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Functional analysis of single nucleotide polymorphisms (SNPs) in the 5' regulatory region on the SRD5A2 gene

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Functional analysis of single nucleotide polymorphisms (SNPs) in the 5' regulatory region on the SRD5A2 gene

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Content FUNCTIONAL ANALYSIS OF SINGLE NUCLEOTIDE POLYMORPHISMS
(SNPs) IN THE 5’ REGULATORY REGION OF THE SRD5A2 GENE
by
Albert H. Kim
A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(BIOCHEMISTRY AND MOLECULAR BIOLOGY)
May 2005
Copyright 2005 Albert H. Kim
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UMI Number: 1427978
Copyright 2005 by
Kim, Albert H.
All rights reserved.
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DEDICATION
I would like to dedicate this work to my mother and father who have given me
nothing short of the best in every aspect of my life, to my sister for always believing
in me and giving me inspiration and guidance, to my brother for his loyalty,
generosity and support, and to Leslie who has brought out the best in my abilities. I
love you all and I would never have gotten this far without each and every one of
you lifting me through the hard times and encouraging me every step of the way.
Lastly, Dad, I know you think that I never listened to any of your advice when we
had our “talks,” but I did, and I will always remember you telling me not to be
satisfied with doing just enough, or only what is required of me, but to push myself
to use my full abilities to accomplish even greater things. I have tried to live up to
these words, and for that I thank you.
Don't measure yourself by what you have accomplished, but by what you should
have accomplished with your ability.
--John Wooden
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ACKNOWLEDGEMENTS
Without these people, this work would not be possible. I would like to thank Dr.
Juergen Reichardt for the opportunity to conduct research in his laboratory for the
past 3 years. Starting as an Edmondson Summer Research Fellow and extending
into the M.S. program, Juergen has always provided firm guidance and honest
advice that has helped me achieve my goals. His extreme skepticism and idealistic
approach to science has trained me to strive for perfection, which will undoubtedly
serve me well in my future as a physician scientist.
I would also like to thank Dr. Nick Makridakis for his patience and “tough love”
teaching style which helped me develop into an independent researcher. He has
been a tremendous mentor and friend and I feel lucky to have had him there to
guide me through my graduate studies.
I thank my committee members, Dr. Zoltan Tokes for believing in my abilities and
giving me unwavering support, and Dr. Hooman Allayee for his enthusiasm for
science and student-friendly nature.
Lastly, I would like to thank everyone in the IGM especially Troy Phipps, for
answering any and all of my questions. He is the “rock” in the lab and has always
given me great encouragement and support. He is also probably the only man in
the lab who is more meticulous than I, and for this I appreciate and respect him as a
scientist and friend. I would also like to thank Frank Luh, without whom I would not
have had the success that I have had in my graduate education. Thank you for
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everything, I consider you as a brother. To Prutha, Lucy, Hanh, Dolly, Susan,
Phung, Natalie, Tommy, and Chirag, you have all played important roles in my
development as a scientist, but more importantly, as a person, and for that I thank
you.
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TABLE OF CONTENTS
v
DEDICATION...................................................................................................................ii
ACKNOWLEDGEMENTS...............................................................................................iii
LIST OF TABLES.......................................................................................................... vii
LIST OF FIGURES....................................................................................................... viii
ABSTRACT......................................................................................................................x
CHAPTER I: INTRODUCTION.......................................................................................1
I. A. Risk Factors.........................................................................................................2
A ge........................................................................................................................... 2
Race/Ethnicity..........................................................................................................3
Family History..........................................................................................................4
Diet........................................................................................................................... 5
I. B. Prevention/Detection...........................................................................................6
I. C. The SRD5A2 Gene and Prostate Cancer......................................................... 6
I. D. Prostate Cancer Prevention Trial (PCPT)........................................................10
I. E. Molecular Markers: Single Nucleotide Polymorphisms (SNPs).....................12
I. F. Transcriptional Regulation— Promoters and Transcription Factors.................15
Homeodomain........................................................................................................ 17
Helix-Loop-Helix (HLH).........................................................................................18
Zinc Finger..............................................................................................................18
Leucine Zipper[39].................................................................................................18
CHAPTER II: MATERIALS AND METHODS..............................................................20
II. A. SNP Identification............................................................................................. 20
II. B. Plasmid Construction........................................................................................20
II. C. Site-directed Mutagenesis............................................................................... 21
II. D. Transformation..................................................................................................22
II. E. Plasmid Purification..........................................................................................23
II. F. DNA Sequencing.............................................................................................. 23
II. G. Cell Line Determination....................................................................................26
II. H. Transfection......................................................................................................26
ll.l. Bradford Assay...................................................................................................27
II. J. /?-Galactosidase Assay......................................................................................27
ILK. Luciferase Assay.............................................................................................. 28
ILL. Reporter Gene Analysis....................................................................................28
II. M. Gel Shift Assay.................................................................................................28
CHAPTER III: RESULTS...............................................................................................32
III. A. Controls.............................................................................................................32
III. B. Transfections....................................................................................................37
III. C. Transcription Factors..................................................................................... 40
III. D. Gel-Shift Experiments.................................................................................... 42
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VI
CHAPTER IV: DISCUSSION....................................................................................... 54
IV. A. Reporter Gene Analysis............................................................................... 54
IV. B. Gel Mobility Shift Assays................................................................................55
CHAPTER V: CONCLUSION...................................................................................... 58
V. A. Future Directions..............................................................................................58
REFERENCES..............................................................................................................61
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vii
LIST OF TABLES
Table 1: Mutagenic Primer Sequences.......................................................................21
Table 2: Cycling Parameters for Mutagenesis............................................................ 22
Table 3: PCR Sequencing Conditions......................................................................... 24
Table 4: Primers for Gel Shift Experiment...................................................................29
Table 5: Data for transfection of triplicate clones for each SNP in COS-7 and PC-3
cells. Note: Ratios are taken from normalized RLU values................................ 38
Table 6: Summary of relative activation of each SNP in COS-7 and PC-3 cells 40
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LIST OF FIGURES
vni
Figure 1: Anatomy of the prostate (adapted from www.cancer.org)..............................1
Figure 2: SEER data for prostate cancer incidence between age categories for
Caucasian males in the United States...................................................................2
Figure 3: Age-adjusted incidence and mortality of prostate cancer in the U.S.
(adapted from SEER).............................................................................................. 3
Figure 4: Racial/ethnic variance in prostate cancer incidence (adapted from
http://seer.cancer.gov/faststats/html/inc_prost.html)............................................ 4
Figure 5: Schematic of androgen metabolism leading to increased cell division in the
prostate. Steroid abbreviations: Preg (pregnenolone), DHEA
(dehydroepiandrosterone), 4-dione (4-androstenedione), T (testosterone), DFIT
(dihydrotestosterone), 3-alpha-Diol (3-alpha-androstanediol), 3-beta-Diol (3-
beta-androstanediol), AR (androgen receptor). Adapted from Makridakis and
Reichardt [12]...........................................................................................................7
Figure 6: SRD5A2 gene...................................................................................................8
Figure 7: Conversion of testosterone to dihydrotestosterone.......................................8
Figure 8: Mechanism of transcriptional activation in the prostate.
(Adapted from http://hcp.prostateline.com)............................................................9
Figure 9: Chemical structure of the steroid 5-alpha reductase inhibitor finasteride. 11
Figure 10: Initiation of transcription of a eukaryotic gene by RNA polymerase II.
(Adapted from Alberts et al., Molecular Biology of the Cell, 4th ed.)................ 15
Figure 11: Consensus sequences found in the vicinity of eukaryotic RNA
polymerase II start points. (Adapted from Molecular Biology of the Cell)........16
Figure 12: Expression vector with SRD5A2 promoter insert...................................... 20
Figure 13: Wild-Type and Mutant Sequences of -A647C........................................ 25
Figure 14: Wild-Type and Mutant Sequences of -A645T........................................ 25
Figure 15: Wild-Type and Mutant Sequences of -G382A........................................ 25
Figure 16: Wild-Type and Mutant Sequences of -C216A........................................ 26
Figure 17: DNA Titration Experiment for COS-7 Cells................................................32
Figure 18: DNA Titration Experiment for PC-3 Cells................................................... 33
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IX
Figure 19: Schematic-Optimal Confluency Experiment............................................34
Figure 20: Results-Optimal Confluency Experiment.................................................34
Figure 21: Schematic—Optimal Time of Harvest Experiment...................................35
Figure 22: Results-Optimal Time of Harvest Experiment..........................................36
Figure 23: Comparison of cell lysis methods..............................................................37
Figure 24: Transfection schematic (WT=Wild-type, EV=Enhancer vector control).. 38
Figure 25: Average activation of SNP over wild-type in COS-7 and PC-3 cells......39
Figure 26: Schematic of putative transcription factor binding.....................................41
Figure 27: Gel-shift schematic. Lane 1=Probe only; Lane 2=probe+cell extract(CE);
Lane 3=probe, CE, 10X cold probe; Lane 4=probe, CE, 100X cold probe 42
Figure 28: Gel shift using -A647C probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom)...................................................................................43
Figure 29: Gel shift using -A645T probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom)...................................................................................44
Figure 30: Gel shift using -G382A probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom)...................................................................................45
Figure 31: Gel shift using -C216A probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom)...................................................................................46
Figure 32: Gel-shift schematic. Lane 1=Probe only; Lane 2=Probe + CE; Lane
3=Probe, CE, 10X cold probe (self); Lane 4=Probe, CE, 10X cold probe (non
self); Lane 5=Probe, CE, 100X cold probe (self); Lane 6= Probe, CE, 100X
cold probe (non-self)..............................................................................................48
Figure 33: Competition gel shift using -A647C probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom).......................................... 49
Figure 34: Competition gel shift using -A645T probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom).............................................................................. 50
Figure 35: Competition gel shift using -G382A probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom)...................................................................................51
Figure 36: Competition gel shift using -C216A probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom)................................................................................... 52
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X
ABSTRACT
The human steroid 5-alpha reductase type II enzyme (encoded by the SRD5A2
gene) has been implicated in prostate carcinogenesis for its role in catalyzing the
conversion of testosterone to DHT, a potent androgen responsible for cellular
growth and differentiation in the prostate. Four SNPs in the promoter region of the
SRD5A2 gene were characterized in two mammalian cell lines, COS-7 and PC-3.
The results revealed three SNPs— A647C, -A645T, and -G382A—confer a
significant activation of 1.33 + 0.14,1.39 + 0.09, and 1.40 ± 0.12-fold respectively
over wild-type in COS-7 cells and 1.51+0.07, 1.47+0.08, and 1.36+0.06-fold
respectively in PC-3 cells (p<0.05). Gel shift assays were subsequently performed
to gain insight into the mechanism responsible for this activation. However, no
differences could be seen in protein binding between mutant and wild-type probes,
suggesting the activation seen previously is not a result of the binding of a novel
transcription factor.
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1
I. INTRODUCTION
The adult prostate is a walnut-sized gland that lies immediately below the urinary
bladder surrounding the upper part of the urethra (Figure 1). The urethra carries urine
from the bladder and semen from the sex glands out through the penis. The main
function of the prostate gland is to secrete a milky, alkaline fluid (one of the
components of semen) into the urethra at the point of ejaculation (Figure 1). This fluid
helps to nourish and protect the sperm during intercourse and forms the main bulk of
the ejaculate volume.
Figure 1: Anatomy of the prostate (adapted from www.cancer.org/docroot/CRI/content).
In 2005, the American Cancer Society estimates that in the United States, 232,090
men will be diagnosed with prostate cancer and 30,350 men will die of the disease,
making it the second leading cause of cancer death in the U.S., exceeded only by
lung cancer (American Cancer Society Website). With the aging of the U.S.
population and improved detection, an increase in the incidence rate has occurred in
recent years. Yet, despite the huge burden of prostate cancer in this country,
relatively little is known about its causes. Currently, the most noted risk factors for
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2
prostate cancer include age, race/ethnicity, and family history, although other factors
such as diet have been well-documented.
I. A. Risk Factors
Age
Prostate cancer incidence increases dramatically with age, with men over the age of
65 at highest risk and increasing steadily so that by the age of 90, a man has almost
a 100% chance of having prostate cancer[1]. As Figure 2 shows, there are dramatic
increases in the number of prostate cancer cases between age categories. The sharp
rise in incidence with age is a hallmark of this cancer and according to a study by the
Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer
Institute, 60 percent of all newly diagnosed prostate cancer cases and almost 80
percent of all deaths occur in men 70 years of age and older.
Rate per 100,000
2500
Detailed View
Age <65
2000
1500
Age 75+
1000
Age 65-74
500
Age < 65
K
Y ear of Diagnosis
Figure 2: SEER data for prostate cancer incidence between age categories for
Caucasian males in the United States.
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3
Race/Ethnicity
Interestingly, prostate cancer is also characterized by a marked variation of incidence
in racial and ethnic populations in the United States. As figure 3 shows, the risk of
prostate cancer is approximately 60% higher in African Americans than in whites, and
mortality in African Americans is approximately double that of whites. Furthermore,
SEER shows an interesting variation in racial/ethnic incidence of prostate cancer by
year—highest in African-Americans, intermediate in Caucasians and Hispanics, and
lowest in Asian/Pacific Islanders (Figure 4). Conflicting data exists however as to
whether this trend is explained by differences in environment and socioeconomic
status, or whether an inherent difference exists between these racial/ethnic groups in
the underlying biology of the disease.
400
267
Incidence-Black
168
Incidence-W hite
100
Mo rtaN ty-_Bl a ck
C l
29
M ortality-W hite
1973 1978 1983 1988
Year of Diagnosis/Death
1999
Figure 3: Age-adjusted incidence and mortality of prostate cancer in the U.S.
(adapted from SEER).
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4
300
250
200
S'
c s W hite
Hispanic
Asian or Pacific Islander
100 A -
...❖
50
Am erican Indian/Alaska Native
1994 1995 1 9 9 2000 2001
Year o f diagnosis
Figure 4: Racial/ethnic variance in prostate cancer incidence (adapted from
http://seer.cancer.gov).
Family History
Case control analysis has identified familial patterns of prostate cancer[2], perhaps
the most revealing being the study performed by Steinberg et al. at Johns Hopkins
University. Extensive cancer pedigrees were obtained on 691 men with prostate
cancer and 640 spouse controls to estimate the relative risk of developing prostate
cancer for men with a positive family history. The results showed that men with a
father or brother affected were twice as likely to develop prostate cancer compared to
men with no relatives affected. Furthermore, a trend of increasing risk with increasing
number of affected family members was discovered, such that men with two or three
first degree relatives affected had a five to 11-fold increased risk of developing
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5
prostate cancer[3]. Thus, taken together with the variability seen in racial/ethnic
incidence, there can be no doubt that a genetic component to prostate cancer exists.
Diet
A trio of dietary antioxidants has been linked to the reduced risk of prostate cancer—
selenium, vitamin E, and lycopene. In the case of selenium and vitamin E, the
associations were observed in clinical trials that were originally designed to address
other endpoints. In one study, men at increased risk for a recurrence of skin cancer
were randomly assigned to 200 ug/day of selenium or placebo. Although the effects
on skin cancer were null, there was a 67% reduction in prostate cancer in the group
receiving selenium[4]. Similarly, in the Alpha-Tocopherol Beta-Carotene Cancer
Prevention Study, the group receiving alpha-tocopherol (vitamin E) at a dose of 50
mg/day experienced a 35% reduction in prostate cancer incidence[5]. These post
hoc findings, together with supportive evidence from some observational studies, led
to the development of the Selenium and Vitamin E Cancer Prevention Trial (SELECT)
in the United States.
Recently, another major dietary carotenoid compound, lycopene, has become the
focus of considerable attention. Lycopene, which enters the body largely from the
consumption of tomato foods, is the predominant carotenoid in the diet of most
Americans. In the Physicians’ Health Study, plasma obtained long before diagnosis
in 578 cases was compared to plasma in 1294 matched controls[6]. The results
show a strong trend towards lower risk with higher plasma lycopene levels,
suggesting that one could reduce prostate cancer risk 40% by consuming a diet high
in lycopene.
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I. B. Prevention/Detection
The two most commonly administered tests for the early detection of prostate cancer
include the prostate-specific antigen (PSA) blood test, and the digital rectal
examination (DRE). Prostate-specific antigen is a substance made by the normal
prostate gland. Although PSA is mostly found in the semen, a small amount is found
in the blood. When prostate cancer develops, the PSA level increases. However,
because PSA levels can be affected by a variety of other factors such as prostatitis
(inflammation of the prostate gland), benign prostatic hyperplasia (BPH), herbal
dietary supplements, and age, the PSA test should be interpreted rather loosely.
The other common screening for prostate cancer is accomplished by the digital rectal
examination. During this exam, a doctor inserts a gloved, lubricated finger into the
rectum to feel for any irregular or firm area that might be cancerous. The prostate
gland is located just in front of the rectum, and most cancers can be reached by a
rectal exam. Although uncomfortable, the exam causes no pain and only takes a
short time. The DRE is known to be less effective than the PSA test, but it can
sometimes find cancers in men with normal PSA levels. Thus, when screening is
done, it is recommended to administer both the PSA and DRE tests.
I. C. The SRD5A2 Gene and Prostate Cancer
Genes involved in androgen metabolism have long been implicated in the etiology of
prostate cancer[7]. The earliest evidence coming in 1941 when Huggins and Hodges
demonstrated the successful use of castration as a therapeutic modality in the
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7
treatment of metastatic prostate cancer[8]. Subsequent studies have demonstrated
high levels of androgens in the blood, namely testosterone, to be associated with an
approximately 2.5-fold increase in risk for developing prostate cancer[9].
Furthermore, when administered in large amounts, androgens have been found to
produce prostate cancer in rodents[10,11]. Figure 5 depicts the role of the four major
genes studied in the androgen metabolic pathway which include the androgen
receptor gene, the 17-hydroxlylase cytochrome P450 gene (CYP17), the 3-beta-
hydroxysteroid dehydrogenase type II gene (HSD3B2), and the steroid 5-alpha-
reductase type II gene (SRD5A2). Flowever, the most extensive work has been done
on the SRD5A2 gene and the androgen receptor (AR) due to the major role they play
in androgen stimulation within prostate epithelial cells.
HSD3B2 gene -
1
3 p-Hydroxystei 01 c l
Dehvdrosenase
Pres; ►DHEA 4-D ione
17a-H ydroxylase
1 ' 20-Lvnse
f
C YP 1" gene
3p-Diol
/
3p-Hydroxy steroid / 3 a -D io l
Dehydrogenase /
5a-Reductase
t
SRD5A2 gene
D H T
Androgen
Receptor
A R
gene
D H T /A R
Complex
1
Transactivation
I
Cell Division
Figure 5: Schematic of androgen metabolism leading to increased ceil division in the
prostate. Steroid abbreviations: Preg (pregnenolone), DHEA
(dehydroepiandrosterone), 4-dione (4-androstenedione), T (testosterone), DHT
(dihydrotestosterone), 3-alpha-Diol (3-alpha-androstanediol), 3-beta-Diol (3-beta-
androstanediol), AR (androgen receptor). Adapted from Makridakis and Reichardt [12].
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The SRD5A2 gene spans over 40 kilobases of genomic DNA and is comprised of five
exons and four introns (Figure 6). It is located on the short arm of human
chromosome 2 (band 2p23).
350bp 165bp 101bp 150bp 1676bp
3.0kb 1.9kb 2.1 kb 4S.8kb
5’ Regulatory Region
Exon I Exon II Exon III Exon IV Exon V
3'
Figure 6: SRD5A2 gene.
Two isozymes of 5-alpha reductase have been characterized in humans. Type I,
encoded by the SRD5A1 gene is expressed primarily in the newborn scalp, skin, and
liver, while type II, encoded by the SRD5A2 gene is expressed primarily in the genital
skin and the prostate gland[13]. Of the two isozymes, the type II enzyme is more
active in prostate tissue. Steroid 5-alpha-reductase is a membrane-bound enzyme
that catalyzes the irreversible conversion of testosterone to dihydrotestosterone
(DHT), using NADPH as a cofactor[14] (Figure 7).
5-alpha-reductase type II
NADPH NADP+ H
Di hydrotestosterone
Testosterone
Figure 7: Conversion of testosterone to dihydrotestosterone.
This reaction usually occurs once testosterone has entered the prostate cell and
although both testosterone and DHT can bind to the androgen receptor, DHT exhibits
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9
a higher binding affinity for, and lower dissociation rate from the AR, which acts as a
transcription factor. The DHT-AR complex then translocates to the nucleus where it
binds as a homodimer to the androgen responsive element (ARE), a specific DNA
site in the promoter of androgen-responsive genes (Figure 8). This binding then
facilitates transcriptional activation of a number of androgen responsive genes,
including those that control cell division[15].
Thus, due to their importance in the control of cellular proliferation in the prostate,
numerous studies have investigated the relationship of the SRD5A2 gene and DHT
with prostate cancer progression and risk[16].
DMA
re p lic a tio n
'. - . t - k Su-reductasel DHT Dihydrolestosterorie ntsrogen receptor
Figure 8: Mechanism of transcriptional activation in the prostate.
(Adapted from http://hcp.prostateline.com).
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10
It has also been found that in humans, a deficiency in 5-alpha-reductase causes a
rare disorder of male sexual differentiation, pseudohermaphroditism. Males affected
exhibit genital ambiguity and external female characteristics until puberty at which
point there is some development of male secondary sex characteristics, but the
prostate remains highly underdeveloped[17]. Similarly, it has been reported that mice
lacking steroid 5-alpha-reductase type II experience a mild virilization defect marked
by a reduction in the size of their secondary sex glands[18]. Thus, it can be seen that
normal prostate development requires normal function of the SRD5A2 gene.
Finally, studies have also been done on inhibitors of 5-alpha reductase, perhaps the
most significant being that of the Prostate Cancer Prevention Trial.
I. D. Prostate Cancer Prevention Trial (PCPT)
Because the prostate and most primary prostate tumors depend on androgens for
growth and the avoidance of apoptosis, standard therapy in prostate cancer relies on
removing, or blocking the actions of androgens. Several competitive inhibitors of
prostatic steroid 5-alpha reductase exist, the best known being finasteride.
Finasteride, which selectively inhibits type II [19], is a steroidal analog of testosterone
that functions as a reversible competitive inhibitor (Figure 9).
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Figure 9: Chemical structure of the steroid 5-alpha reductase inhibitor finasteride.
With this knowledge, in October of 1993, the Prostate Cancer Prevention Trial
(PCPT) was initiated, its main objective being to see whether the drug finasteride
(trade name Proscar), could prevent prostate cancer in men age 55 and older.
18,882 men enrolled in the study (92 percent Caucasian, 4 percent African-American,
4 percent other race/ethnicity), were randomly assigned to take either 5 milligrams of
finasteride or placebo once daily for seven years. All men had an annual DRE and
PSA test. At the end of seven years, men who had not been diagnosed with prostate
cancer were asked to have a prostate biopsy to see if they were truly cancer free.
In June 2003, the PCPT was stopped early because of the clear finding that
finasteride reduced the incidence of prostate cancer. Prostate Cancer was detected
in 803 of the 4368 men in the finasteride group who had data for the final analysis
(18.4 percent) versus 1147 of the 4692 men in the placebo group (24.4 percent),
indicating a 24.8 percent reduction in prevalence over the seven year period
(p<0.001 )[20]. These results suggest that finasteride prevents or delays the
appearance of prostate cancer. However, those trial participants that did develop
prostate cancer while taking finasteride experienced a slightly higher incidence of
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12
high-grade tumors. Ongoing research is being done to find out if finasteride actually
caused the high-grade tumors.
I. E. Molecular Markers: Single Nucleotide Polymorphisms (SNPs)
The most common type of human genetic variation is the single nucleotide
polymorphism (SNP), a position at which two alternative bases occur at appreciable
frequency in the human population. Over 1.4 million SNPs have been identified, an
average of one for every 2.0 kilobases of sequence (SNP Group, 2001). Many of
these SNPs have no effect on the function of the genome but many others do. An
estimated 60,000 SNPs lie within genes and at least some of these have an impact
on gene activity, leading to the variations that give each of us our own individual
biological characteristics^]. Thus, due their very high marker densities and
allowance for ultra-high throughput genotyping[22], SNPs are ideal for use as genetic
markers for identifying disease genes by linkage studies in families, linkage
disequilibrium in isolated populations and association analysis of patients and
controls[23].
The associations between prostate cancer risk and several sequence variants in the
SRD5A2 gene have been investigated. More than 22 mutations, including 10
missense substitutions have been reported[24], the most significant being the A49T
(alanine to threonine at codon 49) missense mutation. Makridakis et al. showed the
A49T mutation is associated with a 7.2-fold increased risk of advanced prostate
cancer in African-American men (p=0.001), and a 3.6-fold increased risk in Latino
men (p=0.04)[12]. Additionally, when the A49T mutation was constructed in wild-type
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13
SRD5A2 cDNA, the mutant enzyme was found to have a higher in vitro Vmax than
the wild-type enzyme[25]. Thus, it is postulated that the A49T mutation might lead to
a higher rate of formation of DHT and ultimately raise the risk of more aggressive
prostate cancer. Subsequently, Jaffe et al. conducted a case-control analysis of 265
Caucasian men treated with radical prostatectomy and confirmed the
overrepresentation of the A49T variant, suggesting the mutation may influence the
pathological characteristics of prostate cancer[26]. Schatzl et al. also found that
individuals carrying the mutant T allele had larger prostates, higher PSA levels and
lower testosterone levels suggesting the T allele confers an increase in activity of the
5-alpha-reductase enzyme[27],
Makridakis et al. have also characterized a missense substitution V89L, which
substitutes valine with leucine at codon 89. This mutation appears to parallel prostate
cancer risk between different ethnic groups[28]. It was found that African-Americans,
the group at highest risk for prostate cancer in the United States, have the highest
frequency for the valine 89 allele, while Asians, the lowest risk population, have the
highest frequency for the leucine 89 allele, suggesting the leucine allele acts as a
protective mutation. In a Japanese population, Li et al. found that males homozygous
for the valine allele (VV) were at significantly increased risk for prostate cancer
compared with those homozygous for the leucine allele (LL)[29].
A polymorphism in the 3’ untranslated region of the SRD5A2 gene has also been
investigated. The allele frequencies of a TAn dinucleotide repeat were found to vary
among racial/ethnic groups, and a series of alleles with relatively high number of
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14
repeats were found to be unique to African-Americans[30, 31]. The most common
allele being the TA0, while TA9 and TA1 8 repeats have also been reported[32].
Despite these positive associations, other molecular epidemiological studies have
presented contradictory results concerning the potential role of these polymorphisms.
In a case control study, Hsing et al. found no statistically significant associations with
prostate cancer risk of the A49T, V89L, and TA repeat polymorphisms in the SRD5A2
gene, although the V89L and TA repeat showed a modest effect that could not be
ruled out[33]. Similarly, Chang et al. looked at the A49T, V89L, and a third
polymorphism, C682G in a case-control study and found no difference in increased
susceptibility to hereditary or sporadic prostate cancer in the study populations[34].
Others have also found only a small, non-significant protective association between
the V89L substitution and prostate cancer risk in multi-ethnic population studies[27,
31, 35, 36]. Finally, in a meta-analysis of many studies implicating the
polymorphisms as risk factors for prostate cancer, Ntais et al. found the A49T, V89L,
and TA repeat to show no difference in prostate cancer susceptibility[37]. The
seemingly contradictory results of these epidemiological studies can mostly be
attributed to the low frequency of mutant alleles and therefore, larger studies in
various racial/ethnic groups are needed to further validate the hypothesis that these
polymorphisms indeed contribute to the progression and development of prostate
cancer.
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15
I. F. Transcriptional Regulation—Promoters and Transcription Factors
One of the most important differences between the bacterial RNA polymerase and
the eukaryotic RNA polymerase II is that the latter requires the help of a large set of
proteins known as general transcription factors, which must assemble at the promoter
before the polymerase can begin transcription. These general transcription factors,
(designated TFIIA,TFIIB, and so on), help to position the RNA polymerase correctly at
the promoter, aid in pulling apart the two strands of DNA to allow transcription to
begin, and release RNA polymerase from the promoter into the elongation mode
once transcription has begun. Figure 10 shows how the general transcription
factors assemble in vitro at promoters used by RNA polymerase II.
start o f tnm scfipfiQ n
■0
- ” /7 t . . , n
T fllf s
\ ')®QQQ
RNA polym er as*?
U fP . A T r
CTP. G TP
TRANSCRIPTION
Figure 10: Initiation of transcription of a eukaryotic gene by RNA polymerase II.
(Adapted from Alberts et al., Molecular Biology of the Cell, 4th ed.)
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16
Transcription initiation begins with the binding of TFIID to a DNA sequence called the
TATA box, which is typically located 25 nucleotides upstream from the transcription
start site (AUG). It is not the only sequence that signals the start of transcription, but
for most polymerase II promoters, it is the most important. Other consensus
sequences found in the vicinity of eukaryotic RNA polymerase promoters are shown
in Figure 11.
-35 30
BRE TATA
transcription
st#fi point
r ______
ilM'R
*30
DPE
nr.i
TATA
!NR
DPE
I lilL S tT F s U S
011 .. i, • A t C i f . i
T A T .A A T A A T
e/T O T A N T/A C.-T C T
A/C G A T C G T 6
| | 0 > - V I ( | |
f.-vnor
TBP
TFIID
TFIID
Figure 11: Consensus sequences found in the vicinity of eukaryotic RNA polymerase II
start points. (Adapted from Molecular Biology of the Cell, 4th ed., Figure 6-17)
For most RNA polymerase II transcription start points, only two or three of the four
sequences are present. It should also be noted that although most DNA sequences
that influence transcription initiation are located upstream of the transcription start
point, a few such as the DPE are located in the transcribed region.
Another feature of promoters that has important consequences for their arrangement
in genomes is that they are asymmetric. Since DNA is double-stranded, two different
RNA molecules could in principle be transcribed from any gene, using each of the two
DNA strands as a template. However a gene typically has only a single promoter, and
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17
because the nucleotide sequences of eukaryotic (as well as prokaryotic) promoters
are asymmetric, the polymerase can bind in only one orientation[38]. The polymerase
thus has no option but to transcribe only one DNA strand since it can synthesize RNA
f J
only in the 5 to 3 direction. Thus, the choice of template strand for each gene is
determined by promoter location and orientation.
RNA polymerase II not only requires general transcription factors and consensus
sequences in the proper orientation, but it also requires the presence of regulatory
proteins known as transcriptional activators, which bind to specific sequences in DNA
and help to attract RNA polymerase II to the start point of transcription. These gene
regulatory proteins, or transcription factors, recognize their specific DNA sequences
using one of the following DNA binding motifs:
Homeodomain[39]
The homeodomain is a highly conserved domain of 60 amino acids found in a large
family of transcription factors. This family was first identified in Drosophila as a group
of genes that, when altered, would cause transformations of one body part for
another (i.e. legs for antenna), so called homeotic transformations. This class of
genes has been identified in both invertebrate and vertebrate organisms. The
homeodomain itself forms a structure highly similar to the bacterial helix-turn-helix
proteins. The principal function of all homeodomain containing proteins is in the
establishment of pattern in an organism such as that of the spinal column in
vertebrates.
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18
Helix-Loop-Helix (HLH)[39]
The HLH motif is composed of two regions of alpha-helix separated by a region of
variable length which forms a loop between the 2 alpha-helices. The alpha-helical
domains are structurally similar and are necessary for protein interaction with
sequence elements that exhibit a two-fold axis of symmetry. This class of
transcription factor most often contains a region of basic amino acids located on the
N-terminal side of the HLH domain that is necessary for the protein to bind DNA at
specific sequences. Examples of HLH proteins include MyoD (a myogenesis
inducing transcription factor) and c-Myc (originally identified as a retroviral oncogene).
Zinc Finger[39]
The zinc finger domain is a DNA-binding motif consisting of specific spacings of
cysteine and histidine residues that allow the protein to bind zinc atoms. The metal
atom coordinates the sequences around the cysteine and histidine residues into a
finger-like domain. The finger domains can interdigitate into the major groove of the
DNA helix. A particular advantage of this motif is that the strength and specificity of
the DNA-protein interaction can be adjusted during evolution by changes in the
number of zinc finger repeats.
Leucine Zipper[39]
The leucine zipper is a motif generated by a repeating distribution of leucine residues
spaced 7 amino acids apart within alpha-helical regions of the protein. These leucine
residues end up with their R-groups protruding from the alpha-helical domain in which
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19
the leucine residues reside. The protruding R-groups are thought to interdigitate with
leucine R-groups of another leucine zipper domain, thus stabilizing homo- or
heterodimerization. The two alpha-helices separate from each other to form a Y-
shaped structure and thus grips the double helix like a clothespin on a clothesline.
Once bound to DNA, eukaryotic gene activator proteins increase the rate of
transcription initiation by several mechanisms: (1) they interact with the RNA
polymerase II holoenzyme (RNA polymerase, general transcription factors, and
mediator), making it more energetically favorable for it to assemble on the promoter,
(2) they attract and position RNA polymerase II to specific sites on DNA, and (3) they
alter chromatin structure for greater accessibility of the DNA for the assembly of
general transcription factors and RNA polymerase II at the promoter, as well as
allowing for the binding of additional gene regulatory proteins[39]. In this way, gene
activator proteins increase the rate of transcription by acting directly on the
transcription machinery itself and by changing the chromatin structure around the
promoter.
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20
II. MATERIALS AND METHODS
II. A. SNP Identification
The SNPs were identified by personal communication from Dr. Nick Makridakis in a
blind pilot study of 25 patients and 25 controls. The DNA was extracted from blood
and the region of interest was amplified by PCR. Four SNPs were discovered,
-A647C, -A645C, -G382A, and -C216A, each occurring once.
II. B. Plasmid Construction
A 745 base pair fragment upstream of the translational start site of the human
SRD5A2 gene, (GenBank accession number L03843), was cloned into the pGL3-
enhancer vector (Promega) utilizing the Xhol and Hindlll cloning sites. Previous
primer extension analysis indicates three transcription start sites at 71, 145, and 712
base pairs upstream of the ATG initiating codon[40]. Thus, the resulting construct
contains all transcription start sites.
Figure 12: Expression vector with SRD5A2 promoter insert.
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21
II. C. Site-directed Mutagenesis
The mutations were introduced into the constructs via a PCR-based QuickChange
Site-Directed Mutagenesis Kit (Stratagene, CA, USA). First, mutagenic primers were
designed with the desired mutation in the middle of the primer according to Table 1,
making sure the melting temperature (Tm) for all primers was greater than 78°C.
Note: Bold letters indicates site of SNP.
Table 1: Mutagenic primer sequences. Note: Bold letters indicate polymorphic base.
Primer 5' --> 3' Sequence
-A647C Forward
-A647C Reverse
GGGCCGGGAGCGACTGGTACCTG
CAGGTACCAGTCGCTCCCGGCCC
-A645T Forward
-A645T Reverse
GGCCGGGAGAGTCTGGTAGCTGCC
GGCAGGTACCAGACTCTCCCGGCC
-G382A Forward
-G382A Reverse
GTGTGTTGGGGCAGAAGAACCACCC
g gg tg g ttc ttc tg c c c c aac ac ac
-C216A Forward
-C216A Reverse
CTAAGAAGGCCTTAGTTCTCCTCCGG
CCGG AGG AG AACT AAG G CCTT CTT AG
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22
Next, the mutagenesis reaction was set up for each SNP according to the
manufacturer’s recommended protocol (Stratagene, CA, USA):
5ul 10X Reaction Buffer
1.5ul Double-stranded DNA Template (30ng)
2.5ul Forward Primer (125ng)
2.5ul Reverse Primer (125ng)
1 ul dNTP Mix (25mM)
38.5ul dH20
1 ul PfuTurbo DNA Polymerase (2.5 Units)
s : 50ul
The reaction was then cycled in a PTC-100 Programmable Thermal Controller (MJ
Research, Inc.) following the parameters in Table 2.
Table 2: Cycling parameters for mutagenesis.
Segment Cycles Temperature (°C) Time
1 1 95 30 sec
2 12 95 30 sec
55 1 min
68 12 min
Dpn I (1 unit) was then added to the products of the mutagenesis reaction and
incubated for 1 hour at 37°C in order to digest the non-mutated, parental DNA.
II. D. Transformation
The resulting mutated DNA from the mutagenesis reaction was then transformed into
XL1-Blue supercompetent cells (Stratagene, CA, USA). 7ul of Dpn I treated DNA
was added to 50ul of supercompetent cells and chilled on ice for 30 minutes. The
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23
reaction was then heat pulsed for 45 seconds at 42°C and placed on ice for 2
minutes. 0.5ml_ of preheated LB broth was then added to the reaction and incubated
at 37°C for 1 hour with shaking at 225rpm. The cells were then spun down, re
suspended in 250ul pre-heated LB, plated on 10cm agar dishes with 100ug/mL
ampicillin, and incubated for 16 hours at 37°C.
II. E. Plasmid Purification
All constructs, mutant and wild-type, were isolated via alkaline lysis using Spin
MiniPrep and EndoFree MaxiPrep kits from Qiagen (Qiagen, MD, USA).
II. F. DNA Sequencing
Sequencing the constructs to confirm the desired mutation was present without
insertions, deletions, and the like, was achieved using fluorescently labeled chain
terminating dideoxy-NTPs (ddNTPs). The following master mix was used to set up
the PCR-based reaction (Applied Biosystems, CA, USA):
4ul Big Dye version 3.0 (Proprietary)
2ul 5X Dilution Buffer
0.5ul Forward or Reverse Primer (25ng)
9.5ul dH20
16ul of master mix was then added to 4ul of DNA template (300ng) giving a final
reaction volume of 20ul per reaction. Each reaction was then thermocyled following
the parameters outlined in Table 3.
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24
Table 3: PCR Sequencing Conditions
Segment Cycles Temperature (°C) Time
1 1 96 3 min
2 30 96 3 sec
50 15 sec
60 4 min
3 1 4 2 min
To purify the reaction, the PCR products were then run through Auto-Seq G-50 size
exclusion columns, speed vacuumed, and re-suspended in formamide. The reactions
were then loaded into a 96-well plate and heat denatured at 95°C. After cooling on
ice for 10 minutes, the plate was then loaded into the ABI 3100 Genetic Analyzer to
be sequenced using fluorescently labeled dNTPs. Sequence analysis software was
used to analyze the DNA sequences (GeneScan).
Mutagenesis, transformation, and plasmid purifications were performed until three
clones for each of the four SNPs, -A647C, -A645T, -G382A, and -C216A were
obtained and confirmed by sequencing (Figures 13-16). In addition, digestions were
performed with Hindlll and Xhol, the restriction enzymes used to clone in the
promoter fragment, to re-confirm the constructs were indeed correct.
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25
WT -A647 C* Mutant -ABAJC*
G G
Figure 13: Wild-type and mutant sequences of -A647C.
Note: * indicates reverse strand was used for sequencing
W T -A645T’ Mutant -A645T"
Figure 14: Wild-type and mutant sequences of -A645T.
Note: * indicates reverse strand was used for sequencing
WT -G382A
Mutant -G382A
Figure 15: Wild-type and mutant sequences of -G382A.
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26
WT -C216A Mutant -C216A
Figure 16: Wild-type and mutant sequences of -C216A.
II. G. Cell Line Determination
Two different cell lines were used to express the constructs, COS-7, stemming from
African green monkey kidney cells (www.atcc.org), and PC-3, stemming from human
prostate adenocarcinoma cells (www.atcc.org). The COS-7 cells, not expressing the
SRD5A2 gene, were used as a negative control for the PC-3 cells which do express
the SRD5A2 gene. COS-7 cells were cultured in Dulbecco’s Modified Eagle Medium
(Gibco) and PC-3 cells were cultured in RPMI 1640 (Cellgro), both were
supplemented with 5% fetal bovine serum (FBS), 2mM glutamine, and 1% Antibiotic-
Antimycotic (Gibco).
II. H. Transfection
Transfection was accomplished by lipofection, using 4ul LipofectAMINE reagent and
6ul PLUS reagent from Invitrogen. The cells were transfected in six-well clusters at
70% confluency and harvested at 100% confluency 48 hours post-transfection.
(Medium on cells was changed at 24hrs). Each experiment required 0.6ug and 0.8ug
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27
of DNA for COS-7 and PC-3 cells respectively, to be co-transfected with 25ng of
pCMV(3 plasmid (P-Galactosidase) to normalize for transfection efficiency.
Cells were harvested at 100% confluency 48 hours post-transfection and suspended
in 450uL of a storage buffer comprised of 10mM potassium phosphate at pH 7.4,
150mM potassium chloride, and 1mM EDTA. The cell extract was then subjected to
three rounds of sonication, each round consisting of sonication at 3.0 Watts for 15
seconds and cooling on ice for 15 seconds. The resulting cell extract was then stored
at -80°C for future use.
II. I. Bradford Assay
The Bradford assay for total protein was conducted using 20ul of cell extract and 100
ul of a 1:4 solution of Protein Assay Reagent (Bio-Rad, CA, USA). The reactions
were incubated at room temperature for at least 5 minutes and measured at a
wavelength of 595 nm on a spectrophotometer. Prior to performing the assay, a
bovine serum albumin (BSA) standard curve was determined using 5, 10, 15, 20, and
25 ug of BSA respectively. The total protein concentration could then be determined
by extrapolating the optical density of the samples at 595nm on the standard curve.
II. J. p-Galactosidase Assay
In order to normalize for transfection efficiency, p-Galactosidase assays were
performed using a uniform amount of protein for all experiments. The appropriate
amount of cell extract (extrapolated from the total protein assay) was mixed with
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28
270ul of a solution containing 0.1 M Magnesium Chloride, 0.1 M Sodium Phosphate
(pH 7.5), and 1X ONPG substrate (4mg/mL). The reactions were stopped at the
same time at least 5 minutes after the start of the reaction by adding 500ul 1M
Sodium Carbonate and subsequently measured at a wavelength of 420nm.
II. K. Luciferase Assay
The luciferase assay was conducting by pipetting 20ul of cell extract into a 96-well
plate. The plate was then loaded into a microtiter plate luminometer (Dynex
Technologies, VA, USA) which automatically injected 100ul of Luciferase Assay
Substrate (Promega, Wl, USA) per well. Immediately following the injection of
substrate, flash readings were recorded by a luminometer for a period of 10 seconds.
II. L. Reporter Gene Analysis
The readings from the luminometer, given as relative luciferase units (RLU), were
normalized for protein and for transfection efficiency by division of the raw RLU value
by the specific activity of the p-Galactosidase enzyme (umol/min/mg protein).
II. M. Gel Shift Assay
The gel shift assay can be divided into five stages: (1) labeling the DNA probe, (2)
making the nuclear cell extract, (3) pouring a nondenaturing acrylamide gel, (4)
setting a binding reaction of the nuclear cell extract and the DNA probe, and (5)
electrophoresis of the protein-DNA complexes through the gel and autoradiography.
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29
Forward and reverse 31-mer oligonucleotides were ordered from Integrated DNA
Technologies corresponding to the SNP and wild-type sequences in the promoter
region of the gene (Table 4). Note: Bold letter indicates SNP at that position and the
same wild-type probe was used for both -A647C and -A645T SNPs due to their
closeness in position. They were then annealed and labeled with gamma-ATP
(Amersham, NJ, USA) via the polynucleotide kinase enzyme (PNK) from Gibco. The
resulting labeled probe was then purified through a size exclusion column and
counted using a scintillation counter.
Table 4: Primers for gel shift experiment. Note: Bold letters indicate polymorphic base.
Primer 5' --> 3' Sequence
WT 647/645 Forward AATTAGGGCCGGGAGAGACTGGTACCTGCCG
WT 647/645 Reverse CG G C AG GT ACC AGT CTCTCCCG G CCCT A ATT
-A647C Reverse
-A647C Forward AATTAGGGCCGGGAGCGACTGGTACCTGCC
CGGCAGGTACCAGTCGCTCCCGGCCCTAATT
-A645T Reverse
-A645T Forward TTAGGGCCGGGAGAGTCTGGTACCTGCCGGG
CCCGGCAGGTACCAGACTCTCCCGGCCGTAA
WT -G382A Forward GGTGTGTGTTGGGGCGGAAGAACCACCCCAG
WT -G382A Reverse CTGGGGTGGTTCTTCCGCCCCAACACACACC
-G382A Forward
-G382A Reverse
GGTGTGTGTTGGGGCAGAAGAACCACCCCAG
CTGGGGTGGTTCTTCTGCCCCAACACACACC
WT -C216A Forward AACTAAGAAG GCCTTCGTTCTCCTCCG G CCA
WT -C216A Reverse TGGCCGGAGGAGAACGAAGGCCTTCTTAGTT
-C216A Forward
-C216A Reverse
AACTAAG AAGGCCTTAGTTCTCCTCCGGCCA
TG G CCG G AG G AG AACTAAGG CCTTCTTAGTT
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The nuclear cell extract was made by starting out with one confluent 10 cm dish
(approximately 1X 10^ cells) and subjecting the cells to a low salt buffer, buffer A
(10mM HEPES-KOH pH 7.9, 1.5mM MgCI2, 10mM KCI, 0.5mM Dithiothreitol, 0.2mM
Phenyl Methyl Sulfonyl Flouride (PMSF)), and then to a high salt buffer, buffer C
(20mM HEPES-KOH ph 7.9, 25% Glycerol, 420mM NaCI, 1.5mM MgCI2, 0.2mM
EDTA, 0.5mM Dithiothreitol, 0.2mM (PMSF)[41j. The protein concentration of the
extract was then quantified by the Bradford assay.
6% acrylamide gel was poured according to the following protocol[42]:
6.0mL 10x TBE electrophoresis buffer
12mL 50% Glycerol (add 10% glycerol by volume)
8.57mL 40% Acrylamide/Bis-acrylamide (37.5:1)
33.21 mL dH20
150ul 30% Ammonium Persulfate (APS)
70ul TEMED
With the nuclear cell extract prepared and the gel poured, the binding reactions were
then ready to be set. First, two master mixes were made containing 0.1 ul of freshly
labeled mutant and wild-type probe respectively, which was then mixed with 6.51 ul of
binding buffer (20mM HEPES pH 7.4, 1mM MgCI2, and 2mM EDTA pH 8.0). Next,
another separate master mix was made containing glycerol, BSA, non-specific carrier
DNA (pGL3-Basic Vector), and 10ug of cell extract[42]. The appropriate volumes of
the master mixes were then combined and incubated at room temperature for 30
minutes.
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31
While the binding reaction was incubating, the gel was pre-run at 4°C and 50mA.
Once the incubation was complete, the reactions were loaded into the gel and run at
50mA for 3-4 hours. The gel was then dried and exposed to a phosphor screen for
15 hours, scanned on a phosphoimager (Molecular Dynamics, CA, USA), and
analyzed with ImageQuant v.1.1.
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32
III. RESULTS
III. A. Controls
Prior to performing the reporter gene assays, a series of control experiments were
performed to optimize the transfection conditions. First, to determine the amount of
DNA to transfect, a linear range titration experiment was performed for each cell line
by keeping the total amount of DNA constant and only varying the amount of reporter
plasmid. The reporter gene plasmid was transfected in twelve different amounts—
0.1 ug, 0.3ug, 0.5ug, 0.7ug, 0.8ug, 0.9ug, 1.0ug, 1.3ug, 1.5ug, 2.0ug, 2.5ug, and
3.0ug. PUC-18 plasmid was used as a filler DNA to keep the total amount of DNA
transfected constant at 3.0ug, and pCMV(3 was co-transfected to control for
transfection efficiency. Results for both cell lines are shown in Figures 17 and 18.
Linear Range COS-7 Cells
700000
600000
3 500000
cc
■ u
o >
N
| 300000
| 200000
100000
400000
3.5 1.5 2 2.5 3 0 0.5 1
D N A (ug)
Figure 17: DNA titration experiment for COS-7 cells.
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33
Linear Range PC-3 Cells
1400
1200
1 800
N
« b 600
£
o 400
200
0 0.5 1 2.5 1.5 2 3 3.5
DNA(ug)
Figure 18: DNA titration experiment for PC-3 cells.
The experiments show that both cell lines are linear to about 1,5ug of DNA. Thus, by
using any amount of DNA less than 1,5ug, it can be safely assumed that the system
is not being saturated. As a result, 0.6ug and 0.8ug of DNA were chosen for
transfection into COS-7 and PC-3 cells respectively. (More DNA was chosen to be
transfected in PC-3 cells due to the lower signal produced in these cells).
Next, the optimal confluency at which to transfect the cells was determined
experimentally. Multiple dishes at different starting confluencies were plated,
transfected, and harvested after the cells reached 100% confluency. (Note: The cells
were plated to reach 100% confluency at 1,2,3,4 and 5 days post transfection). A
schematic of the experiment is shown in Figure 19. The results of the experiments
are shown in Figure 20.
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34
Starling
Confluency (%)
% Confluency After Day
100
100
100
100
100
Figure 19: Schematic-optimal confluency experiment.
Optimal C onfluency Upon Transfection
35000
30000
3 25000
-A 647C
TJ 2 0 0 0 0
-A 645T
15000
-G 382A
-C 216A
z 10000
5000
Days After Transfection
Figure 20: Results-optimal confluency experiment.
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35
Clearly, transfecting at 70% confluency and harvesting two days after gives the
optimum normalized luciferase values for all constructs. With this established, the
stability of the transfection was then tested by starting with the same number of cells
at the time of transfection (all dishes being 70% confluent) and harvesting the cells 1
to 4 days post-transfection. The experiment schematic is shown in Figure 21. The
results are shown in Figure 22.
Starting
Confluency (%)
% Confluency After Day
100
100+ 100
100+ 100+
100
100+ 100 100+ 100+
Figure 21: Schematic—optimal time of harvest experiment.
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36
Optimal Time of H arvest
100000
90000
80000
70000
WT
60000
-A 647C
50000
-A 645T
40000
-G 3S2A
-C 216A
30000
20000
10000
; 2 2.5
DaysP ost-T ra nsfectio n
0.5 3.5 4.5
Figure 22: Results-optimal time of harvest experiment.
Again, the graph clearly shows the optimum time to harvest the cells is at 2 days
post-transfection when the greatest luciferase signal is obtained. Thus, the results of
the two control experiments show that transfecting at 70% confluency and harvesting
after 2 days will yield the optimum results.
Finally, an additional control experiment was run to compare two different methods of
cell lysis. After harvesting the cells, lysis was split into two batches, one for
sonication and one for chemical lysis with the Reporter Lysis Buffer (Promega, Wl,
USA). The cell extracts were then assayed for luciferase and normalized to protein
and B-galactosidase, the results being shown in Figure 23.
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37
Sonication vs. Lysis Buffer
31X00 T ----------— -..........-.... ...- ----------------------------------- -------
29000
□ Sonication
Figure 23: Comparison of cell lysis methods.
Because the normalized luciferase signal seems to be only slightly greater using the
lysis buffer, to facilitate use of cell extract in future applications, sonication was
chosen as the method of cell lysis.
III. B. Transfections
Now that the amount of DNA to transfect, the optimal time of transfection, the optimal
time of harvest, and lysis method have been determined, the constructs were then
transfected into each cell line. Each set of experiments included transfection of the
wild-type construct, the mutant constructs, and the empty pGL3 enhancer vector
(Promega) as a baseline control. Every construct was transfected in triplicate, and
triplicate clones were made of each SNP, resulting in nine data points per SNP.
Figure 24 shows a sample transfection schematic of two of the four SNPs and data
for all SNPs is shown in Table 5.
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38
w r W T W T
EV EV EV
SNP 1
Clone 3
SNP 1
Clone 3
SNP 1
Clone 3
SNP 2
Clone 1
SNP 2
Clone 1
SNP 2
Clone 1
SNP 2
Clone 2
SNP 2
Clone 2
SNP 2
Clone 2
SNP 2
Clone 3
SNP 2
Clone 3
SNP 2
Clone 3
SNP 1
Clone 1
SNP 1
Clone 1
SNP 1
Clone 1
SNP 1
Clone 2
SNP 1
Clone 2
SNP 1
Clone 2
Figure 24: Transfection schematic (WT=Wild-type, EV=Enhancer vector control).
Table 5: Data for transfection of triplicate clones for each SNP in COS-7 and PC-3 cells.
Note: Ratios are taken from normalized RLU values.
COS-7 PC-3 COS-7 PC-3
SNP Ratio fSNP WT! Ratio (SNP/WT) SNP Ratio (SNP WT) Ratio (SNP/WT)
WT 1
-A647C 1 1.52 1.63 -G382A 1 1.46 1.32
-A647C 1 1.23 1.53 -G382A 1 1.30 1.42
-A647C 1 1.24 1.59 -G382A 1 1.33 1.41
-A647C 2 1.31 1.45 -G382A 2 1.62 1.43
-A647C 2 1.52 1.55 -G382A 2 1.36 1.40
-A647C 2 1.22 1.48 -G382A 2 1.32 1.29
-A647C 3 1.55 1.49 -G382A 3 1.61 1.35
-A647C 3 1.27 1.45 -G382A 3 1.43 1.29
-A647C 3 1.23 1.44 -G382A 3 1.43 1.35
-A645T 1 1.49 1.65 -C216A 1 0.85 1.01
-A645T 1 1.38 1.49 -C216A 1 0.91 0.98
-AJ645T 1 1.54 1.43 -C216A 1 0.9 0.99
-A645T 2 1.36 1.46 -C216A 2 0.86 1.05
-A645T 2 1.36 1.42 -C216A 2 0.85 0.99
-.A£45T 2 1.30 1.36 -C216A 2 0.85 0.99
-A645T 3 1.55 1.47 -C216A 3 1.15 0.97
-A645T 3 1.53 1.49 -C216A 3 0.99 0.95
-A645T 3 1.40 1.45 -C216A 3 0.98 0.97
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39
Activation Ratio Over Wild-Type □ cos-7
■ PC-3
16 -r-........
C216A
A647C A645T
0.9
0.B J -------------------------------------------------- ------------------------------------ ---------------------------------
Figure 25: Average activation of SNP over wild-type in COS-7 and PC-3 cells.
The graph in Figure 25 above shows the ratio of the normalized relative luciferase
units for each SNP compared to wild-type. For COS-7 cells, the results indicate 3 out
of 4 SNPs, -A647C, -A645T, and -G382A show a modest activation of 1.33 ± 0.14,
1.39 ± 0.09, and 1.40 ± 0.12-fold respectively compared to wild-type. Results in PC-3
cells confirm those in COS-7 cells, yielding an activation of 1.51+0.07, 1.47+0.08, and
1.36+0.06-fold respectively compared to the wild-type. A summary of the results are
shown in Table 6. It should be noted that the activation seen in PC-3 cells is slightly
higher than that seen in COS-7 cells. Because the SRD5A2 gene is expressed in
PC-3[43], but not in COS-7 cells, this may indicate a transcription factor is present in
PC-3 cells which is responsible for the difference in activation.
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40
Table 6: Summary of relative activation of each SNP in COS-7 and PC-3 cells.
Average
Ratio
COS-7 PC-3
-A647C 1.34 ♦ 0.14 1.51 +/- 0.07
-A645T 1.43 +/- 0.09 1.47 +••- 0.08
-G382A 1.43 + -0.12 1.36 +/-0.06
-C216A 0.93 +/- 0.10 0.99 +/- 0.03
III. C. Transcription Factors
Having confirmed that three SNPs confer activation in two mammalian cell lines, the
next step was to find out the underlying mechanism for this activation. To accomplish
this, the wild-type and mutant sequences were run through a transcription factor
binding program called MATCH. Using a similarity matrix score cut-off of 85%, it was
found that the -A645T SNP creates a binding site for the helix-loop-helix transcription
factor E-47 (similarity score 95.4%). E-47 is ubiquitously expressed (UniGene) and is
known to play a major role in determining tissue-specific cell fate during
embryogenesis such as in early B-cell differentiation[44]. Studies have also shown
the E-47 protein functions as a transcriptional activator mapping to two domains
found in the N-terminal region[45, 46].
Conversely, the -G382A SNP abolishes a binding site for the Elk-1 transcription factor
which has previously been shown by RT-PCR to be expressed in the lungs, testis,
kidney, muscle, and extensively in the brain[47], while further reports using expressed
sequence tags (ESTs) show expression to be ubiquitous (UniGene). Elk-1 belongs to
the Ets family of transcription factors which includes nuclear phosphoproteins that are
involved in cell proliferation, differentiation, and oncogenic transformation[48]. The
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family is defined by a conserved DNA-binding domain, which forms a winged, helix-
turn-helix structural motif. Furthermore, Elk-1 is known to stimulate transcription by
binding to purine-rich DNA sequences and is a strong transactivator of serum
responsive element (SRE) driven gene expression[48], A schematic for the binding
of these transcription factors is shown in Figure 26.
r - -i
I I
- A — A -
k i
- h m m - a m j t
I * § 0
k
-Q3S2A
E H
-C216A
Exoni
Pronto!©*
Q L m.
k
-A647C -A645T
I J
‘ hr
K
-Q M 2A
r;c
-C2I6A
\
E » » l
Figure 26: Schematic of putative transcription factor binding.
Thus, because the -A645T polymorphism creates a binding site for the transcriptional
activator E-47, we would expect this polymorphism to confer an increase in
transcription. On the other hand, the -G382A abolishes a binding site for the
transcriptional activator Elk-1, and hence we would expect this polymorphism to
repress transcription. It should also be noted that both the E-47 and Elk-1
transcription factors are expressed ubiquitously and therefore should be present in
both the COS-7 and PC-3 cell lines[47].
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42
III. D. Gel-Shift Experiments
To test whether the SNPs indeed create or destroy a transcription factor binding site,
gel mobility shift assays were run for each SNP in each cell line. Figure 27 shows a
schematic of the experiment and hypothetical results, demonstrating a band shift
between wild-type and mutant probes (lane 2 versus lane 6). This shift would
indicate that the SNP in the mutant probe confers a difference in the binding of
proteins to its specific nucleotide sequence. Figures 28-31 show the results for each
mutant probe using nuclear extract from both cell lines.
Figure 27: Gel-shift schematic. Lane 1=Probe only; Lane 2=probe+cell extract(CE);
Lane 3=probe, CE, 10X cold probe; Lane 4=probe, CE, 100X cold probe.
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43
PC-3 Cell Extract
Probe:
Competitor:
COS-7 Cell Extract
Probe:
Competitor:
Figure 28: Gel shift using -A647C probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom).
WT -A647C
10x 100x
self self
10x
self
100x
self
A647C
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44
PC-3 Cell Extract
n u V V T -A645T
Probe: , --------------------------------------- , , --------------------------------------- ,
Competitor: _ _ 10x 100x _ - 10x 100x
self self self self
1 2 3 4 5 6 7 8
COS-7 Cell Extract
Probe: r
Competitor:
WT
10x
self
100x
self
-A645T
10x
self
100x
self
Figure 29: Gel shift using -A645T probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom).
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45
PC-3 Cell Extract
W T -G382A
Probe: . --------------------------------------- 1 i-----------------------------
Competitor: _ _ IQ * 100x - - 10x 100x
self self self self
COS-7 Cell Extract
Probe: j-
Competitor:
m
10x
self
100x
self
-G382A
10x 100x
self self
Figure 30: Gel shift using -G382A probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom).
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
46
PC-3 Cell Extract
WT -C216A
Probe:---------- , ---------------------------------------- ,--------------------------- , ---------------------------------------- ,
Competitor: _ _ i o x 100x _ _ 10x 100x
self self self self
1 2 3 4 5 6 7 8
COS-7 Cell Extract
WT -C216A
Probe: , ---------------------------------------- , i---------------------------------------- 1
Competitor: _ _ i o x io o x _ _ 10x 100x
se lf self self self
1 2 3 4 5 6 7 8
Figure 31: Gel shift using -C216A probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom).
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47
As seen in Figures 28-31, the gels indicate no difference in transcription factor
binding when using wild-type or mutant probes in either cell line (lane 2 versus lane
6). However, by seeing a gradual disappearance of the bands in the competition
lanes, (lanes 3 and 4, and lanes 7 and 8), we do know that protein is binding
specifically to the DNA probe. Once may also argue that a quantitative difference
exists in transcription factor binding, i.e. more protein appears to be able to bind to
the wild-type probe than the mutant probe or vice versa. Thus, to quell this argument,
another gel shift experiment was run using the mutant probe competed with either
“self” (cold mutant probe), or “non-self” (cold wild-type probe). If a quantitative
difference exists in the ability of the wild-type or mutant probe to bind transcription
factors, a difference in intensity will be seen between lanes 3 and 4, as well as lanes
5 and 6 (Figure 32). The results for each SNP and cell line are shown in Figures 33-
36.
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48
V
M u tx it P rob* M utant Probe (S E LF)
Wid-Type Probe (NON-SELF)
IOX Self IOX Non-Self 100X Self 100X Non-Self
Figure 32: Gel-shift schematic. Lane 1=Probe only; Lane 2=Probe + CE; Lane 3=Probe,
CE, 10X cold probe (self); Lane 4=Probe, CE, 10X cold probe (non-self); Lane 5=Probe,
CE, 100X cold probe (self); Lane 6= Probe, CE, 100X cold probe (non-self).
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
49
PC-3 Cell Extract
, -A 6 4 7 C
Probe. p —— — - — ----------------------------------- 1
Competitor: - - 1° * 10° * lt
self non-self se lf non-self
1 2 3 4 5 6
COS-7 Cell Extract
-A 6 4 7 C
Probe: , ----------------------------------------------------------------------------- 1
Competitor: - - 10» 1° * 10° * 100» lt
self non-self self non-self
1 2 3 4 5 6
Figure 33: Competition gel shift using -A647C probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom).
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50
PC-3 Cell Extract
-A 6 4 5 T
i-----------------------------------------------------------1
10x 10x 100x 100x
self non-self self non-self
1 2 3 4 5 6
Probe:
Competitor:
COS-7 Cell Extract
Probe: r
Competitor:
-A 645T
10x 10x 100x
self non-self self
— i
100x
non-self
1 2 3 4 5 6
Figure 34: Competition gel shift using -A645T probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom).
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51
PC-3 Cell Extract
Probe:
Competitor:
COS-7 Cell Extract
Probe:
Com petitor:
Figure 35: Competition gel shift using -G382A probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom).
-G 382A
i--------------------------------------
1Qx 10x 100x 100x
self non-self self non-self
1 2 3 4 5 6
-G 3 8 2 A
i----------------------------------------------------------- 1
10x 10x 100x 100x
self non-self self non-self
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52
PC-3 Cell Extract
Probe:
Competitor:
COS-7 Cell Extract
-C216A
10x 10x 100x 100x
self non-self se lf non-self
-C216A
Probe:------------------------, ----------------------------------------------------------------------------- 1
Competitor: - - 1° * 10* 10° * „
self non-self se lf non-self
1 2 3 4 5 6
Figure 36: Competition gel shift using -C216A probe with PC-3 cell extract (top) and
COS-7 cell extract (bottom).
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A seen in Figures 33-36, the gels indicate no difference in the affinity of transcription
factor binding to the wiid-type or the mutant probe in either cell line (lane 3 versus
lane 4). This data in conjunction with data from the previous gel shift experiments,
suggest that none of the four SNPs confer a difference in creating or destroying a
novel transcription factor binding site, nor is the binding affinity for a transcription
factor altered.
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54
IV. DISCUSSION
The SRD5A2 gene is an ideal candidate gene for prostate cancer because its product
is directly involved in the production of DHT which, coupled with the androgen
receptor, is responsible for activating a number of genes responsible for cellular
proliferation and differentiation in the prostate[15]. Furthermore, SNP studies,
compared to serum-based studies, offer two distinct advantages. First, molecular
assays of SNPs usually produce more qualitative results with higher reproducibility
than the continuous data typically produced by serologic assays. Second, unlike
serologic markers, genetic susceptibility, or genotype, is not affected by the presence
or process of disease or by other exposures that may change over time[49J. Thus,
characterization of SNPs provides an opportunity to examine the prostate cancer at
the cellular level.
IV. A. Reporter Gene Analysis
In this study, four SNPs in the promoter region of the SRD5A2 gene were examined
for their potential role in altering transcriptional regulation. A 745 base pair fragment
encompassing all three transcriptional start sites upstream of the SRD5A2 gene was
used to drive transcription of the luciferase gene in a reporter gene vector[40].
Subsequent reporter gene analysis in two distinct mammalian cell lines, COS-7 and
PC-3, showed three out of the four polymorphisms, (-A647C, -A645T, and -G382A),
confer an increase or up-regulation of transcription of the luciferase gene compared
to wild-type. The differences in transcriptional activation conferred by these three
SNPs—1.33 ± 0.14, 1.39 ± 0.09, and 1.40 ± 0.12-fold respectively in COS-7 cells and
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55
1.51 ±0.07, 1.47+0.08, and 1.36+0.06-fold respectively in PC-3 cells—were found to
be statistically significant (p<0.05). However, based on functional analyses of 91
haplotypes in 41 cloned promoters using three human cell lines, Hoogendoorn et al.
classify a relative difference of 1.5 times as functionally important[50, 51]. Based on
this criterion, only one SNP, -A647C in PC-3 cells, drove expression by more than 1.5
times over wild-type, the next closest being 1.47-fold by the -A645T SNP in PC-3
cells as well. Regardless, the reproducibility of the results across nine replicates of
each SNP show that the presence of these variants increase the activity of the
luciferase gene. This result is consistent with the idea that the -A647C, -A645T, and
-G382A SNPs may contribute to an increased production of the steroid 5-alpha
reductase enzyme, resulting in an increased conversion of testosterone to DHT,
ultimately affecting prostate cell growth.
IV. B. Gel Mobility Shift Assays
Next, the context of each polymorphism in the SRD5A2 promoter was further tested
using a putative transcription factor binding program (MATCH). Comparing each
variant to the wild-type sequence, the results suggest the -A645T and -G382A SNPs,
two of the three SNPs that were found to be activating in the reporter gene analysis,
create and destroy putative transcription factor binding sites respectively.
Interestingly, the -A647C polymorphism, the only SNP to meet the threshold of
functional significance defined by Hoogendoorn et al., showed no difference in
putative transcription factor binding sites.
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56
Knowing that two out of the three SNPs found to be functionally significant may make
a difference in transcription factor binding, gel mobility shift assays were run with the
hypothesis that the transcriptional activation conferred by the -A645T polymorphism
is caused by the creation of a binding site for a transcriptional activator, whereas the
activation conferred by the -G382A polymorphism is not mechanistically clear due to
the fact that the mutation is activating even though the binding site for a
transcriptional activator is abolished. 31-mer oligonucleotide probes were
constructed for each SNP and wild-type, end-labelled, and incubated with nuclear cell
extract from either COS-7 or PC-3 cells. The mutant and wild-type probes were then
run side by side on a polyacrylamide gel to see whether a difference, or “shift” in
binding could be detected. The results show no difference in binding of a
transcription factor between each SNP and wild-type using either COS-7 or PC-3
nuclear cell extract. However, a protein is binding specifically to the probe in both
cases as evidenced by the disappearance of the band when competed with
unlabelled probe.
Although no “shift” was observed, it appears as though the band seen in the lanes
involving the mutant probe is significantly more intense than the band seen in the
lanes involving the wild-type probe or vice versa (Figures 28-31). This can be
explained by one of two scenarios: (1) one of the probes is significantly more
radioactively labeled than the other, thereby resulting in a more intense band, or (2)
the DNA binding protein has a higher affinity for the mutant probe resulting in more
probe being bound, and therefore, a more intense band. The former is the more
likely case due to the fact that gel-shift assays are to be used qualitatively and not
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57
quantitatively. Nevertheless, to resolve the latter issue, another set of gel shift
experiments were run but this time only end-labeling the mutant probe and competing
with “self” (unlabelled mutant) probe, and “non-self” (unlabelled wild-type) probe. If
the mutant probe does indeed exhibit a higher affinity for the DNA binding protein,
then we would expect the band in the lane competed with “non-self” probe to be more
intense than the band in the lane competed with “self” probe (Figures 33-36). Once
again, the results show no difference in the protein binding affinity of the mutant and
wild-type probes.
Thus, the null findings in the gel shift assays demonstrate two points: (1) despite the
information gathered from the putative transcription factor binding program, none of
the SNPs studied were found to create or destroy a transcription factor binding site in
vitro, and (2) none of the SNPs confer an increased affinity for binding of a
transcription factor.
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58
V. CONCLUSION
In conducting reporter gene assays for triplicate clones of four SNPs found in the
promoter region of the SRD5A2 gene, the results of this study provide solid evidence
that three of the four SNPs studied individually increase transcriptional activity. The
results were highly reproducible across nine replicates of each SNP, exhibiting a
small standard deviation from the mean, not only in one, but in two distinct
mammalian cell lines. The gel shift experiments indicate the cause of the activation
seen in the three activating SNPs cannot be attributed to the binding of a novel
transcription factor, nor an increase in binding affinity for a transcription factor.
However, though the mechanism of activation is still not clear, this study provides
evidence that SNPs in the promoter region may contribute to prostate carcinogenesis.
V. A. Future Directions
Despite the advantages, SNP studies have their limitations, namely, statistical power.
In this study, out of the 50 patients genotyped, the four SNPs characterized (-A647C,
-A645T, -G382A, and -C216A), were found to occur only once with no known
haplotypes. Thus, larger studies in various racial/ethnic groups are needed to further
validate the hypothesis that the three activating polymorphisms indeed contribute to
the progression and development of prostate cancer.
Aside from genotyping more patients, more gel shift experiments could be run with
slight modifications. Knowing the identity of the putative DNA binding proteins, (E-47
and Elk-1), purified protein, obtained via co-transfection with an E-47 or Elk-1
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59
expression plasmid, could be used in place of the general nuclear cell extract. If a
shift is seen using the modified nuclear cell extract abundant with the protein of
interest, it would provide solid evidence implicating the protein as the cause of
transcriptional activation seen previously. Along the same lines, DNase I footprinting
could be used to figure out the identity of the consensus sequence bound by the
protein in the gel shift assays. This experiment would tell us whether the protein is
binding to the expected consensus sequence, which would thereby confirm the
protein is indeed present in the nuclear cell extract.
Another direction that could be taken is to test whether the SNPs are affecting mRNA
stability. As noted earlier, if the longest of the three transcription initiation sites is
used, i.e. if the longest transcript is made, all the SNPs identified would then be
located in the 5’-UTR region of the gene, and therefore present in the mRNA. In a
functional study of 22 mutations in the SRD5A2 gene, Wigley et al. found that almost
all mutations decreased the half-life of the protein, and all but one of the impaired
enzymes had an altered pH optimum[52]. Although mutations are often found to
reduce enzyme activity by destabilizing the protein, SNPs found in this study to be
activating may actually increase mRNA stability, thereby allowing the enzyme to
convert testosterone to DHT much more readily. To test for mRNA stability, Northern
blots or RT-PCR could be utilized to quantify and compare the amount of mRNA
being made by the wild-type and mutant promoters.
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60
Finally, instead of using the luciferase reporter gene vector to characterize the
potential effects of the polymorphisms, using a more “native” construct could reveal a
greater difference. A new vector could be constructed with the SRD5A2 gene cDNA
being driven by wild-type and mutant promoter sequences. This new construct could
then be transfected into a mammalian cell line and assayed for the steroid 5-alpha
reductase type II enzyme rather than luciferase.
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61
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Asset Metadata

Creator Kim, Albert H. (author)

Core Title Functional analysis of single nucleotide polymorphisms (SNPs) in the 5' regulatory region on the SRD5A2 gene

School Graduate School

Degree Master of Science

Degree Program Biochemistry and Molecular Biology

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

Tag biology, genetics,biology, molecular,OAI-PMH Harvest

Language English

Contributor Digitized by ProQuest (provenance)

Advisor Reichardt, Juergen (committee chair), Allayee, Hooman (committee member), Tokes, Zoltan A. (committee member)

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c16-47770

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Identifier 1427978.pdf (filename),usctheses-c16-47770 (legacy record id)

Legacy Identifier 1427978.pdf

Dmrecord 47770

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Rights Kim, Albert H.

Type texts

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

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the au...

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