hypothetical protein flj23375 NM_024956 -2.00 -2.50 -2.50 (flj23375), mRNA. yz36g02.s1morton fetal cochlea homo sapiens N71923 -2.00 -20.50 -24.50 cDNA clone image:285170 3', mRNA sequence. homo sapiens hypothetical protein mgc10981, BC004397 -2.00 -8.00 -10.00 mRNA (cdna clone mgc:10981 image:3636109), complete cds. homo sapiens mRNA for kiaa1700 protein, partial AB051487 -2.00 -2.25 -3.75 cds. wi55h03.x1 nci_cgap_co16 homo sapiens cDNA AI763378 -2.00 -2.00 -2.50 clone image:2394197 3', mRNA sequence. au119437 hemba1 homo sapiens cDNA clone AU119437 -2.00 -4.00 -14.75 hemba1005808 5', mRNA sequence. tj54g06.x1 soares_nsf_f8_9w_ot_pa_p_s1 homo sapiens cDNA clone image:2145370 3' similar to AI459194 -2.00 -2.00 -2.50 gb:m62829 early growth response protein 1 (human); mRNA sequence. hc95f03.x1 soares_nfl_t_gbc_s1 homo sapiens AW340311 -2.00 -4.00 -9.50 cDNA clone image:2907773 3', mRNA sequence. oy90d11.x1 soares_fetal_liver_spleen_1nfls_s1 homo sapiens cDNA clone image:1673109 3' AI051248 -2.00 -11.00 -5.00 similar to gb:m61877 spectrin alpha chain (human);, mRNA sequence. yz60e11.s1morton fetal cochlea homo sapiens N69091 -2.00 -4.50 -204.75 cDNA clone image:287468 3', mRNA sequence. au146924 hembb1 homo sapiens cDNA clone AU146924 -2.00 -2.50 -2.25 hembb1001899 3', mRNA sequence. rc4-ht0276-100300-015-e11 ht0276 homo sapiens BE150929 -2.00 -3.00 -2.00 cDNA, mRNA sequence. aa17e01.s1 soares_nhhmpu_s1 homo sapiens cDNA AA456099 -2.00 -3.25 -9.50 clone image:813528 3', mRNA sequence. nj59c10.s1 nci_cgap_pr9 homo sapiens cDNA AA532718 -2.00 -4.00 -2.00 clone image:996786, mRNA sequence. 602504814f1 nih_mgc_77 homo sapiens cDNA BG484193 -2.00 -2.00 -6.00 clone image:4618490 5', mRNA sequence.

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4.1.3 Validation of c-Maf Involvement in ARKIL-3 toxicity

Introduction of c-Maf

Firstly, we were interested in the gene AF055376 from the upregulated DEGs list (Table

4-1), because it showed the highest upregulated expression of all common upregulated transcripts from the AK3RVs. AF055376 is the short form of homo sapiens transcription factor c-Maf mRNA, which is the cellular homolog of the viral proto-oncogene maf

(Motohashi et al., 1997). C-Maf belongs to a large macrophage-activating factor (MAF) subfamily of the bZIP transcription factor family. Members of this family have an N- terminal transactivation domain and a C-terminal DNA binding domain, which binds to the DNA maf recognition element (MARE) as a homo- or heterodimer (Ho et al., 1996;

Valanciute et al., 2004) (Figure 4-4). The human c-Maf gene is located on chromosome

16q22-q23 (Chesi et al., 1998). Short form c-Maf is an intronless genomic sequence of

4248 bp encoding a 373aa protein(50 kDa) compared to the alternatively spliced long form c-Maf, which has an extra short exon inserted at the position 1925 in the coding sequence of short form c-Maf (Chesi et al., 1998; Omoteyama et al., 2006). C-Maf has been found to play a crucial role in cell differentiation (Valanciute et al., 2004), lens formation (Perveen et al., 2007; Yoshida et al., 2001), myeloma cells (Chang et al., 2007;

Kienast and Berdel, 2004), and T cells (Chen et al., 2005; Ho et al., 1998; Tanaka et al.,

2005; Voice et al., 2004).Short form c-Maf may be involved in glaucoma pathogenesis

(Shepard et al., 2005). To identify whether upregulation ofshort form c-Maf is the key factor X or just one of the secondary factor(s) involved in the resistance to ARKILs, a series of experiments have been performed

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Validation of c-Maf expression

To validate upregulated expression of c-Maf in AK3RVs, reverse transcription (RT) -

PCR and northern blotting were used to check the relative expression level of c-Maf in

22Rv1 and AK3RV cells. Primers located in the 3’UTR of short form c-Maf (sense sequence: 5'-TGCACTTCGACGACCGCTTCTC-3', in AF055376 position 1571–1592; antisense sequence: 5'-GGTGGCTAGCTGGAATCGCG-3', in AF055376 position 1957–

1938) were chosen. The Semiquantitative RT-PCR was performed with Invitrogen

SuperScript RTII kit as described in Chapter 2. The expression of c-Maf was normalized by the expression of GAPDH. RT-PCR results showed high expression of c-Maf in all

AK3RVs compared to the parental cell line 22Rv1 (Figure 4-4A).

To confirm the RT-PCR results, northern blot was performed using total RNA from the same cell cultures whose expression of c-Maf was detected by the RT-PCR assay.

Northern blot was conducted with Megaprimer labeling kit from GE healthcare. All total

RNAs of 22Rv1 andAK3RVswere hybridized by probe, a fragment of c-Maf (AF055376) from 2625 bp to 3162bp. The result of northern blot confirmed overexpression of c-Maf in AK3RVs (Figure 4-4B).

In addition, we analyzed potential c-Maf amplification by southern blot. Amplification of c-Maf in AK3RVs was not detected (Figure 4-4C). Moreover, AK3R4 showed a recombination. Since AKRVs showed cross-resistance to all ARKILs, we hypothesized that upregulated c-Maf could be found in all AKRVs if c-Maf was the key factor.

However, upregulated c-Maf in other AKRVs was not found in RT-PCR assay as describe previously (data not shown). This result indicated that c-Maf may not be the

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common key factor for all ARKILs toxicity. Instead, validated upregulation of c-Maf indicated that c-Maf was the potential key factor in ARKIL-3 toxicity. Thus, functional confirmation of c-Maf was conducted.

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B C Figure 4-4. Validation of c-Maf expression in AK3RVs Total RNAs of 22Rv1 and AK3RVs (1-AK3RVs from one selection and 2-AK3RVs from another independent selection) were prepared. Expression of c-Maf was examined in RP-PCR and northern blot as described in text. Upregulated expression of c-Maf in AK3RVs was confirmed.

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Functional confirmation of c-Maf

To test whether c-Maf is the key factor X for AK3RVs resistance to ARKIL-3, both overexpression and knockdown of c-Maf were used in functional studies.

Overexpression of c-Maf. If c-Maf is the key factor X, overexpression of short form of the c-Maf gene, c-Maf in 22Rv1 cells would be expect to make the sensitive 22Rv1 cells resistance to ARKIL-3. Firstly, the full length cDNA of c-Maf (4.2kb) were cloned into retrovirus expressing vector pBabe, which has a puromycin selection marker. Parental

22Rv1 cells were infected with virus of empty vector, pBabe or c-Maf expressing construct, pBabe-c-Maf. Stable expressing c-Maf clones (22Rv1/pBabe-c-Maf) were selected with puromycin treatment. Overexpression of c-Maf in 22Rv1/pBabe-c-Maf cells was confirmed by western blotting (Figure 4-5 Left). The cytotoxicity assays showed a slight increase in resistance in 22Rv1/pBabe-c-Maf cells compared to vector only cells, such increase may indicate partially contribution of c-Maf to the resistance to

ARKIL-3 (Figure 4-5 Right).

Knockdown of c-Maf. Conversely, knockdown of c-Maf in AK3RVs would be expected to sensitize AK3RVs to ARKIL-3, if c-Maf is the key factor X. The knockdown of c-

Maf was conducted with siRNA smart pool of c-Maf (siMaf) from Dharmacon Inc.. The control siRNAs were siCntl smart pool as used in the experiment of knockdown of AR described previously. siMaf didn’t show a significant increase in the sensitivity of

AK3RVs to ARKIL-3 (Figure 4-6 Right), although they could inhibit expression of c-

Maf partially (Figure 4-6 Left).

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In summary, these results indicate that short form c-Maf may be, at least partially, responsible for ARKIL-3 resistance, and therefore, represents a potential ARKIL-3 target. Alternatively, the short form of c-Maf may be one of the secondary factors that are regulated by the key factor X.

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Figure 4-5. Cytotoxicity assay for c-Maf overexpressed 22Rv1 cells 22Rv1 cells were infected with virus of short form c-Maf expressing construct, pBabe-c-Maf or the control construct, pBabe. Stable expressing clones were selected with puromycin treatment. Left. Overexpression of c-Maf was confirmed by western blot of cell lysates with anti-AR antiserum. Samples of 22Rv1 and AK3R4 cells were used as control. Right. 22Rv1/pBabe-c-Maf cells were plated in 96 wells plates for cytotoxicity assays with ARKIL-3 as indicated concentration in triplicate. The cells were fixed and stained after 72 hours. 22Rv1/pBabe cells were used as control. Overexpression of c-Maf in 22Rv1 cells did not significantly increase resistance of 22Rv1 against ARKIL-3.

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Figure 4-6. Cytotoxicity assay for siMaf knockdown AK3R4 cells Left. 22Rv1 and AK3R4s were transiently transfected with siMaf, or siCntl. After 72 hours, cells were collected and analyzed by western blot. The expression of c-Maf was partially inhibited by siMaf in AK3R4 cells. Right. 48 hours after transfection, AK3R4 cells transfected with siMaf or siCntl were plated in 96 wells plates for cytotoxicity assay as indicated concentration in triplicate. The cells were fixed and stained after 72 hours. 22Rv1/ and AK3R4 cells were used as control. Knockdown of c-Maf did not sensitize AK3R4 cells to ARKILs.

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Promoter regulation analysis

Gene expression is closely controlled by transcription. A lot of compound targets in tumor cells are usually transcription factors, which transcriptionally activate downstream genes. The promoter region of a gene is important in its transcriptional regulation.

Analysis of the promoter regulation of known genes would be very useful for a genetic regulation study. If c-Maf is not the key factor X response to ARKIL-3, c-Maf may work as a response factor of this key factor as shown in the hypothesis model presented in

Figure 4-1. Since c-Maf is upregulated in AK3RVs, promoter regulation analysis on c-

Maf may reveal the key factor from transcription factors which can regulate and activate c-Maf.

To investigate activation of c-Maf transcription, Dual-Luciferase Reporter (DLR

Promega Co.) assay system was used. Three fragments upstream of c-Maf, s1 (578bp, from -478 to +101), s2 (1177bp, from -1077 to +101), and s3 (1930bp, from -1829bp to

+101bp) were chosen (Figure 4-7A). The fragments were amplified from genomic DNA of 22Rv1 and AK3RV cells, and cloned into firefly luciferase reporter vector pGL3.

These constructs included pGL3-22s1,pGL3-22s2, pGL3-22s3 which have fragments amplified from 22Rv1 cell genomic DNA, and pGL3-R4s1,pGL3-R4s2, pGL3-R4s3 which have fragments amplified from AK3R4 cell genomic DNA. The constructs were transformed into DH5α cells. Clones containing the inserted fragment in plasmid pGL3 were picked up for each construct and sequenced. The constructs containing s1 fragments contained the correct sequence between 22Rv1 and AK3R4, except that one pGL3-s1 construct which the s1 fragment was cloned from AK3R4 genomic DNA contained a

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point mutant (A→G, -339). Hence, two constructs pGL3-R4s1f4 (same as s1 fragment in

22Rv1, named s1) and pGL3-R4s1f3 (mutant s1, named s1m) was chosen for promoter regulation analysis. The sequences of s2 or s3 of AK3R4 were not the same as those of

22Rv1. Hence, three s2 constructs, pGL3-22s2a3 (named 22s2), pGL3-R4s2f2 (named

R4s21), pGL3-R4s2f4 (named R4s22), and three s3 constructs, pGL3-22s3f2 (named

22s3), pGL3-R4s3f2 (named R4s31), pGL3-R4s3f4 (named R4s32) were used for promoter regulation analysis.

These selected constructs were transfected into 22Rv1 and AK3RVs together with internal control construct renilla luciferase reporter pRL-RT. There would be two possibilities: 1) the key factor X, also a transcriptional activator of c-Maf, was upregulated in AK3R4; or 2) the mutation in c-Maf promoter of AK3R4 increased the affinity of the c-Maf promoter for the key factor X. If the first hypothesis was true, the activation of c-Maf promoter luciferase reporters would be increased in AK3RV cells. If the secondary hypothesis was true, activated c-Maf promoter luciferase reporters would be among pGL3-R4 constructs depending on location of binding sites of the key factor X.

However, in the DLR assay, these constructs didn’t show increased luciferase reporter following normalization with control renilla luciferase reporter (Fold = the value of pGL3 construct / the value of Renilla pRL-RT control) in either 22Rv1 or AK3RVs (Figure

4-7B). This result indicated that c-Maf may not the related gene on AK3RVs resistance.

Moreover, fast validation of other DEG candidates (TGFβ1, febnectin1, Cadherin6 etc.) in RT-PCR did not show significant difference between 22Rv1 cells and AK3RVs (data

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not shown). Further verification was needed for target discovery for resistance mechanism of AKRVs to ARKILs toxicity.

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Figure 4-7. Promoter regulation analysis on the promoter of c-Maf A.Schematic structure of the fragments of c-Maf promoters used for analysis of luciferase activity is as described in the text. Fragment s1 was from -487 to +101 in c-Maf (AF055376). Fragment s2 was from -1077 to +101 in c-Maf. Fragment s3 was from -1829 to +101. These fragments were cloned from genomic DNAs of 22Rv1 or AK3RV cells, and inserted into luciferase reporter empty vector pGL3 basic. B. c-Maf promoter-luciferase pGL3 constructs were described in text.22Rv1 or AK3RVs cells were co-transfected with the indicated c-Maf promoter-luciferase constructs together with control construct, Renilla luciferase reporter pRL-RT. The luciferase activity, expressed relative to the activity of pRL-RT was calculated. The result of promoter regulation analysis showed no significant difference between 22Rv1 and AK3RV cells in c-Maf promoter regulation.

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4.2 DEGs Validation by shRNA Library High Throughput Screening

Compared to the method used for validation of upregulated DEGs (e.g. ARSP, PDZ/LIM,

FABP5, MAOA), shRNA library screening provided a relatively faster and more efficient method for target discovery. The hypothesis was that the key factor X of ARKIL-3 toxicity could be suppressed by shRNA of X; systematic analysis shRNA-mediated gene knockdown via identifying constructs that restore ARKIL-3 sensitivity in AK3RVs in the cytotoxicity assay would reveal the target of ARKILs. With the annotated result from microarray, the screening can start with shRNA constructs targeting upregulated DEGs instead of using all shRNA constructs from the library. If this approach failed, full library shRNA constructs screening can be conducted. The candidate shRNA constructs were picked up from the Openbiosystems expression arrest human cancer shRNAmir retroviral library. Each shRNA construct is already cloned into retroviral vector pSM2 with puromycin selection marker. 35 candidate constructs, which targeted 11 upregulated

DEGs identified in the microarray annotated results were obtained from shRNA core facility in Roswell Park Cancer Institute (Table 4-4).

AK3R1 cells were infected by virus containing the shRNA constructs. Stable expressing shRNA clones were selected with puromycin treatment. At the same time, 22Rv1 cells were used as control by being infected by same virus and selected with puromycin treatment. The sensitivity of these clones was evaluation by cytotoxicity assay with

ARKIL-3. IC50 of each clone was calculated and compared (Figure 4-8A). The result suggested involvement of ARSP, PDZ/LIM, FABP5, MAOA in resistant phenotype

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AK3R1 (Figure 4-8B). Evaluation of these promising candidates is currently being pursued.

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Table 4-4. shRNA constructs for AKIL targets validation

No. ID Target DEG No. ID Target DEG 1a V2HS_37132 18 V2HS_94515 MAF 1b V2HS_37130 19 V2HS_94516 Anxa 6 2 V2HS_64727 20 V2HS_94518 3 V2HS_64731 21 V2HS_19582 PCOLCE 4 V2HS_64732 22 V2HS_19584 HEY1 5 V2HS_64728 23 V2HS_19587 6 V2HS_136880 24 V2HS_198814 APG like 1 7 V2HS_136881 25 V2HS_199057 PDZ/LIM 8 V2HS_62160 26 V2HS_197008 9 V2HS_62161 27 V2HS_6074 Cadherin 6 10 V2HS_62234 28 V2HS_131713 11 V2HS_62197 29 V2HS_131714 LDLP 12 V2HS_113935 30 V2HS_131715 FN1 13 V2HS_113940 31 V2MM_176607 14 V2HS_56183 32 V2HS_76627 15 V2HS_56184 33 V2HS_76628 MAOA ARSP 16 V2HS_56185 34 V2HS_256708 17 V2HS_56187

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Figure 4-8. Knockdown candidate DEGs by shRNAs shRNAs targeting to candidate upregulated DEGs discovered in microarray assay were collected from a shRNAmir retroviral library. 22Rv1 cells were infected with retrovirus of each shRNA, and selected for stable expressing clones. The constructs, pLPCX 1st and pLPCX 2nd were used as inflectional controls. In the experiments, 22Rv1/shRNA or AK3R1/shRNA cells were plated in 96 wells plates for cytotoxicity assays with ARKIL-3 in triplicate. Uninfected cells or cells infected with retrovirus of pLPCX (pLPCX 1st and pLPCX 2nd) were used as control. The cells were fixed and stained after 72 hours. The survival ratio was calculated by comparing cell numbers in treated wells with control untreated samples. The IC50 of each shRNA was calculated by Originlab8.1. The potential candidate shRNA constructs were listed and will be validated in future.

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4.3 Summary

Microarray analysis showed profiles of commonly upregulated DEGs in all three

AK3RVs. No such trend was found for downregulated DEGs. The identification of upregulated DEGs shared by all three AK3RVs strongly indicated that they may share a similar resistance mechanism and these shared genes were potential druggable targets.

Hence, we hypothesized that these AK3RVs obtained resistance by overexpression some genes in all AK3RVs clones which would be drugable targets. Functional analysis of c-

Maf showed partially involvement in AK3RVs’ resistance against ARKIL-3. ShRNA library screening was employed in validation of upregulated DEGs. Primary screening with clones infected shRNA constructs revealed several promising candidate shRNA constructs of ARSP, PDZ/LIM, LDLP, and MAOA that are the focus of future studies.

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Chapter 5. In vivo Evaluation of Therapeutic Potential

5.1. Pilot Toxicity Assessment of ARKILS

To determine the potential of ARKILs as an anti-PCa therapy, the biological activity of

ARKILs must be evaluated in vivo. Before efficacy can be evaluated, however, a safe dose of the selected panel of ARKILs (ARKIL-1, ARKIL-3, ARKIL-7, and ARKIL-8) had to be established. Testing of compound safety in mice was done according to an

IACUC-approved protocol (Cleveland Clinic Foundation, CCF). As a starting point, 100 mg/kg of each selected ARKIL (in 25% DMSO) was administered to NIH Swiss mice

(n=1 male and 1 female) by a single intraperitoneal (i.p.) injection. No abnormalities were observed in any of the compound-injected mice upon weight monitoring, visual inspection during a three-week post-injection period or and upon gross pathology examination at the completion of the study (Figure 5-1).

Independently, a maximum tolerated dose (MTD) of ARKIL-8 was evaluated by Dr.

Gurova’s group (Narizhneva et al., 2009). Based on those experiments, 18 mg/kg/day (3 daily injections) of ARKIL-8 (equivalent 200 x IC50 of in vitro cytotoxicity assay) was delivered by intravenous (i.v.) injection without any apparent side effects.

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Figure 5-1. Effect of ARKILS on mouse weight 6 week old NIH Swiss mice (n=1 male and 1 female) were injected i.p. with 100 mg/kg of ARKILs. Mouse weight was measured daily for 3 weeks. No weight loss or any other abnormalities were observed for the duration of the experiment.

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When injected i.p., neither ARKIL-3 nor ARKIL-8 showed an antitumor effect to 22Rv1 xenograft tumor model as strong as the cytotoxicity of ARKILs to 22Rv1 cells observed in vitro (ARKIL-3, Figure 5-3; ARKIL-8, refer to the result of Dr. Gurova’s group in the

Introduction). One possibility is that the low metabolic stability of these molecules makes i.p. treatment of mice inefficient. Metabolic stability as assessed with rat liver microsomes resulted in only 9.8% ARKIL-3 (data not shown) and 17% of ARKIL-8 remaining after an one hour incubation (Narizhneva et al., 2009).

In attempt to circumvent the rapid degradation of the ARKILs by liver metabolism, i.v. injection was evaluated. This is the fastest way to deliver fluids and medications throughout the body and, at the same time, avoid liver metabolism (Ahmad et al., 1984;

Rowland, 1972). However, i.v. injection requires higher solubility in aqueous solutions than that required for i.p. injection and ARKIL-3 is poorly soluble. To overcome the solubility issue, a liposome-based drug delivery system was tried. the system has been shown to enhance the solubility and efficacy of anticancer agents (Batist et al., 2001).

Liposomes can encapsulate hydrophilic molecules into aqueous solution inside the liposomal aqueous core and at the same time, hydrophobic chemicals can be dissolved into the lipid membrane. The lipid bilayer can then fuse with the cell membrane to deliver the liposome contents. Hence, a liposome-compound complex can increase solubility of the compound and shorten delivery time via i.v. injection. The safety of liposome-

ARKILs (ARKIL-3 and ARKIL-8) complexes was evaluated via a MTD test. Two mice for each complex (in PBS) were injected with four independent i.v. injections with doses of 8 mg/kg, 20 mg/kg, 20 mg/kg (repeat once), and 60 mg/kg. To evaluate the toxicity of the liposome-compound complex (lipo-ARKIL-3 and lipo-ARKIL-8), mice were

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monitored by visual inspection over 3 weeks or by gross pathology examination following euthanasia at the end of the three weeks. The MTD testing demonstrated that both Lipo-ARKIL-3 and Lipo-ARKIL-8 could be delivered at a dose of 60 mg/kg by i.v. injection without any adverse effects on the weight of the animals (Figure 5-2).

Therefore, the liposome-ARKILs drug delivery system will be used in future in vivo efficacy studies.

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Figure 5-2. Cytotoxic Assay of Cell Lines 6 week old nude mice (n=2 male) were injected i.v. with a dosed 8 mg/kg, 20 mg/kg, 20 mg/kg, and 60 mg/kg of Lipo-ARKIL-3 or Lipo-ARKIL-8. Mouse weight was measured in following 3 weeks. No weight loss or any other abnormalities were observed for the duration of the experiment.

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5.2. Evaluation of in vivo Efficacy of ARKIL-3

To evaluate the potential value of the identified compounds, we conducted in vivo experiments in immune incompetent nude mice. Due to cost and time constraints, only

ARKIL-3 was tested for in vivo efficacy.

In the initial study, xenograft efficacy evaluation following i.p. injection was conducted according to NCI recommendation for primary compounds evaluation (Teicher and

Andrews, 2004). 22Rv1 cells were suspended at 4 x 107 cells/ml in PBS. Cells (4 x 106 cells/site) were injected subcutaneously (s.c.) into the flank of Harland nude mice (four sites each mouse: two uppers and two bottoms) according to an IACUC-approved protocol (Cleveland Clinic Foundation). After 2 weeks, tumors had an average volume of

~10 - 20 mm3. Tumor diameters were measured with a digital caliper, and the tumor volume in mm3 was calculated by the formula: Volume = (width)2 x length/2. Five tumor-bearing mice were obtained. Three of the mice were treated with ARKIL-3 to estimate efficacy and toxicity. The mice were injected i.p. for five consecutive days with a dose of 52mg/kg of ARKIL-3 (in 50% DMSO). Two of the mice were used as controls with injection of 50% DMSO only. During ARKIL-3 treatment, the weights of treated mice showed a slight loss (data not shown). Two of the treated mice died at day 3 and day 8 (could be from injection mistakes), indicating that while 52 mg/kg was safe for iv injection, it was too high for ip injection. Compared to control group tumors, tumors in treated mice showed less growth (Figure 5-3). The difference between the treated group and the control group was not statistically significant. However, the trend in antitumor activity in this study indicated that more efficient in vivo evaluation methods (better

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solubility, alternative modes of administration) in future work might yield promising antitumor activity.

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Figure 5-3. Xenografts with ARKIL-3 treatment via i.p. administration 22Rv1 cells were suspended at 4 x 107 cells/ml in PBS. Cells (4 x 106 cells/site) were injected subcutaneously (s.c.) into the flank of Harland nude mice (four sites each mouse: two uppers and two bottoms) according to an IACUC-approved protocol (Cleveland Clinic Foundation). when tumors had an average volume of ~10 - 20 mm3, all tumor-bearing mice were divided two groups. The treatment group consisted of three mice and the control group consisted of two mice. The tumors were measured before injection every day. Tumor diameters were measured with a digital caliper, and the tumor volume in mm3 was calculated by the formula: Volume = (width)2 x length/2.

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5.3. Summary

ARKIL-3 is generally non-toxic in DMSO solution or liposome formulation. ARKIL-3 showed modest, but not statistically significant, inhibition of 22Rv1 xenograft tumors but may yield promising efficacy following future optimization. Therefore, ARKILs, as represented by ARKIL-3 and ARKIL-8 (Narizhneva et al., 2009), have potential for development into therapeutic agents against PCa.

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Chapter 6. Conclusions and Discussion

6.1. Conclusions

To identify potential anti-CRPCa agents, a large-scale high throughput screen of a small molecule library was conducted. However, no compound that was selectively toxic to all

PCa-derived cells were identified suggesting the lack of a universal, highly druggable prostate specific target. A series of small molecules, ARKILs, with selective toxicity for

AR-expressing PCa-derived cells were isolated. This result suggests a role of the AR signaling pathway as a target for some anti-prostate cancer therapies. The cytotoxicity of

ARKILs was associated with a strong induction of apoptosis in 22Rv1 CRPCa cells. All four characterized classes of isolated compounds (ARKIL-1, ARKIL-3, ARKIL-7 and

ARKIL-8) caused downregulation of AR protein activity and abundance. ARKILs do not affect AR mRNA or protein so the downregulation of AR protein levels presumably occurs due to suppression some unknown factors related to AR signaling pathway.

Cell variants selected for resistance to one ARKIL (AKRVs) were cross-resistant to all

ARKILs to varying degrees, suggesting that a common resistance mechanism was shared by all the ARKILs. This mechanism is essential for the viability of AR-expressing PCa- derived cells and does not involve ATP dependent P-gp or MRP1 multidrug transporters.

The latter conclusion is based on the use of inhibitors of these transporters that did not change the sensitivity of the AKRVs to the ARKILs. In AKRVs, the AR expression level and activity was not changed in the presence of ARKILs indicating that ARKILs affect a 169

highly druggable cellular mechanism related to AR. The data indicate that AR itself is not directly involved in the resistance to ARKILs, however, signalling through the AR pathway may be affected by ARKILs. This conclusion is further supported by the fact that siRNAs to AR could not restore ARKIL sensitivity in the AKRVs. Successful isolation of AKRVs provided a useful tools for unbiased mechanistic studies. Comparing the difference of gene profiling between 22Rv1 and AKRVs via microarray analysis didn’t discover the unknown factors of ARKILs toxicity. Some of shRNAs from the shRNA library showed promising to sensitize AKRVs to ARKILs. Further investigation is needed for exploring the unknown factors. Moreover, ARKILs possess anti-tumor activity in vivo in mouse tumor model of CRPCa indicating the anti-cancer potential of this class of compounds.

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6.2. Discussion

In past decades, the productivity of target-based drug discovery has steadily declined

(Sams-Dodd, 2005). Most small molecules that were identified from target-based screening have failed due to poor pharmacological activity (FDA, 2004). General disadvantages of target-based screening are the restrictions it places on the target. Direct inhibition of a target is usually not feasible in a cellular system. Moreover, the targets available for screening are often key factors shared by all cells’ development and proliferation, which means the unique targeting would bring some unpredicted side effects. Hence, we adopted an alternative approach, namely tissue targeting. Prostate is an epithelial, gender-specific organ that is not essential for overall viability of the organism

(the same as breast and skin). It is a complex tissue consisting of various components built around highly specialized epithelia adapted for specific secretion. The degree of specialization of this epithelium makes it significantly different from other types of epithelia, thus creating a possibility of identifying pharmacological agents capable of its selective elimination. The possibility of finding such compounds is supported by the fact that these cell types are dependent on the presence of certain gender-specific steroid hormones (estrogens for breast and androgens for prostate). In fact, hormone ablation therapy, which is broadly used for the treatment of advanced prostate cancer, causes general involution of normal prostate tissue. In this approach, a cell-based assay is employed in which the effect of a compound is measured using a simple phenotypic endpoint, such as cell death. Unlike target-based screening, cell-based screening is not

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target specific, thus it has the advantage of unbiased testing of a large number of small- molecule compounds that could potentially target PCa cells even without knowing the specific target at the beginning of the process. In addition, this approach has the potential to discover key targets that are essential for PCa cell viability that are not presently known. Because it is cell-based, cell populations provide a time saving advantage and also an early measure of compound toxicity. The work presented in this thesis demonstrates the technical feasibility of this approach (Figure 6-1), which includes cell phenotype-based screening followed by validation and identification of the mechanism of action and the target. To develop a readout system for screening chemicals that are selectively toxic for prostate cells in vitro, we assessed the growth properties and suitability for high throughput screening of a series of prostate cancer-derived cell lines

LNCaP, PC3, DU145, C4-2 and 22Rv1. The 22Rv1 cells were chosen as an ultimate screening system.

For a large scale screening, the screening standard for candidate compounds is very important. In the primary screening, we chose the difference between the inhibition of

22Rv1 cells and Mel-7 cells >30% to ensure all possible candidates were selected in the absence of a significant effect on cells of non-prostate origin. Since this experiment was finished in relative short time (48 hours), it is possible that some of chemicals were neglected if they were not “fast” killing compounds. Under those circumstances, an alternative readout system, such as the creation of cell system enabling the monitoring of the activity of AR in androgen-independent PCa lines in a relative long term (>10 days) need to be developed. In the secondary screening, a more detailed assessment of the prostate-specificity of primary hits was performed using a broader panel of prostate and 172

non-prostate derived cell lines to ensure that true anti-prostate tissue (anti-PCa) candidates were isolated. After the initial secondary screening, we realized that comparison of chemicals at a single dose may not be sufficient to judge the potency of the compounds. This is because a single dose is just a snapshot of activity and a slightly higher or lower dose could provide dramatically different results for both the sensitivity of PCa cell lines as well as for the non-prostate cell lines used for assessing actual prostate specificity. Hence, desired toxicity could be achieved via dose escalation in the future, provided that the compounds exhibit sufficient specificity.

It is not surprising that the ARKILs did not kill all types of PCa cell lines. Although an ideal compound would be inhibitory to all PCa cell lines, the chances of obtaining such a hit are relatively low. In fact, considering the natural variety among and within the tumors, this may not be feasible at all. One reason may be due to the fact that the PCa cell lines used in these studies are metastatic cells isolated from metastatic sites and maintained in culture for a very long time. Because of this, they may have partially lost some of the key characteristics that originally defined their prostate status, thus making them closer to non-prostate cells compared to prostate cells and therefore insensitive to

ARKILs. Alternatively, the toxicity of ARKILs may only be specific towards a special type PCa cells as represented by 22Rv1 cells. These results indicate that the ARKILs may represent an effective therapy for a particular subtype of this disease. We expect that the cell lines on our prostate cancer panel are representative of at least some of the types of clinically relevant tumors and their respective inhibitors may represent an effective, albeit not universal, therapy for the disease. In fact, a compound specifically toxic to a subset of

PCa, rather than to all PCa derived cells, might have a reduced toxicity against the 173

normal prostate as well, which is an important quality of life issue for the PCa patients.

Moreover, the isolated chemicals have dual value: (i) as prototype drugs and (ii) as tools for mechanism and target discovery. As an unbiased method, generation and analysis of resistant variants isolated from long-term incubation with ARKILs is proof in this work that this may be an effective approach for target and mechanism identification.

Isolation of AKAKRVs from a one step selection experiment may indicate that there were resistant cells preexisting within the cultured cells. It seems that there would not be too many hidden targets for anti-tissue therapy since all newly isolated molecules happened to target a previously established target, AR or at the very least the signaling pathway(s) involved in AR function. At the same time, this further strengthens importance of AR as a drug target, AR has remained the major target for PCa treatment for 70 years (Huggins and Hodges, 1941). The majority of drug discovery for PCa has been focused on blocking the interaction between AR and androgen. Although ~5% of the genes expressed in PCa cells are regulated by androgens (Dehm and Tindall, 2006), the initial success of anti-androgen as the main hormone therapy does not result in a permanent cure for PCa. On the contrary, the cancer cells always find a way around the therapy over the long term. CRPCa cells enlist several pathways (the hypersensitive pathway, the promiscuous pathway, the outlaw pathway, and the bypass pathway) to relax AR ligand specificity (Figure 1-5) (Feldman and Feldman, 2001). To sum up, the

AR signaling pathway is vital as a potential therapeutic target.

The physical amounts of AR protein was downregulated in treated 22Rv1 cells by all

ARKILs, whereas this was not been in AKRVs (Figure 3-10 and Figure 3-30). These data

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indicate the potential involvement of the AR pathway in the targeted activity of the isolated compounds. At the same time, there was not a clear correlation between the biological effects of siRNA inhibiting AR and the isolated compounds, suggesting that their mechanism of activity does not involve direct targeting of AR. More than 200 coregulators of AR have been identified to date, including, ARA70, PPARγ (Heemers and Tindall, 2007; Rahman et al., 2004). These coregulators or interactions between AR and these co-regulators would be potential targets of ARKILs. At the same time, unknown components, such as miRNAs, are also possible candidates for further research.

These known coregulators and unknown factors would not only function in hormone dependent PCa, but rather in all types of PCa. However, it is clear from our results that

AR must be present in the PCa cancer cell in some form (wild type or mutant) in order for ARKILs to exert their effects, suggesting that the target(s) is most likely an interaction between a co-regulator and AR rather than direct inhibition of the co-regulator that is involved in AR function. Hence, ARKILs as new class of prototype drugs for indirect targeting of AR would be equally effective for hormone dependent and hormone- independent PCa (didn’t follow. David. ****How should I adjust it? Jack).

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Figure 6-1. The approach of anti-PCa screening in the project Details were described in text.

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The history of CRPCa development indicates that prostate tumor cells survive in an un- friendly environment (at least to them) via any kind of alteration that can counteract stress. The AKRVs from this project also showed such characteristic changes. However, there is always the involvement of some key signaling pathways, which are potential pharmaceutical targets for new drug development. We did not expect to find a small molecule or method that provide a 100% cured PCa, but rather molecules that can stop the progression of CRPCa and improve the quality of a patient’s life. This work indicates that ARKILs target a similar mechanism but not necessarily the same exact factor. It is very important to identify the ARKIL target(s) as this would facilitate rational drug design and accelerate drug development. In depth analysis of resistant variants (global gene expression profiling, miRNA expression profiling and functional genomics-based validation) should lead to the identification of a target/mechanism.

The history of CRPCa development indicates that prostate tumor cells survive in an un- friendly environment (at least to them) via any kind of alteration that can counteract stress. The AKRVs from this project also showed such characteristic changes. However, there is always the involvement of some key signaling pathways, which are potential pharmaceutical targets for new drug development. We did not expect to find a small molecule or method that provide a 100% cure of PCa, but rather molecules that can stop the progression of CRPCa and improve the quality of a patient’s life. This work indicates that ARKILs target a similar mechanism but not necessarily the same exact factor. It is very important to identify the ARKIL target(s) as this would facilitate rational drug design and accelerated drug development. In depth analysis of gene expression profiling of resistant variants via microarray assay had the potential to lead to the identification of 177

a target/mechanism. In the annotated results, the profiles of AK3RVs only exhibited accordingly trend in upregulated DGEs relative to profiles of 22Rv1 cells but not in downregulated DEGs. This phenomenon was corresponding with the hypothesized model that alteration of a key factor gene X was a possible resistance mechanism in

AKRVs (Figure 4-1).However, functional studies on c-Maf together with inconsistent results of primary validation of other candidate DEGs indicated that it was not simple mechanism behind resistance of AKRVs against ARKILs. These upregulated DEGs besides c-Maf may play the similar role as AR which is not a direct responsor to

ARKILs. To validate other candidate DEGs in an efficient way, shRNA retroviral constructs from a shRNA library were used to knockdown the candidate DEGs in

AKRVs by retroviral infection. The primary result of knockdown of the DEGs showed several promising candidates including ARSP, PDZ/LIM, LDLP, and MAOA which may be involved in the resistance of AK3RVs to ARKILs. In the continued work, sensitization by these shRNA constructs will be validated. If the validation failed, large scale shRNA library screening will be employed to find potential shRNA which could sensitize

AKRVs to ARKILs. Moreover, miRNA expression profiling and functional genomics- based validation will also be used for target/mechanism searching. The results from microarray assays of miRNA have generated some promising candidates for further exploration.

Moreover, ARKILs exhibit the promising ability to target AR or its pathway without depending on blocking the AR-ligand interaction. The isolation of AKRVs by long-term incubation with ARKILs suggests that tumors can do the same in future clinical

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application. Nevertheless, the potential disadvantage may be overcome by combinations with existing and emerging therapies.

The ARKILs were toxic to CRPCa cells in vitro but had attenuated or even unnoticeable effects on in vivo tumor growth in the mouse models that were examined. However, this most likely reflects the poor pharmacological properties of the compounds (e.g. poor solubility, microsomal instability). Thus, optimization of delivery and dosing schedules based on pharmacokinetic/pharmacodynamic evaluation should allow for a better means for assessing efficacy in vivo. In addition, the ARKILs tested thus far represent primary hits. In the typical drug development process, further rounds of screening of focused libraries of small molecules selected based on structural similarity to the primary compound and subsequent synthetic chemistry around the selected molecules often yield more potent molecules with improved pharmacological properties. Thus, based on degree of efficacy observed under suboptimal conditions, we anticipate that hit-to-lead optimization will yield improved molecules with potential for development into drugs for the treatment of PCa.

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6.3. Working Model

We have shown that ARKILs, small molecules with anti-PCa activity, inhibits the AR activity which is a key factor in human PCa. But who is the direct target of ARKILs is still unknown. Given the results from this work, the unknown factor (x in Figure 6-2) should be strongly related to AR singling pathway. We propose that most probably

ARKILs inhibit the unknown factor X, or disturb interaction between AR and X (Figure

6-2). This results inhibition of AR transcriptional activity of 22Rv1 cells response to

DHT induction. This is the earliest event we observe after ARKILs treatment. Deceased activity of AR leads to initiation of apoptotic steps. The consequence of this event is reduction of AR abundance as well as transcription of AR mRNA. Impaired AR expression in turn additional accelerates the apoptosis.

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Figure 6-2. Current model and proposed mechanism of ARKILs anti-PCa activity ARKILs effects are shown in red. Detailed explanations can be found in the text.

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