University of Southern California Dissertations and Theses

Co-chaperone influence on androgen receptor signaling and identification of androgen receptor genes in prostate cancer

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Co-chaperone influence on androgen receptor signaling and identification of androgen receptor genes in prostate cancer

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CO-CHAPERONE INFLUENCE ON ANDROGEN RECEPTOR SIGNALING
AND IDENTIFICATION OF ANDROGEN RECEPTOR GENES IN
PROSTATE CANCER

by

Jennifer Prescott

A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(MOLECULAR EPIDEMIOLOGY)

May 2007

Copyright 2007 Jennifer Prescott

ii
DEDICATION

To my husband, Eric Prescott
For bringing out the best in me

iii
ACKNOWLEDGMENTS

Where do I begin! I’ve had the pleasure of working with so many wonderful
people over the last 5+ years. Probably the person I need to thank the most is my PI,
Gerry Coetzee, who involved me in such interesting collaborative projects, as well as
opportunities to present at meetings both here and abroad. I appreciate the autonomy
you have given me while remaining accessible when guidance was needed.
The COETZEE LAB, at least as it was in the days of Marcus Wantroba.
Rather than the technical help I received from Marcus and Howie Shen, what I’ll
remember most about being in the lab is the way you guys synergized make us the
loudest, most distracting lab on the floor. Thanks for all the laughs!
A special thanks has to go to Howie. We essentially started the program at
the same time and encountered a lot of the same obstacles. Thanks for watching out
for me and for helping me with issues that came up - both research related and
personal.
A sincere thank you to Li Jia, who put up with all of my questions when I
started in the lab (and I asked a lot). You have always been ready and willing to help
guide me through or provide material for my projects.
Grant Buchanan, when I first met you as a fledgling graduate student, with
the combination of your wonderful Australian accent, rapid thinking/speech, and vast
scientific knowledge, I could barely understand a word you were saying. Thankfully,
I’ve gotten used to the accent and know a bit more science than when I first started.

iv
In the short intervals you’ve worked in the Coetzee lab, you’ve mentored me a great
deal and provided great insight into scientific projects. Of course, thank you for
guiding us on the exhilarating ride across Fraser Island!
A thank you to Wayne Tilley as well for the suggestions you’ve provided
throughout the αSGT project and for providing me with the opportunity and
recognition from presenting at the 3
rd
Pacific Rim Meeting.
The ‘CD players’ (and affiliates)! Baruch Frenkel, you have such a creative
mind, never afraid to think outside the box, and an amazing ability to construct
enticing scientific stories. Thank you for all your help in designing, conducting,
interpreting, and communicating experiments. I also want to thank Artem Barski,
Steve Pregizer, Jon Cogan, Nathalie Leclerc, Tommy Noh, and Unnati Jariwala for
the help/collaboration throughout the CD project and for including me as part of the
IGM/Frenkel family. Although I could’ve gone without the trip to the ER, thank you
for all of the memories.
I would also like to thank Sue Ingles and her girls – Melissa Wilson, Wei
Wang, and Hui Lee Wong. All of you have helped guide me in conducting and/or
analyzing the αSGT-prostate cancer association project. Sue, I also really appreciate
the opportunity to TA your course. It was an interesting experience seeing the
teaching side of the classroom. An additional thank you to Hui Lee for going above
and beyond to introduce me to fellow scientists at the 2006 Annual AACR meeting
and for assisting me in whatever way she could during my postdoctoral search.

v
Giske, you provided me with the data analysis experience I had been craving
and have challenged me to think like an epidemiologist. Thank you for your
guidance and for your help during my postdoctoral search (even though you don’t
want me to leave USC).
Leslie Bernstein, I have such respect and admiration for you. I’m so glad you
put together the Ph.D. mentoring meeting, because otherwise I might not have met
you! Thank you for the suggestions you’ve made regarding my scientific
presentations and proposals, and for all your help in my postdoctoral search. Even
though you don’t want me to leave USC either, you did what you felt was best for
my career. I’m eternally grateful and will try to be as productive as humanly possible
for the short time that I am your postdoc.
Judy Garner, you have a passion for helping students that comes through in
your teaching style. Our encounters outside the classroom have been brief, but I want
to thank you for taking the time to give me suggestions and talk about my projects as
well as potential career possibilities.
Omar and Allison, you haven’t been in the lab for very long so there’s not
much that I can say except: Allison thank you for keeping the lab well stocked. Omar
thank you for the fries.
And last but not least, I want to thank my husband Eric, my parents, and my
in-laws for all of their love and words of encouragement throughout the journey that
is the graduate student experience.

vi
TABLE OF CONTENTS

DEDICATION ii

ACKNOWLEDGMENTS iii

LIST OF TABLES ix

LIST OF FIGURES x

ABBREVIATIONS xi

ABSTRACT xiv

CHAPTER 1: Introduction 1

1.1 Androgen Physiology 1
1.2 Normal Prostate Development 2
1.3 Androgen Receptor (AR) 4
1.3.1 Characterization of the AR 4
1.3.2 Chaperone Involvement in AR Function 5
1.4 Prostate Cancer 6
1.4.1 Natural History 6
1.4.2 Pathophysiology 7
1.4.3 Early Androgen-Dependent Disease 8
1.4.4 Progression to Ablation-Resistant Disease 10
1.4.5 PSA Screening 14
1.4.6 Statistics and Epidemiology 15
1.4.6.1 Race 16
1.4.6.2 Genetic Predisposition 18
1.5 Thesis overview 20

CHAPTER 2: Molecular Chaperones Throughout the Life Cycle
of the Androgen Receptor 23

2.1 Introduction 23
2.2 Minimal Molecular Chaperone Complex 25
2.3 AR Translocation 28
2.4 Transcriptional Activation 29
2.5 Transcription Complex Disassembly 31
2.6 Degradation 32
2.7 Chaperones in Prostate Cancer 33
2.8 Clinical Implications 34
2.9 Conclusion 34

vii

CHAPTER 3: αSGT: An Androgen Receptor Co-Chaperone 37

3.1 Introduction 37
3.1.1 Tetratricopeptide repeat (TPR)-containing proteins 37
3.1.2 Small glutamine-rich TPR-containing protein, alpha (αSGT) 38
3.2 Materials and Methods 40
3.2.1 Cell culture and materials 40
3.2.2 Transactivation assay 41
3.2.3 siRNA knockdown 42
3.2.4 Western blot analysis 43
3.2.5 Quantitative Reverse Transcription-PCR (qRT-PCR) 44
3.3 Results 45
3.3.1 Overexpression of αSGT decreases AR transactivation 45
3.3.2 Antibody detects endogenous and transfected αSGT protein 46
3.3.3 αSGT-specific siRNA decreases αSGT protein levels 47
3.3.4 αSGT knockdown increases AR responsiveness to DHT 49
3.3.5 αSGT knockdown increases AR activity in a ligand
specific manner 50
3.4 Discussion 52
3.4.1 αSGT modulates AR function 52
3.4.2 Potential function of αSGT 52
3.4.3 Clinical relevance 55

CHAPTER 4: Repressed Genes Identified in a Screen for Androgen
Receptor Occupancy Regions in Prostate Cancer 64

4.1 Introduction 64
4.1.1 Methods for AR target gene identification 65
4.1.1.1 Expression-based methods 65
4.1.1.2 Location analysis methods 67
4.1.2 Transcriptional Repression 69
4.2 Materials and Methods 71
4.2.1 Cell culture and materials 71
4.2.2 Chromatin Immunoprecipitation (ChIP) 71
4.2.3 ChIP Display (CD) 72
4.2.4 Quantitative Reverse Transcription-PCR (qRT-PCR) 74
4.2.5 Expression in clinical PCa samples 75
4.2.6 siRNA Transfection 76
4.3 Results 76
4.3.1 ChIP Display reveals novel AR targets in C4-2B PCa cells 76
4.3.2 ChIP Display discloses 19 novel AR binding sites 78
4.3.3 DHT treatment detects subsets of gene expression patterns 80
4.3.3.1 DHT-stimulated genes 80

viii
4.3.3.2 DHT-repressed genes 81
4.3.4 Pathophysiologic relevance of novel AR target genes 82
4.3.5 AR represses target genes in the presence and absence
of ligand 85
4.3.6 Evidence for direct involvement of the AR in gene
suppression 86
4.3.7 Bicalutamide counteracts DHT-mediated repression of
KIAA1217 88
4.4 Discussion 89
4.4.1 Location analysis 89
4.4.2 CD-disclosed repressed targets 91
4.4.3 Active repression by nuclear hormone receptors 92
4.4.4 Additional mechanisms of transcriptional repression 92
4.4.5 Direct versus indirect repression of CD-disclosed genes 93
4.4.6 Relevance to PCa 96
4.4.7 Conclusion 98

CHAPTER 5: Summary of Principal Findings 116

REFERENCES 119

ix
LIST OF TABLES

Table 4.1 Primer and oligo sequences 99

Table 4.2 CD-identified AR targets 101

x
LIST OF FIGURES

Figure 1.1 Steroid biosynthesis pathway 22

Figure 2.1 Itinerary of the AR with emphasis on molecular chaperones 36

Figure 3.1 αSGT overexpression inhibits AR activity 56

Figure 3.2 Antibody detects transfected and endogenous αSGT protein 57

Figure 3.3 αSGT-specific siRNA reduces endogenous αSGT protein levels 58

Figure 3.4 Knockdown of αSGT increases DHT-mediated PSA expression 60

Figure 3.5 Knockdown of αSGT increases AR activity in response to non-
classical ligands 62

Figure 3.6 αSGT interacts with a wide range of proteins 63

Figure 4.1 AR occupies novel loci in C4-2B PCa cells 104

Figure 4.2 DHT stimulates and represses novel AR target genes 106

Figure 4.3 Expression of CD-disclosed genes in PCa tumors 109

Figure 4.4 Expression of KIAA1217 differs by location of probesets 110

Figure 4.5 AR represses genes in the presence and absence of added ligand 112

Figure 4.6 DHT represses the pre-mRNA of novel AR target genes 113

Figure 4.7 KIAA1217 mirrors the concentration- and time-dependent
response of PSA to DHT 114

Figure 4.8 Bicalutamide counteracts DHT-mediated repression 115

xi
ABBREVIATIONS

18S 18S ribosomal RNA
AAT androgen ablation therapy
ACBD6 acyl-Coenzyme A binding domain containing 6
AKR1C2 aldo-keto reductase family 1, member C2
ALG12 asparagine-linked glycosylation 12 homolog
AP-1 activator protein-1
AP2A2 adaptor-related protein complex 2, alpha 2 subunit
AQP12A aquaporin 12A
AR androgen receptor
ARE androgen response element
ASD androstenedione
ATF2 activating transcription factor 2
BAG-1 BCL-2-associated athanogene
BAZ1B bromodomain adjacent to zinc finger domain, 1B
BCL-2 B-cell CLL / lymphoma 2
BIC bicalutamide
BPH benign prostatic hyperplasia
CAG cytosine-adenine-guanine
CARKL carbohydrate kinase-like
CD ChIP Display
Cdc37 cell division cycle 37 homolog (S. cerevisiae)
CEP350 centrosomal protein 350kDa
ChIP chromatin immunoprecipitation
CHIP carboxy terminus of Hsp70-interacting protein
CHRM1 cholinergic receptor, muscarinic 1
CLDN4 claudin 4
CPA cyproterone acetate
CRELD2 cysteine-rich with EGF-like domains 2
CSS charcoal-dextran stripped serum
CYP11A1 cytochrome P450, family 11, subfamily A, polypeptide 1
CYP17A1 cytochrome P450, family 17, subfamily A, polypeptide 1
CYP19A1 cytochrome P450, family 19, subfamily A, polypeptide 1
CYP3A4 cytochrome P450, family 3, subfamily A, polypeptide 4
CyP40 cyclophilin 40
DDT D-dopachrome tautomerase
DHEA dehydroepiandrosterone
DHEAS dehydroepiandrosterone sulfate
DHT 5α-dihydrotestosterone
DMSO dimethylsulfoxide
E estradiol
EGF epidermal growth factor
ER estrogen receptor

xii
FBS fetal bovine serum
FKBP51 FK506-binding protein 51
FKBP52 FK506-binding protein 52
FSK forskolin
FZD9 frizzled homolog 9
GAPDH glyceraldehyde-3-phosphate dehydrogenase
GR glucocorticoid receptor
GSTT2 glutathione S-transferase theta 2
HA hemagglutinin
HDAC1 histone deacetylase 1
HDAC2 histone deacetylase 2
HGPIN high-grade prostatic intraepithelial neoplasia
Hip Hsp70-interacting protein
Hop Hsp70/Hsp90-organizing protein
HSD3B2 hydroxy-δ-5-steroid dehydrogenase, 3 β- and steroid δ-isomerase 2
HSD17B2 hydroxysteroid (17-beta) dehydrogenase 2
HSD17B3 hydroxysteroid (17-beta) dehydrogenase 3
Hsp40 heat shock 40kD protein
Hsp70 heat shock 70kD protein
Hsp90 heat shock 90kD protein
IGF-1 insulin-like growth factor 1
IL-6 interleukin 6
JAK janus kinase
KGF keratinocyte growth factor
KIF1A kinesin family member 1A
KLK2 kallikrein-related peptidase 2
LBD ligand-binding domain
LHPP phospholysine phosphohistidine inorganic pyrophosphate phosphatase
LHX4 LIM homeobox 4
MAFG v-maf musculoaponeurotic fibrosarcoma oncogene homolog G
MAN2B2 mannosidase, alpha, class 2B, member 2
MAPK mitogen-activated protein kinase
MAP3K7IP1 mitogen-activated protein kinase kinase kinase 7 interacting protein 1
MME membrane metallo-endopeptidase
MPA medroxyprogesterone 17-acetate
MR mineralocorticoid receptor
MRFAP1 Mof4 family associated protein 1
MSR1 macrophage scavenger receptor 1
MUC6 mucin 6, oligomeric mucus/gel-forming
NCoR nuclear receptor corepressor
NF-κB nuclear factor of kappa light polypeptide gene enhancer in B-cells
NLS nuclear localization signal
NTD amino-terminal domain
OAT ornithine aminotransferase (gyrate atrophy)

xiii
PCa prostate cancer
PHB prohibitin
PI3K phosphatidylinositol 3-kinase
PIRH2 ring finger and CHY zinc finger domain containing 1
PP5 protein phosphatase 5
PR progesterone receptor
PROG progesterone
PRKCD protein kinase C, delta
PSA prostate-specific antigen
PYCR1 pyrroline-5-carboxylate reductase 1
QSCN6 quiescin Q6
R1881 methyltrienolone
RAC3 receptor associated coactivator 3
RNAi RNA interference
SD standard deviation
SEM standard error of the mean
αSGT small glutamine-rich tetratricopeptide repeat-containing, alpha
siRNA short interfering RNA
SIRT7 sirtuin (silent mating type information regulation 2 homolog) 7
SLC22A6 solute carrier family 22 (organic ion transporter), member 6
SLC22A8 solute carrier family 22 (organic ion transporter), member 8
SMRT silencing mediator for retinoid and thyroid hormone receptors
SRC1 steroid receptor coactivator-1
SRD5A2 steroid-5-alpha-reductase, alpha polypeptide 2
STAT signal transducer and activator of transcription
SULT2A1 sulfotransferase family, cytosolic, 2A, DHEA-preferring member 1
SYNGR1 synaptogyrin 1
T testosterone
TAF TBP-associated factors
TBP TATA box-binding protein
TFIID complex of TBP and TAFs for RNA polymerase II transcription
TIF2 transcriptional intermediary factor 2
Tip60 HIV-1 Tat interacting protein, 60kD
TMPRSS2 transmembrane protease, serine 2
TPR tetratricopeptide repeat motif
TRAMP transgenic adenocarcinoma of mouse prostate
TRPV1 transient receptor potential cation channel, subfamily V, member 1
TRPV3 transient receptor potential cation channel, subfamily V, member 3
TSA trichostatin A
TSS transcription start site
UGE urogenital sinus epithelium
UGM urogenital sinus mesenchyme
WBSCR27 Williams Beuren syndrome chromosome region 27
WBSCR28 Williams Beuren syndrome chromosome region 28

xiv
ABSTRACT

The androgen receptor (AR) plays pivotal roles in the initiation and
progression of prostate cancer, which is a major health burden worldwide. Initially,
the disease is androgen-dependent and readily responds to androgen-ablation
therapies. However, after a relatively short period of ablation therapy, the tumor
returns as a more aggressive androgen-ablation resistant disease for which there are
no effective therapies. Thus, the detection of prostate cancer at an early curable
stage, as well as understanding the mechanisms of cancer progression are of utmost
importance.
Though ablation-resistant prostate tumors often respond to alternate ablation
therapies, eventually such tumors become refractile to all. This occurs not from a
loss of AR, but rather the acquired ability of the AR to signal at subphysiologic
levels of androgen. While various mechanisms have been proposed, the details and
the relative contribution of each mechanism are poorly understood. The following
thesis attempts to enhance our knowledge of progression to advanced prostate cancer
by examining an upstream factor as well as downstream effectors of AR signaling.
AR activation requires the proper high ligand-binding affinity conformation
assembled by molecular chaperones to unfold and maintain accessibility to the
ligand-binding pocket. The core complex of molecular chaperones are assisted and
regulated by accessory proteins, including TPR-containing proteins. In collaboration
with Dr. Wayne Tilley’s group (Adelaide, Australia), we were able to demonstrate

xv
modulation of AR function by a novel TPR-containing protein, αSGT. The effect
appeared to be the result of an influence on nuclear translocation.
With a relatively small number of known AR-regulated genes, it is difficult to
understand the biological effects of AR signaling in normal, let alone advanced
prostate tumors. Using ChIP Display, we identified several new AR binding sites,
which were in the vicinity of androgen-regulated genes. A subset of genes was
repressed upon androgen-treatment, a group that has been largely ignored. Our
findings provide novel targets for the study of AR function in prostate cancer.

1
CHAPTER 1: Introduction

1.1 Androgen Physiology
Endocrine signaling molecules, known as hormones, were first recognized as
potent regulators of organ physiology in the early 1900s (Tata, 2002). Human
hormones consist of three major classes: protein and peptide hormones, steroids, and
tyrosine derivatives (Nussey and Whitehead, 2001). Glucocorticoids,
mineralocorticoids, progestogens, estrogens, and androgens make up the five
subclasses of steroid hormones, which are cholesterol-derived lipophilic compounds
secreted by the gonads and adrenal cortex (Berg et al., 2002; Nussey and Whitehead,
2001).
Androgens are the key regulators of male sexual characteristics. During
testicular development, fetal-type Leydig cells begin to functionally differentiate by
6 to 7 weeks of gestation. Testosterone (T) biosynthesis in these cells begins within
the mitochondria with the rate-limiting conversion of cholesterol to pregnenolone by
cytochrome P450, family 11, subfamily A, polypeptide 1 (CYP11A1) (Figure 1.1).
Pregnenolone is rapidly transported into the cytosol where it is converted into either
17α-hydroxypregnenolone by the 17α-hydroxylase activity of cytochrome P450,
family 17, subfamily A, polypeptide 1 (CYP17A1) or progesterone by hydroxy-δ-5-
steroid dehydrogenase, 3 β- and steroid δ-isomerase 2 (HSD3B2). In humans, the
preferred pathway appears to be the production of 17α-hydroxypregnenolone, which
is then cleaved by the 17,20-lyase activity of CYP17A1 to produce
dehydroepiandrosterone (DHEA). HSD3B2 converts DHEA to androstenedione

2
(ASD). 17β-hydroxysteroid dehydrogenase 3 (HSD17B3) can then catalyze the
interconversion of DHEA and T (Saez, 1994).
Testosterone production peaks by about 14 weeks of gestation, followed by a
decline starting in the second trimester of pregnancy (Tapanainen et al., 1981).
Exposure to T during fetal development is responsible for the differentiation of
primary male sex characteristics (Saez, 1994). Circulating T induces the wolffian
duct system to differentiate into epididymis, vas deferens, and the seminal vesicles.
In some androgen target tissues, steroid 5α-reductase type II (SRD5A2) converts T
into a more active metabolite, 5α-dihydrotestosterone (DHT) (Bruchovsky and
Wilson, 1968a; Migeon and Wisniewski, 1998; Saez, 1994), to enhance the relatively
weak androgenic signal (Wilson, 2003). The biological activity of DHT is 10-times
more potent than T, with a 10-times lower Kd for the androgen receptor (Deslypere
et al., 1992). DHT mainly promotes the differentiation of the prostate, a male
accessory sex organ, and the masculinization of the external genitalia (Migeon and
Wisniewski, 1998; Saez, 1994). The efficiency of the prostate to convert T into DHT
is associated with mature prostate size (Wilson, 2003). All androgenic effects seem
to be mediated by T and DHT. The weak androgenic activity exhibited by other
androgens appears to depend on conversion to T and DHT (Bruchovsky and Wilson,
1999).

1.2 Normal Prostate Development
The prostate gland is a slow-growing, encapsulated secretory organ of the
male reproductive system encircling the urethra at the base of the bladder (McNeal,

3
1988). Development of the prostate is a highly androgen-regulated process, relying
on complex interactions between the urogenital sinus epithelium (UGE) and
urogenital sinus mesenchyme (UGM), the surrounding connective tissue. Androgen
signaling within the UGM releases critical growth factors to regulate the
proliferation and differentiation of the UGE. UGM induces UGE to form epithelial
buds from the urethra, differentiate into prostatic secretory epithelium, and
subsequently promote extensive ductal elongation and branching morphogenesis. In
turn, androgen signaling within the differentiated prostatic epithelium supports the
proper differentiation and organization of the UGM into a fibromuscular stroma
(Cunha et al., 2004b). The final morphology of the prostate consists of the three
major glandular regions: the peripheral zone (70%), the central zone (25%), and the
transition zone (5-10%). The uniformly branched network of ducts and acini within
each zone is lined with glandular epithelium, which consists of a layer of luminal
secretory cells over a basal cell layer. The secretory cells secrete and store large
amounts of prostatic fluid. Dense fibromuscular stroma surrounding the epithelium
allows for rapid discharge of the fluid into the prostatic urethra (McNeal, 1988).
Continued epithelial-mesenchymal interactions throughout life stabilize the size of
the prostate by establishing an equilibrium between proliferation, differentiation, and
apoptosis (Long et al., 2005) until about the third decade of life when it slowly
begins to grow (Hayward and Cunha, 2000).

4
1.3 Androgen Receptor (AR)
1.3.1 Characterization of the AR
In the late 1960s, the ability of a protein to retain DHT in the nucleus of
prostate cells suggested the existence of an androgen receptor (AR) (Anderson and
Liao, 1968; Bruchovsky and Wilson, 1968a; Fang et al., 1969), which was eventually
demonstrated to be required for normal male sexual development (Wilson, 1992). As
a result of its lower dissociation rate (Grino et al., 1990), DHT was found to have at
least a 5-fold higher binding affinity for the AR than T (Wilbert et al., 1983) and is
the predominant androgen bound to the receptor in prostate cells (Bruchovsky and
Wilson, 1968b). Other steroids such as androstanediol, estradiol, and progesterone
are also capable of binding to the AR, but only at very high concentrations (Wilson
and French, 1976).
The AR is a member of a large nuclear receptor superfamily, which includes
other steroid, retinoid, and thyroid hormone receptors. These receptors regulate
critical processes in organ development through transcriptional control (Chawla et
al., 2001; Mangelsdorf et al., 1995). Cloned and localized to chromosome Xq11-12
in 1988, the AR was found to have considerable structural and functional homology
to the other steroid receptors, particularly the progesterone receptor (PR),
mineralocorticoid receptor (MR), and the glucocorticoid receptor (GR) (Brinkmann
et al., 1989; Chang et al., 1988; Lubahn et al., 1988a; Lubahn et al., 1988b; Tilley et
al., 1989). The 8 exons of the gene span 90kb, which encode a 919 amino acid
protein consisting of 4 distinct functional domains: the amino terminal
transactivation domain (residues 1-537), the DNA binding domain (residues 538-

5
627), the hinge region (residues 628-669), and the ligand binding domain (residues
670-919). The DNA binding domain and the ligand binding domain share the most
sequence similarity with the other nuclear receptors, whereas the hinge region and
the large, highly polymorphic amino-terminal transactivation domain share the least
homology (Quigley et al., 1995).

1.3.2 Chaperone Involvement in AR function
As reviewed by Pratt & Toft, most work on chaperone involvement in steroid
receptor function has focused primarily on the PR and GR (Pratt and Toft, 1997).
Though, being structurally and functionally similar, progress among the other steroid
receptors quickly revealed a common mechanism for chaperone involvement in
priming the receptor for activation. In the absence of ligand, the AR exists as a large
~9S heterocomplex within the cytosol. For the AR to acquire ligand-binding ability,
it undergoes a dynamic assembly-disassembly cycling process through associations
with heat-shock protein (hsp) 90, hsp70, and other components of the chaperone
machinery. The receptor-chaperone heterocomplex forms a partially unfolded
intermediate with a high ligand-binding affinity, keeping the receptor poised for
activation. Though this assembly cycle is the best characterized function, chaperone
and large tetratricopeptide repeat (TPR) domain-containing immunophilin proteins
have also been observed to play a role in nuclear receptor trafficking (Pratt and Toft,
1997). Following hormone binding, rather than dissociation of the complex, there
appears to be a switch in the associated proteins dictating the direction of transport
into or out of the nucleus (Davies et al., 2002; Pratt et al., 1999). Once inside the

6
nucleus, chaperones continue to interact with steroid receptors to influence
transcriptional activity (Caplan et al., 1995; Freeman et al., 2000; Freeman and
Yamamoto, 2002; Froesch et al., 1998; He et al., 2004; Shatkina et al., 2003).

1.4 Prostate Cancer
1.4.1 Natural History
For decades, autopsy investigations of latent disease across different
populations have revealed relatively high occurrences of prostate cancer. Similar to
clinically significant prostate carcinomas, the prevalence of latent prostate cancer
increases with age. Latent disease has been detected in 20% of men over 44 years of
age, reaching about 70% by the eighth decade of life (Breslow et al., 1977; Franks,
1954). Small carcinomas were found to have a prevalence of 12.3%, which did not
differ significantly with age or geographic location (Breslow et al., 1977). Latent
disease also appears to be similar among different ethnicities (Haas and Sakr, 1997).
In contrast, medium and large latent carcinomas increased with age and
demonstrated variation in prevalence among the different study sites. The overall
frequencies of indolent prostate cancer correlate with the age-standardized incidence
and mortality rates of each region (Breslow et al., 1977) suggesting environmental
factors may promote the development of clinical disease from latent prostate cancer.
Prostate cancer is generally a slow growing progressive disease. Untreated
localized prostate cancer has been shown to follow a relatively benign course for
about 10-15 years after diagnosis (Albertsen et al., 1995; Albertsen et al., 1998;
Chodak et al., 1994; Johansson et al., 2004). However, after 15 years the rate of

7
tumor progression increases even among patients diagnosed with well-differentiated
tumors (Johansson et al., 2004). Poor tumor differentiation at diagnosis appears to be
a strong predictor for disease progression (Chodak et al., 1994; Johansson et al.,
2004). When mortality due to competing causes were excluded, a comparison of
multiple studies seemed to suggest men with poorly differentiated tumors have a 10-
fold higher risk of death due to prostate cancer compared to men with well-
differentiated tumors (Kessler and Albertsen, 2003).

1.4.2 Pathophysiology
Adenocarcinomas, the most common form of prostate cancer, mainly
originate from the prostatic epithelium of the peripheral zone (Breslow et al., 1977;
McNeal, 1988). A majority of prostate cancers contain multiple morphologically and
genetically distinct foci, which presumably arise independently (Bostwick et al.,
1998; Cheng et al., 1998b; Kastendieck et al., 1976; Ruijter et al., 1996). This
heterogeneity introduces some difficulty in properly assessing prostate cancer
characteristics (Arora et al., 2004; Hoedemaeker et al., 2000). However, standardized
pathologic staging and grading systems are still useful prognostic indicators for the
natural progression of disease. Within the U.S., TNM staging is typically the system
used to classify tumor volume and the extent of spread. Characterization of the size
and local invasiveness of the primary tumor (T), lymph node involvement (N) and
presence or absence of distant metastases (M) (Hoedemaeker et al., 2000) are used to
classify tumors into 4 stage groups. Stage I cancers are the least advanced and have
the best prognosis for survival (Society, 2007b).

8
The Gleason grading system histologically classifies the foci of prostate
tumors based on glandular architectural patterns as seen under low magnification.
Each pattern has been defined and assigned a numerical value (1-5). The sum of the
primary and secondary Gleason grades generate the Gleason score (2-10), with
higher scores representing more aggressive, poorly differentiated cancers. Among
clinically localized tumors, high-grade continues to be an important preoperative
indicator of progression-free survival (Epstein et al., 1996; Gerber et al., 1996).
However, modifications to take into account any presence of Gleason grades 4 and 5
within smaller foci would significantly improve predictability (Arora et al., 2004;
Wise et al., 2002).
High-grade prostatic intraepithelial neoplasia (HGPIN), which is often found
concurrent with malignant disease, is considered the putative precursor of
moderately- and poorly-differentiatied carcinomas (Bostwick, 1996; Bostwick et al.,
1998; Montironi et al., 1996), whereas atypical adenomatous hyperplasia may give
rise to the well-differentiated adenocarcinomas, particularly those originating within
the transition zone (Cheng et al., 1998a; Montironi et al., 1996). Compared to
HGPIN, prostate cancers generally have a higher frequency of allelic imbalance, i.e.
the gain or loss of chromosomal regions, and are characterized by a loss of the basal
cell layer (Bostwick et al., 1998; Montironi et al., 1996).

1.4.3 Early Androgen-Dependent Disease
Since the early 1940s, it has been evident that early prostate cancer is a
highly androgen-dependent disease (Huggins and Hodges, 2002). All phases of

9
prostate cancer, from genetic predisposition through disease progression, involve the
androgen-signaling axis via the AR (Buchanan et al., 2001b). Several lines of
evidence support an important role for the AR receptor in the development of
prostate cancer. Men castrated or hypopituitary before 40 years of age do not
develop prostate cancer (Geller, 1995). Furthermore, though not as common as in
advanced disease, AR mutations have been detected in localized human prostate
cancers (Buchanan et al., 2001a). At least one somatic AR mutation was found
within each spontaneous tumor that developed in the transgenic adenocarcinoma of
mouse prostate (TRAMP) model (Han et al., 2001). Additionally, transgenic
expression of AR-E231G demonstrated that mutation of the AR was sufficient for
prostate carcinogenesis (Han et al., 2005).
Transplantation studies demonstrated that the epithelial expressed AR is
neither required nor sufficient for proliferation of the epithelium during the
development and maintenance of the normal prostate (Cunha et al., 2004a).
Additionally, tissue recombinants in rats utilizing normal UGM or carcinoma-
associated fibroblasts combined with a human BPH cell line established the ability of
the malignant prostatic stroma to induce carcinogenic growth (Cunha et al., 2003).
Consequently, it was presumed that the proliferation of malignant epithelial cells
relied on the androgen-dependent paracrine signals derived from the underlying
prostatic stroma. However, other evidence suggests that the epithelial AR is also
critical to the progression of prostate cancer. Utilizing 4 different prostate cancer
cells lines (human PC-82, human LNCaP, human LAPC-4, rat R3327G) epithelial
transplantation experiments into homozygous nude/AR-null male mice, which do not

10
express functional AR within any cell type, demonstrated the ability of the epithelial
AR to promote cancer proliferation. These results suggest that the malignant
epithelial cells acquire the ability for autocrine signaling in response to androgens
during its transformation from normal to prostatic disease. Presumably, the epithelial
AR obtains the ability to bind to and stimulate growth factor expression, which may
or may not be the same as those expressed in the normal stroma (Gao et al., 2001).
Alternatively, recurrent gene transfusions between an androgen responsive promoter
and a transcription factor, such as those occurring between TMPRSS2 and ETS
family members, may promote the malignant transformation of epithelial cells by
regulating a whole new cascade of genes (Tomlins et al., 2005).

1.4.4 Progression to Ablation-Resistant Disease
Over long-term follow-up, 30% of men diagnosed with localized disease that
underwent radical retropubic prostatectomy will experience biochemical recurrence
(Han et al., 2003) and about one-third of these patients will develop metastatic
disease (Swindle et al., 2003), particularly those initially diagnosed with a higher
grade tumor (Chodak et al., 1994). Treatment of advanced prostate cancer with
androgen ablation therapy has a good initial response in 70-80% of patients
(Kozlowski et al., 1991; Santos et al., 2004). However, treatment is not curative.
Almost all of the initially responsive tumors eventually progress (Kozlowski et al.,
1991). The median length of time from metastasis to death is roughly 1.5 years
(Chodak et al., 1994).

11
Virtually all ablation-resistant tumors express the androgen receptor (Bentel
and Tilley, 1996; Brolin et al., 1992; Hobisch et al., 1995). Survival of these cells is
not brought about by the loss of androgen sensitivity, but rather the gain of AR
activity through an aberrantly regulated androgen-signaling axis. In fact, blocking
AR activity via an anti-AR antibody or by knockdown of its expression inhibited the
growth of ablation-resistant cell lines (Zegarra-Moro et al., 2002).
AR activity in ablation-resistant cells may arise through various mechanisms.
Twenty-five to thirty percent of ablation-resistant tumors exhibit AR amplification,
which effectively restores androgen signaling in the presence of low circulating
androgens in hormone-ablated patients (Taplin and Balk, 2004). AR amplification
has also been shown to be necessary and sufficient for the conversion of androgen-
dependent growth to ablation-resistant prostate cancer, being the only consistent
change associated with the progression of isogenic prostate xenograft models. In AR
amplified cells, modest changes in the relative recruitment of coactivators and
corepressors to androgen-regulated promoters may be responsible for the observed
AR activity in the presence of anti-androgens (Chen et al., 2004).
Androgen-ablation therapy also establishes a selection pressure for the
emergence of assumed AR gain-of-function point mutations, which has been
documented in up to 50% of ablation-resistant prostate cancers (Buchanan et al.,
2001a). Probably the most well known and one of the more frequent mutations
occurs within the ligand-binding domain (Thr877Ala) of the AR (Taplin and Balk,
2004). This mutation is found within the human metastatic prostate cancer-derived
LNCaP cell line. With this particular mutation, the AR is activated in response to

12
non-classical ligands such as estrogen and progesterone, as well as the androgen
antagonists, hydroxyflutamide and cyproterone acetate (Berrevoets et al., 1993). The
particular localization of spontaneous AR mutations appears to be dependent on the
specific hormonal environment of the tumor (Han et al., 2001).
Another potential mechanism involved in maintaining androgen signaling in
androgen-ablated tissue is the increased expression of AR coactivators. The protein
expression of transcriptional intermediary factor 2 (TIF2) and steroid receptor
coactivator 1 (SRC1) were both observed to increase with prostate cancer
progression to ablation-resistant disease. Not only did the overexpression of TIF2
enhance AR signaling in response to androgens, but it also promoted AR activation
in the presence of physiologic concentrations of non-classical ligands (Gregory et al.,
2001). Though, other studies did not find similar results for TIF2 and SRC1 (Li et
al., 2002; Linja et al., 2004). PIRH2 (Logan et al., 2006), RAC3 (Gnanapragasam et
al., 2001), and Tip60 (Halkidou et al., 2003) are other AR coactivator proteins,
which in these initial studies had altered expression levels associated with prostate
cancer progression. Conversely, a downregulation of AR corepressor proteins in
ablation-resistant prostate cancer would theoretically also result in higher AR
activity. This has yet to be demonstrated in human prostate tissues. Nevertheless,
prohibitin (PHB), a recently characterized androgen-repressed gene, appears to be a
corepressor of AR activity, inhibiting the growth of prostate cells (Gamble et al.,
2006).
Ligand-independent activation of AR may also occur in ablation-resistant
cells via crosstalk with alternate signaling pathways. Growth factors and cytokines

13
such as insulin-like growth factor-I (IGF-I), keratinocyte growth factor (KGF),
epidermal growth factor (EGF), forskolin (FSK), and interleukin-6 (IL-6) have been
shown to regulate AR activity in the absence of androgen (Culig et al., 1994;
Hakariya et al., 2006). Signaling by these peptide factors often occurs via the
MAPK, JAK/STAT, and PI3K/Akt pathways (Gioeli et al., 1999; Jia et al., 2004;
Peterziel et al., 1999; Ueda et al., 2002), which if inhibited could potentially restore
androgen sensitivity to ablation-resistant cells (Bakin et al., 2003a; Bakin et al.,
2003b).
Finally, progression to ablation-resistant disease may involve mechanisms,
which bypasses the AR altogether. The anti-apoptotic protein, BCL-2, is not
expressed in normal prostate epithelium. However, both human primary and
ablation-resistant tumors expressed significant amounts of this protein, which may
promote the growth and survival of these cells in the absence of androgens (Raffo et
al., 1995). Additionally, in the absence of androgen treatment, the hormone
refractory cell line, C4-2B, has been shown to exhibit greater histone acetylation
than in LNCaP cells (Jia et al., 2006), the parental androgen-dependent cell line
(Thalmann et al., 1994). Such modified chromatin presumably allows for increased
accessibility to basal transcriptional machinery such as RNA polymerase II,
providing the means for more efficient gene transcription (Jia et al., 2006).
The majority of these mechanisms highlight the strong selective pressure for
continued AR signaling in ablation-resistant prostate tumors (Taplin and Balk,
2004). It has been hypothesized that deregulation of the androgen signaling axis may
be the unifying factor responsible for the growth of prostate tumors (Balk, 2002;

14
Buchanan et al., 2001b; Taplin and Balk, 2004). Whether a subpopulation of cells
harboring such mechanisms already exists (Isaacs, 1999) and/or these mechanisms
develop as a result of selection pressure is still uncertain and may differ from tumor
to tumor (So et al., 2005).

1.4.5 PSA Screening
Treatment of advanced prostate cancer is not curative making the early
detection and treatment of localized prostate cancer a priority (Isaacs, 1999),
particularly among younger men with life expectancies exceeding 10 years. In the
late 1980s, detection of elevated plasma levels of the androgen-regulated gene,
prostate-specific antigen (PSA), was determined to be a reliable indicator for the
presence and recurrence of prostate cancers (Stamey et al., 1987). A prospective
study revealed that a serum PSA cutoff of 4.0 ng/mL was remarkably sensitive in
detecting aggressive tumors, which arose within 4 years after testing (Gann et al.,
1995). Advancing clinical stage and estimated tumor volume correlate positively
with PSA levels (Stamey et al., 1987).
The implementation of transurethral ultrasound in 1986 factored somewhat in
the increase in prostate cancer detection that occurred in the late 1980s. However,
PSA screening was, by far, the main contributor to the steep rise in prostate cancer
incidence. The rise began in 1988 (Potosky et al., 1995) and reached it’s peak in
1992 before dramatically decreasing between 1992 and 1995 (Society, 2007a).
Compared to digital rectal examination, PSA screening increased the proportion of
early, organ-confined disease detected among patients (Catalona et al., 1993). At the

15
4.0 ng/mL cutoff, PSA testing was estimated to detect prostate tumors on average 5.5
years ahead of clinical diagnosis (Gann et al., 1995). Traditionally, PSA values
between 0 and 4.0 ng/mL have been considered “normal” (Smith et al., 2001).
However, men with PSA levels between 2.0 – 4.0 ng/mL may also have nonpalpable
tumors, which eventually progress (Carter et al., 1997). Even small elevations in
PSA compared to the lowest levels have been associated with increased prostate
cancer risk (Gann et al., 1995).
A proportion of PSA-detected disease is likely to represent latent prostate
cancers that never would have exhibited clinical symptoms (Catalona et al., 1993;
Johansson et al., 2004). Additionally, though PSA may be specifically expressed in
the prostate, it is not a disease-specific marker. Patients with BPH or prostatitis also
experience increased PSA levels in the “abnormal” range (Smith et al., 2001; Stamey
et al., 1987). In men with prostate cancer, a greater proportion of PSA is complexed
to serum proteins as compared to men with BPH. Therefore, measuring complexed
PSA or the ratio of free-to-total PSA with a 20-25% threshold may improve the
positive predictive value of PSA testing and reduce the number of negative prostate
biopsies performed (Parsons et al., 2004; Smith et al., 2001).

1.4.6 Statistics and Epidemiology
Worldwide, prostate cancer is the third most common cancer in men.
Considerable variation in incidence rates exists with the highest rates found in North
America and the lowest in Asian countries. All countries have been experiencing
increasing incidence rates over the past few decades (Quinn and Babb, 2002).

16
Among men in the United States, prostate cancer is the number one type of newly
diagnosed invasive cancer, excluding non-melanoma skin cancers, and second in
terms of mortality. In 2007, an estimated 29% of all diagnosed cancer cases among
males will comprise of prostate cancer (218,890). Ninety-one percent of these is
expected to be diagnosed at the local or regional stage, which have 100% 5-year
survival rates (Jemal et al., 2007).

1.4.6.1 Race
African-Americans have the highest incidence rates (243.0 per 100,000) in
the world. Black men within the U.S. have incidence and mortality rates that are
roughly 1.6 and 2.4 times higher, respectively, than that of white U.S. males.
African-Americans are also more likely to be diagnosed with a more advanced stage
disease, where the 5-year survival rate drops to 31% (Jemal et al., 2007). A meta-
analysis investigating this disparity in cancer survival between black and white men
suggest that death rates may actually be quite similar when analyses are adjusted for
quality of health care and comorbid conditions in addition to health insurance
coverage, socioeconomic status, and stage at diagnosis (Bach et al., 2002). This is an
important consideration since comorbities were found to be the second most
important predictor of survival following tumor grade (Albertsen et al., 1995).
However, these factors cannot entirely account for the gap in the incidence
rates of prostate cancer (Freedland and Isaacs, 2005). Migration studies and the
worldwide trends of increasing prostate cancer incidence suggest environmental
factors are involved in prostate cancer etiology (Clinton and Giovannucci, 1998).

17
Epidemiologic studies have investigated numerous exposures including
socioeconomic status, occupation, smoking, sexual activity, hormones,
anthropometrics, diet, and obesity as putative risk factors for prostate cancer (Clinton
and Giovannucci, 1998; Haas and Sakr, 1997). Still, the only established risk factors
for prostate cancer are age, race, and a family history of prostate cancer (Society,
2007a), which have been known for some time (Franks, 1973). Until 40 years of age,
prostate cancer is fairly uncommon (Jemal et al., 2007). After 40 years of age
incidence increases exponentially at a rate that surpasses that of any other cancer
(Ross et al., 1995). The majority of prostate cancers (65%) are diagnosed in men
over 65 years of age (Society, 2007a) and men with a brother or father diagnosed
with prostate cancer have about a 2-fold increased risk of developing prostate cancer
themselves as compared to the general population (Haas and Sakr, 1997).
The high rate of prostate cancer among African-American men was believed
to involve a strong environmental component. African-American males are
descendents of populations within west and central African countries where low
prostate cancer rates have been reported. Though, more recent evidence suggests
these low rates may be an artifact of underreporting as well as a lack of accuracy and
detail in diagnosing prostate cancer (Angwafo et al., 2003; Echimane et al., 2000;
Odedina et al., 2006). Several studies involving different cities within the West
African country of Nigeria report high incidence rates of prostate cancer approaching
those of African-American males (Odedina et al., 2006). Furthermore, throughout
various geographic locations, men of African descent generally have higher
frequencies of HGPIN and clinically significant prostate cancer, which are diagnosed

18
at younger ages and at more advanced stages than white men of the same region
(Haas and Sakr, 1997).

1.4.6.2 Genetic Predisposition
While environment is likely to contribute to prostate cancer risk, genetics
may play an even bigger role in this disease. Linkage studies have attempted to
identify prostate cancer susceptibility genes. These studies have not been entirely
successful, owing to the heterogeneity of prostate cancer along with the inability to
distinguish true hereditary cancers from the sporadic cases (Hughes et al., 2005;
Simard et al., 2002). Though, recent linkage and admixture mapping studies have
identified a highly significant susceptibility locus at 8q24 (Amundadottir et al., 2006;
Freedman et al., 2006). Even so, a strong genetic predisposition due to highly
penetrant genes has been estimated to account for only about 5-10% of all prostate
cancer cases (Society, 2007a). For a complex disease such as prostate cancer, it is
more likely that the development of prostate cancer is influenced by a number of
common genetic variants, each potentially contributing a small increase in risk
(Hughes et al., 2005).
Though certainly not the only pathway involved, due to the hormonal aspect
of normal and prostate cancer development, genes regulating androgen biosynthesis
and activity are of interest in prostate cancer etiology. Circulating levels of
androgens have not shown consistent associations with prostate cancer risk.
However, even though androgen levels may be similar among the case and control
groups, the responsiveness to androgens may be higher among case subjects than

19
controls (Carter et al., 1992). Consequently, genetic variants that potentially confer a
higher degree of androgenicity are likely candidates in prostate cancer etiology.
Common polymorphisms within such genes have been associated with prostate
cancer risk (Freedland and Isaacs, 2005). One example is the cytosine-adenine-
guanine (CAG) repeat polymorphism within the first exon of the AR, which encodes
a variable polyglutamine tract within the amino-terminal activation domain (NTD).
The normal range varies from 9 to 31 repeats. Most epidemiologic studies suggest an
association between the shorter polyglutamine repeat lengths and increased prostate
cancer risk. Moreover, transient transfection experiments demonstrate that androgen
receptors with shorter CAG repeat lengths possess higher transcriptional activity as
compared to receptors with longer repeat lengths, thus providing a molecular
mechanism for the observed risk (Buchanan et al., 2001b; Nelson and Witte, 2002;
Ross et al., 1995).
Starting in utero, African-American men generally appear to have greater
exposure to androgens and its effects throughout life. Besides having relatively high
circulating levels of androgens (Ross et al., 1995), black men are also more likely to
have the genetic variants that would increase responsiveness to androgens. Studies
have revealed that African-Americans, in addition to having higher prostatic levels
of AR, tend to have the more active AR variants consisting of shorter CAG repeat
lengths as compared to white men. A higher frequency of the less active variant of
the testosterone deactivating gene, CYP3A4, and the more active SRD5A2 and
HSD3B2 variants, may work together to effectively increase prostate-specific
exposure to androgens (Freedland and Isaacs, 2005). These observations suggest

20
genetic differences between ethnic groups may play an important role in the
malignant transformation of prostate cancer. For this reason, further exploration into
the regulation of AR signaling and its effects on downstream events is warranted.

1.5 Thesis Overview
Chapter 2 is a review of the involvement of chaperone proteins in the
processes of folding, activation, trafficking, and transcriptional activity of the
androgen receptor. These proteins provide different points along the androgen-
signaling axis where regulation of androgen receptor activity can be hijacked to
provide growth signals for clonal selection in cancer progression. Abnormal
chaperone expression could contribute to the upregulation of AR activity in prostate
tumors.
Chapter 3 describes the functional analysis of a novel co-chaperone, αSGT,
which was found to interact with the androgen receptor. Manipulation of αSGT
expression in prostate cancer cells had a subsequent effect on AR activity. This, in
conjunction with its altered expression from normal to abnormal prostate tissue,
suggests αSGT may be a candidate gene in prostate cancer.
Chapter 4 presents data obtained from a screen conducted to identify direct
AR target genes. A number of binding regions were identified and validated, many
of which were not within what would be considered the classical 5’ promoter region.
Analyzing the androgen-responsiveness of genes in relatively close proximity to the
binding region identified novel androgen-regulated genes, a subset of which was
repressed. Further analyses on the regulation of the downregulated genes, which

21
ultimately focused on one gene in particular, KIAA1217, suggests mechanisms other
than active repression exist for transcriptional gene repression from a distal
regulatory site.
Chapter 5 provides a general conclusion with insights for future work.

22
FIGURE 1.1

Steroid biosynthesis pathway. The diagram illustrates the metabolic conversion of
cholesterol into a number of sex steroids. Genes responsible for the conversion
reactions are italicized and in parentheses.

23
CHAPTER 2: Molecular Chaperones Throughout the Life Cycle
of the Androgen Receptor

This chapter contains a literature review. Though the involvement of molecular
chaperones in the basic maturation of steroid hormone receptors is fairly well
understood, more recent studies have demonstrated additional roles for these
proteins in other aspects of receptor function. Moreover, most literature has focused
on the glucocorticoid and progesterone receptors. This review fills a gap by
providing a review of molecular chaperone involvement throughout the life cycle of
the AR. This chapter is an updated version of the final document published in the
January 2006 issue of Cancer Letters. (Prescott & Coetzee, Cancer Letters, 231:12-
19, 2006)
2.1 Introduction
The androgen receptor (AR) is a transcription factor belonging to the class I
subgroup of the nuclear receptor superfamily. Members of this family are ligand-
responsive and share structural and functional similarities with one another
(Mangelsdorf et al., 1995). Stimulated by androgens, the AR signaling pathway plays
an important role in the development and differentiation of target tissues (Evans,
1988; Mangelsdorf et al., 1995), as well as a critical role in the initiation,
proliferation, and progression of prostate cancer to ablation-resistant disease
(Heinlein and Chang, 2004; Taplin and Balk, 2004).
The predominantly cytoplasmic AR rapidly translocates into the nucleus in
response to androgen (Georget et al., 1997; Simental et al., 1991). As with any signal

24
transduction pathway, proper signaling is dependent upon the receptor’s ability to
acquire more than one conformational state (Bohen et al., 1995). Unbound to ligand,
the AR is maintained in an inactive, but highly responsive state by a large dynamic
heterocomplex composed of heat shock proteins, co-chaperones, and
tetratricopeptide repeat (TPR)-containing proteins (Pratt and Toft, 1997). Most of the
androgen receptor-chaperone interactions identified so far appear to involve the
ligand-binding domain (LBD) of the receptor. Deletion of the AR-LBD abolishes
hormone-responsiveness, and results in the constitutive activity of the receptor
(Evans, 1988; Simental et al., 1991). Therefore, neither the LBD nor hormone is
believed to be necessary for AR transactivation activity. Instead, the primary
function of the LBD may be to inhibit activation of the AR and, therefore, the
transcriptional activation of its target genes in the absence of hormone. Binding of
5α-dihydrotestosterone (DHT) to AR relieves the inhibition imposed by the LBD
(Evans, 1988).
The molecular chaperone complex is believed to configure the ligand-binding
domain into a relatively stable, partially unfolded, inactive intermediate with a high-
affinity for DHT (Bohen et al., 1995; Pratt and Toft, 1997). Hormone binding to the
complex permits the folding of the AR into an active conformation (Evans, 1988;
Pratt and Toft, 1997). Binding of ligand, followed by the dissociation of the receptor-
chaperone complex and activation of the receptor is viewed as the general regulatory
mechanism of AR signaling (Richter and Buchner, 2001). However, molecular
chaperones remain important players in the events downstream of receptor
activation, and throughout the life cycle of the AR (see below).

25
2.2 Minimal Molecular Chaperone Complex
Initially identified by their accumulation in response to cellular stress,
chaperone proteins are able to recognize and bind to hydrophobic regions on
unfolded or partially folded proteins preventing their irreversible aggregation,
promoting cycles of chaperone-mediated folding instead (Bukau and Horwich, 1998;
Fliss et al., 1999). However, even under normal cellular conditions molecular
chaperones assist in the proper folding of steroid hormone receptors. The structural
conformation of the LBD required for AR activation is accomplished through
multiple cycles of binding and release of the AR by the components of the
multichaperone complex (Figure 2.1) (Bohen et al., 1995; Bukau and Horwich, 1998;
Smith and Toft, 1993). Without these chaperone proteins, the receptor is not
denatured. Instead the receptor acquires a conformation where the hydrophobic
pocket within the ligand-binding domain remains inaccessible to hormone,
preventing activation. Therefore, the receptor is required to be in a partially unfolded
high-affinity ligand-binding conformation stabilized by the chaperone heterocomplex
in order to be responsive to stimuli (Pratt et al., 2004).
Much of the work on the chaperone-steroid hormone relationship prior to the
1990s did not specifically focus on the AR. Studies had identified receptor-Hsp90
heterocomplexes for the glucocorticoid receptor (GR), progesterone receptor (PR),
mineralocorticoid receptor (MR), and estrogen receptor (ER), which sediment at ~9S
(Pratt and Toft, 1997). The highly conserved LBD among nuclear receptors (Tilley et
al., 1989) and the existence of a ~9S form of AR (Pratt and Toft, 1997) suggested
that a similar AR-Hsp90 heterocomplex existed as well. Later studies confirmed that

26
Hsp90 does in fact interact with the LBD of the AR along with Hsp70 and
Hsp56/FKBP52 (Marivoet et al., 1992; Veldscholte et al., 1992b), which were
required to maintain the AR in a high affinity ligand-binding state that is hormone-
(Fang et al., 1996) and temperature-dependent (Nemoto et al., 1992; Smith, 1993).
The basic heterocomplex, dubbed the “foldosome”, generally required for the
efficient folding and stabilization of steroid hormone receptors consists of Hsp70
(hsc70), Hsp40 (Ydj1), Hop (p60), Hsp90, and p23 (Dittmar et al., 1998; Kosano et
al., 1998). This minimal complex is believed to be essential for ligand responsive
signaling of all full-length steroid hormone receptors (Bohen et al., 1995).
Subcomplexes of chaperone proteins lacking receptor or other substrate peptides
have been found to exist within the cytosol (Perdew and Whitelaw, 1991). However,
the assembly of steroid hormone receptors into the ligand competent state is believed
to occur in an assembly-line type of process (Langer et al., 1992; Pratt and Toft,
1997; Shatkina et al., 2003). Having been shown to associate with ribosomes during
translation (Frydman et al., 1994), the first chaperone protein likely to interact
cotranslationally with the AR is Hsp70 along with its co-chaperone Ydj1, a DnaJ-
like member of the Hsp40 family. Ydj1 augments Hsp70’s ability to reversibly bind
to small stretches of hydrophobic amino acids (Bukau and Horwich, 1998; Cyr et al.,
1994; Smith and Toft, 1993) on the nascent peptide to maintain the receptor in a
soluble state, preventing irreversible aggregation (Cyr, 1995). Ydj1 may actually
bind to the non-native peptide prior to Hsp70 binding to facilitate the transfer of AR
to Hsp70 (Fan et al., 2004). Ydj1 is hypothesized to potentially assist in correctly
aligning the Hsp70 and receptor interaction surfaces (Fliss et al., 1999).

27
After the initial binding of Hsp70 and Ydj1 to the receptor, Hip/p48 (hsc70
interacting protein), another Hsp70 co-chaperone, binds to stabilize and prolong the
interaction between the receptor and this intermediate chaperone complex (Hohfeld
et al., 1995). Hop (Hsp organizer protein) then binds to the complex and recruits a
homodimer of Hsp90 (Freeman et al., 2000) by physically forming a bridge between
Hsp70 and Hsp90 using its TPR motifs in the interactions. In addition, Hop
contributes to more efficient folding by influencing conformational changes within
Hsp70 and Hsp90 (Pratt et al., 2004). To stabilize the AR in the high-affinity,
inactive intermediate conformation, p23, a small molecular weight chaperone, binds
to Hsp90 within the complex as Hip, Hop, and Hsp70 dissociate (Davies et al., 2002;
Freeman et al., 2000; Frydman and Hohfeld, 1997; Georget et al., 2002). The release
of Hop allows for the interaction of a late-stage TPR-containing protein (e.g.
immunophilins) with Hsp90, generating the “final complex” (Richter and Buchner,
2001).
The interactions between steroid hormone receptors and molecular
chaperones are transient (Jakob and Buchner, 1994; Smith, 1993) resulting in a
dynamic folding/refolding cycle (Pratt et al., 2004) driven by conformational
changes within Hsp90 (Georget et al., 2002). In the absence of hormone, an
equilibrium is established which maintains the AR in an overall high-affinity ligand-
binding state. Hormone binding causes the receptor to undergo a sequential loss of
chaperones, a process thought to occur as a result of blocking the formation of the
receptor-Hsp70 complex and, therefore, the subsequent interactions that occur in the
assembly/disassembly cycle of the disactivation loop (Smith, 1993). With the

28
assistance of Hsp90 (Georget et al., 2002), transformation of the receptor into the
DNA-binding competent state (Veldscholte et al., 1992b) is followed by nuclear
translocation, recruitment of cofactors, and transcription of target genes (Georget et
al., 2002).

2.3 AR Translocation
Based on studies of PR, ER, and GR, it is known that steroid hormone
receptors undergo continuous nucleocytoplasmic shuttling (Guiochon-Mantel et al.,
1996) with the predominant localization determined by the accessibility of the
nuclear localization signal (NLS) (Pratt et al., 1999). The NLS of the AR, assumed to
be hidden in the inactive conformation, is unmasked upon receptor activation
allowing transport into the nucleus (Black et al., 2004). Nuclear transfer of the AR
has been shown to be hormone concentration- (Georget et al., 1997) and Hsp90-
dependent (Georget et al., 2002).
A recent study proposes that the earliest step in receptor activation is not the
dissociation of the heterochaperone complex, but the exchange of one late-stage
TPR-containing protein for another along with the recruitment of cytoplasmic dynein
(Figure 2.1) (Davies et al., 2002). This, in conjunction with the reported finding of an
Hsp90 interaction with the cytoskeleton (Smith and Toft, 1993), provides a
mechanism for the translocation and accumulation of the AR within nuclear foci
(Black et al., 2004; Hager et al., 2000). The model developed proposes the
involvement of Hsp90 complexes in the trafficking of the receptor along
microtubules, using the particular TPR-containing protein associated with the

29
heterocomplex as a guide to sites of receptor action (Owens-Grillo et al., 1996).
Once the receptor is activated, the association of an immunophilin with the Hsp90
complex is thought to guide the receptor in a retrograde direction along
microtubules. Conversely, binding of Cdc37 (p50) is believed to be the Hsp90-
associated protein that is responsible for anterograde trafficking (Pratt et al., 2004;
Pratt et al., 1999).
Hsp70 proteins have also been found to associate with steroid hormone
receptors in the presence of ligand (Rao et al., 2001) and are thought to play a role in
translocating the receptor across intranuclear membranes presumably by temporarily
unfolding the receptor (Rassow et al., 1995; Smith and Toft, 1993). Ydj1, a putative
component of the matrix lamina pore complex, may assist Hsp70 in
unfolding/refolding the AR as the receptor is transported across the nuclear
membrane (Caplan and Douglas, 1991). Once inside the nucleus, the chaperone
complex dissociates from the receptor (Davies et al., 2002).

2.4 Transcriptional Activation
In addition to the influence of cofactors on AR activity, there is also evidence
for molecular chaperone involvement in the activation of target genes. Bag-1
proteins, which are Hsp70 co-chaperones, are involved in hormone receptor
transactivation. Specifically Bag-1L, the long, constitutively nuclear isoform of the
Bag-1 proteins (Takayama et al., 1997) has been shown to complex with the AR in
the presence of hormone to upregulate its activity (Froesch et al., 1998). Bag-1L may
act directly on the transcription factor complex as it was found to associate with

30
androgen response elements in the absence of hormone. With recruitment of AR and
Hsp70 to the PSA promoter, Bag-1L could perhaps assist these proteins in
conformational changes that enhance interactions between the amino-terminal and
the carboxyl-terminal regions of the AR. Bag-1L could also contribute to an increase
in transcriptional activity through the recruitment of coactivators to the transcription
regulatory complex (Shatkina et al., 2003), as well as potentially facilitate the cross-
talk of AR with alternate signaling pathways via its association with kinases
(Takayama et al., 1997). However, this stimulatory effect of Bag-1L on AR activity
cannot be generalized to all steroid hormone receptors. In contrast to AR, studies
have shown that Bag-1L inhibits GR activity (Schneikert et al., 1999).
Cdc37, which was initially thought to be exclusively associated with kinase-
chaperone complexes because of the lack of an association with GR (Whitelaw et al.,
1991), was later shown to directly interact with the LBD of the AR (Rao et al.,
2001). Cdc37 appears to influence AR transactivational activity in a partially
hormone-dependent manner downstream of hormone binding (Fliss et al., 1997; Rao
et al., 2001), possibly by assisting the receptor in acquiring conformational changes
required for activation. Cdc37 may also make a small contribution to androgen-
independent AR activity as well (Robzyk et al., 2007). This effect cannot be inferred
to all steroid hormone receptors as the loss of Cdc37 function did not have much of
an effect on GR activation (Fliss et al., 1997).
More recently, the TPR-containing immunophilin, FKBP52, was found to
interact with the Hsp90-AR heterocomplex and increase the sensitivity of the AR to
lower concentrations of DHT treatment (Cheung-Flynn et al., 2005), but not the

31
closely related FKBP51 (Yong et al., 2007). Whereas FKBP52 is believed to have a
role in the nuclear translocation of the GR in response to ligand, AR transport does
not appear to be affected. Though FKBP52 augments AR sensitivity to ligand, this
does not appear to be the result of increased ligand binding affinity (Cheung-Flynn et
al., 2005; Yong et al., 2007). An alteration in AR stability was suggested in one
study (Cheung-Flynn et al., 2005), but not another (Yong et al., 2007). While the
exact mechanism remains elusive, the increased potentiation of the AR by FKBP52
is consistent.
Additional chaperone proteins that have exhibited a role in AR
transactivation activity, independent of their roles in previous folding processes,
include Ydj1 as a stimulatory factor (Caplan et al., 1995), and p23 as an inhibitory
factor on AR activity. The inhibitory effect of p23 is yet another example of
receptor-specific regulation since p23 was found to increase the transcriptional
activity of GR (Freeman et al., 2000). Why these co-chaperone proteins exert
differential effects with respect to the associated receptor is unknown. Even though
steroid hormone receptors interact with the same minimal chaperone complex, it may
be the absolute composition of the receptor-chaperone heterocomplex, with all of its
associated proteins, that dictates the functional activity of the receptor.

2.5 Transcription Complex Disassembly
As mentioned above, the heterocomplex dissociates from the receptor once it
has translocated into the nucleus. Yet, molecular chaperones remain implicated in
receptor activity since the disactivation loop is believed to occur within the nucleus

32
as well (Figure 2.1). A recent model proposed that molecular chaperones are
involved in the disassembly of transcription factor complexes in order to promote the
dissociation of hormone from the receptor and reassemble the receptor in the inactive
state. Thus, if DHT is still present, reactivation of the AR occurs. However, if the
hormone is no longer around, the receptor reenters the disactivation loop. In this
manner, intranuclear cycling provides a transcriptional regulatory mechanism that is
capable of detecting declining levels of ligand, resulting in the rapid termination of
receptor activity once the signal is abolished (Freeman and Yamamoto, 2001; Pratt et
al., 2004). In testing this disassembly model, it was revealed that p23, and possibly to
a lesser extent Hsp90, actively disassembled regulatory complexes from DNA
elements (Freeman and Yamamoto, 2002).

2.6 Degradation
Steroid hormone receptor degradation occurs via the ubiquitin-proteasome
pathway (Pratt et al., 2004). When a receptor is unable to successfully transition into
the high-affinity ligand-binding conformation the receptor undergoes degradation.
CHIP (carboxyl terminus of Hsc70-interacting protein), an Hsp70 co-chaperone
protein, has been shown to directly interact with the AR (He et al., 2004) and Hsp90
in the apo-receptor complex, causing the dissociation of p23 and loss of steroid
binding ability (Connell et al., 2001). In a phosphorylation- and sequence-specific
manner, CHIP was found to interact with the hinge region of the AR (Rees et al.,
2006), which contains a PEST sequence degradation motif (Sheflin et al., 2000).
Ubiquitylation is induced, followed by degradation via the proteasome (Cardozo et

33
al., 2003; Connell et al., 2001; He et al., 2004). CHIP-mediated degradation of the
AR (Cardozo et al., 2003; He et al., 2004) has been put forth as a quality control
mechanism to prevent protein aggregation (Murata et al., 2001). CHIP may also
prevent the accumulation of structurally unsound AR through the reduction in the
rate of AR synthesis (Cardozo et al., 2003).

2.7 Chaperones in Prostate Cancer
An increase in certain chaperone proteins has been documented for prostate
cancer. Normally, the basal cells of a benign prostate express Bag-1L, but the
epithelial cells do not. However, in prostate cancer, the opposite is observed where
Bag-1L is expressed in malignant epithelial cells and is no longer expressed in the
basal cells. The distribution of Bag-1L is similar to Hsp70, which could possibly act
synergistically to increase AR transcriptional activity (Shatkina et al., 2003). Cdc37
is another chaperone protein that has displayed increased expression in carcinomas.
Animal studies suggest a potential early role for Cdc37 in prostate cancer
development. Overexpression of this protein in animal models has been associated
with abnormalities such as prostatic epithelial cell hyperplasia and dysplasia
(Stepanova et al., 2000). In the human male, abnormal expression of these proteins
may act to enhance androgen receptor action providing a selective advantage to
tumor cells during androgen ablation therapy (Froesch et al., 1998; Krajewska et al.,
2006).

34
2.8 Clinical Implications
Alterations in the receptor-chaperone complex may well lead to aberrant AR
signaling that could contribute to prostate carcinogenesis (Shatkina et al., 2003). As
described above, overexpression of certain molecular chaperones would enhance
androgen receptor activity. Whereas a downregulation of inhibitory chaperones such
as CHIP, which has a putative role in maintaining low levels of AR in the normal
prostate (He et al., 2004), would contribute to progression via an accumulation of the
receptor, resulting in an upregulation of AR action.
However, even in the absence of a causal role for chaperones in prostate
cancer development, molecular chaperones serve as potential therapeutic targets in
prostate cancer treatment. Currently, Hsp90 is a therapeutic target in prostate cancer
clinical drugs trials (Neckers and Ivy, 2003). Inhibition of Hsp90 with drugs such as
geldanamycin prevents the stable association of p23 with the receptor-chaperone
complex, therefore trapping the AR in an intermediate state (Buchner, 1999). The
persistent interaction between Hsp90 and steroid hormone receptors shifts the
balance between folding and degradation toward degradation (Pratt et al., 2004).
Targeting chaperone proteins in combination with AR antagonists or radiation may
have a synergistic effect in impeding AR activity in prostate cancer (Georget et al.,
2002; Harashima et al., 2003).

2.9 Conclusion
Molecular chaperones play key roles in the folding, translocation, activation,
and degradation of steroid hormone receptors depending on whether the receptor is

35
in its inactive or active state (Caplan et al., 1995; Frydman and Hohfeld, 1997).
There is a core minimal complex involved in the folding of steroid hormone
receptors. When activated, the conformational state of the AR may recruit specific
late-stage TPR-containing proteins depending on its trafficking and/or functional
needs (Bukau and Horwich, 1998; Freeman et al., 2000; Jakob and Buchner, 1994).
Competition for the AR between stimulatory factors and inhibitory molecular
chaperones such as p23 (Freeman and Yamamoto, 2002) could influence the rate of
disassembly of the transcription factor complex and, in turn, have an impact on the
receptor’s ability to rebind to the promoter and initiate another round of
transcription.
Altered expression and/or function of molecular chaperones have the
potential of augmenting AR signaling, which would then contribute to prostate
carcinogenesis. One of the main molecular chaperones, Hsp90, is already being
pursued as a potential therapeutic target. However, due to the ubiquitous nature of
this chaperone, the potential for side effects as a result of targeting this protein is
great. To minimize potential toxicities, efforts may need to be focused on
discovering and targeting co-chaperone and chaperone-associated proteins, which
have specific functional effects on the AR, but do not disrupt the signaling pathways
of the other steroid hormone receptors.

36
FIGURE 2.1

Itinerary of the AR with emphasis on molecular chaperones. The diagram
illustrates the involvement of molecular chaperones and co-chaperones within the
different phases of AR regulation and function.

37
CHAPTER 3: αSGT: An Androgen Receptor Co-Chaperone

3.1 Introduction
3.1.1 Tetratricopeptide repeat (TPR)-containing proteins
As discussed in chapter 2, a dynamic molecular chaperone-mediated
maturation cycle maintains nuclear receptors, such as the AR, poised for activation
by ligand binding (Bohen et al., 1995; Pratt and Toft, 1997). While the core proteins
of this cycle sustain the ligand responsiveness of receptors, chaperone-associated
proteins appear to dictate the specific biologic response of steroid receptors. A
subgroup of these co-chaperone proteins contains a degenerate, but functionally
important protein-protein interaction domain known as the tetratricopeptide repeat
(TPR). TPR-containing proteins will often consist of multiple repeats aligned one
right after the other, each forming a pair of antiparallel α-helices. The tandem
arrangement of these α-helical pairs creates an amphipathic groove capable of
binding to structural motifs of partner proteins. Correspondingly, TPR-containing
proteins are commonly found as members of large protein complexes, where they
may serve as adaptor molecules or influence overall protein conformation. Though
functionally unrelated, TPR-containing proteins can generally be classified to the
different complexes involved in four major cellular processes: the regulation of
substrate folding, transcriptional repression, protein transport and in particular the
import of proteins into organelles, and promotion through the cell cycle (Blatch and
Lassle, 1999; Smith, 2004).

38
Several characterized TPR-containing proteins are involved in steroid
receptor function. Hop and Hip utilize their TPR domains to interact with and
regulate Hsp90 and/or Hsp70 during the dynamic folding/refolding cycle (Freeman
et al., 2000; Hohfeld et al., 1995; Pratt et al., 2004), as described in chapter 2. TPR-
containing proteins such as the large molecular weight immunophilins (FKBP51,
FKBP52, CyP40) or protein phosphatase 5 (PP5) are incorporated into Hsp90-steroid
receptor heterocomplexes during the final stages of the assembly cycle. However,
rather than having an effect on folding of the ligand-binding domain, these late-stage
chaperone-associated proteins appear to influence the receptor’s cellular response.
This is supported by the observation that even though TPR-containing proteins are
equally capable of competitively binding to non-receptor bound Hsp90, steroid
receptors exhibit clear preferences for specific TPR-containing proteins, which can
promptly switch upon hormone binding (Pratt and Toft, 1997; Smith, 2004). This
rapid exchange implies an important role in receptor mediated signaling.

3.1.2 Small glutamine-rich TPR-containing protein, alpha (αSGT)
Using the hinge region and signature sequence (aa616-752) of the AR as bait
in a yeast-two-hybrid screen, Dr. Grant Buchanan (from Adelaide University,
Australia) identified a TPR-containing protein, small glutamine-rich tetratricopeptide
repeat-containing protein (αSGT), as a novel AR interacting protein during a visit to
the Coetzee laboratory in 1999. Dr. Buchanan confirmed the AR-αSGT interaction
using co-immunoprecipitation and GST pulldown assays.

39
αSGT is a 313 amino acid phosphoprotein located at chromosomal position
19p13.3 and has been well conserved across species (Cziepluch et al., 1998; Kordes
et al., 1998; Yamagata et al., 2002). Initially identified by its interactions with
nonstructural protein, NS1, of parvovirus H-1 and the Gag and Vpu proteins of
human immunodeficiency virus type 1 (Callahan et al., 1998; Cziepluch et al., 1998),
αSGT has since been found to interact with several different proteins (Fonte et al.,
2002; Handley et al., 2001; Schantl et al., 2003; Tobaben et al., 2001; Wang et al.,
2003; Winnefeld et al., 2006). αSGT has been present in all human tissues tested
thus far and has been observed in both the cytoplasm and nucleus of cells, supporting
a putative role as a housekeeping protein (Cziepluch et al., 1998; Kordes et al.,
1998).
αSGT does not have a clearly defined function. Outside of the TPR domain,
αSGT does not exhibit significant homology to any other known proteins or protein
motifs (Cziepluch et al., 1998). Studies have reported an ATP-dependent interaction
with the constituitively-expressed Hsc70 and stress-inducible Hsp70 (Angeletti et al.,
2002; Liu et al., 1999; Tobaben et al., 2001), which may negatively regulate their
refolding capacity (Wu et al., 2001). Some also report an Hsp90-αSGT interaction
(Tobaben et al., 2001; Yin et al., 2006), whereas others have detected a weak or no
interaction at all (Angeletti et al., 2002; Winnefeld et al., 2006). As Hsp70 and
Hsp90 are major chaperones with a vast number of client proteins including
transcription factors, protein kinases, and other proteins (Pratt and Toft, 2003),
interaction of αSGT with these chaperones does not provide much insight into its

40
function. Interestingly, work by one group has demonstrated a potential role for
αSGT in progression through the cell cycle (Winnefeld et al., 2006; Winnefeld et al.,
2004).
To date, only one late-stage TPR-containing protein, FK506-binding protein
52 (FKBP52), has consistently been reported to interact with AR. FKBP52 appears
to influence the AR through multiple mechanisms, which may be cell type specific.
Nevertheless, regardless of the mechanism FKBP52 appears to promote AR activity
(Cheung-Flynn et al., 2005; Yong et al., 2007). With respect to αSGT, Dr. Buchanan
demonstrated the functional significance of the AR-αSGT interaction using
cotransfection experiments of wildtype AR along with increasing amounts of αSGT
and an AR responsive luciferase reporter. In contrast to the reported effects of
FKBP52, overexpression of αSGT resulted in an overall ligand-dependent decrease
in AR activity. This chapter provides additional supporting evidence for a role of
αSGT in the modulation of AR activity.

3.2 Material and Methods
3.2.1 Cell culture and materials
The human prostate LNCaP (CRL-1740), PC3 (CRL-1435), and DU-145
(HTB-81) cell lines, the African green monkey kidney CV-1 (CCL-70) and COS-7
(CRL-1651) cell lines, and the human breast cancer cell line T-47D (HTB-133) were
obtained from American Type Culture Collection (ATCC; Manassas, VA). The
human ablation-resistant prostate C4-2B cell line was obtained from ViroMed
Laboratories (Minnetonka, MN). The human cell lines were maintained in RPMI

41
1640 supplemented with 5% fetal bovine serum (FBS). COS-7 cells were maintained
in Dulbecco’s modified Eagle’s medium supplemented with 5% FBS and 0.5% L-
glutamine. Ligands: 4-Androstene-3,17-dione (ASD), Cyproterone Acetate (CPA),
Dihydrotestosterone (DHT), Estradiol (E), Medroxyprogesterone 17-acetate (MPA),
and Progesterone (PROG) were purchased from Sigma Chemical Co. (St. Louis,
MO). Methyltrienolone (R1881) was purchased from PerkinElmer, Inc. (Waltham,
MA).

3.2.2 Transactivation assay
PC3 cells seeded at a density of 10,000 cells/well in 96 well plates (6.4 mm
surface area) were grown in phenol red-free RPMI 1640 supplemented with 5%
charcoal-dextran stripped serum (CSS) for 24 hours before transfection. Each well
received 1 ng pcDNA3.1:AR(CAG)
21
and 100 ng of the pGL3:PSA-540 androgen-
responsive luciferase reporter. Cells were also transfected with either pSG5:HA-
αSGT or pSG5:HA and pCAT3-Basic to balance both the molar ratio of the pSG5
vector and total DNA. Cells were transfected with DNA vectors for 3 hours using
Opti-MEM I Reduced Serum media (Invitrogen Corporation, Carlsbad, CA) using
0.4 uL Lipofectamine 2000 Transfection Reagent (Invitrogen Corporation) per
well according to manufacturer’s protocol. DNA treatments were removed prior to
addition of 200 uL of 5% CSS phenol red-free RPMI 1640 containing either 10
-10
to
10
-7
M DHT or ethanol vehicle control for 36 hours. Cells were lysed and assayed
using the Luciferase Assay System (Promega Corporation, Madison, WI) on the
MLX Microtiter Plate Luminometer (Dynex Technologies, Chantilly, VA).

42
3.2.3 siRNA knockdown
C4-2B (1 x 10
5
cells/35mm well) and LNCaP (2 x 10
5
cells/35mm well) cells
were plated and incubated in phenol red-free RPMI 1640 supplemented with 5%
CSS for 3 days prior to transfection. To knockdown αSGT expression, cells were
transfected with an siRNA duplex (100 nmol/L final concentration) directed against
the coding region (sense: 5’- ACU UUG AAG CUG CCG UGC ATT-3’; antisense:
5’-UGC ACG GCA GCU UCA AAG UTT-3’) or the 3’ UTR (sense: 5’-AGC UCG
GUC ACU UGA GUG UTT-3’; antisense: 5’-ACA CUC AAG UGA CCG AGC
UTT-3’) of αSGT using the OligofectAMINE reagent (Invitrogen Corporation),
according to manufacturer’s protocol using 4 uL reagent per dish. A non-specific
siRNA (sense: 5’-AGA UCU GGC UAU CGC GGU ATT-3’; antisense: 5’-UAC
CGC GAU AGC CAG AUC UTT-3’), the sequence of which was given to us by Dr.
Ebrahim Zandi, was transfected as control. After 4 hours of transfection in Opti-
MEM I Reduced Serum media (Invitrogen Corporation), an equal volume of 10%
CSS phenol red-free RPMI 1640 was added for a final serum concentration of 5%.
Cells were grown in the same medium for up to 4 days, as indicated. For dose-
response experiments, after 3 days medium was replaced with 5% CSS phenol red-
free RPMI 1640 containing various ligands at different concentrations as indicated or
ethanol vehicle control for 24 hours. Knockdown experiments were then assessed by
Western or qRT-PCR analysis.

43
3.2.4 Western blot analysis
Cold PBS was used to wash cells before lysis with RIPA buffer (1% NP40,
1% C
24
H
39
NaO
4
, 0.1% SDS, 150 mM NaCl, 10 mM Na
3
PO
4
, 2 mM EDTA pH 8.0,
50 mM NaF) containing a protease inhibitor cocktail (Sigma) and 1 mM PMSF. An
equal volume of sample buffer (62.5 mM Tris-HCl pH 6.7, 10% glycerol, 2% SDS,
.05% bromophenol blue, 50 uL/mL 2-β-mercaptoethanol) was added to each sample
and boiled for 5 minutes. Bio-Rad Protein Assay Dye Reagent (Hercules, CA) was
used to quantitate 5 uL of each extract on the Molecular Devices Microplate reader
(OD at 600) with Softmax 2.35 software (Sunnyvale, CA). Roughly equal amounts
of protein were resolved with 4-20% gradient precast gels using the Ready Gel
System (Bio-Rad). Proteins were transferred onto Hybond-P membrane
(Amersham Biosciences, Piscataway, NJ) and blocked using 5% milk buffer (0.1%
Tween 20, 5% skim milk, 10 mM Tris-HCl, 150 mM NaCl) overnight at 4°C. Blots
were then washed with 1% milk buffer followed by a 1 hour incubation with primary
antibody in 1% milk buffer: rabbit AR-N20 (1:1000; Santa Cruz Biotechnology,
Santa Cruz, CA), rabbit HA (1:200; Santa Cruz Biotechnology), or rabbit αSGT
(1:3000; Zymed Laboratories Inc., San Francisco, CA). Blots were washed 3x with
TBST (0.1% Tween 20, 10 mM Tris-HCl, 150 mM NaCl) before incubation with the
secondary antibody, anti-rabbit IgG-horseradish peroxidase conjugated (1:2000;
Santa Cruz Biotechnology), at room temperature for 1 hour. Blots were washed 3x
with TBST followed by one wash with TBS (10 mM Tris-HCl, 150 mM 150 mM
NaCl) before visualizing by chemiluminescence with Western Blotting Luminol
Reagent (Santa Cruz Biotechnology). Membranes were then stripped of antibody by

44
incubating blots in stripping buffer (2% SDS, 62.5 mM Tris-HCl, 100 mM 2-β-
mercaptoethanol) at 60°C for 30 minutes, vortexing occasionally. Blots were washed
twice with TBST for 10 minutes and then blocked with 5% milk buffer overnight at
4°C. Blots were then reprobed with goat Actin-I19 (1:1000; Santa Cruz
Biotechnology) as the primary antibody, followed by rabbit anti-goat IgG-
horseradish peroxidase conjugated (1:2000; Santa Cruz Biotechnology) as the
secondary antibody. Blots were exposed to X-ray film for various lengths of time or
scanned using the Fluor-S Max Quantification System Imager (Bio-Rad) and
analyzed with The Discovery Series Quantity One software (Bio-Rad).

3.2.5 Quantitative Reverse Transcription-PCR (qRT-PCR)
Purified total cellular RNA was prepared from LNCaP and C4-2B cells using
Promega’s SV Total RNA Isolation System (Promega, Madison, WI) according to
the manufacturer’s protocol, which includes a DNaseI treatment step to eliminate
genomic DNA contamination. TaqMan® Reverse Transcription Reagents (Applied
Biosystems) were used to reverse transcribe 100-600 ng of the isolated RNA with
random hexamer or Oligo-d(T) primers, according to the manufacturer’s protocol.
Quantitative analysis of the PSA enhancer and glyceraldehyde-3-phosphate
dehydrogenase (GAPDH) was performed using AmpliTaq Gold® PCR Master Mix
(Applied Biosystems), primers, and probes as previously described (Jia et al., 2003).
Triplicate PCR reactions were carried out for each sample on the iCycler thermal
cycler (Bio-Rad). Each PCR plate included a 1:5 dilution series of C4-2B cDNA,
which was used to create a standard curve. The relative copy number value of each

45
sample was determined by its location on the standard curve. Results are reported as
the ratio of PSA to GAPDH mRNA. RT-PCR of αSGT (forward: 5’-CCT ACA
GCA AAC TCG GCA AC-3’; reverse: 5’-AAG CCA GGG TTG TTC AGC AG-3’)
and β-actin (forward: 5’-GTG ATG GTG GGC ATG GGT CA-3’; reverse: 5’-ATG
CCG TGC TCG ATG GGG TA-3’) were also used to confirm knockdown of αSGT
within the cDNA material. Conditions were optimized to amplify αSGT and β-actin
within a single 5% DMSO PCR reaction using 30 cycles of the following steps: 94°C
for 1 minute; 59°C for 1 minute; 72°C for 1 minute. Products were resolved on 4%
OmniPur Agarose PCR Plus gels (EMD Chemicals, Inc., Gibbstown, NJ).

3.3 Results
3.3.1 Overexpression of αSGT decreases AR transactivation
Using the AR-negative PC3 cell line (Tilley et al., 1990), Dr. Grant
Buchanan observed a ligand-dependent decrease in the activity of an androgen-
responsive luciferase reporter (ARR3-tk-Luc) upon cotransfection of wildtype AR
and αSGT plasmid (data not shown). To confirm this observation, wildtype AR and
αSGT were transfected into PC3 cells along with the pGL3:PSA-540 androgen-
responsive luciferase reporter. PC3 cells transfected with αSGT in this experiment
displayed about a 3-fold reduction in sensitivity (Figure 3.1). The experiment also
replicated the overall reduction in AR responsiveness in cells overexpressing αSGT.
Notably, the extent to which AR activity was reduced differed by DHT concentration
as expected from the change in affinity. αSGT overexpression resulted in a 57%

46
decrease in AR activity at 10
-10
M DHT, compared to an 18% decrease at 10
-07
M
DHT.

3.3.2 Antibody detects endogenous and transfected αSGT protein
DNA transfection efficiency in PC3 cells using cationic-lipid transfection
reagents is generally low (Iczkowski et al., 2004; Lindholm et al., 2000). To verify
the results shown in Figure 3.1 could be attributed to the successful transfection and
expression of αSGT protein in PC3 cells, antibodies against αSGT were generated
by Zymed Laboratories Inc., which has since been acquired by Invitrogen
Corporation. Zymed Laboratories used a computer algorithm, which incorporated
hydropathic character, secondary structure, peptide location, and regions of
flexibility to suggest a short list of peptides likely to generate high antibody titers, as
well as specificity for cognate proteins. After running a BLAST search, the carboxyl-
terminal peptide, amino acids 296-313 [(C)RSQIRSRTPSASNDDQQE-COOH],
was selected to raise antibodies. The affinity purified antibodies from two rabbits
were obtained from Zymed Laboratories and tested on PC3 protein extracts
transfected with or without pSG5:HA-αSGT (Figure 3.2A).
Using the same amount of protein and antibody concentration (1:3000
dilution of 1.0 mg/mL), the αSGT antibody raised within the second rabbit (anti-
αSGT-2) appeared to yield a stronger signal of both the endogenous αSGT and the
exogenous hemagglutinin (HA) epitope [YPYDVPDYA] tagged αSGT (HA-αSGT)
proteins, with less background than the αSGT antibody raised within the first rabbit

47
(anti-αSGT-1) (Figure 3.2A). The HA epitope tag slightly increases the molecular
weight of the exogenous αSGT protein, which appears to have a molecular weight
around 43 kilodaltons (Kd). HA-αSGT protein present within the pSG5:HA-αSGT
transfected cells is indicated by the top arrow. An antibody directed against the HA
tag (anti-HA) was used to confirm this top band as the transfected HA-αSGT protein.
Specificity of the second rabbit antibody was demonstrated in a competition
experiment using a 5-fold excess by weight of the original peptide (anti-αSGT-2 +
peptide) (Figure 3.2A).
Anti-αSGT-2 antibody has since been used in many subsequent experiments
conducted within the laboratories of Dr. Coetzee and Dr. Tilley, including
immunohistochemical analyses and screening of additional tissue culture cell lines
for endogenous αSGT protein levels. Figure 3.2B demonstrates the abundant
expression of αSGT protein within human prostate cancer, breast cancer, and
monkey kidney-derived cell lines. Due to the slower growth of the T-47D breast
cancer cell line, less protein was loaded onto the gel than protein from the other cell
lines. Once correcting for the amount of protein loaded, αSGT protein expression
was similar among the cell lines.

3.3.3 αSGT-specific siRNA decreases αSGT protein levels
A pitfall of overexpression experiments is the possibility of producing results
that are an artifact of forced protein overexpression, rather than the product of true
biological interactions (Hall et al., 2002). If the observed overexpression effect on

48
AR activity has indeed real physiological merit, we hypothesized that a decrease in
αSGT expression could potentially increase AR activity. To provide support for a
putative role of αSGT in modulating AR activity, siRNA duplexes were designed
against αSGT according to suggested criteria (Elbashir et al., 2001). Knockdown of
αSGT protein levels in PC3 cells was successful (data not shown). However,
numerous attempts of subsequent DNA plasmid transfection into αSGT knockdown
PC3 cells could not generate reproducible results, possibly due to cytotoxicity of two
transfection protocols employed in series (siRNA followed by DNA plasmids). Thus,
the AR-negative PC3 cell line was exchanged for the LNCaP and C4-2B human
prostate cancer cell lines. These cell lines express endogenous AR and an
endogenous reporter of AR activity, the prostate-specific antigen (PSA), which is
routinely used in the lab. Thus, only one transfection (siRNA) is needed to do the
experiment.
LNCaP and C4-2B cells were transfected with an αSGT-specific (αSGT) or
non-specific control (n.s.) siRNA and incubated for the indicated number of days
(Figure 3.3), to determine when the greatest αSGT knockdown occurred. Although
siRNA most likely inhibits expression within several hours, the turnover rate of
αSGT will determine when the protein will be significantly depleted. In both LNCaP
and C4-2B cells, significant knockdown was already apparent after one day.
However, the best knockdown was achieved by 4 days post-transfection, where
protein levels were reduced by 90-95% as compared to controls. The reduction in

49
αSGT protein levels did not have a dramatic effect on endogenous AR protein levels
(Figure 3.3). βactin is shown as a loading and toxicity control.

3.3.4 αSGT knockdown increases AR responsiveness to DHT
Different concentrations of DHT, as indicated, were used to determine
whether a knockdown in αSGT levels would have an effect on AR activity in
LNCaP (Figure 3.4A) and C4-2B (Figure 3.4B) cells. A ratio of PSA to GAPDH
mRNA expression was used as a measure of AR activity. Due to the higher basal AR
activity within C4-2B cells (Jia and Coetzee, 2005), the induction of AR activity
over the basal state in response to androgen is higher among LNCaP cells. However,
qRT-PCR analysis for PSA revealed that a knockdown of αSGT actually resulted in
a greater fold difference in AR responsiveness within C4-2B cells. As expected from
αSGT overexpression (Figure 3.1), the effect of an αSGT knockdown on AR
activity peaked at 10
-10
M DHT. Within C4-2B cells, the knockdown resulted in 3.5-
fold higher PSA expression as compared to the non-specific control, whereas LNCaP
cells exhibited only a 2.6-fold increase in AR activity.
Successful degradation of αSGT mRNA within samples transfected with a
3’UTR-targeted siRNA duplex (αSGT siRNA) as compared to controls (n.s. siRNA)
for the various 24-hour DHT treatments is shown (Figure 3.4, insets). To control for
potential “off-target” effects (Anonymous, 2003), the above experiment was repeated
in C4-2B cells using a different αSGT-specific siRNA duplex designed toward the
coding region of the gene. Results were similar (data not shown).

50
3.3.5 αSGT knockdown increases AR activity in a ligand specific manner
AR is closely related to the glucocorticoid (GR), mineralocorticoid (MR),
and progesterone receptors (PR), not only in sequence homology, but also in their
ability to recognize the same hormone response element of target genes. The AR
ligand-binding domain shares about 50% homology with the ligand-binding domains
of these receptors (Quigley et al., 1995). Yet, in spite of this similarity, this group of
steroid receptors is able to distinguish between closely related 3-keto steroid
structures (Ekena et al., 1998). The molecular basis for this selectivity is a current
topic of interest. In one study, molecular dynamics simulations were found to
provide a fairly accurate model of GR complexed with cortisol, its natural ligand.
However, these simulations also predicted fairly strong GR interactions for
aldosterone and estradiol, even though experimental in vitro data demonstrated much
lower binding affinities (von Langen et al., 2005). Whereas one possibility is that the
GR-ligand model simulations may not be optimal, another is that interacting proteins
may influence the binding specificity of the receptor for cognate ligand in vivo.
To determine whether αSGT potentially influences AR binding affinity for
other ligands, Dr. Buchanan repeated the αSGT overexpression experiments, treating
PC3 cells with various ligands. Compared to DHT treatment, similar decreases in
AR activity were observed in cells treated with the adrenal androgen,
androstenedione (ASD) and the steroidal anti-androgen, medroxyprogesterone
acetate (MPA) (data not shown), which actually also exhibits agonist activity (Bentel
et al., 1999; Kemppainen et al., 1999). However, in cells overexpressing αSGT, AR

51
activity was essentially abolished when treated with the weak AR agonist,
progesterone (PROG) and an AR antagonist, hydroxyflutamide (data not shown).
Knockdown of αSGT had the expected opposite effect on AR activity in
LNCaP cells treated with alternate ligands (Figure 3.5). Treatment of LNCaP cells
with ASD essentially mirrored the effect seen with αSGT overexpression, with a
maximum 3.5-fold difference in AR activity occurring at 10
-8
M ASD (Figure 3.5A).
Suppression of αSGT increased AR responsiveness to treatments with PROG, MPA,
the synthetic androgen methyltrienolone (R1881), the anti-androgen cyproterone
acetate (CPA), and possibly estradiol (E) (Figure 3.5B-F). The greatest fold increase
(8.4) in AR activity between control and αSGT knockdown cells occurred in LNCaP
cells treated with 10
-8
M CPA. In contrast, knockdown of αSGT in C4-2B cells did
not alter the response of AR to treatment with PROG or MPA as compared to control
cells (data not shown).
These results need to be interpreted with caution, as the point mutation within
the LNCaP (and C4-2B) AR-ligand binding domain confers a higher binding affinity
and thus higher induction by non-classical ligands as well as some anti-androgens
(Veldscholte et al., 1992a; Veldscholte et al., 1990a; Veldscholte et al., 1990b).
However, overall the data suggest αSGT modulates ligand-dependent AR activation
in the presence of low concentrations of steroids, while also making the AR much
more specific for physiological androgens.

52
3.4 Discussion
3.4.1 αSGT modulates AR function
Upon hormone binding, the earliest alteration detected thus far appears to be
a rapid exchange in the TPR-containing protein associated with Hsp90-receptor
heterocomplex (Davies et al., 2002; Smith, 2004). This observation, along with the
selectivity exhibited by nuclear receptors for TPR-containing proteins, suggests these
proteins may be involved in guiding biological responses to environmental cues. Dr.
Buchanan had isolated αSGT as a novel AR interacting protein. The overexpression
results shown here demonstrate an influence on AR activity; increased αSGT
expression significantly inhibited AR transactivation activity. In line with an
inhibitory role for αSGT on AR activity, αSGT knockdown experiments
demonstrated increased endogenous expression of the AR-regulated PSA gene. The
observed increase in activity was not the result of increased AR protein levels.
Together the data indicate αSGT assists in making the AR much more specific for
physiological androgens. The clinical implications of this are discussed below.

3.4.2 Potential function of αSGT
Additional interesting observations may indicate how αSGT exerts its effect
on the AR (Buchanan et al, manuscript in preparation). In a co-immunoprecipitation
experiment, it was noted that αSGT interacts with the AR in a ligand-dependent
manner and that the interaction occurred only in the absence, not presence of DHT.
Secondly, confocal immunofluorescence data demonstrated that in untreated PC3

53
cells transfected with AR, the receptor was predominantly cytoplasmic in the
absence of ligand. The weak diffuse nuclear staining of AR in the majority of cells
was eliminated by coexpression of αSGT. Treatment with a saturating concentration
of DHT (10
-9
M) resulted in the nuclear localization of AR in either the absence or
presence of exogenous αSGT. However, at a lower concentration of ligand (10
-10
M
DHT), the distribution of AR was shifted from the nucleus to the cytoplasm in the
presence of exogenous αSGT. Merged images clearly show that AR and αSGT co-
localize in the cytoplasm at 10
-10
M DHT treatment, but at 10
-9
M DHT AR
translocated into the nucleus, while αSGT remained cytoplasmic.
One potential mechanism by which αSGT retains AR in cytoplasm may be
through anchoring the Hsp90-AR heterocomplex to or near the cytoskeleton. Then
only upon sufficient stimulation with the proper ligand is αSGT exchanged for a
TPR-containing protein that would direct translocation of the AR into the nucleus.
Such an idea is supported by a few pieces of information. First, the region used to
identify αSGT as an AR-interacting protein includes the AR nuclear localization
signal (AR-NLS: aa617-633) (Saporita et al., 2003). This motif has previously been
shown to interact with TPR-containing cochaperones (Owens-Grillo et al., 1996). By
interacting with the AR-NLS, αSGT may competitively inhibit the binding of a
TPR-containing protein, which may be responsible for shuttling the AR into the
nucleus.
Secondly, αSGT has also been found to collocalize with microtubules
(Handley et al., 2001; Winnefeld et al., 2004). Tethering of the Hsp90-AR

54
heterocomplex to the microtubules would prevent nuclear translocation of the
receptor. However, interaction of αSGT with the cytoskeleton is believed to be weak
or indirect (Handley et al., 2001). An additional consideration to keep in mind is that
microtubules serve as the superhighway of cell (Radtke et al., 2006). Tethering
complexes directly to microtubules would effectively cause a cellular traffic jam.
Instead, αSGT could possibly interact with proteins that are closely associated with
the microtubule network. The association of αSGT with multiprotein complexes,
such as the Hsp90-AR heterocomplex, may inhibit the proper assembly of “cargo”
for transport (Handley et al., 2001; Tobaben et al., 2001). Nevertheless, the
localization of αSGT-associated complexes in the vicinity of microtubules would
facilitate a rapid response upon proper stimulation.
αSGT has been shown to interact with a diverse range of proteins (Figure
3.6). Furthermore, recent yeast-2-hybrid screens have identified additional putative
interacting partner proteins for αSGT, none of which seem to be related (Rual et al.,
2005; Stelzl et al., 2005). It remains possible that αSGT exhibits different functional
activities for each of these protein partners. However, a more likely explanation is
that αSGT serves a more general housekeeping role, possibly as an adaptor protein
of inhibitory complexes. Moreover, both overexpression (Wang et al., 2005) and
knockdown of αSGT (Winnefeld et al., 2006; Winnefeld et al., 2004) expression has
been associated with apoptosis. This may suggest a stochiometric balance between
αSGT and interacting proteins is required for the proper formation of multiprotein
complexes.

55
3.4.3 Clinical relevance
Overexpression and knockdown studies of αSGT represent extreme changes
in protein levels, not to mention the stress caused by transfection of cells in an in
vitro setting may contribute to the apoptotic response. Additionally, these effects
may be cell type specific. Though αSGT has been reported as ubiquitously expressed
in all tissues tested thus far, immunohistochemistry of non-malignant human prostate
tissue by Carmela Ricciardelli of the laboratory of Dr. Wayne Tilley revealed a lack
of αSGT protein within prostatic stroma as compared to the surrounding prostate
epithelium (data not shown). Given that cancerous prostate epithelia seems to
acquire a more stromal-like phenotype with disease progression (Gao et al., 2001),
the necessity of αSGT for cell survival may be reduced. Therefore, it would be
advantageous for cells to decrease αSGT expression, as the increased AR to αSGT
ratio would allow for increased AR signaling at subphysiologic levels of androgen,
which is experienced during androgen-ablation therapy for prostate cancer.
Additionally, the loss of αSGT would allow non-classical ligands to stimulate the
AR even in the absence of receptor mutations, such as the one found in the ligand
binding domain of the LNCaP AR. Immunostaining of primary prostate cancer and
metastatic prostate samples suggests such a mechanism may occur, as the mean
immunoreactivity of αSGT appeared to decrease with progression, while mean AR
immunoreactivity increased.

56
FIGURE 3.1

αSGT overexpression inhibits AR activity. PC3 cells (1x10
4
cells/6.4 mm well)
were transfected with 1ng wildtype AR, 100 ng of an androgen-responsive luciferase
reporter, and either 50 ng of HA-αSGT (broken line, open squares) or the
corresponding empty vector construct along with a eukaryotic promoterless DNA
construct (solid line, filled in squares) to balance both the molar ratio of the pSG5
vector and total DNA. Transfected cells were incubated in phenol red-free RPMI
1640 supplemented with 5% CSS containing either ethanol vehicle control (0) or 10
-
10
to 10
-7
M DHT for 36 hours. Results represent the mean (+ standard error of the
mean; SEM) relative luciferase units of 8 determinations.

57
FIGURE 3.2

Antibody detects transfected and endogenous αSGT protein. A. PC3 cells
transfected with 50 ng of HA-αSGT or empty vector constructs were harvested as
described in Materials and Methods. Proteins were resolved on 4-20% gradient
precast gels and incubated with various primary antibodies, as indicated. Arrows
indicate the endogenous and transfected αSGT protein. Binding of anti-αSGT-2 was
competed with a 5-fold excess by weight of the original peptide antigen. Kd,
molecular weight measured in kilodaltons. B. Western blot analysis of endogenous
αSGT using anti-αSGT-2 in human prostate cancer (PC3, DU-145, LNCaP), human
breast cancer (T-47D), and African monkey kidney (CV-1, COS-7) cell lines.

58
FIGURE 3.3

αSGT-specific siRNA reduces endogenous αSGT protein levels. LNCaP (2 x 10
5

cells/35mm well) and C4-2B (1 x 10
5
cells/35mm well) cells were transfected with
100 nM αSGT-specific (αSGT) targeting the 3’UTR or non-specific control (n.s.)
siRNA for 1-4 days, as indicated. Western blot analysis indicates the relative levels
of αSGT, AR, and βactin within these samples.

59
FIGURE 3.4 LEGEND

Knockdown of αSGT increases DHT-mediated PSA expression. LNCaP (2 x 10
5

cells/35mm well) (A) and C4-2B (1 x 10
5
cells/35mm well) (B) cells were
transfected with 100 nM αSGT-specific (αSGT siRNA; solid line, filled in squares)
targeting the 3’UTR or non-specific control (n.s. siRNA; broken line, open squares)
siRNA for 3 days and then incubated in phenol red-free RPMI 1640 supplemented
with 5% CSS containing either ethanol vehicle control (0) or 10
-13
to 10
-8
M DHT for
24 hours. qRT-PCR analysis measured PSA and GAPDH mRNA expression within
each sample. Each data point represents the fold difference in the PSA:GAPDH ratio
of the DHT treated cells as compared to the PSA:GAPDH vehicle control reference,
which was set to a value of 1. Error bars represent the SEM of 6 qRT-PCR
determinations. RT-PCR products of αSGT and βactin were resolved on 4% agarose
gels to confirm the knockdown of αSGT within these samples (insets). Numbers
within the inset refer to ethanol vehicle control (0) or the various concentrations of
DHT (10
-13
to 10
-8
M). M, DNA size ladder. N, no template control.

60
FIGURE 3.4

61
FIGURE 3.5 LEGEND

Knockdown of αSGT increases AR activity in response to non-classical ligands.
qRT-PCR of PSA and GAPDH expression was measured and analyzed in LNCaP
αSGT knockdown experiments essentially as described in Figure 3.4. Instead of
DHT, cells were treated with androstenedione (ASD; A), progesterone (P; B),
estradiol (E; C), methyltrienolone (R1881; D), medroxyprogesterone acetate (MPA;
E), and cyproterone acetate (CPA; F) at the various concentrations indicated. Error
bars for PROG and MPA represent the SEM of 6 qRT-PCR determinations, whereas
the error bars for the other treatments represent the standard deviation of 3 qRT-PCR
determinations.

62
FIGURE 3.5

63
FIGURE 3.6

αSGT interacts with a wide range of proteins. αSGT has been reported to interact
and influence the activity of a diverse set of proteins, many of which are unrelated.
Arrows denote protein-protein interactions.

64
CHAPTER 4: Repressed Genes Identified in a Screen for Androgen
Receptor Occupancy Regions in Prostate Cancer

A manuscript based on the repression data within this chapter was recently accepted
for publication in The Prostate.
4.1 Introduction
The androgen receptor (AR) plays a pivotal role in normal prostate
development, as well as all stages of prostate cancer (PCa), by regulating cell
proliferation, differentiation, and apoptosis (Kozlowski et al., 1991; Nelson et al.,
2002; Santos et al., 2004; Xu et al., 2001). Early prostate tumors are highly
dependent on androgens, and are therefore effectively treated by hormone ablation
therapy (Kozlowski et al., 1991; Santos et al., 2004). However, after a period of
some time, the disease recurs as an ablation-resistant PCa, often termed hormone-
refractory, androgen-independent, or castrate-resistant (Balk, 2002; Buchanan et al.,
2001b; Debes and Tindall, 2004; Feldman and Feldman, 2001). Ablation-resistant
PCa develops as a result of a selection pressure for cells in which AR signaling has
reemerged within the hypoandrogenic environment, either through amplification or
mutation of the AR, an increase in AR coactivators, cross-talk with other signaling
pathways (Buchanan et al., 2001b), or by AR-mediated chromatin remodeling of AR
target genes (Jia et al., 2006). Persistent AR signaling associated with disease
progression, in turn, aberrantly regulates genes involved in a variety of cellular
processes (Holzbeierlein et al., 2004). Consequently, increased expression of AR
target genes, such as prostate-specific antigen (PSA), which is otherwise strongly
dependent on intact androgen biosynthesis, is not only a clinical marker for disease

65
initiation, but also for disease recurrence in castrated patients (Balk, 2002; Buchanan
et al., 2001b; Debes and Tindall, 2004; Feldman and Feldman, 2001). However, not
only increased expression of AR targets, but also repression of genes is evident from
the literature (see below). How these genes influence the etiology of PCa progression
and the mechanisms of AR-modulation of specific gene expression are unknown.

4.1.1 Methods for AR target gene identification
4.1.1.1 Expression-based methods
Given that the AR is necessary throughout all stages of PCa, there is
continued interest in identifying direct AR target genes in an effort to gain further
insight into the transcriptional regulatory networks underlying the initiation and
progression of PCa (Burnstein, 2005; Nantermet et al., 2004). Compared to the
thousands of functional androgen response elements (AREs) estimated to reside
within the human genome (Horie-Inoue et al., 2004), there are still relatively few
known direct AR-regulated genes (Bai et al., 1998; Balbin and Lopez-Otin, 1996;
Bao et al., 2006; Cheng et al., 2003; Clay et al., 1993; Cleutjens et al., 1997;
Cleutjens et al., 1996; Crossley et al., 1992; Curtin et al., 2001; Dai and Burnstein,
1996; Gavrielides et al., 2006; Gnanapragasam et al., 2002; Grad et al., 2001;
Haelens et al., 2001; Haendler et al., 2001; Heckert et al., 1997; Heemers et al.,
2004; Huang et al., 1999; Jain et al., 2002; Jave-Suarez et al., 2004; Jeong et al.,
2006; Jorgensen and Nilson, 2001a; Jorgensen and Nilson, 2001b; Lu et al., 1999;
Magee et al., 2006; Masuda et al., 2005; Moilanen et al., 2006; Murtha et al., 1993;
Phan et al., 2001; Riegman et al., 1991; Rokhlin et al., 2005; Salah et al., 2005;

66
Schneikert et al., 1996; Zhang et al., 1997; Zheng et al., 2006). Although, the number
of experimentally verified targets has grown in recent years. Additionally, various
expression-based studies involving oligonucleotide or cDNA microarray, expressed
sequence tag (EST) quantitation, and serial analysis of gene expression (SAGE) have
been conducted lately in an attempt to identify a comprehensive list of androgen-
regulated genes (Clegg et al., 2002; DePrimo et al., 2002; Holzbeierlein et al., 2004;
Nelson et al., 2002; Velasco et al., 2004; Xu et al., 2001) (reviewed in Dehm, 2006
#152}). Together, over one thousand androgen-regulated genes have been
discovered, with surprisingly little overlap between studies (Velasco et al., 2004).
However, in the absence of computational analyses for transcription factor binding
sites and experimental verification, these methods do not distinguish between genes
that are directly regulated by the AR and those indirectly regulated as a result of
regulatory cascades or physiological responses such as oxidative stress (DePrimo et
al., 2002).
To distinguish between direct and indirect AR targets, some of these studies
have utilized in silico prediction methods to identify putative AREs within the 5’
regulatory regions in a subset of the newly identified genes (Holzbeierlein et al.,
2004; Nelson et al., 2002). Still, not even every consensus ARE (5’-
AGAACAnnnTGTTCT-3’) (Nelson et al., 2002) is bound by the AR in vivo (Horie-
Inoue et al., 2004), whereas some functional AREs poorly resemble the consensus
sequence (Dai and Burnstein, 1996). As well, if the unbiased mapping of
transcription factor binding sites on chromosomes 21 and 22 are any indication, only
about one-quarter of transcription factor binding sites occur within 5-kb of the 5’

67
most exon (Cawley et al., 2004; Martone et al., 2003). By narrowing the search for
putative AREs to the promoter region, the majority of AR-binding sites would
probably be overlooked, resulting in the misclassification of many androgen-
regulated genes as indirect targets.

4.1.1.2 Location analysis methods
Several location analysis methods have been developed to ascertain
functional in vivo protein-DNA interactions as a means of distinguishing direct
transcription factor target genes. Other than DamID, which requires the introduction
of a fusion protein between the transcription factor of interest and the Escherichia
coli DNA adenine methyltransferase (Dam) into cells (van Steensel and Henikoff,
2000), location analyses are generally conducted using ChIP-based methods for
endogenous proteins. The utility of ChIP DNA material hybridized to DNA
microarray chips (ChIP-on-chip) was initially limited to small genomes, such as the
yeast genome, or selected regions of the human genome, such as core promoter
sequences, CpG islands, or specific human chromosomes (Boyer et al., 2005;
Cawley et al., 2004; Horak and Snyder, 2002; Martone et al., 2003; Ren et al., 2000).
More recently, a genome-wide analysis of estrogen receptor (ER) binding sites was
successfully completed utilizing ChIP-on-chip (Carroll et al., 2006). Nonetheless,
encompassing the nonrepetitive regions of the human genome still requires several
microarray chips, making such a comprehensive project extremely expensive.
Several other techniques have been developed, which essentially combine ChIP
DNA with SAGE or a SAGE-derived analysis. These have been termed genome-

68
wide mapping technique (GMAT) (Roh et al., 2004), serial analysis of chromatin
occupancy (SACO) (Impey et al., 2004), sequence tag analysis of genomic
enrichment (STAGE) (Kim et al., 2005a), serial analysis of binding elements
(SABE) (Chen and Sadowski, 2005), and ChIP followed by paired end ditag (ChIP-
PET) (Wei et al., 2006). Analysis of digital expression profiles is computationally
intensive and may suffer from errors in statistical predictions. Additionally, these
methods are not capable of discriminating differential expression among low
abundance transcripts (Clegg et al., 2002).
ChIP Display (CD) is yet another ChIP-based location analysis (Barski and
Frenkel, 2004), which was developed by Dr. Artem Barski while a student in
laboratory of Dr. Baruch Frenkel (Institute of Genetic Medicine, USC). Though not
comprehensive, the method is economically feasible by using basic molecular
biology techniques, relatively insensitive to the high non-specific ChIP background,
and visually reveals more intense signals for regions that are highly occupied by the
transcription factor (Barski and Frenkel, 2004). In the present study, CD was utilized
to identify novel androgen receptor genomic binding regions in an unbiased manner.
Examination of genes within the vicinity of these AR-binding regions uncovered
several gene expression changes upon treatment with 5α-dihydrotestosterone (DHT).
In addition to upregulated targets, a few androgen-regulated genes were repressed
upon DHT treatment.

69
4.1.2 Transcriptional Repression
Stimulation of gene expression is only one aspect of AR signaling.
Representing a substantial proportion of androgen-responsive genes (Holzbeierlein et
al., 2004; Nelson et al., 2002; Velasco et al., 2004; Xu et al., 2001), repressed genes
also appear to play important roles in regulating cell growth (Bai et al., 1998),
differentiation (Bellido et al., 1995; Leppa et al., 1991), survival (Caccamo et al.,
2003; Rokhlin et al., 2005), and migration (Schneikert et al., 1996; Zhang et al.,
1997), as well as the androgen signaling axis itself (Heckert et al., 1997; Jorgensen
and Nilson, 2001b). The expression of androgen-repressed genes upon ablation
therapy is thought to contribute to disease regression (Leger et al., 1987). With the
reemergence of AR signaling in advanced, ablation-resistant disease, these genes
may be repressed once again. Yet, despite the importance of repressed genes, most
studies have focused on the transcriptionally activated targets (Subramaniam et al.,
1997), particularly PSA (Lee and Chang, 2003). Additionally, work on gene
repression in the context of AR signaling have dealt with mechanisms that
antagonize the positive action of AR on upregulated target genes (Agoulnik et al.,
2003; Balk, 2002; Burd et al., 2006; Mu and Chang, 2003). Relatively little attention
has been paid to bona fide AR-mediated gene repression.
Diverse mechanisms of transcriptional repression have been proposed for
eukaryotic genes (Levine and Manley, 1989). Most studies of transcriptional
repression by nuclear hormone receptors have focused on the nonsteroidal, class II
receptors such as the thyroid and retinoid hormone receptors. In the absence of
ligand, these receptors bind constitutively to their respective response elements to

70
mediate strong active repression, a mechanism which entails the formation of a
corepressor complex consisting of corepressors (e.g. NCoR, SMRT) and histone
modifiers (e.g. HDACs). Corepressors competitively inhibit coactivator recruitment,
whereas histone deacetylases configure chromatin into a condensed state, limiting
DNA accessibility to the basal transcriptional machinery and consequently result in
transcriptional repression (Glass and Rosenfeld, 2000; Nagy et al., 1999; Zhang and
Lazar, 2000). Active repression via the recruitment of corepressor complexes has
been observed for the steroidal, class I receptors such as ER and AR. Although this
has mainly been examined in the setting of antagonist-mediated repression (Hodgson
et al., 2005; Jackson et al., 1997; Lavinsky et al., 1998; Yoon and Wong, 2006),
recent evidence suggest that ligand-activated ER (Carroll et al., 2006) and AR
(Hodgson et al., 2005; Yoon and Wong, 2006) do engage in active repression in a
context-dependent manner.
Other studies on negatively regulated AR target genes provoke a mechanism
of repression through physical interference with other transcription factors at their
cognate promoter elements (Bai et al., 1998; Heckert et al., 1997; Jorgensen and
Nilson, 2001a; Jorgensen and Nilson, 2001b; Schneikert et al., 1996). Alternate
mechanisms include squelching, competition for binding sites, and interference with
transcription factors (Levine and Manley, 1989). However, given the scarcity of our
knowledge of AR-repressed genes, other potential repression mechanisms likely
remain elusive. Moreover, the investigation of AR-mediated transcriptional
regulation has focused mainly on proximal 5’-flanking regulatory sequences,
overlooking genes that may be repressed via AR binding to sites further upstream, or

71
even downstream of the transcription start site (Carroll et al., 2006; Cawley et al.,
2004).
This chapter presents data on the discovery of androgen-regulated genes in
the vicinity of novel AR-binding regions within the C4-2B cell line. Additional
experiments focus on target genes repressed by androgen treatment: KIAA1217,
mucin 6 (MUC6), cholinergic receptor, muscarinic 1 (CHRM1), and Williams-
Beuren syndrome chromosome region 28 (WBSCR28).

4.2 Material and Methods
4.2.1 Cell culture and Materials
C4-2B, an ablation-resistant cell line derived from the LNCaP human PCa cell line
(Thalmann et al., 1994), was obtained from ViroMed Laboratories (Minnetonka,
MN). The LNCaP (CRL-1740) cell line was obtained from American Type Culture
Collection (ATCC, Manassas, VA). Both cell lines were maintained in RPMI 1640
supplemented with 5% fetal bovine serum. Dihydrotestosterone (DHT) was
purchased from Sigma Chemical Co. (St. Louis, MO) and bicalutamide (BIC) was
obtained from AstraZeneca (Wilmington, DE).

4.2.2 Chromatin Immunoprecipitation (ChIP)
AR ChIP assays were performed by Dr. Li Jia in the laboratory of Dr.
Gerhard A. Coetzee as previously described (Jia et al., 2003). The salmon sperm pre-
clearance step was omitted for ChIP material intended for ChIP Display. Briefly, C4-
2B (3 x 10
6
cells/150mm dish) and LNCaP cells (6 x 10
6
cells/150mm dish) were

72
plated and grown in phenol red-free RPMI 1640 supplemented with 5% charcoal
dextran-stripped serum for 3 days. Cells were then treated with 10 nM DHT for 4
hours, after which cells were cross-linked using 1% formaldehyde for 10 minutes.
Chromatin fragmentation by sonication with the Fisher Sonic Dismembrator Model
60 (Tustin, CA) was followed by an overnight incubation at 4°C with the androgen
receptor NH
2
-terminal (N20) antibody (Santa Cruz Biotechnology, Santa Cruz, CA).
Primers used for locus-specific ChIP assays are listed in Table 4.1B.

4.2.3 ChIP Display (CD)
ChIP Display identified regions occupied by the AR essentially as previously
described (Barski and Frenkel, 2004). Briefly, C4-2B cells were treated with 10 nM
DHT for 4 hours before harvesting AR ChIP or IgG control ChIP DNA, as described
above. Dr. Artem Barski processed approximately one-fifth of each ChIP DNA in a
series of steps. ChIP DNA was dephosphorylated using shrimp alkaline phosphatase
(New England Biolabs, Ipswich, MA) and digested with the AvaII restriction enzyme
(New England Biolabs), which recognizes the 5 bp sequence GGA/TCC as the
restriction site. The AvaII DNA fragments were then ligated to linkers and amplified
by ligation-mediated PCR using nested primers (Table 4.1A). Each nested primer
had either an A or T at the +3 position of the AvaII site, and an A, T, G, or C
immediately after the AvaII site, the so-called +6 position, which was also the last
nucleotide at the 3’ end of the primer. The nested primers are named according to the
nucleotides occupying these two positions. For example, the ‘AG’ nested primer has
an ‘A’ at the +3 position and a ‘G’ at the +6 position. A total of 36 primer pairs were

73
possible with the 8 nested primers. At the beginning of the project the primer pairs
were split equally among myself (primer pairs: AA/AA, AA/AT, AA/AG, AA/AC,
AA/TA, AA/TT, AA/TG, AA/TC, AT/AT, AT/AG, AT/AC, AT/TA), and 2
members of Dr. Frenkel’s laboratory, Unnati Jariwala (primer pairs: AT/TT, AT/TG,
AT/TC, AG/AG, AG/AC, AG/TA, AG/TT, AG/TG, AC/AC, AC/TA, AC/TT,
TA/TA) and Jon P. Cogan (primer pairs: AG/TC, AC/TG, AC/TC, TA/TT, TA/TG,
TA/TC, TT/TT, TT/TG, TT/TC, TG/TG, TG/TC, TC/TC). For a short period of time
Armin Arasheben, a medical student volunteering in Dr. Frenkel’s lab, also provided
some assistance in the identification of putative AR targets.
Using these primer combinations, each processed ChIP DNA was PCR
amplified using 46 cycles of the following steps: 95°C for 45 seconds; 69°C for 45
seconds; 72°C for 1 minute 30 seconds. The PCR products of 3 independent AR
ChIP and 3 control ChIP samples were resolved by 8% polyacrylamide gel
electrophoresis (PAGE) and stained with ethidium bromide. DNA from bands
enriched in the AR ChIPs as compared to control ChIPs were excised, reamplified,
digested with each of HaeIII, HinfI, and MspI restriction enzymes (New England
Biolabs), and resolved on 2% agarose gels. Products of the secondary digestion were
extracted and sequenced on the ABI 3100 Genetic Analyzer (Applied Biosystems,
Foster City, CA) following a sequencing reaction using the BigDye Terminator
v3.1 Cycle Sequencing kit (Applied Biosystems). Sequences were then mapped onto
the human genome using the BLASTN tool on the Ensembl web server
(www.ensembl.org). The DNA fragment and the surrounding sequences were
analyzed for the presence of AvaII, HaeIII, HinfI, and MspI restriction sites at the

74
expected locations, the presence of evolutionarily conserved regions, putative AREs
within 500-bp on either side of the fragment (the expected fragment size obtained by
the sonication step of the ChIP protocol), and for exclusion from repetitive
sequences. For the identification of putative AREs we used the public web server
ConSite (mordor.cgb.ki.se/cgi-bin/CONSITE/consite), with a transcription factor
score cutoff of at least 75%.

4.2.4 Quantitative Reverse Transcription-PCR (qRT-PCR)
Purified total cellular RNA was prepared from LNCaP and C4-2B cells using
Promega’s SV Total RNA Isolation System (Promega, Madison, WI) according to
the manufacturer’s protocol, which includes a DNaseI treatment step to eliminate
genomic DNA contamination. The integrity of denatured RNA (Gel Loading Buffer
II; Ambion Inc., Austin, TX) was evaluated on a 1% agarose gel prior to reverse
transcription. TaqMan® Reverse Transcription Reagents (Applied Biosystems) were
used to reverse transcribe 200-1500 ng of the isolated RNA with random hexamer
primers, according to the manufacturer’s protocol. A reaction without reverse
transcriptase (RT) was included as an additional control. Quantitative analysis of the
PSA enhancer and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was
performed using AmpliTaq Gold® PCR Master Mix (Applied Biosystems), primers,
and probes as previously described (Jia et al., 2003). Gene-specific primers and iQ™
SYBR® Green Supermix from Bio-Rad (Hercules, CA) were used to quantitatively
analyze the expression of our genes of interest and 18S (Table 4.1C). Triplicate PCR
reactions were carried out for each sample on either the iCycler thermal cycler (Bio-

75
Rad) or the DNA Engine OPTICON (MJ Research Inc., Waltham, MA). Each PCR
plate included a 1:5 dilution series of C4-2B cDNA, which was used to create a
standard curve. The relative copy number value of each sample was determined by
its location on the standard curve. Results were normalized by taking the ratio of the
gene of interest mRNA to either GAPDH mRNA or 18S RNA.

4.2.5 Expression in clinical PCa samples
Drs. William L. Gerald and Howard I. Scher (Memorial Sloan-Kettering
Cancer Center, New York, NY) granted Dr. Grant Buchanan of the laboratory of Dr.
Gerhard A. Coetzee access to expression microarray data of clinical prostate cancer
samples. The data were used to examine the expression of genes identified by our
CD screen. The details of the study have been published elsewhere (Holzbeierlein et
al., 2004). Briefly, 40 clinical tumor specimens were isolated during radical
prostatectomy from patients with primary prostate cancer. Twenty-three of the
primary tumors were obtained from patients who had not received therapy before
surgery, whereas the remaining 17 tumors were from patients that had received 3
months of androgen-ablation therapy (AAT; 3.6mg of goserelin monthly plus
750mg/day of flutamide) prior to surgery. An additional 7 AR-positive metastatic
prostate cancer lesions were also obtained. All tissues were acquired during routine
clinical management at the Memorial Sloan-Kettering Cancer Center, under
protocols approved by the Institutional Review Board. After careful manual
microdissection from frozen tissue blocks, samples contained ~60-80% prostate
cancer cell nuclei. RNA was extracted and purified from homogenized tissues,

76
synthesized into complementary DNA, and then analyzed using the Affymetrix
(Santa Clara, CA) Human Genome U95 A-E GeneChip Array set. Dr. Grant
Buchanan, currently a postdoc in the laboratory of Dr. Coetzee, compiled the data for
our genes of interest and generated a heat-map using ‘Heatmap Builder’ (Stanford
University) to display the results, with data routed to 50 equal gates for each probeset
(row) using a linear gray scale gradient from white (lowest value) to black (highest
value).

4.2.6 siRNA Transfection
C4-2B cells (3 x 10
5
cells/60mm dish) were plated and incubated in phenol
red-free RPMI 1640 supplemented with 5% charcoal dextran-stripped serum for 2
days prior to transfection. To knockdown AR expression, cells were transfected with
an siRNA duplex (100 nmol/L final concentration) directed against the AR coding
region using the OligofectAMINE reagent (Invitrogen Corp., Carlsbad, CA),
according to manufacturer’s protocol using 10 uL reagent per dish. A non-specific
siRNA was transfected as control (Table 4.1D). After transfection, cells were grown
in the same medium for an additional 3 days. Medium was then supplemented with
10 nM DHT or ethanol vehicle control for 24 hours before qRT-PCR analysis.

4.3 Results
4.3.1 ChIP Display reveals novel AR targets in C4-2B PCa cells
To ascertain genes, which are potentially aberrantly regulated by AR
signaling during the late stages of PCa progression, we employed AR ChIP Display

77
(CD) (Barski and Frenkel, 2004) in the C4-2B PCa cell culture model. In
collaboration with Dr. Li Jia (Coetzee lab), three independent AR and control IgG
ChIP assays were performed in C4-2B cells treated with 10 nM DHT for 4 hours.
Samples were processed according to the CD protocol (as described in Materials and
Methods). Some troubleshooting was initially required, as after a period of time, the
amplified ChIP material produced very faint bands (data not shown). Testing of the
individual variables within a PCR reaction revealed that the concentration of ChIP
samples needed to be diluted before proceeding with CD. Based on the standard
curve-derived quantitative real-time RT-PCR copy number for the PSA enhancer
region (ARE III), each AR ChIP sample was diluted to PSA copy numbers of 40 or
160. IgG ChIPs were diluted according to its paired AR ChIP. Rather than using two
different annealing temperatures, subsequent PCR reactions were carried out using
these two ChIP DNA dilutions before resolution on an 8% PAGE.
Figure 4.1A displays an example of a novel AR-bound genomic fragment
disclosed by the amplification of the ‘AT’ and ‘AG’ primer pair. The arrowhead
indicates DNA fragments enriched in each of the AR ChIP lanes, but in only one of
the non-specific IgG control ChIP lanes. Representing a putative AR target, this band
was excised from the gel, re-amplified, and subjected to secondary digestion with
each of HaeIII, HinfI, and MspI restriction enzymes. A comparison of the digested
CD bands revealed similar digestion patterns demonstrating that the comigrating
bands on the original CD gel contained the same DNA fragment (Figure 4.1B).
Digested products of equivalent size in the MspI restriction digest lanes (arrowheads)
were excised, sequenced, and mapped onto the human genome. Figure 4.1C is a

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schematic diagram illustrating the location to which the sequenced fragment from
Figure 4.1A was mapped. The sequence mapped to an AvaII fragment at position
72,922,165-72,922,474 (ENSEMBL, release 42) on chromosome 7q11.23. This
putative AR-binding region is 4.3-kb downstream of the 3’ end of the nearest
annotated gene, WBSCR28 (NM_182504.2). The AvaII fragment identified by CD
(black box, marked ‘hit’) lies within an area of evolutionary conservation (black
peaks), falls outside of repetitive regions (gray boxes), and is displayed in relation to
putative AREs (white triangle). One ARE is within the AvaII fragment itself. The
transcription start site (TSS; arrow) and exons (black boxes, top line) of the putative
gene are indicated. Locus-specific primers for the chromosome 7q11.23 region were
used to verify AR occupancy at this site within the original ChIP material (Figure
4.1D). An additional 3 independent AR and IgG control ChIP experiments in C4-2B
cells, which had not been used for the identification of CD hits, were conducted for
further verification of AR occupancy at this and other loci (Table 4.2). PSA and a
non-targeted region are included as positive and negative controls, respectively
(Figure 4.1D).

4.3.2 ChIP Display discloses 19 novel AR binding sites
Together, our group discovered a total of 19 unique confirmed AR binding
regions using the 36 nested primer pair combinations (Table 4.2). Contrary to the
traditional view of gene regulatory elements, only 3 of the 19 AR-occupied regions
identified were within 5-kb upstream of the 5’ end of annotated genes. In relation to
the nearest gene (bolded; Table 4.2), most AR occupied sites were found to be

79
intragenic (8 out of 19). Though, some hits were also located within 5-kb
downstream of the 3’ end of the nearest gene (3 out of 19) or within intergenic
regions (5 out of 19). Four of the intergenic AR binding sites identified were in gene
desert regions where the nearest annotated gene was at least 197-kb away.
During malignant transformation of epithelial cells from normal to prostatic
disease, cells transition from stroma-dependent paracrine signaling to stroma-
independent autocrine signaling in response to androgens. Presumably, this occurs
when the epithelial AR obtains the ability to bind to and stimulate growth factor
expression, which may or may not be the same as those expressed within normal
stroma (Gao et al., 2001). We hypothesized a similar phenomenon may occur, where
novel AR gene targets may arise during the transition from androgen-dependent to
ablation-resistant prostate cancer. The C4-2B prostate cancer cell line is an ablation-
resistant derivative of the androgen-dependent parental LNCaP cell line. Together,
the two cell lines represent a model for the study of the molecular mechanisms of
prostate cancer progression to ablation-resistant disease (Thalmann et al., 1994). To
determine whether the AR regions we identified were specifically targeted in
ablation-resistant prostate cancer, we conducted conventional ChIP assays with
locus-specific primers for our hits in 3 independent AR and IgG control ChIP
experiments using LNCaP cells. Contrary to what we expected, almost all of the AR
occupied regions discovered in C4-2B cells also exhibited some AR occupancy
within LNCaP cells after 4 hours of 10 nM DHT treatment (16 out of 17).
Chromosome region 10q26.13 was the only locus that did not appear to have AR
occupancy after a 4-hour DHT treatment in LNCaP cells (Table 4.2).

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4.3.3 DHT treatment detects subsets of gene expression patterns
AR binding to evolutionarily conserved regions suggests a functional
interaction (Carroll et al., 2006). For each of the 15 androgen-occupied regions,
which were not within gene desert regions, we analyzed the DHT-mediated
expression of a few nearby annotated genes. Several distant genes up to 100-kb from
the androgen-occupied region were also included as potential controls for DHT-
mediated regulation. To measure a time-dependent response via qRT-PCR analysis,
total RNA was collected at 0, 2, 4, 8, 16, 24, and 48 hours after treatment of C4-2B
cells with either DHT or ethanol vehicle control. Additionally, though the androgen-
dependent LNCaP cell line demonstrated AR occupancy at almost every region
identified within the ablation-resistant C4-2B cell line (Table 4.1), the magnitude
and/or direction of response to androgen treatment may differ (Bai et al., 1998). As a
result, the expression of each gene was analyzed in a similar timecourse experiment
using LNCaP cells.

4.3.3.1 DHT-stimulated genes
We attempted to measure the expression of a total of 34 annotated genes
within 100-kb of the AR-occupied regions via qRT-PCR analysis (Table 4.2). Two
genes, SLC22A8 and AQP12, did not appear to be expressed in either C4-2B or
LNCaP cells. Of the remaining 32 genes, 9 genes showed at least a 2-fold DHT-
mediated increase in expression at some point during the C4-2B cell timecourse
experiment: DDT (maximum 5.8-fold stimulation at 24 hours; NM_001355.2),
CRELD2 (max: 2.3-fold at 48 hours; NM_024324.2), PRKCD (max: 2.2-fold at 48

81
hours; NM_006254.3), GSTT2 (max: 3.0-fold at 24 hours; NM_000854.2), TRPV3
(max: 2.7-fold at 24 hours; NM_145068.2), PYCR1 (max: 2.0-fold at 16 hours;
NM_153824.1), AP2A2 (max: 2.4-fold at 16 hours; NM_012305.2), ACBD6 (max:
2.6-fold at 2 hours; NM_032360.2), and FZD9 (max: 2.3-fold at 16 hours;
NM_003508.2) (Figure 4.2A-H, J). Interestingly, the DHT-mediated expression of
these genes in LNCaP cells exhibited differences in magnitude or time-dependent
effects. Generally, DHT treatment resulted in greater stimulation of these genes
within C4-2B than in LNCaP cells. TRPV3 represents an extreme example where
gene expression was essentially not detectable in LNCaP cells (Figure 4.2E). In
contrast, the DHT-mediated response of CRELD2 (maximum 17.4-fold stimulation
in LNCaP cells at 24 hours) and MRFAP1 (max: 2.5-fold at 24 hours;
NM_033296.1) demonstrated greater stimulation in LNCaP than in C4-2B cells
(Figure 4.2B,I).

4.3.3.2 DHT-repressed genes
Several genes within our screen were repressed upon DHT treatment, as
demonstrated by qRT-PCR. DHT treatment resulted in decreased expression of
MUC6 (XM_290540), CHRM1 (NM_000738.2), KIAA1217 (NM_019590.2), and
WBSCR28 within C4-2B cells (Figure 4.2ZC-ZF). An 8-hour DHT treatment of C4-
2B cells decreased KIAA1217 mRNA levels by 48% and MUC6 mRNA levels by
36% when compared to vehicle-treated cells (Figure 4.2ZC,ZE). Repression of
KIAA1217 was sustained for the entire 48-hour experimental period, with a
maximum 67% inhibition observed after 48 hours of treatment (Figure 4.2ZE).

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Though a possible derepression occurred after 24 hours of DHT treatment, MUC6
showed a general pattern of repression for most of the experimental period,
exhibiting a maximum 89% decrease at 48 hours of DHT treatment. Repression of
CHRM1 (by 33%) and WBSCR28 (44%) was already apparent at the 4-hour time
point in C4-2B cells (Figure 4.2ZD,ZF). WBSCR28 continued to exhibit strong,
persistent inhibition at later time points, down to 12% of mRNA levels measured at
48 hours in control cultures. CHRM1 mRNA levels reached a maximum 65%
inhibition at 8 hours of DHT treatment, followed by a gradual derepression at later
time points exhibiting only a 41% inhibition at 48 hours of DHT treatment. These
genes also displayed repression patterns in DHT-treated LNCaP cells. However, the
extent of gene inhibition was generally not as strong and consistent when compared
to the repression that occurred in C4-2B cells. Though most DHT-mediated effects
appeared stronger in C4-2B cells, similar to CRELD2 and MRFAP1 in the
stimulated subset of genes, QSCN6 (NM_002826.4) demonstrated an early and
strong repression pattern within the LNCaP cell line, whereas little to no repression
occurred within the C4-2B cell line (Figure 4.2ZB). QSCN6 mRNA levels exhibited
a 36% repression by 8 hours of DHT treatment and reached a maximum inhibition of
69% by 48 hours.

4.3.4 Pathophysiologic relevance of novel AR target genes
Though the LNCaP and C4-2B cell lines are considered good models for the
study of human prostate cancer (Thalmann et al., 1994), retaining many features of
prostate epithelial cells (DePrimo et al., 2002), the androgen-responsiveness of the

83
genes disclosed by our CD screen may have occurred as a cell culture artifact of this
in vitro system. To determine whether these genes reflect an accurate picture of the
in vivo androgen-regulated cell processes involved in human prostate cancer, we
mined the microarray database for the expression of the CD-identified genes. Figure
4.3 displays the relative expression of these genes within the 23 untreated (Primary)
and 17 androgen-ablated primary prostate cancers (Primary + AAT), as well as
within the 7 metastatic tumors (Mets). Several of the CD-identified genes, which
exhibited DHT-mediated expression changes in vitro, were also significantly
androgen-regulated in vivo. The expression of DDT, CRELD2, PRKCD, and PYCR1
were downregulated within the androgen-ablated tissues, but upregulated in
metastatic disease (Figure 4.3, Group II), presumably due to reactivated AR
signaling (Sato et al., 2005). The androgen-stimulation of these genes is consistent
with our in vitro data. Likewise, probesets for KIAA1217 and QSCN6 demonstrated
these genes are generally repressed in prostate epithelium when exposed to androgen
(Figure 4.3, Group III).
However, not all of the Affymetrix probesets measuring KIAA1217 gene
expression were similarly regulated. In fact, the results from one probeset suggest an
upregulation of KIAA1217 expression occurs when stimulated by androgens (Figure
4.3, Group II). Nevertheless, if the probesets are mapped along KIAA1217, which is
a gene 338.7-kb in length, half of the probesets cluster toward the 5’ region of the
gene (white and light gray boxes), whereas the other half clusters toward the 3’ end
of the gene (dark gray and black boxes) (Figure 4.4). Calculating the average
expression of the 5’ probeset cluster revealed higher mean expression of KIAA1217

84
in the AAT-treated than the untreated or metastatic PCa samples, demonstrating
androgen-mediated repression. Whereas, averaging the expression of the probesets at
the 3’ end of KIAA1217 revealed no difference in mean expression between the
untreated, treated, and metastatic prostate cancers. The probesets at the 3’ end of the
gene overlap a large number of possible alternative mRNA transcripts as illustrated
in Figure 4.4. In addition to capturing the expression of the full-length KIAA1217
transcript, these 3’ probesets may also be measuring the expression of smaller
alternative transcripts. If these additional transcripts are unaffected or even
stimulated by androgen treatment, the repression of the full-length KIAA1217 gene
will be masked.
Probeset location may explain some of the discrepancy observed between the
in vitro and the in vivo data. For example, one probeset each for LHX4
(NM_033343.2) and TRPV1 (NM_018727.4) were significantly upregulated by
androgen within the clinical samples (Figure 4.3, Group II), but did not appear to be
regulated by DHT treatment in vitro (Figure 4.2P,W). More consistent with our in
vitro data, two additional probesets for each gene did not demonstrate significant
expression changes with androgen-ablation treatment status (Figure 4.3, Group IV).
Alternatively, the androgen-mediated regulation of genes such as CLDN4
(NM_001305.3) and SYNGR1 (NM_004711.3), which appear to be repressed by
androgens in vivo (Figure 4.3, Group III), may not occur until later time points. In
fact, substantial repression of SYNGR1 was detected at later time points - 24 and 48
hours after DHT treatment within C4-2B cells (Figure 4.2ZA).

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4.3.5 AR represses target genes in the presence and absence of ligand
Despite the pervasiveness and potential importance of androgen-repressed
genes in both normal and prostate cancer development (Hendriksen et al., 2006;
Leger et al., 1987; Moehren et al., 2004; Velasco et al., 2004), most studies have
focused on studying the transcriptionally activated AR targets (Subramaniam et al.,
1997), while repressed genes have been largely ignored. To contribute toward this
underdeveloped area, additional experiments focused on studying genes that are
repressed by androgen in both C4-2B and LNCaP cells.
As demonstrated in Figure 4.2 and elsewhere (Denmeade et al., 2003; Jia and
Coetzee, 2005; Jia et al., 2006), AR-target genes in C4-2B cells respond to
androgens despite the hormone-independent growth of this PCa cell culture model.
Owing to the ablation-resistant phenotype of these cells, some androgen-responsive
genes, such as PSA and kallikrein-related peptidase 2 (KLK2), already exhibit AR-
dependent expression in cells not treated with androgens (Jia and Coetzee, 2005; Jia
et al., 2006). To determine the AR dependence of the CD-identified androgen-
repressed genes in C4-2B cells, we examined the effect of an AR knockdown on the
repression of these genes in the absence as well as presence of DHT. In the absence
of added ligand, qRT-PCR results demonstrate a 2.4-fold increase in KIAA1217, a
1.7-fold increase in CHRM1 and a 3.4-fold increase in WBSCR28 mRNA in AR
siRNA-treated cells (black bars) as compared to non-specific siRNA-treated cells
(white bars) (Figure 4.5A-C). On the other hand, MUC6 expression was repressed by
46% (Figure 4.5D) upon a knockdown of AR by 59% (Figure 4.5F). So, even though
DHT treatment repressed MUC6 expression (compare – versus + DHT among white

86
or black bars; Figure 4.5D), AR also appears to support a basal level of MUC6
expression. This observation suggests potentially more complex MUC6 regulation
by the AR. The increase in KIAA1217, CHRM1, and WBSCR28 mRNA levels upon
AR knockdown was a mirror image of the expected and observed downregulation of
the mRNA for PSA in the same samples (Figure 4.3E). Thus, the ligand-independent
regulation of AR target genes in ablation-resistant PCa cells (Jia and Coetzee, 2005;
Jia et al., 2006) extends to AR-mediated gene repression. AR autorepression (Figure
4.5F) has previously been shown in prostate cells (Krongrad et al., 1991; Nastiuk and
Clayton, 1994; Prins and Woodham, 1995; Quarmby et al., 1990; Shan et al., 1990).
In order to simplify the study of repressed genes, further experiments examining AR-
mediated repression will focus on KIAA1217, CHRM1, and WBSCR28.

4.3.6 Evidence for direct involvement of the AR in gene suppression
The observed AR occupancy (Figure 4.1D, Table 4.2) and early response to
DHT treatment (Figure 4.2ZD-ZF) are suggestive of direct involvement of the AR in
the repression of KIAA1217, CHRM1, and WBSCR28. However, mRNA levels are
determined by both their transcription and degradation rates. To investigate more
rigorously the potential for direct AR involvement in the transcriptional repression of
KIAA1217, CHRM1, and WBSCR28, we measured their pre-mRNA levels in the
same DHT timecourse samples used in Figure 4.2. Pre-mRNA levels are less prone
to post-transcriptional regulation and serve as a close estimation of transcription rates
(Elferink and Reiners, 1996). Transcripts were analyzed by qRT-PCR using primers
that spanned an exon-intron boundary in each of the three genes. DNaseI treatment

87
and appropriate controls without RT verified that genomic DNA was excluded from
our RNA preparations (data not shown). Rather than decreasing expression, a 2-hour
DHT treatment clearly increased KIAA1217 and CHRM1 pre-mRNA levels by 1.6-
and 3-fold, respectively (Figure 4.6). In both cases, this increase in pre-mRNA was
followed by a decrease in expression to levels lower than those measured in vehicle-
treated cells. Eight hours after DHT treatment, the pre-mRNA levels for these genes
were repressed by 41-43%, and suppression persisted for at least 16 hours after DHT
administration (Figure 4.6). WBSCR28 pre-mRNA levels were not detectable, likely
due to very low steady state levels.
PSA is unquestionably a direct AR gene target. If AR directly regulates the
DHT-repressed genes, then these genes are likely to respond to DHT in a manner
exactly opposite to PSA. We tested this premise with KIAA1217, whose pre-mRNA
was most strongly downregulated by DHT. Plotted as a percentage of the respective
maximum values, the DHT concentration-dependent repression of KIAA1217
closely mirrored the concentration-dependent activation of PSA (Figure 4.7A). The
responses of the two genes were also compared as a function of time after
administration of DHT at a concentration 10-fold lower than that used in Figure 4.2.
As shown in Figure 4.7B, 1 nM DHT repressed KIAA1217 in a time-dependent
manner that closely resembled a mirror image of PSA stimulation in the same
samples. Since PSA stimulation results from direct AR interactions with the
enhancer and promoter elements of the PSA gene, the mirrored effects of DHT on
KIAA1217 expression are consistent with the AR having a direct effect on the
KIAA1217 locus.

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4.3.7 Bicalutamide counteracts DHT-mediated repression of KIAA1217
Bicalutamide, a non-steroidal AR antagonist that inhibits AR transactivation
activity, stimulates nuclear translocation and DNA-binding of the AR to its cognate
response elements (Masiello et al., 2002). However, instead of recruiting co-
activators (Shang et al., 2002), bicalutamide-bound AR is thought to recruit
corepressors (Masiello et al., 2002). The DHT-mediated repression of KIAA1217
was preceded by transient stimulation (Figure 4.7B), particularly at the pre-mRNA
level (Figure 4.6A). This expression pattern could be explained by the initial
recruitment of co-activators, as observed in classical AR target loci after DHT
stimulation, but subsequent replacement of these co-activators with co-repressors at
the KIAA1217 locus. Conceivably, bicalutamide could also repress KIAA1217 via
the recruitment of co-repressors. We measured KIAA1217 expression after treatment
of C4-2B cells with 10 µM bicalutamide, in the absence or presence of 1 nM DHT
(Figure 4.8A). Bicalutamide alone did not repress KIAA1217 expression as
compared to the vehicle control. Moreover, the administration of bicalutamide in the
presence of DHT completely reversed the DHT-mediated repressive effects on
KIAA1217 expression. Bicalutamide also counteracted the DHT-mediated
stimulation of PSA in the same samples (Figure 4.8B), albeit not completely. These
results suggest that the AR-mediated negative regulation of KIAA1217 shares some
essential mechanistic aspects with the classical mode of AR action on positively
regulated genes.

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4.4 Discussion
4.4.1 Location analysis
The AR plays pivotal roles in both early, ligand-dependent PCa and advanced
disease, where it can function under conditions of androgen ablation (Kozlowski et
al., 1991; Nelson et al., 2002; Santos et al., 2004; Sato et al., 2005; Xu et al., 2001).
Despite a large body of published work on the AR, only a relatively small number of
direct AR target genes have been identified to date (Bai et al., 1998; Balbin and
Lopez-Otin, 1996; Bao et al., 2006; Cheng et al., 2003; Clay et al., 1993; Cleutjens et
al., 1997; Cleutjens et al., 1996; Crossley et al., 1992; Curtin et al., 2001; Dai and
Burnstein, 1996; Gavrielides et al., 2006; Gnanapragasam et al., 2002; Grad et al.,
2001; Haelens et al., 2001; Haendler et al., 2001; Heckert et al., 1997; Heemers et
al., 2004; Huang et al., 1999; Jain et al., 2002; Jave-Suarez et al., 2004; Jeong et al.,
2006; Jorgensen and Nilson, 2001a; Jorgensen and Nilson, 2001b; Lu et al., 1999;
Magee et al., 2006; Masuda et al., 2005; Moilanen et al., 2006; Murtha et al., 1993;
Phan et al., 2001; Riegman et al., 1991; Rokhlin et al., 2005; Salah et al., 2005;
Schneikert et al., 1996; Velasco et al., 2004; Zhang et al., 1997; Zheng et al., 2006),
with PSA being the best characterized gene (Lee and Chang, 2003). Moreover, the
determination of genes as direct targets has been biased toward those with AR-
binding sites within the 5’ flanking region. In our study, only 3 of the 19 CD
disclosed AR-occupied regions were mapped within 5-kb of the 5’ end of the nearest
annotated gene, whereas almost half of the AR-occupied regions were intragenic.
This is consistent with data from recent location analyses of transcription factors,
where the majority of binding sites are outside of the canonical 5’ regulatory region

90
(Carroll et al., 2006; Cawley et al., 2004; Chen and Sadowski, 2005; Horie-Inoue et
al., 2004; Kim et al., 2005a; Martone et al., 2003). However, proteins of the
preinitiation complex, such as RNA polymerase II and TFIID, are still predominantly
localized to promoter-proximal regions (Carroll et al., 2006; Kim et al., 2005b).
Though not in the immediate 5’ flanking region, transcription factor binding
sites still appear to have a bias toward residing within 50-kb of the TSS of regulated
genes (Carroll et al., 2006). Even so, regulatory elements have been observed to
influence the transcription of genes from as far as half a megabase (Spitz et al.,
2003). Such regulation is possible through chromosomal looping, which may bring
the distal regulatory region into close physical proximity of the gene promoter
(Shang et al., 2002).
On the other hand, several of the AR-occupied regions identified could
potentially regulate the transcription of unannotated transcripts. Four of the 19 AR-
occupied loci reside with gene poor regions, where the nearest annotated RefSeq
gene is 197-kb away, but the site is surrounded by evolutionarily conserved
sequences. It is predicted that as much as 60% of the nonrepetitive human genome is
transcribed, which may even be an underestimate (Willingham and Gingeras, 2006).
Recent analysis of these novel unannotated transcripts revealed that the majority of
protein coding genes has alternative splice forms (Carninci et al., 2005).
Furthermore, intragenic and 3’ AR-occupied sites may denote promoter regions of
noncoding RNAs, which appear to share mechanistic similarity to the promoters of
protein coding genes (Cawley et al., 2004). In fact, a large proportion of the human
genome exhibits overlapping transcription with concordant regulation of sense and

91
antisense transcripts. Antisense transcripts may then potentially interfere with the
transcription or RNA stability of the sense transcripts (Cheng et al., 2005; Katayama
et al., 2005).

4.4.2 CD-disclosed repressed targets
An overwhelming proportion of the investigation of AR targets has focused
on stimulated genes (Subramaniam et al., 1997) even though agonist-mediated AR-
target gene repression likely plays an important role in PCa progression (Hendriksen
et al., 2006; Moehren et al., 2004). In addition to detecting androgen-stimulated
genes, expression analysis of annotated genes in the vicinity of the disclosed AR-
occupied loci revealed four novel DHT-repressed genes: KIAA1217, MUC6,
CHRM1, and WBSCR28. KIAA1217, CHRM1, and WBSCR28 were not only
repressed in response to DHT, but were also under constitutive AR-mediated
negative regulation, which became apparent upon treatment of steroid-deprived C4-
2B cells with AR siRNA. In contrast, though the mRNA levels of MUC6 were
repressed by DHT treatment, an AR knockdown resulted in a decrease of MUC6
expression rather than the expected increase. This observation indicates complex
regulation of the gene, suggesting the potential presence of repressor as well as
enhancer AREs that coordinately regulate MUC6 to tightly control the overall
expression level. Cooperative regulation of AR-regulated targets by multiple AREs
has been shown previously for membrane metallo-endopeptidase (MME) (Zheng et
al., 2006), PSA (Cleutjens et al., 1997; Cleutjens et al., 1996; Pang et al., 1997), and
the AR itself (Dai and Burnstein, 1996).

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4.4.3 Active repression by nuclear hormone receptors
Previous work on nuclear hormone receptors has revealed the existence of
multiple mechanisms for ligand-mediated transrepression. Nuclear hormone
receptors can actively repress target genes through the recruitment of corepressors,
such as nuclear receptor corepressor (NCoR) and silencing mediator of retinoid and
thyroid hormone receptor (SMRT), which in turn interact with histone deacetylases
(HDACs) and histone methyltransferases to modify the N-terminal tails of histone
proteins. These particular histone modifications favor the formation of higher order,
compact chromatin structures, which limit access to transcriptional machinery and,
consequently, diminish gene transcription. Traditionally, hormone receptor agonists
were thought to abolish the interaction between nuclear hormone receptors and
NCoR and SMRT (Moehren et al., 2004). However, more recent data demonstrate
that these corepressors are recruited along with the AR to AREs of target genes when
treated with AR agonists (Hodgson et al., 2005; Yoon and Wong, 2006). The extent
of agonist-mediated activation or repression may depend on the relative proportion
of coactivators to corepressors that are recruited (Hodgson et al., 2005; Yoon and
Wong, 2006), a balance which may be influenced by allosteric differences in
receptor conformation that arise from the particular sequence composition of, and
around the ARE (Moehren et al., 2004).

4.4.4 Additional mechanisms of transcriptional repression
Alternatively, nuclear hormone receptors may also repress transcription via
cross talk with other signaling pathways. Such mechanisms may involve squelching,

93
competition for overlapping binding sequences, or the formation of inhibitory
protein-protein interactions with transcription factors such as activator protein-1
(AP-1) and nuclear factor κB (NF-κB) (Beato et al., 1995; Levine and Manley,
1989). In most of these cases, AR interferes with the activity of transcription factors
(e.g. c-Jun, ATF2) at the respective basal promoters (Bai et al., 1998; Heckert et al.,
1997; Jorgensen and Nilson, 2001a; Jorgensen and Nilson, 2001b; Schneikert et al.,
1996), possibly through steric hindrance (Gast et al., 1998). However, additional
repression mechanisms may exist, as 3 of the 4 AR-occupied regions in the vicinity
of the androgen-repressed genes were not within the 5’ promoter-proximal region.
Instead, they were 46.5-kb downstream of the TSS residing within the second intron
of KIAA1217, 87.4-kb upstream of the TSS (CHRM1), and 4.3-kb downstream of
the 3’ end of the gene (WBSCR28). AR occupancy far from the transcription start
sites of androgen-repressed genes provides an opportunity to expand our knowledge
of AR-mediated gene repression.

4.4.5 Direct versus indirect repression of CD-disclosed genes
Although changes in mRNA levels can be ascribed to alterations in both
transcription and degradation rates, the rapid changes in KIAA1217, MUC6,
CHRM1, and WBSCR28 mRNA in the present study, and more so the decrease we
observed in the unspliced primary transcripts of KIAA1217 and CHRM1, suggest
that at least some aspect of the DHT-mediated gene repression is attributable to
transcriptional regulation. Additional support for some transcriptional effect, at least
with respect to KIAA1217, is that in response to DHT treatment, the concentration-

94
and time-dependent regulation revealed similar, but of course opposite dynamics to
the response of the established AR-target gene, PSA. The distances between the AR-
occupied regions and the respective transcription start sites of KIAA1217, CHRM1,
and WBSCR28 do not necessarily argue against transcriptional regulation from these
distal locations. Active gene repression from a distant domain may involve the
recruitment of corepressors and HDACs to the locus, which would inhibit activity of
the respective basal promoter by looping, sliding/tracking, or propagating a histone
modification signal along the chromosome (Talbert and Henikoff, 2006).
However, the results are not fully supportive of an active transcriptional
repression mechanism of the KIAA1217 locus. The AR competitive antagonist,
bicalutamide, was used to examine whether the putative transcriptional component of
KIAA1217 downregulation involved active repression. In normal and malignant
prostate epithelial cells bicalutamide does not prevent, but actually stimulates the
rapid nuclear translocation and association of AR with its target DNA sequences.
However, instead of forming a transcriptionally active complex, the AR is assembled
into an inactive state (Masiello et al., 2002), presumably by interacting with the
corepressors, NCoR and SMRT, and HDAC1 and HDAC2 (Shang et al., 2002). In
our study, however, rather than mimicking, bicalutamide inhibited the repressive
effect of DHT on KIAA1217 expression. Furthermore, treatment with the HDAC
inhibitor, trichostatin A (TSA), had no impact on the degree of DHT-mediated
KIAA1217 repression (data not shown). These data do not support active repression
as the potential silencing mechanism for KIAA1217 expression. On the contrary, it
appears as if agonist-mediated repression of KIAA1217 shares mechanistic aspects

95
with a classically activated AR. With respect to the CHRM1, another argument
against direct repression is that the mRNA was repressed by 4 hours, prior to the
repression of the pre-mRNA, which was observed only at the 8-hr time point. In
fact, this observation suggests that transcriptional repression of CHRM1 could have
been secondary to a post-transcriptional effect.
As mentioned above, another potential mechanism of AR target gene
repression could occur through AR-mediated expression of antisense non-coding
RNAs, which then downregulate the sense transcript levels, particularly when AR
binding occurs within an intron (KIAA1217) or downstream of the gene
(WBSCR28) (Cawley et al., 2004). Interestingly, a microRNA (MIRN603) in the
antisense direction is located within intron 2 of KIAA1217 ~20-kb from the CD-
identified AR-occupied region. Though this would be a posttranscriptional mode of
repression, the upregulation of a microRNA antisense transcript may cause a loss in
pre-mRNA stability and result in degradation of the primary transcript. Such a
hypothesis is also supported by the bicalutamide experiment, which indicated
KIAA1217 repression shares mechanistic aspects with AR-activated transcription. A
few conditions would have to be true for this mechanism to be plausible: 1)
MIRN603 targets intron 2 of KIAA1217, 2) the rate at which KIAA1217 intron 2 is
spliced from the pre-mRNA transcript is relatively slow, and 3) RNA interference
(RNAi) occurs within the nucleus. However, RNAi is thought to occur
predominantly, if not exclusively, within the cytoplasm (Elbashir et al., 2002).
Regardless of whether the first two conditions are true, exclusion of RNAi from the
nucleus would argue against this as a potential mechanism for KIAA1217 repression.

96
4.4.6 Relevance to PCa
Our study uncovered several examples from what is likely a vast number of
androgen-regulated genes (Velasco et al., 2004). Though we used an in vitro system,
most of the CD-identified genes examined were similarly regulated or not regulated
in clinical prostate tumors. As noted by other studies (Chen et al., 2006; DePrimo et
al., 2002; Thalmann et al., 1994), LNCaP and C4-2B cells appear to be good models
for the study of molecular mechanisms involved in prostate cancer progression. Cell
culture artifacts may account for some of the observed discrepancies, however other
factors may play a role as well. Firstly, probesets and qRT-PCR primers targeting
different locations of a gene, potentially measuring alternative splice transcripts, may
account for some of the discrepancy between the in vivo and in vitro data. Second,
the in vitro expression changes in response to DHT treatment were measured over
the course of a 48-hour period, whereas the in vivo samples were quantified after 3
months of AAT. Differences in short- versus long-term androgen-mediated
regulation are supported by the late trends observed in the DHT-mediated repression
of SYNGR1 or stimulation of CHRM1, which is particularly noticeable at the pre-
mRNA level. Finally, LNCaP and C4-2B are homogeneous populations of prostatic
epithelial cells, whereas clinical prostate cancer samples are generally contaminated
with stromal cells, which are known to exhibit androgen-mediated responses that
differ from the prostatic epithelium (Cunha et al., 2004a).
Regardless of whether androgen-mediated inhibition is direct or indirect,
which of these genes are most important in prostate cancer is beyond the scope of the
present work. Not much is known about the repressed genes identified in our study.

97
KIAA1217 is a large gene of unknown function, exhibiting some sequence similarity
to KIAA1684/p130Cas-associated protein (p140Cap)/SNAP-25-interacting protein
(SNIP) (Nagase et al., 1999; Nagase et al., 2000), a tyrosine-phosphorylated protein
involved in actin cytoskeleton reorganization (Di Stefano et al., 2004). Yeast-2-
hybrid analyses have also revealed several new interacting partners of KIAA1217
(Rual et al., 2005), three of which [Sorbin and SH3 domain containing 3
(SORBS3/SCAM-1/vinexin), NCK adaptor protein 2 (NCK2/GRB4), and keratin 15
(KRT15)] interact with cytoskeletal components to influence cellular differentiation
and motility (Goicoechea et al., 2002; Kioka et al., 1999; Leube et al., 1988;
Mitsushima et al., 2004), suggesting KIAA1217 may be involved in processes such
as cell adhesion and migration. CHRM1, a G protein-coupled receptor, has been
shown to increase intracellular zinc concentrations (Zuchner et al., 2006), which in
turn inhibit the growth, proliferation, and invasive capacity of PCa cells (Huang et
al., 2006). MUC6 is a member of a family of high molecular weight glycoproteins
generally found on the surface of epithelial cells. These glycoproteins provide
protection and lubrication for cells, but may become altered during cancer
progression. However, whereas the MUC1 glycoprotein appeared to be
overexpressed with prostate cancer progression, MUC6 was not expressed in normal
or untreated prostate cancer samples (Cozzi et al., 2005). WBSCR28 is another gene
of unknown function, which is typically deleted along with 28 other genes on one
copy of chromosome 7 in Williams-Beuren syndrome (Bhattacharjee, 2005).

98
4.4.7 Conclusion
Based on an unbiased, genome-wide, expression-based study, at least half of
all androgen regulated genes are repressed (Xu et al., 2001) with many being
involved in growth inhibitory, differentiation, and apoptotic pathways (Hendriksen et
al., 2006). One of today’s biggest challenges in PCa treatment is an insufficient
understanding of the biological mechanisms underlying disease progression
(Evangelou et al., 2004). Like Maspin, a tumor-suppressor gene (Zhang et al., 1997),
inhibition of CHRM1 and KIAA1217 expression may contribute to the oncogenic
activity of AR signaling in PCa. More importantly, the present study sets the
foundation for future investigation, which will elucidate novel mechanisms of AR-
mediated gene repression from sites located many kilobases away from transcription
start sites.

99

Table 4.1 Primer and oligo sequences
A) CD Oligoligonucleotides
Short linker oligo 5'-TTCGCGGCCGCAC-3'
Long A linker oligo 5'-GACGTGCGGCCGCGAA-3'
Long T linker oligo 5'-GTCGTGCGGCCGCGAA-3'
"AA" PCR primer 5'-CGGCCGCACGACCA-3'
"AT" PCR primer 5'-CGGCCGCACGACCT-3'
"AG" PCR primer 5'-CGGCCGCACGACCG-3'
"AC" PCR primer 5'-CGGCCGCACGACCC-3'
"TA" PCR primer 5'-CGGCCGCACGTCCA-3'
"TT" PCR primer 5'-CGGCCGCACGTCCT-3'
"TG" PCR primer 5'-CGGCCGCACGTCCG-3'
"TC" PCR primer 5'-CGGCCGCACGTCCC-3'
B) ChIP Validation Primers
Chromosome region Forward Primer Reverse Primer
1p35.2 5'-AGGGACAACATCACCAGGAG-3' 5'-AGCACGGCTACTGCACCTAC-3'
1q25.2 (QSCN6) 5'-CCTTCCGGACAATGAAGAAG-3' 5'-AAGCAAGCCACTCACCCTAC-3'
2q37.3 (KIF1A) 5'-GCTTCTCCAGCGTCCAGTAG-3' 5'-CTGACGAGTGGTCATCTTCC-3'
3p21.1 (PRKCD) 5'-CCAGAGAACAGCATGCTCAA-3' 5'-TACAACCAGGCAGGATGACA-3'
4p16.1 (MAN2B2) 5'-GTGGAAACTGTTGGGTGGAG-3' 5'-CTGGTCCCCACTGAGTCTTC-3'
7q11.23 (FZD9) 5'-CTCAAGAGGATCGGGAGATG-3' 5'-TCCTGGGCTCAAGTGATTCT-3'
7q11.23 (WBSCR28) 5'-ACCAGAGGGGTCTGTGTGTC-3' 5'-AAGCGAGAAGCGCTAATAGG-3'
8q24.3 5'-GTGGATGGATGGCAAATAGG-3' 5'-GCTCCTTTGTCAGGGATCAG-3'
10p12.1 (KIAA1217) 5'-GTGGGCTCAGCACTGGAC-3' 5'-CAGGGAAACCCCAGAATCAG-3'
10q26.13 (OAT) 5'-CTCCCAAACTCCTCCAACTG-3' 5'-GGGTAGAACATCAGGGCAAC-3'
11p15.5 (MUC6) 5'-GTGATGCCGTTGATGACAGT-3' 5'-ACGGGTAACACCACCTTCAG-3'
11q12.3 (SLC22A8) 5'-CATTAAGTCATTGTAAGGCCTGTG-3' 5'-TCCAGGATCAGGAACTCACC-3'
11q25 5'-GTCCTACCCTGGAGGGACTG-3' 5'-GGAGGAGAGGAATCGAGGTC-3'
14q31.3 5'-CCATCTGCTTAGATGTTCATGC-3' 5'-TGGGATCTTTGAGGGGATAAC-3'
17p13.2 (TRPV1) 5'-GCAAAAATGATGGGAAAAGC-3' 5'-CTTGAAGGCGGTTGCTACTC-3'
17q25.3 (MAFG) 5'-ACCCCAACTCCTCCTCACAG-3' 5'-CCAAGAAGATTCTGGGGTGA-3'
22q11.23 (GSTT2) 5'-GATTGGCCATCAGGGAGTAG-3' 5'-TGAGATCAGCCAGTGTCACC-3'
22q13.1 (SYNGR1) 5'-CATGGGAGATGCACTCTTGA-3' 5'-GTTCAGTGGGTTGTCCTTGG-3'
22q13.3 (CRELD2) 5'-ACCACCCACTCCTCAGTCAC-3' 5'-ACAGGGGCTCTTCCAATACC-3'
PSA AREIII 5'-TGAAAACAGACCTACTCTGGA-3' 5'-AGCAAAGACAGCAACACCTT-3'
11p11.2 (non-target) 5'-CCGACTTCCTCTCCTGACTG-3' 5'-TCAGCTTGCTCCCCATTTAT-3'
C) qRT-PCR Primers
Gene Forward Primer Reverse Primer
18S RNA 5'-CCGCAGCTAGGAATAATGGA-3' 5'-CGGTCCAAGAATTTCACCTC-3'
ACBD6 mRNA 5'-GGCCTGTGATCGAGGACATA-3' 5'-TAAGCCTTGCCAGTTGTGTG-3'
ALG12 mRNA 5'-GCGTGATTTTTGGACTCTGG-3' 5'-GAACACGATGATGGCGAAG-3'
AP2A2 mRNA 5'-TGACGTCTGCATCCACAGAT-3' 5'-TGCTGGACCTTCTTCGACTT-3'
AQP12A mRNA 5'-CGTCTGCCTTCTTCAACC-3' 5'-CTCGGTACTTGTTCTTCTGG-3'
AR mRNA 5'-CTGGACACGACAACAACCAG-3' 5'-CAGATCAGGGGCGAAGTAGA-3'
BAZ1B mRNA 5'-AAAGCCTTCCACCTGTTTTG-3' 5'-GCAAACCAGCCACCTCATAA-3'
CARKL mRNA 5'-AATGGACAGAGGGAGGGATT-3' 5'-TACGTTCCAGCTTTGGCTCT-3'
CEP350 mRNA 5'-AGAATGGAGCCAAAAGAGCA-3' 5'-CAAGAATGCCACGAATTTCA-3'
CHRM1 mRNA 5'-CCGCTACTTCTCCGTGACTC-3' 5'-GTGCTCGGTTCTCTGTCTCC-3'
CHRM1 pre-mRNA 5'-CAAAGCCCATGTCCTCTCTT-3' 5'-CTTGAGCTCCGTGTTGACCT-3'
CLDN4 mRNA 5'-TGCTTTGTTCTTCCCTGGAC-3' 5'-ACCACCACACCCTGTCACTT-3'
CRELD2 mRNA 5'-GGAGATGGGAGCAGACAGG-3' 5'-ACCCAGCCCACTTCACACT-3'
DDT mRNA 5'-CTGGAGCTGGACACGAATTT-3' 5'-GGCTAGCTCCTTGGTGAGAA-3'
FZD9 mRNA 5'-AGACCATCGTCATCCTGACC-3' 5'-CCGATCTTGACCATGAGCTT-3'
GSTT2 mRNA 5'-CAATGGCTGGAGGACAAGTT-3' 5'-CCTGATAGGCCTCTGGTGAG-3'

100

Table 4.1 (continued)
Gene Forward Primer Reverse Primer
KIAA1217 mRNA 5'-CCATGAGTGCCAAGAACAGA-3' 5'-TTGACTCTGCGGTGAGAATG-3'
KIAA1217 pre-mRNA 5'-CTACAGCACGGCGACAATAC-3' 5'-GGTGGCTTTGACACCACTCT-3'
KIF1A mRNA 5'-AAGGCCTCCTCCTAGACAGC-3' 5'-CTGTGTTCTTCAGGGGCTCT-3'
LHPP mRNA 5'-GAGGTTCTGCACCAACGAGT-3' 5'-CACACAGTTTGGGTTGGATG-3'
LHX4 mRNA 5'-CAGGCGGACAGTTAATGAATGG-3' 5'-GGACGATATGGAGGATGGAGAC-3'
MAFG mRNA 5'-GAGAAGCTGGCCTCAGAGAA-3' 5'-GGCATCCGTCTTGGACTTTA-3'
MAN2B2 mRNA 5'-GGGTGTACCCCAACATGAGT-3' 5'-CTGTGGAATAGGGCAGGAAG-3'
MAP3K7IP1 mRNA 5'-CCAAGCTGGACAGATGACCT-3' 5'-CCACGAAGTTGGTCACTCG-3'
MRFAP1 mRNA 5'-TGCTCATCCAGATCAAAACG-3' 5'-CAAAAGGCTCTCTGGTTTCG-3'
MUC6 mRNA 5'-AACATCATCACCCAGCAGGT-3' 5'-TGGTGGGTGTTTTCCTGTCT-3'
OAT mRNA 5'-TTCTGGGGTAGGACGTTGTC-3' 5'-GAGCTCTCGCACTCCCATTA-3'
PRKCD mRNA 5'-CCTGACTATATCGCCCCTGA-3' 5'-GTCCTTGGACTCCTTGGTGA-3'
PYCR1 mRNA 5'-ACACCCCACAACAAGGAGAC-3' 5'-CTGGAGTGTTGGTCATGCAG-3'
QSCN6 mRNA 5'-ACCCTCAACTTCCTCAAG-3' 5'-TCATCATCTCAGGCTTCC-3'
SIRT7 mRNA 5'-GGACCTGGTAACGGAGCTG-3' 5'-CGCCTGTGTAGACGACCAAG-3'
SLC22A6 mRNA 5'-ACCCTCCGCCACCTCTTCC-3' 5'-GGCAGGCAGGTCCACAGC-3'
SLC22A8 mRNA 5'-TTGCTACCGGTTTTGCCTAC-3' 5'-AGCCAATACTGTCCTCACGG-3'
SYNGR1 mRNA 5'-TCTGCATCTACAACCGCAAC-3' 5'-TTCAGTGGGTTGTCCTTGG-3'
TRPV1 mRNA 5'-GCCCATGGGGACTTCTTTA-3' 5'-TTCCCTTCTTGTTGGTGAGC-3'
TRPV3 mRNA 5'-GAGCCTGTCCAGGAAGTTCA-3' 5'-GTGCTTGGCAAACTTCTTCC-3'
WBSCR27 mRNA 5'-GTCTGACCACCAGGACCAAC-3' 5'-AGACAATGCCGGAGATGAAG-3'
WBSCR28 mRNA 5'-AGTGACCTGGAGGGTGTGTC-3' 5'-CTGGGTCGTGTGCTCAAAG-3'
WBSCR28 pre-mRNA 5'-TGTGTCAGAAGTCCCACTGC-3' 5'-GGAGCTCATAGGGTTACACTGC-3'
D) siRNA Oligos
Target Sense Oligo Anti-sense Oligo
AR 5'-GAAGACCUGCCUGAUCUGUTT-3' 5'-ACAGAUCAGGCAGGUCUUCTT-3'
Non-specific 5'-AGAUCUGGCUAUCGCGGUATT-3' 5'-UACCGCGAUAGCCAGAUCUTT-3'

101
Adapted from a table generated by Unnati Jariwala.
Table 4.2 CD-identified AR targets
Primer CD hit position
pair
Band
1
AvaII-AvaII
2
relative to gene C4-2B LNCaP
AT / TA 1p35.2 30,256,041-30,256,222 4 of 6 2 of 3
QSCN6 exon 13
LHX4 32.7-kb 5'
CEP350 84.2-kb 3'
ACBD6 90.6-kb 3'
KIF1A intron 23/exon 24
AQP12A 62.4-kb 3'
TT / TT 3p21.1 53,169,093-53,169,401 PRKCD 0.8-kb 5' 4 of 6 N/D
MAN2B2 intron 5
MRFAP1 48.7-kb 5'
FZD9 2.7-kb 5'
BAZ1B 10.0-kb 3'
WBSCR28 4.3-kb 3'
WBSCR27 27.4-kb 5'
CLDN4 37.2-kb 3'
AA / AG 8q24.3 143,094,298-143,094,518 3 of 6 2 of 3
AC / TC 10p12.1 24,584,349-24,584,579 KIAA1217 intron2 4 of 6 3 of 3
OAT 3.4-kb 3'
LHPP 67.9-kb 5'
MUC6 10.0-kb 5'
AP2A2 15.0-kb 3'
SLC22A8 intron 2
SLC22A6 23.9-kb 5'
CHRM1 87.3-kb 5'
AT / AT 11q25 134,102,859-134,103,167 2 of 6 3 of 3
AT / AT 14q31.3 86,510,091-86,510,360 3 of 6 2 of 3
TRPV1 exon 1/intron 1
CARKL 11.4-kb 3'
TRPV3 39.0-kb 5'
MAFG 1.5-kb 5'
PYCR1 2.5-kb 3'
SIRT7 12.0-kb 5'
GSTT2 exon 4/intron 4
DDT 3.1-kb 5'
SYNGR1 intron 2
MAP3K7IP1 25.0-kb 5'
CRELD2 1.0-kb 3'
ALG12 10.0-kb 5'
1
Cytogenetic band containing the CD hit.
2
Absolute positions of the AvaII sites flanking the fragment identified by PAGE.
3
Nearest Refseq annotated gene in Ensembl is shown in bold text.
4
Number of independent conventional ChIP assays in which AR occupancy was confirmed. N/D , Not Determined.
1 of 3
3 of 6 2 of 3 22,655,127-22,655,462
2 of 3
AC / TC 22q13.3 48,707,684-48,707,956 3 of 6
AG / AG 22q13.1 38,101,611-38,101,989 3 of 6
2 of 3
Nearest gene is 959-kb away
AT / AC 17p13.2 3,446,846-3,447,080
AC / TG 17q25.3 77,480,155-77,480,527
3 of 6 1 of 3
AA / AA 22q11.23
3 of 6 3 of 3
AT / AT 11q12.3 62,532,814-62,532,977 5 of 6 2 of 3
4 of 6
2 of 6 0 of 3 126,072,189-126,072,473
Nearest gene is 316-kb away
Nearest gene is 197-kb away
AT / AG 10q26.13
AC / TC 11p15.5 1,017,234-1,017,529
N/D
AT / AG 7q11.23 72,922,165-72,922,474 4 of 6 2 of 3
AA / TC 7q11.23 72,483,118-72,483,317 4 of 6
ChIP validation
4
AT / AC 4p16.1 6,644,411-6,644,619 3 of 6 3 of 3
Nearby genes
3
3 of 6 1 of 3
AT / AT 2q37.3 241,348,804-241-348,990 3 of 6 1 of 3
Chromosome postion
Nearest gene is 679-kb away
AA / TC 1q25.2 178,433,288-178,433,456

102
FIGURE 4.1 LEGEND

AR occupies novel loci in C4-2B PCa cells. A. An example of ChIP Display (CD).
DNA obtained by chromatin immunoprecipitaiton with AR antibodies (AR) or IgG
control antibodies (IgG) was processed as described in Materials and Methods,
diluted to a 160 PSA copy number as described in Results, amplified using the ‘AT’
and ‘AG’ primer pair, and resolved on an 8% polyacrylamide gel. The arrowhead
indicates DNA fragments enriched in the 3 independent AR ChIP samples, but in
only one control sample. M, DNA size ladder. B. Secondary digestion of DNA
fragments. DNA bands indicated by the arrowhead in Panel A were excised from the
AR
1
and AR
3
ChIP lanes, reamplified using the same primer pair as in the original
CD, and subjected to secondary digestions using the HaeIII, HinfI, and MspI
restriction enzymes as indicated. Digestions were resolved on a 2% agarose gel.
DNA from similar sized MspI bands (arrowheads) were extracted, sequenced, and
mapped to chromosome 7q11.23. UC, uncut DNA. C. Genomic context of the AR-
occupied region disclosed in Panel A. Position of the fragment from Panel A is
indicated by a black box marked “hit” in relation to the exons (black boxes, top line)
of the WBSCR28 gene. Vertebrate conservation (black peaks), repetitive sequences
(gray boxes), and putative androgen response elements (triangle) are shown. The
arrow represents the transcription start site for the WBSCR28 gene. D. Validation of
AR occupancy. Locus-specific primers were used in a conventional ChIP assay to
PCR-amplify the region disclosed in Panel A. Amplification of the PSA enhancer
region (PSA AREIII) served as the positive control, whereas a non-targeted region

103
was used as the negative control. A serial dilution (4-fold steps) of genomic DNA
demonstrates that amplification was within a dynamic range. N, no template control.

104
FIGURE 4.1

105
FIGURE 4.2 LEGEND

DHT stimulates and represses novel AR target genes. C4-2B (solid lines, filled in
squares) and LNCaP (broken lines, open squares) cells were incubated in phenol red-
free RPMI 1640 containing 5% charcoal-stripped serum (CSS) for 3 days and then
treated either 10 nM DHT or ethanol vehicle as control for the indicated period of
time. Expression of annotated genes in the vicinity of each CD identified AR-binding
region was measured by qRT-PCR as a function of time. Each data point represents
the ratio between the mRNA level in DHT-treated versus vehicle-treated cultures
after normalization for the respective 18S RNA levels, which remained stable
throughout the timecourse (data not shown). Error bars represent the standard
deviation (SD) of 3 qRT-PCR determinations. Genes were roughly ordered based on
their responsiveness to DHT starting with the stimulated genes (Panels A-J) to the
repressed genes (Panels ZC-ZF). TRPV3 mRNA was undetectable in LNCaP cells.
Figure 4.2 is adapted from a figure created by Unnati Jariwala.

106
FIGURE 4.2

107
FIGURE 4.2 (continued)

108
FIGURE 4.3 LEGEND

Expression of CD-disclosed genes in PCa tumors. RNA from 23 untreated primary
prostate cancers (Primary), 17 primary prostate cancers obtained after 3 months of
neoadjuvant androgen-ablation therapy (Primary + AAT), and 7 AR-positive
metastatic lesions (Mets) were analyzed using the Affymetrix Human Genome U95
A-E GeneChip Array set (Holzbeierlein et al., 2004). Data were mined for
probesets representing the 32 CD-disclosed genes. All probesets for each gene are
shown (rows) except for probesets 59776_at (WBSCR28) and 36904_at (KIF1A),
which did not detect expression in any of the samples. Relative expression calculated
within each individual probeset is illustrated by this heatmap with darker shades
representing higher mRNA levels. Probesets were grouped and ranked as follows:
Group I – probesets for the known AR-regulated genes PSA/KLK3 and TMPRSS2,
which are stimulated by androgen. Group II – probesets exhibiting statistically
significantly higher mean expression in untreated versus androgen-ablated primary
PCa samples (p<0.05), thus representing putative AR-stimulated genes. Group III –
probesets exhibiting statistically significantly lower mean expression in untreated
versus androgen-ablated primary PCa samples (p<0.05), thus representing putative
AR-repressed genes. Group IV – probesets exhibiting no statistically significant
difference between the untreated and the androgen-ablated tissue samples. Probesets
in Groups II-IV are ranked by p-value in descending order. Figure 4.3 was created by
Dr. Grant Buchanan.

109
FIGURE 4.3

110
FIGURE 4.4

Expression of KIAA1217 differs by location of probesets. The individual
Affymetrix probesets used to measure KIAA1217 expression were mapped along the
gene. Each probeset was aligned to the KIAA1217 gene structure and human
mRNAs reported in GenBank. Arrows indicate the position of each probeset with the
specific location on chromosome 10 listed in parentheses. Relative mean expression
values for the untreated, AAT-treated, and metastatic PCa samples were obtained by
averaging the 5 probesets clustered toward the 5’ region of the gene (white and light
gray squares) separately from the 6 probesets clustered toward the 3’ end of the gene
(dark gray and black squares). Figure 4.4 is adapted from a figure originally
generated by Dr. Grant Buchanan.

111
FIGURE 4.5 LEGEND

AR represses genes in the presence and absence of added ligand. C4-2B cells
were transfected with 100 nM non-specific control (white bars) or AR-specific
siRNA (black bars) and incubated for 3 days in medium containing CSS prior to a
24-hour treatment with either 10 nM DHT or ethanol vehicle control. Expression
levels of the indicated genes were measured by qRT-PCR. Results were normalized
for 18S RNA. The corrected non-specific, vehicle control culture served as the
reference for each gene, which was set to a value of 100. Error bars represent the SD
of at least 3 determinations.

112
FIGURE 4.5

113
FIGURE 4.6

DHT represses the pre-mRNA of novel AR target genes. The pre-mRNA levels of
KIAA1217 (A), CHRM1 (B), and WBSCR28 (undetectable) were measured as in
Figure 4.2 using the same RNA samples. Primers spanned an exon-intron boundary,
and absence of genomic DNA was confirmed by eliminating the RT step (data not
shown). Error bars represent the SD of 3 determinations.

114
FIGURE 4.7

KIAA1217 mirrors the concentration- and time- dependent response of PSA to
DHT. A. C4-2B cells were incubated in phenol red-free RPMI 1640 containing 5%
CSS for 2 days and then treated with the indicated concentrations of DHT or vehicle
control for 16 hours. Messenger RNA levels were measured by qRT-PCR and
corrected for GAPDH. The fold difference at each concentration was plotted as a
percentage of the maximum value for each gene, which was set to 100. B. C4-2B
cells were treated with 1 nM DHT or vehicle for the indicated time period and the
expression of PSA and KIAA1217 was measured and plotted as in Panel A. Error
bars represent the standard error of the mean (SEM) of at least 6 determinations.

115
FIGURE 4.8

Bicalutamide counteracts DHT-mediated repression. C4-2B cells were incubated
in phenol red-free RPMI 1640 containing 5% CSS for 2 days and then treated for 16
hours with vehicle, 1 nM DHT, and/or 10 µM bicalutamide (BIC), as indicated.
Expression of KIAA1217 (A) and PSA (B) was measured by qRT-PCR, corrected
for GAPDH mRNA, and expressed relative to the control values, which were set to
100. Error bars represent the SEM of at least 6 determinations.

116
CHAPTER 5: Summary of Principal Findings

Prostate cancer is a major health burden worldwide (Quinn and Babb, 2002).
Despite research efforts, the incidence of prostate cancer continues to increase
(Jemal et al., 2007). Only age, ethnicity, and family history of prostate cancer have
been established as risk factors (Society, 2006) with familial clustering likely to be a
mixture of both genetic and environmental components. By uncovering the genetic
determinants, we may be able to identify subsets of individuals at higher risk of
prostate cancer. Stratifying populations into more homogeneous high-risk groups
based on genetic factors would help identify environmental exposures that influence
prostate cancer risk. Genetic screening can then be used to personalize
environmental modification and chemoprevention efforts (Kibel, 2006).
Understanding the mechanisms, which lead to ablation-resistant disease,
represents the biggest challenge in developing cancer therapeutics (Evangelou et al.,
2004). Aberrant signaling by the AR is thought to play a key role in the initiation and
progression of prostate cancer. Molecular chaperones mediate the folding,
translocation, activation, and degradation of steroid hormone receptors (Caplan et al.,
1995; Frydman and Hohfeld, 1997) providing different points along the androgen-
signaling axis where regulation of AR activity can be hijacked to provide growth
signals for clonal selection in cancer progression.
Experimentally varying the levels of the AR-interacting co-chaperone,
αSGT, was found to influence AR activity in vitro. Additional work by the Tilley
laboratory reveals in vivo levels of αSGT appear to decrease with prostate cancer

117
progression. It would be interesting to determine whether functional polymorphisms
exist within the coding region or regulatory regions of αSGT that would dictate the
protein level within cells. Future association studies could then be implemented to
assess whether these polymorphisms are disease-causing variants. Alternatively, the
decrease in αSGT expression with disease progression in human prostate cancer
samples may occur through epigenetic silencing. A CpG island overlaps the
proximal promoter and first exon of αSGT. Aberrant DNA methylation of the CpG
island would silence αSGT expression. To investigate this possibility we could
examine whether αSGT is reexpressed in prostate tumors from patients treated with
demethylating drugs, such as 5-aza-2’-deoxycytidine, as compared to patients
undergoing different treatment options.
Discovery of AR target genes and the corresponding regulatory cis-elements
not only reveals potential key regulators of downstream androgen-signaling
pathways, but it also provides additional models for the study of AR transcriptional
regulation. Of particular interest is the mechanism by which AR represses target
genes, which are likely to be growth inhibitory and pro-apoptotic (Hendriksen et al.,
2006). Uncovering the mechanisms of gene repression would allow us the ability to
tailor therapeutic drugs to specifically target those mechanisms in advanced prostate
cancer where AR signaling has reemerged to upregulate potentially pro-apoptotic
genes.
Even though an AR binding site may reside within relatively close proximity
to an androgen-regulated gene, discerning direct regulation of the gene from a distal
cis-elements is difficult. However, the recently developed chromosome conformation

118
capture (3C) assay provides a means for detecting direct interactions between a
putative distal regulatory element and the promoter region of a gene (Dekker, 2006).
The identification of regulatory elements would also help direct the selection
of SNPs of novel candidate prostate cancer genes for association studies without
limiting the search to the proximal promoter and coding regions. Genetic testing
based on susceptibility genes would promote the identification of individuals in the
early stages of disease, when it is most curable. With such a high prevalence of this
disease, advancement in the prevention or treatment of prostate cancer is likely to
have a significant public health impact.

119
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Abstract (if available)

Abstract The androgen receptor (AR) plays pivotal roles in the initiation and progression of prostate cancer, which is a major health burden worldwide. Initially, the disease is androgen-dependent and readily responds to androgen-ablation therapies. However, after a relatively short period of ablation therapy, the tumor returns as a more aggressive androgen-ablation resistant disease for which there are no effective therapies. Thus, the detection of prostate cancer at an early curable stage, as well as understanding the mechanisms of cancer progression are of utmost importance.

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University of Southern California Dissertations and Theses

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Asset Metadata

Creator Prescott, Jennifer (author)

Core Title Co-chaperone influence on androgen receptor signaling and identification of androgen receptor genes in prostate cancer

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Molecular Epidemiology

Publication Date 04/21/2007

Defense Date 03/28/2007

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag androgen receptor,chaperone,OAI-PMH Harvest,prostate cancer,repression

Language English

Advisor Coetzee, Gerhard A. (committee chair), Frenkel, Baruch (committee member), Garner, Judy A. (committee member), Ingles, Sue A. (committee member), Ursin, Giske (committee member)

Creator Email jstepcic@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m435

Unique identifier UC1464006

Identifier etd-Prescott-20070421 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-496233 (legacy record id),usctheses-m435 (legacy record id)

Legacy Identifier etd-Prescott-20070421.pdf

Dmrecord 496233

Document Type Dissertation

Rights Prescott, Jennifer

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu