University of Southern California Dissertations and Theses

POLR2B and its contributions to cancer cell growth

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POLR2B and its contributions to cancer cell growth

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POLR2B AND ITS CONTRIBUTIONS TO CANCER CELL GROWTH

by

George Kohan

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
(MOLECULAR AND EXPERIMENTAL PATHOLOGY)

December 2009

Copyright 2009 George Kohan
ii

Acknowledgements

I would like to thank Dr. Louis Dubeau for allowing me to become a member of
his laboratory. Dr. Dubeau, thank you for supporting and encouraging me to think
independently about my research and my future goals, and for motivating me to
become a harder worker, and a more persistent and patient person. I would also
like to thank Dr. Vanessa Yu and Jennifer Yeh Lee for all of your support during
my time in the laboratory; completing my research objectives and my thesis
would not have been possible if it were not for your constant guidance and
motivation. I would also like to thank the other members of the Dubeau
laboratory, Ying Liu, Hao Hong, and Christine Marion for their friendship,
camaraderie, and support. I would also like to thank Dr. Timothy Triche’s
laboratory for performing the exon microarray and providing us with the resultant
data. I would also like to thank Dr. Jonathan Buckley for assisting me with his
biostatistical expertise to analyze the microarray data. I would also like to thank
my thesis committee; Dr. Louis Dubeau, Dr. Florence Hofman, and Dr. Gerhard
Coetzee for their time and contributions to my earning of the degree. Finally, I
would like to thank my parents, Masoud and Jaklin, and my siblings, Joseph-
Ramin and Josephine, for supporting me and motivating me throughout my life,
through the peaceful times and the trying times, and inspiring me to achieve my
goals. Thank you all for helping me become the man that I am today.

iii

Table of Contents

Acknowledgements ii

List of Figures iv

List of Tables v

Abstract vi

Chapter 1: Introduction 1
1.1 Ovarian Cancer 1
1.2 Ovarian Cancer Genetics 4
1.3 Transcription Factors 8
1.4 Transcription Factors and Ovarian Cancer 10
1.5 Basis For Thesis Project 12
1.6 POLR2B 14
1.7 Thesis Project Summary 14

Chapter 2: Experimental Methods 17
2.1 Cell Culture 17
2.2 RNA Isolation 18
2.3 Semi-Quantitative Two Step RT-PCR 19
2.4 Agarose Gel Electrophoresis 21
2.5 siRNA Transfection 22
2.6 Cell Number Determination 22

Chapter 3: Results 24

Chapter 4: Discussion & Future Directions 30

References 36

iv

List of Tables

Table 1: Putative Tumor Suppressor Genes Involved in Ovarian Cancer 6

Table 2: Oncogenes Associated With Ovarian Cancer 8

Table 3: Primers Used For Semi-Quantitative PCR 21

Table 4: Microarray Data Showing Expression Level Differences 28
Between HEY/Chr6 Hybrid Cells and NM22B Cells for the Subunits of RNA
Pol II

v

List of Figures

Figure 1: Diagram of the Pre-Initiation and Open Complexes 10

Figure 2: Agarose Gel Showing Results of Semi-Quantitative RT-PCR
Amplification of Four mRNA Transcripts (Cyclin B2, Elongin A, POLR2B, 24
and Beta-Actin)

Figure 3: Agarose Gels Showing Effects of siRNA Transfection on POLR2B 25
and Beta-Actin Transcript Levels

Figure 4: Effects of siRNA Transfection 26

Figure 5: Agarose Gel Showing Results of Semi-Quantitative RT-PCR
Amplification of Five mRNA Transcripts (POLR2A, POLR2B, POLR2F, 29
POLR2I, and Beta-Actin)

vi

Abstract
Ovarian cancer incidence is highest in the western world, where it is the leading
cause of death from gynecological malignancies. Numerous risk factors for
ovarian cancer have been identified, including the substantial risk associated with
family history of the disease. Genetic predispositions contribute to familial risk,
and at least 10% of ovarian cancer incidence is thought to be attributable to
genetic factors. Several of the proteins that are associated with ovarian cancer
are Transcription Factors that promote cancer cell growth and tumor progression.
POLR2B is the second largest subunit of RNA Polymerase II, which is the
polymerase responsible for transcription of mRNA in eukaryotes. POLR2B binds
to DNA, helps maintain contact in the active site of RNA Polymerase II between
the DNA template and the newly synthesized RNA, and plays a key role in
facilitating the formation of a phosphodiester bond between an incoming
ribonucleoside triphosphate and the elongating RNA transcript. The studies
presented here have shown that POLR2B is upregulated in the NM22B ovarian
carcinoma cell line to the point that it exceeds the availability of the other
subunits of RNA Polymerase II examined, and that knocking down the
expression of this subunit via siRNA results in decreased rates of cell growth.
These findings suggest that POLR2B has a role, separate from its functions as a
subunit of RNA Pol II, as a Transcription Factor that promotes cancer cell growth
and tumor progression.
1

Chapter 1: Introduction

1.1 Ovarian Cancer
Ovarian cancer incidence is highest in the Western world, where it is the
leading cause of death from gynecological malignancies. There were an
estimated 21,650 new cases of ovarian cancer in the United States alone in
2008, with an estimated 15,520 ovarian cancer-associated deaths (Jemal et al.
2008). Ovarian cancer patients frequently present with non-specific symptoms,
such as abdominal pain, bloating, and fatigue, which make diagnosis difficult until
the late stages of the disease (Goff et al. 2000).In fact, about 75% of patients
with ovarian cancer present with metastasis beyond the ovaries at diagnosis,
with only about 25% of patients having the cancer limited to the ovaries (Bast et
al. 2009; Dinh et al. 2008). Although up to 90% of patients that have the cancer
restricted to the ovaries can be cured with conventional surgery and
chemotherapy, this percentage drops drastically as the disease progresses.

1.1.1 Ovarian Cancer Detection
The high cure rate among patients with the early stages of ovarian cancer
has fueled attempts to develop and evaluate strategies for early detection of
ovarian cancer. One such strategy is a Transvaginal Sonography (TVS), where a
transducer that emits high frequency soundwaves is placed in the vagina to
image the ovaries. Proponents argue that TVS could potentially detect small
malignant lesions that have not metastasized, but in practice, it can be difficult to
2

distinguish benign from malignant abnormalities, requiring surgery to achieve a
definitive diagnosis (Bast, 2004). In addition, limitations in specificity, sensitivity,
and the current cost of the procedure prevent annual TVS screening of
populations at normal risk. Another strategy involves measuring the levels of the
glycoprotein CA 125 (MUC 16). A study showed that serum levels of CA 125
above 35 U/ml were observed more frequently in women with ovarian carcinoma
(82%) compared to women in the general population (1%), women with benign
disease (6%), or women with non-gynecological malignancies (28.5%) (Bast et
al.1983). The study also showed that decreasing or increasing levels of CA 125
correlated with regression or progression of ovarian cancer in 42 out of 45 cases
(93%). However, elevated CA 125 levels are seen in many other conditions,
including in cancers of the pancreas, bladder, breast, liver, lung, and
endometrium, in pericarditis, colitis, endometriosis, menstruation, cirrhosis, etc
(Neesham, 2007), reducing its specificity for ovarian cancer and thereby limiting
its use as a primary diagnostic tool. A third strategy involves combining TVS with
measuring CA 125 levels in serum. Data from the first two years of a 200,000
subject trial in the United Kingdom where elevated serum levels of CA 125 are
being used to prompt the use of TVS to detect lesions suggests that this strategy
could increase the percentage of ovarian cancer detected during its early stages
from 20% to 48% (Menon et al. 2009). In addition, this screening method
provides both adequate sensitivity (89.4%) and specificity (99.8%).

3

1.1.2 Ovarian Cancer Treatment
Treatment options currently available for ovarian cancer patients include
surgery and chemotherapy. Surgery is the primary treatment approach and
involves an abdominal hysterectomy (removal of the uterus) and bilateral
salpingo-oophorectomy (removal of the fallopian tubes and ovaries) (Martin
2007). During surgery, the surgeon strives for optimal debulking of the tumor(s),
which can improve patients' responses to chemotherapy and relieve their
symptoms. Among the chemotherapeutic drugs used in ovarian cancer treatment
are Cisplatin and Paclitaxel (Taxol) (Martin 2007). Cisplatin interferes with mitosis
by crosslinking DNA (Siddik et al. 2003). The damaged DNA then elicits DNA
repair mechanisms, which in turn activate apoptosis once the cell is unable to
repair itself. Paclitaxel interferes with the mitotic process by preventing
microtubule disassembly by binding to the β subunit of tubulin, locking the
microtubules in place (Herman et al. 1983). There is also evidence to suggest
that Paclitaxel may be effective in treating Cisplatin-resistant tumors (Stordal et
al. 2007), probably due to its different mechanism of action.

1.1.3 Ovarian Cancer Risk Factors
Numerous factors that are protective against ovarian cancer have been
identified, including use of oral contraceptives, multiparity, and lactation, all of
which prevent ovulation (Pike et al. 2000; Rosenberg et al. 1994; Salehi et al.
2008). Conversely, risk factors for ovarian cancer have been identified as well,
including several associated with lifestyle, environment, and reproduction. Such
4

factors include obesity, red meat consumption, cigarette smoking, insecticide and
herbicide exposure, nulliparity (having never given birth), hormone replacement
therapy, family history of ovarian cancer, etc (Bosetti et al. 2001; Green et al.
2001; Purdie et al. 2001; Salehi et al. 2008; Young et al. 2005).

1.2 Ovarian Cancer Genetics
Family history of ovarian cancer is a substantial risk factor for the disease,
with an estimated 10-15% of ovarian cancer cases attributable to heredity (Risch
et al. 2001). Women who have one first degree relative with ovarian cancer have
a 5% lifetime risk of developing the disease, and women with two or more
affected first degree relatives have a 7% lifetime risk (Salehi et al. 2008). In
addition, women with a family history of three or more cases of ovarian cancer
are more likely to develop the disease at a younger age (Goldberg et al. 1997).
Genetic predispositions contribute to the observed trends in familial risk, with at
least 10% of the incidence of ovarian cancer thought to be attributable to genetic
factors (Prat et al. 2005; Risch et al. 2001).

1.2.1 Tumor Suppressor Genes
A number of genes that have been implicated in ovarian cancer are Tumor
Suppressor Genes (TSGs), which negatively regulate cell growth and prevent
tumor formation. Knudson’s two-hit hypothesis served to enhance our
understanding of TSG involvement in cancer; it states that two ‘hits’, or genetic
events, can cause cancer development (Knudson, 1971). The two genetic events
5

Knudson spoke of are the loss of both of the TSG’s alleles; if only one of the two
alleles is lost then the second allele can still produce the functional gene product,
thereby maintaining the wild type phenotype. The alleles may be lost in a variety
of ways, including deletion from the genome, mutation so that the gene product
either does not form at all or forms incorrectly, or silence of the allele via
epigenetic means (Jones et al. 1999). As a side note, there are notable
exceptions to the two-hit rule, such as with dominant negative mutations where
the mutated gene product of the affected allele can prevent the function of the
normal gene product of the unaffected allele (Wilkie, 1994). Other TSGs that are
not subject to the two hit rule are those which exhibit haploinsufficiency, where
only one functioning allele cannot maintain the wild type phenotype (Wilkie,
1994).

1.2.2 TSGs Implicated in Ovarian Cancer
90% of the hereditary ovarian cancers (excluding Hereditary NonPolyposis
Colorectal Cancer {HNPCC}) are associated with mutations in BRCA1 and/or
BRCA2. Two-thirds of this sizeable percentage is linked to BRCA1 mutations and
one-third is linked to BRCA2 mutations (Frank et al. 1998). In fact, the risk
associated with these BRCA1 and BRCA2 mutations is so great that prophylactic
bilateral salpingo-oophorectomy is generally recommended in female carriers as
soon as they have completed their families (Bast et al. 2009). BRCA1 and
BRCA2 have many important functions, with the involvement of BRCA1 in
chromatin remodeling, transcriptional regulation, etc (Boulton, 2006), and the
6

involvement of both BRCA1 and BRCA2 in DNA double strand break repair
(Friedenson, 2007). Most of the remaining 10% of the hereditary ovarian cancer
cases are of the HNPCC variety (Prat et al. 2005), which is associated with
mutations in the hMSH2, hMLH1, hPMS1, and hPMS2 mismatch repair genes
(Colombo et al. 2006). Many other putative TSGs play a role in ovarian cancer
(Table 1).
Gene Function
ARHI
(DIRAS3)
GTPase; inhibits proliferation and motility; induces autophagy
and dormancy; upregulates p21; inhibits cyclin D1, PI3K, Ras–
Mapk signalling and STAT3
RASSF1A Inhibits proliferation and tumorigenicity in many different
cancers; interacts with Ras inhibiting and downregulating cyclin
D and signalling through JNK; stabilizes microtubules; regulates
spindle checkpoint; regulates CD95- and TNF -induced
apoptosis
DLEC1 Cytoplasmic protein that inhibits anchorage-dependent growth
SPARC Ca
2+
-binding protein; prevents adhesion
DAB2
(DOC2)
Binds GRB2, preventing Ras and Mapk activation; prevents
FOS induction and decreases ILK activity; contributes to anoikis;
inhibits proliferation; inhibits anchorage-independent growth and
tumorigenicity
PLAGL1
(LOT1)
Nuclear zinc-finger protein; inhibits proliferation and
tumorigenicity
RPS6KA2 Ribosomal S6 serine threonine kinase; inhibits growth; induces
apoptosis; decreases Erk phosphorylation and cyclin D1;
increases p21 and p27
PTEN PI3 phosphatase; decreases proliferation, migration and
survival; decreases cyclin D; increases p27
OPCML GPI-anchored IgLON family member; induces aggregation;
inhibits proliferation and tumorigenicity
ARL11 ADP ribosylation factor; induces apoptosis
WWOX Decreases anchorage-independent growth and tumorigenicity;
mouse homologue required for apoptosis
DPH1 Decreases proliferation and clonogenicity; decreases cyclin D1
PEG3 Induces p53-dependent apoptosis
Table 1: Putative Tumor Suppressor Genes Involved in Ovarian Cancer. This
table briefly describes the functions of several of the putative TSGs that are
either downregulated or inactivated in ovarian cancer. (Table adapted from Bast
et al. 2009).

7

1.2.3 Oncogenes
Oncogenes generally encode proteins that regulate cell growth. An
oncogene arises from a wild type counterpart termed a proto-oncogene that
undergoes some sort of change that increases the gene’s function. The change
could occur in the form of a point mutation that increases the gene product’s
activity, or a translocation that places the gene under the control of a
constitutively active promoter, etc (Li et al. 2001). Unlike TSGs, oncogenes are
typically dominant in nature, requiring only one affected allele in order to cause a
change in phenotype.

1.2.4 Oncogenes Implicated in Ovarian Cancer
HER-2/neu is a proto-oncogene that encodes a transmembrane receptor
tyrosine kinase (Li et al. 2001). Overexpression of this oncogene has
transforming properties in mice, and the rat homologue of this oncogene
promotes anchorage independent cell growth, DNA synthesis, and secretion of
matrix-degrading enzymes (Yu et al. 1991). HER-2/neu is overexpressed in 20%
to 30% of ovarian cancers, and is associated with both aggressive tumor biology
and poor prognosis (Li et al. 2001). Another oncogene that is implicated in
ovarian cancer is the RAB25 GTPase, which regulates cell motility, apoptosis,
autophagy, etc (Cheng et al. 2005). Table 2 lists several more oncogenes that
are implicated in ovarian cancer.

8

Gene Function
EIF5A2 Elongation factor
PRKCI Cytoplasmic serine–threonine protein kinase
PIK3CA Cytoplasmic lipid kinase
FGF1 Growth factor for cancer and angiogenesis
EGFR Protein tyrosine kinase growth factor receptor
NOTCH3 Cell surface growth factor receptor
KRAS Cytoplasmic GTPase
ERBB2 Protein tyrosine kinase growth factor receptor
PIK3R1 Cytoplasmic lipid kinase
CCNE1 Cyclin
AKT2 Cytoplasmic serine–threonine protein kinase
AURKA Nuclear serine–threonine protein kinase
Table 2: Oncogenes Associated With Ovarian Cancer. This table briefly
describes the functions of several of the oncogenes that are either amplified or
overexpressed in ovarian cancer. (Table adapted from Bast et al. 2009).

1.3 Transcription Factors

Transcription Factors (TFs) are proteins that regulate gene transcription
(Latchman, 1997). Many transcription factors can bind to DNA, although not all
TFs share this ability. As such, transcription factors can utilize a variety of
mechanisms in order to modify a specific gene’s rate of transcription. For
example, several General Transcription Factors (GTFs), such as TFIID, regulate
transcription by helping recruit RNA Polymerase II (Pol II), the RNA polymerase
responsible for transcription of mRNA in eukaryotes, to the promoter region of a
gene (Hahn, 2004).
Studies have shown that the GTFs facilitate eukaryotic transcription of
mRNA though several steps. First, the GTF known as Transcription Factor II D
(TFIID) binds to DNA. TFIID is composed of TATA Binding Protein (TBP), and
multiple TBP Associated Factors (TAFs). TBP binds to a sequence of DNA
known as the TATA element (Hernandez, 1993). The TATA element is located
9

about 25-30 base pairs upstream of the transcription start site. Next, TFIIB
recognizes and binds to the TFIID-DNA complex (Maldonado et al. 1990). Then
TFIIF and RNA Pol II are recruited as a complex. Afterwards, TFIIE and TFIIH
arrive and bind concomitantly. In addition, TFIIA can bind any time after TFIID
has, and can help stabilize the interactions amongst the GTFs and Pol II. At this
stage, this multi-protein complex is referred to as the Pre-Initiation-Complex
(PIC). In this state, Pol II is bound to the promoter region, but is not yet in the
active conformation required to begin transcription (Hahn, 2004). Soon a
conformational change occurs where 11-15 base pairs of DNA that surrounds the
transcription start site melts, by which time the PIC has transitioned into the open
complex. Following these events, the first phosphodiester bond of the mRNA
transcript is synthesized, Pol II is released from the promoter, and elongation of
the RNA transcript occurs (Orphanides et al. 1996). As a side note, it is now
known that a multiprotein complex referred to as Mediator binds to the PIC and is
required for nearly all Pol II dependent transcription in Saccharomyces
cerevisiae; however, there is still much left to uncover about the functions and
mechanisms of this multiprotein complex in higher eukaryotes (Björklund et al.
2005; Kornberg 2007).
10

Figure 1: Diagram of the Pre-Initiation and Open Complexes. DNA that surrounds
the Transcription Start Site has been unwound in the open complex. (Figure
adapted from Hahn, 2004)

1.4 Transcription Factors and Ovarian Cancer

In addition to the TSGs and oncogenes previously mentioned, several TFs
have been found to be associated with ovarian cancer as well. Many TFs
regulate the cell cycle and promote cell growth, and overexpression,
underexpression, misexpression, or mutation of these specific TFs can lead to
tumor survival and progression. Two TFs that are involved in ovarian cancer are
the p53 TSG and the MYC oncogene.

1.4.1 p53
The p53 TF stimulates the transcription of p21, which is an inhibitor of the
cell cycle (Vogelstein et al. 2000). p21 works by inhibiting Cyclin Dependent
Kinases (CDKs), which work together with their partner cyclins to promote cell
cycle progression. There is also evidence to suggest that the p53 Tumor
Suppressor Gene contributes to nucleotide excision repair, base excision repair,
11

and mismatch repair, all of which are critical to maintaining genome stability
(Gatz et al. 2006). As a fail-safe protective mechanism, p53 can also initiate
cellular apoptosis (Gottlieb et al. 1992). p53 activity is compromised in the
majority of human cancers, including in 60–80% of both sporadic and hereditary
ovarian cancer cases, leading to tumor progression (Bast et al. 2009).

1.4.2 Myc
Myc is believed to regulate the expression of 15% of all genes, including
several involved in cell division, cell growth, and apoptosis (Gearhart et al. 2007).
MYC also activates transcription of BRCA1, thereby promoting DNA double
strand break repair (Friedenson, 2007; Menssen et al. 2002). In addition, MYC
promotes DNA replication by activating the transcription of enzymes that catalyze
nucleotide biosynthesis (Liu et al. 2008). Furthermore Myc is also closely
involved in the checkpoint processes that monitor progression through the cell
cycle. For example, MYC can indirectly downregulate the expression of p21,
thereby contributing to cell cycle progression (Seoane et al. 2002). Additionally,
MYC induces E2F1 and Cyclin E-CDK2 activity, and since a consequence of the
activation of the G1 restriction checkpoint of the cell cycle is the inhibition of
CDK2 and a subsequent arrest in cell cycle progression, activation of Cyclin E–
CDK2 would allow the bypassing of this checkpoint and progression through the
cell cycle (Pickering et al. 2009). Myc is overexpressed in ovarian cancer, with
this oncogene promoting uncontrolled cell growth and DNA replication, even in
12

the presence of limiting external stimuli and growth factors (Bast et al. 2009;
Eilers et al. 1991).

1.5 Basis For Thesis Project
Previous studies have shown that abnormalities along chromosome 6 are
amongst the most common chromosomal alterations exhibited in human ovarian
carcinomas (Wake et al. 1980). Deletions and translocations involving different
portions of chromosome 6q have been reported in both primary ovarian
carcinomas and ovarian cancer cell lines (Buick et al. 1985; Deger et al. 1997;
Sheer et al. 1987; Tibiletti et al. 1996). Losses of heterozygosity are also
observed along this chromosome in primary ovarian tumors (Cliby et al. 1993;
Ehlen et al. 1990; Foulkes et al. 1993; Lee et al. 1990). In addition, several allelic
deletion mapping studies have found distinct regions of chromosome 6 that are
targeted by losses of heterozygosity (Cooke et al. 1996; Foulkes et al. 1993;
Orphanos et al. 1995, Wan et al. 1994). All of these findings suggest that
chromosome 6 may contain one or several Tumor Suppressor Genes (TSG)
whose loss contributes to ovarian tumor development.
Members of Dr. Louis Dubeau’s laboratory (Wan et al. 1994) attempted to
localize and isolate suspected TSGs on chromosome 6. The HEY ovarian
carcinoma cell line was one of the cell lines used for this purpose, specifically
because it carries karyotypic abnormalities along chromosome 6q. HEY cells are
derived from a human ovarian cancer xenograft (HX-62) that was originally
grown from a peritoneal deposit of a patient with moderately differentiated
13

papillary cystadenocarcinoma of the ovary (Buick et al. 1985). The HEY cell line
exhibits properties of tumorigenicity; it possesses anchorage-independent growth
abilities, and it causes tumor formation in nude mice.
Wan et al. then introduced an exogenous chromosome 6, which was
tagged with a neomycin resistance gene as a positive selection marker, into the
HEY cell line. They did this to verify their hypothesis that introduction of a normal
chromosome 6 would reduce or abolish tumorigenicity in these cells. As
hypothesized, the resultant HEY/Chr6 hybrid cells lost their tumorigenicity. Not
only do the HEY/Chr6 hybrids lack both anchorage-independent growth ability
and the ability to cause tumor formation in nude mice, they also exhibit reduced
rates of growth compared to HEY cells (with a doubling time of 3.38 days vs.
1.34 days) (Wan et al. 1999).
Wan et al. wanted to more finely map the putative locations of suspected
TSGs present on chromosome 6 by identifying revertant subclones of Hey/Chr6
hybrid cells which had lost portions of the exogenous chromosome 6 and had
regained their tumorigenic potential. They did this by inoculating nude mice with
100X10
6
HEY/Chr6 hybrid cells and isolating revertant cells from tissue culture
tumor explants (Wan et al. 1999). One of these revertant subclones is named
Hey/Chr6/R5b (NM22B). NM22B cells are capable of both anchorage
independent growth and tumor formation in nude mice. Upon examination, it was
determined that the NM22B cell line had lost a 0.36 megabase-pair portion of the
exogenous chromosome 6 (Wan et al. 1999).
14

More recently, RNA probes were created for both non-tumorigenic
HEY/Chr6 hybrid cells and revertant NM22B cells and were hybridized to
Affymetrix all exon microarray chips. This was done in order to measure and
compare relative hybridization intensities so that we could identify genes whose
RNA expression levels differ widely between the two cell types. One of the most
notable findings from this study was the discovery of a 15.02 fold increase in the
expression level of POLR2B in the NM22B cell line compared to HEY/Chr6
hybrid cells (P-value 5.1x10
-4
).

1.6 POLR2B
POLR2B [Polymerase (RNA) II (DNA directed) Polypeptide B, 140 kDa] is
the second largest subunit of RNA Pol II (Acker et al. 1992). The gene encoding
POLR2B is located on chromosome 4q12. The POLR2B subunit binds to DNA
(Forget et al. 2004), helps maintain contact in the active site of RNA Pol II
between the DNA template and the newly synthesized RNA, and plays a key role
in facilitating the formation of a phosphodiester bond between an incoming
ribonucleoside triphosphate and the elongating RNA transcript (Langelier et al.
2005).

1.7 Thesis Project Summary
During my studies I: (1) verified the finding from the RNA hybridization
microarray that POLR2B expression is increased in the NM22B cell line
15

compared to HEY/Chr6 hybrid cells (2) determined that knocking down POLR2B
expression in NM22B cells decreases their rate of growth.
To verify the microarray finding, I extracted RNA from both HEY/Chr6
hybrid cells and NM22B cells. Then I utilized semi-quantitative two step Reverse
Transcription-Polymerase Chain Reaction (RT-PCR) to reverse transcribe all of
the extracted RNA into cDNA, and to amplify the POLR2B cDNA. After
amplification of the POLR2B cDNA, I utilized gel electrophoresis to compare the
expression levels of POLR2B transcript between HEY/Chr6 hybrid cells and
NM22B cells.
To determine that knocking down POLR2B expression in the NM22B cell
line affects the rate of cell growth, I first ensured that the small interfering RNA
(siRNA) that I obtained against POLR2B effectively knocks down POLR2B
transcript levels. Then I performed a growth curve analysis where I calculated
cell numbers at regular intervals to compare the rate of cell growth of NM22B
cells treated with POLR2B siRNA to that of NM22B cells that are transfected with
control siRNA.
Research has shown the pivotal roles that Transcription Factors play in
cellular biology, and how aberrant TF activity and expression can severely
disturb normal cellular function. In fact, many oncogenes that promote tumor
survival and progression are TFs (Latchman, 1997).
POLR2B plays multiple critical roles in eukaryotic transcription. In addition
to the functions of POLR2B as a subunit of RNA Polymerase II, my findings
suggest that POLR2B has a previously undocumented role as a Transcription
16

Factor whose increased expression in NM22B cells enhances their rate of
growth, thereby promoting cancer cell growth and tumor progression.

17

Chapter 2: Experimental Methods

2.1 Cell Culture
Both HEY/Chr6 and NM22B cells were cultured in 100 mM petri dishes
(BD Falcon) in 9.75 mL of Dulbecco’s Modification of Eagle’s Medium (DMEM,
USC/Norris Comprehensive Cancer Center Cell Culture Core Facility)
supplemented with 10% Fetal Bovine Serum (FBS, Gemini Bio-Products) and 1%
penicillin/streptomycin (USC/Norris Comprehensive Cancer Center Cell Culture
Core Facility) . In addition, 0.25 mL of the antibiotic neomycin (AG Scientific) was
added to ensure that only cells that contained an exogenous chromosome 6
tagged with a neomycin resistance gene survived. Cells that do not express the
neomycin resistance gene product will not survive in the presence of neomycin.
Cells were passaged using 2 mL Dulbecco’s Phosphate Buffered Saline
(DPBS, Mediatech Inc) as a washing agent, and 2 mL Trypsin (USC/Norris
Comprehensive Cancer Center Cell Culture Core Facility) to resuspend the cells
that adhered to the dish. 2 mL medium was added to neutralize the Trypsin after
3-5 minutes of incubation (VWR) at 37 ° C. The cell susp ension was pipetted into
14 mL round-bottom tubes (BD Falcon) and centrifugated (IEC Clinical
Centrifuge) at setting 5 for 5 minutes. Once centrifugation was complete, the
supernatant was aspirated, leaving only the cell pellet. 5 mL of fresh medium was
then added and pipetted several times to resuspend the cell pellet.1 mL cell
suspension was then placed into new 100mM petri dishes containing 8.75 mL
18

medium and 0.25 mL neomycin. Dishes were incubated (VWR) at 37 ° C and 5%
CO
2
concentration.
2.2 RNA Isolation
RNA was isolated from both HEY/Chr6 hybrid cells and NM22B cells in
order to compare the relative amounts of specific mRNA transcripts between
both cell types.
Cells were grown in 100 mM petri dishes. Once dishes were fully confluent
with cells, medium was removed and cells were washed 2X with 1 mL DPBS in
order to remove any residual medium. Then a guanidinium thiocyanate-phenol-
chloroform extraction (TRIzol, Invitrogen) procedure was implemented to extract
RNA. 3 mL TRIzol was added to each 100 mM dish. The cell lysate was then
repeatedly passed through a pipette in order to maximize the breakdown of cells.
The lysate was then placed into Eppendorf tubes and incubated for 5 minutes at
room temperature (20-25 ° C). This was done to permit the complete dissociation
of nucleoprotein complexes. 0.6 mL chloroform was then added (0.2 mL for each
1 mL of TRIzol used) to the Eppendorf tubes. The tubes were then capped,
shaken vigorously for 15 seconds, incubated at Room Temperature (RT) for 2-3
minutes, and centrifugated (Eppendorf 5415C centrifuge) at 12,000g for 15
minutes at 4 ° C. RNase-AWAY (Invitrogen) was used from this point on to
prevent contamination of the RNA with RNase, which would result in RNA
degradation. The clear phase containing the RNA was removed from the
centrifugated tubes and poured into new Eppendorf tubes. The RNA was
precipitated with 1.5 mL isoprpopyl alcohol (0.5 mL for each mL TRIzol used).
19

The tubes were incubated for 10 minutes at RT. They were then centrifugated at
4 ° C for 10 minutes at 12,000g. The supernatant was de canted, and 3 mL 75%
ethanol was added (1 mL per 1 mL TRIzol used). Tubes were shaken for 5-10
seconds and centrifugated at 7500g for 5 minutes at 4 °C. The supernatant was
decanted, and the RNA precipitate was allowed to air-dry for 5-10 minutes. The
RNA was then dissolved in 50 μL DNase/RNase-free water (Gibco) and then
kept at 55-60 ° C for 10 minutes in a heatblock (VWR).

2.3 Semi-Quantitative Two Step RT-PCR
Semi-quantitative two step RT-PCR was utilized to create amplified DNA
from specific mRNA transcripts. First, cDNA was reverse transcribed from the
extracted RNA, then the cDNA was amplified via PCR.

2.3.1 Reverse Transcription/cDNA Synthesis
A spectrophotometer (Beckman Coulter DU640B) was used to determine
the concentration of RNA collected in each tube. RNA and DNase/RNase-free
water were added to 100 microL Eppendorf tubes in ratios which ensured that
each tube contained the same amount of RNA being prepared for cDNA
synthesis. 1 microL 10 nM dNTP mix (Invitrogen), and 1 microL oligo dT
(Invitrogen) were then added to each tube. The tubes were then incubated in a
thermal cycler (Biorad MJ Mini Personal Thermal Cycler) at 65 ° C for 5 minutes.
Then an Invitrogen kit was used to create a master mix consisting of 2 mL 10X
RT buffer, 4 microL MgCl
2
,

2 microL DTT, and 1 microL RNase-out, providing a
20

total of 9 microL (multiplied by the number of samples). The incubated tubes
were placed on ice for 1-2 minutes. 9 microL of master mix was then added to
each tube, which were then incubated in the thermal cycler at 42 ° C for 2
minutes. 1 microL of Reverse Transcriptase (Invitrogen SuperScript First-Strand
RT) was added to each tube. The tubes were then incubated in the thermal
cycler at 42 ° C for 50 minutes, then 70 ° C for 15 minu tes.

2.3.2 Polymerase Chain Reaction
1 microL RNaseH (Invitrogen) was added to each sample. Samples were
then incubated in the thermal cycler at 37 ° C for 20 m inutes. 2 microL of cDNA
from each sample was placed into new 100 microL Eppendorf tubes. The
reagents used per sample were 1 microL Taq Polymerase (Invitrogen), 2 microL
10X chromoTaq buffer (Invitrogen), 0.8 microL of 50 mM MgCl
2
(Invitrogen), 0.5
microL of 100 mM dNTP mix (Invitrogen), and 13.1 microL DNase/RNase-free
water (Gibco). 0.3 microL of 30 microM forward and reverse primer respectively
were added. The PCR reaction was ran as follows: initial denaturation at 94 ° C
for 5 minutes, 30 cycles of denaturation, annealing, and extension for 30
seconds, 45 seconds, and 30 seconds at 94 ° C, 55 ° C, and 72 ° C respectively,
with a final extension for 3 minutes at 72 ° C.

21

Gene Forward Primer
5’ 3’
Reverse Primer
5’ 3’
ACTB [β-Actin] GAAAATCTGCCACCAC
ACCT
AGAGGCGTACAGGGA
TAGCA
CCNB2 [Cyclin B2] TTGCAGTCCATAAACCC
ACA
ACTTGGAAGCCAAGA
GCAGA
POLR2A [polymerase
(RNA) II (DNA
directed) polypeptide
A, 220kDa]
CAAGTACATCATCCGA
GACAAT
AAAGGTAGACCATGG
GAGAAT
POLR2B [polymerase
(RNA) II (DNA
directed) polypeptide
B, 140kDa]
GGATTTGTGGCAAGAA
GCAT
CAAATATCCTGGCGG
TTCTT
POLR2F [polymerase
(RNA) II (DNA
directed) polypeptide
F]
GAATCACCACACCATA
CATGA
AGTCTTCATAGCTCC
CATCTG
POLR2I [polymerase
(RNA) II (DNA
directed) polypeptide
I, 14.5kDa]
GAACTGTGATTACCAG
CAGGA
CACTGTGTGACTGGA
AGAACA
TCEB3 [transcription
elongation factor B
(SIII), polypeptide 3
(110kDa, elongin A)]
GTTCTTGAACCCGTTTT
GGA
TGTTAGTACTCGTAG
CCGCT
Table 3: Primers Used For Semi-Quantitative PCR. Forward and reverse primers
were made against exons that flank large introns in order to allow for size based
differentiation between cDNA and pre-mRNA on an agarose gel. Primers were
obtained from the USC/Norris Comprehensive Cancer Center DNA Core Facility.

2.4 Agarose Gel Electrophoresis
70 mL TAE buffer, 1% agarose (Phenix), and 3 microL ethidium bromide
(Sigma-Aldrich) were used to create the agarose gel. TAE was used as a running
buffer. 3 microL 2-log DNA ladder (New England Biolabs) was loaded to verify
product size. 5 microL of each PCR product was loaded onto the agarose gel.
22

Electrophoresis was run for 1 hour at 110 volts (Biorad Powerpac 3000).
Electrophoresed samples were exposed to UV light and photographed (Biorad
Gel Doc 1000).

2.5 siRNA Transfection
NM22B cells were plated onto 35 mm dishes (BD Falcon) in 1.5 mL
DMEM supplemented with 10% FBS. Both penicillin/streptomycin and neomycin
were absent, as they would interfere with the transfection process by causing cell
death. The dishes were then transfected when cells were at 30%-50%
confluence. Per sample dish, 5 nM POLR2B siRNA (Ambion) in 250 microL Opti-
MEM I Reduced Serum Medium (Invitrogen) was mixed with 5 microL
Lipofectamine 2000 (Invitrogen) in 245 microL Opti-MEM I Reduced Serum
Medium that had been mixed and incubated at room temperature for 5 minutes.
The resultant mixture was incubated at room temperature for 20 minutes. 500
microL of this mixture was then added to each dish, creating a final volume of 2
mL.

2.6 Cell Number Determination
Cell numbers were determined using a Beckman Coulter Z2 Series
Counter at 0, 2, and 4 days post-transfection. Dishes were washed with DPBS,
and treated with 500 microL Trypsin. 5 mL syringes (BD) with 25 gauge needles
(BD) were used to mix 200 microL of cell suspension from each dish with 9.8 mL
Isoton II Diluent (Beckman Coulter). Blanks with 10 mL Isoton II Diluent were
23

used to ensure accurate cell counts. The counter was flushed with Coulter Clenz
(Beckman Coulter) in between each sample. Triplicates were used for each cell
count measurement.

24

Chapter 3: Results
To verify the results of the microarray, semi-quantitative RT-PCR was
performed on three gene transcripts which the microarray data suggested as
being more highly expressed in the NM22B cell line compared to HEY/Chr6
hybrid cells. CCNB2 was said to have been upregulated ~20 fold (p-value <1X10
-
5
), TCEB3 ~12 fold (p-value 3.4x10
-3
), and POLR2B ~15 fold (p-value 5.1x10
-4
).
Figure 2 shows that, according to the semi-quantitative RT-PCR results, all three
gene transcripts are in fact upregulated in the NM22B cell line compared to the
HEY/Chr6 hybrid cells.

Figure 2: Agarose Gel Showing Results of Semi-Quantitative RT-PCR
Amplification of Four mRNA Transcripts (Cyclin B2, Elongin A, POLR2B, and
Beta-Actin). Lanes with the letter designation H contain cDNA created from
mRNA transcript extracted from HEY/Chr6 hybrid cells; lanes with letter
designation R contain cDNA created from mRNA transcript extracted from the
Revertant NM22B cell line. Beta-Actin served as a loading control. This
experiment was performed in duplicate, with the same findings (duplicate
experiment not shown). DNA ladder values are in kilobases.

Next, two siRNA molecules directed against POLR2B were tested. The
two siRNAs tested were Ambion Silencer Select Pre-designed siRNA ID# s10796
(5’3’ sense sequence GGAACGAGAUUGUCAGAUUTT, anti-sense
25

AAUCUGACAAUCUCGUUCCAT ) and Ambion Silencer Select Pre-designed
siRNA ID# s10797 (5’3’ sense sequence GAAUUGGAGAGCACCAAUATT,
anti-sense UAUUGGUGCUCCAAUUCAT. siRNA ID# s10796 was proven to be
more effective. Based on results shown in figure 3, we decided to use 5 nM
s10796 siRNA to perform our knockdown experiments.

Figure 3: Agarose Gels Showing Effects of siRNA Transfection on POLR2B and
Beta-Actin Transcript Levels. NM22B cells were transfected with 3, 5, 7, or 9 nM
of siRNA. Semi-quantitative RT-PCR was performed at 48 hours and 96 hours
post-transfection.Figures 3A and 3C show the effects of both POLR2B siRNA
and GFP siRNA (Ambion) transfection on POLR2B transcript levels at 48 hours
and 96 hours post-transfection respectively. Figures 3B and 3D show the effects
of POLR2B siRNA and GFP siRNA transfection on Beta-Actin transcript levels at
48 hours and 96 hours respectively as controls. Data shown for Ambion Silencer
Select Pre-designed siRNA # s10796 (s10797 data not shown). Red rectangles
highlight concentration of siRNA chosen for use in knockdown experiments.

26

siRNA treatment was performed at day 0. The numbers of cells per dish
were then counted at day 0, 2, and 4. Figure 4A shows the average number of
cells per 35 mm dish at the designated time points. POLR2B siRNA treatment
resulted in a decreased rate of growth in NM22B cells, markedly increasing their
doubling time as compared to GFP siRNA treated controls (Figure 4C). Semi-
quantitative RT-PCR was then performed at day 4 (Figure 4D). Comparison
between lanes 2 and 6 suggest that POLR2B transcript levels were knocked
down in NM22B cells to levels similar to those found in HEY/Chr6 hybrid cells.
A

DAY 0 DAY 2 DAY 4
GFP siRNA Treated
NM22B cells
87,833 ±
6,966.91
314,733 ±
5,041.61
1,218,433 ±
377,994.00
POLR2B siRNA Treated
NM22B Cells
75,533 ±
8,499.87
278,500 ±
9,247.88
295,100 ±
66,400.40
B
DAY 0 DAY 2 DAY 4
GFP siRNA Treated
NM22B cells
4.94 ± 0.04 5.50 ± 0.01 6.09 ± 0.14
POLR2B siRNA Treated
NM22B Cells
4.88 ± 0.05 5.44 ± 0.01 5.47 ± 0.11
Figure 4: Effects of siRNA Transfection. Cells were transfected with either
POLR2B siRNA or GFP siRNA. Figure 4A shows the average number of cells
per 35 mm dish for each condition at day 0, 2, and 4 respectively. Standard error
shown. Figure 4B shows the log of the average number of cells per 35 mm dish
for each condition at day 0, 2, and 4 respectively. Standard error shown. Figure
4C plots the log values of the average cell counts. Doubling times calculated
using average cell counts at day 0 and day 4. siRNA transfection was performed
at day 0. Triplicates were performed of each cell count. Figure 4D is an agarose
gel. The lane contents are as follows: 1, ladder; 2, POLR2B transcript level in
NM22B after treatment with siRNA against POLR2B; 3, corresponding Beta-Actin
control; 4, POLR2B transcript level in NM22B after treatment with siRNA against
GFP; 5, corresponding Beta-Actin control; 6, empty; 7; endogenous POLR2B
transcript level in HEY/Chr6; 8, endogenous POLR2B transcript level in NM22B;
9 and 10, Beta-Actin controls for NM22B and HEY/Chr6 respectively. Entire
experiment was performed in duplicate (duplicate data not shown).

27

Figure 4, Continued

C

D

We then revisited the microarray data to determine whether differences in
expression levels between the HEY/CHr6 hybrid cells and the NM22B cells
existed for the other 11 subunits of RNA Pol II. As table 4 shows, we were not
able to obtain any microarray data for 2 of the other 11 subunits, and values for
fold expression differences for 4 other subunits were not statistically significant
28

(with P-values greater than 0.05). However, out of the 5 remaining subunits that
the microarray did provide statistically significant data for, none of them were
upregulated more than 5.69 fold, compared to the 15.02 fold upregulation for the
POLR2B subunit.
Gene Name Fold Increase in NM22B
(Compared to HEY/Chr6)
P-Value
POLR2A 3.30
2.8X10
-3

POLR2B 15.02
5.1X10
-4

POLR2C 1.56
3.4X10
-2

POLR2D NA NA
POLR2E 2.51
2.8X10
-3

POLR2F 0.97 0.69
POLR2G 1.40 0.16
POLR2H 3.96
8X10
-3

POLR2I NA NA
POLR2J 1.05 .063
POLR2K 5.68
2.8X10
-3

POLR2L 0.93 0.38
Table 4: Microarray Data Showing Expression Level Differences Between
HEY/Chr6 Hybrid Cells and NM22B Cells for the Subunits of RNA Pol II. Data for
POLR2D and POLR2I are not available, and is not statistically significant for
POLR2F, POLR2G, POLR2J, and POLR2L.

To verify the validity of the microarray data, we performed semi-
quantitative RT-PCR on 4 subunits of RNA Pol II. We examined 2 subunits that
the microarray provided statistically significant data for (POLR2A, and POLR2B),
1 subunit where the data provided was not statistically significant (POLR2F), and
1 subunit where no data was provided from the microarray (POLR2I). Figure 5
confirms the findings that POLR2A and POLR2B expression is upregulated in the
NM22B cell line. Even though the data for POLR2F expression provided by the
29

microarray was not statistically significant, figure 5 confirms that expression
levels in the two cell types are similar. POLR2I expression levels appear similar
as well.

Figure 5: Agarose Gel Showing Results of Semi-Quantitative RT-PCR
Amplification of Five mRNA Transcripts (POLR2A, POLR2B, POLR2F, POLR2I,
and Beta-Actin). Lanes with the letter designation H contain cDNA created from
mRNA transcript extracted from HEY/Chr6 hybrid cells; lanes with letter
designation R contain cDNA created from mRNA transcript extracted from the
Revertant NM22B cell line. Beta-Actin served as a loading control.

30

Chapter 4: Discussion & Future Directions

Epidemiological studies have indicated that family history of ovarian
cancer is a substantial risk factor for the disease, with an estimated 10-15% of
ovarian cancer cases attributable to heredity (Risch et al. 2001). A number of
genes are associated with ovarian cancer, including BRCA1, BRCA2, RAB25,
etc (Tables 1, 2). In addition, several Transcription Factors, such as p53 and
MYC, are now known to be involved in ovarian cancer as well. With all of the
substantial contributions that TFs make to promoting cellular survival and
regulating the cell cycle, one can understand how their aberrant expression or
mutation can lead to tumor growth and progression.
The available information about POLR2B is very sparse, and is limited to
describing its functions as a subunit of RNA Pol II. In my studies, I uncovered
additional information about POLR2B and the roles it plays in cellular biology. I
have shown that POLR2B is upregulated by more than 15 fold in the NM22B
ovarian carcinoma cell line compared to non-tumorigenic HEY/Chr6 hybrid cells.
Knockdown experiments I performed showed that decreasing the amount of
POLR2B transcript in NM22B cells to levels similar to those seen in HEY/Chr6
hybrid cells drastically reduces the rate of growth of those NM22B cells, resulting
in an almost 100% increase in doubling time. The fact that POLR2B is
upregulated by such a substantial amount in NM22B cells suggests that its
quantity inside the cell exceeds that which could be incorporated into Pol II
enzymes; this is especially true when comparing the availability of POLR2B with
the relatively limited availability of the other subunits I examined, which are
31

required to form the complete and active polymerase. These findings suggest
that POLR2B has a role, separate from its functions as a subunit of RNA Pol II,
as a Transcription Factor that promotes cancer cell growth and tumor
progression. The implications this information may have for ovarian cancer
diagnosis and treatment could be profound.
Ovarian cancer claims thousands of lives every year, and despite decades
of continuous research, the 5 year survival rate of patients diagnosed with
ovarian cancer has only modestly increased from 37% in 1975-1977 to 45% in
1996-2003, and the death rate has only slightly decreased from 9.51% in 1991 to
8.75% in 2004 (Jemal et al. 2008). The limited improvement in ovarian cancer
survival is partially due to most cases of the disease being diagnosed in its late
stages, which is in turn due to the absence of both specific disease symptoms
and an effective screening strategy (Bast et al. 2009; Dinh et al. 2008; Goff et al.
2000). While new screening strategies and diagnostic markers are currently
being developed and evaluated, there is still much more work to be done in order
to attain substantial improvements in ovarian cancer survival rates. For instance,
the relatively recently examined diagnostic marker CA 125 is only expressed in
about 80% of ovarian cancers, requiring additional markers to detect early stage
disease (Bast et al. 2009). Such biomarkers are being identified via a variety of
methods, including expression array analyses, which is exactly how we
discovered that POLR2B expression was upregulated in the NM22B cell line. I
propose that we could examine other ovarian cancer cell lines via RT-PCR to
determine whether POLR2B expression is upregulated in those cell types. If
32

POLR2B is upregulated in those cell lines, then we could proceed to examine
early stage ovarian carcinoma tissue samples to determine if POLR2B is
upregulated in those samples as well. After sufficient testing, POLR2B could
eventually serve as a member of a diagnostic marker panel that would identify
ovarian cancer in its early stages.
Many argue that increases in long term survival for ovarian cancer
patients might be achieved by translating recent insights at the molecular and
cellular levels to develop individualized treatment strategies (Bast el a. 2009; Yap
et al. 2009). With this in mind, I propose that we could perform expression array
analyses on patient tumor samples in order to identify proteins that are
abnormally expressed in those tumors. Based on the results, we could then
develop personalized treatment strategies for each patient. For instance, if
upregulation of POLR2B is discovered in a patient’s tumor sample, one could
seriously consider targeting that protein as part of a customized treatment
strategy for that patient, given what I have shown of POLR2B’s ability to
accelerate cell growth. There are plenty of examples of individualized treatment
strategies that are targeting upregulated oncogenes in much the same way that I
propose targeting of POLR2B. For instance, small molecule inhibitors of the
Aurora kinase oncogenes are currently being evaluated for several cancers,
antibodies that inhibit the NOTCH3 oncogene or its ligands are being developed,
new gold compounds have been developed to target the PRKC1 oncogene, and
perhaps most related to my study, the inhibition of the MYC
oncogene/Transcription Factor has proven to be an effective and viable
33

treatment strategy in a preclinical mouse model of lung adenocarcinoma (Bast et
al. 2009; Gautschi et al. 2008; Li et al. 2008; Soucek et al. 2008). In addition, this
information suggests that pharmaceuticals that target POLR2B could be
developed, tested, and proven to be effective in treating ovarian cancer.
Further investigation of POLR2B is required in order to determine whether
POLR2B can directly cause cell transformation. To determine this, one could
increase POLR2B expression in HEY/Chr6 hybrid cells via an expression vector,
and then determine whether the overexpression of POLR2B in the cells confers
properties of tumorigenicity, such as anchorage independent cell growth.
TFs can utilize any of several methods to regulate gene transcription.
General Transcription Factors regulate transcription by helping recruit RNA Pol II
to the promoter region of a gene (Hahn, 2004). Other TFs catalyze acetylation of
DNA via Histone Acyl-Transferase (HAT) activity, where Lysine residues on
histones are acetylated, resulting in chromatin structure alteration and increased
accessibility of DNA to the transcriptional machinery (Narlikar et al. 2002). Still
other TFs work by recruiting coactivator proteins to the transcription factor-DNA
complex, which can increase gene expression by stabilizing the RNA polymerase
complex, allowing a more rapid transition from the initiation phase to the
elongation phase of transcription. POLR2B may be utilizing any of these
mechanisms to regulate gene transcription, and further experimentation is
required in order to determine exactly how POLR2B performs this function. For
instance, an acetylation assay could determine if POLR2B possesses HAT
34

activity, and a co-immunoprecipitation experiment could determine if POLR2B
forms complexes with any coactivator proteins.
Furthermore, determination of the effects of POLR2B upregulation on the
expression levels of other gene products in the NM22B cell line could be
performed by knocking down POLR2B expression in NM22B cells and comparing
the expression pattern of these cells against that of NM22B cells treated with
control siRNA.
In addition to verifying upregulation of POLR2B in the NM22B cell line, I
also verified upregulation of CCNB2 (Cyclin B2) and TCEB3 (Elongin A). Cyclin
B2 is a member of the B-type Cyclin family, which includes Cyclin B1 and Cyclin
B2. The B-type Cyclins associate with p34
cdc2
kinase and are components of the
cell cycle regulatory machinery, being directly involved in the G2-M phase
transition (Minshull et al. 1989). Studies have shown that Cyclin B2 knockout
mice are smaller than normal mice (Brandeis et al. 1998), which suggests that
Cyclin B2 expression gives some sort of growth advantage. Moreover, studies
have reported upregulation of both Cyclins B1 and B2 in human malignant
tumors, such as in colorectal cancer (Park et al. 2007; Sarafan-Vasseur et al.
2002; Soria et al. 2000). Elongin A is the transcriptionally active subunit of
Elongin, and Elongin B and Elongin C are positive regulatory subunits (Aso et al.
1995). Elongin is an elongation factor that increases the rate of RNA Pol II
transcription in vitro by decreasing the frequency and/or duration of pauses that
RNA Pol II makes along the DNA template (Aso et al. 1995; Conaway et al.
2000; Shilatifard et al. 2003; Sims et al. 2004). Given what is known about Cyclin
35

B2 and Elongin A, I propose that further experimental investigation of the
involvement of Cyclin B2 and Elongin A in ovarian cancer may ultimately provide
additional diagnostic and treatment options for ovarian cancer patients in the
future.
Ovarian cancer affects thousands every year, and given that current
treatments have their greatest efficacy against early stage tumors, it is imperative
that we develop improved methods of detect this disease in its infancy. It is also
important that we strive to develop new and improved treatments for ovarian
cancer. POLR2B could prove to be both an important diagnostic tool and
treatment target, but first we must gain a deeper understanding of the
mechanism and consequences of POLR2B’s involvement in ovarian cancer,
thereby gaining a deeper understanding of ovarian cancer itself.

36

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Abstract (if available)

Abstract Ovarian cancer incidence is highest in the western world, where it is the leading cause of death from gynecological malignancies. Numerous risk factors for ovarian cancer have been identified, including the substantial risk associated with family history of the disease. Genetic predispositions contribute to familial risk, and at least 10% of ovarian cancer incidence is thought to be attributable to genetic factors. Several of the proteins that are associated with ovarian cancer are Transcription Factors that promote cancer cell growth and tumor progression. POLR2B is the second largest subunit of RNA Polymerase II, which is the polymerase responsible for transcription of mRNA in eukaryotes. POLR2B binds to DNA, helps maintain contact in the active site of RNA Polymerase II between the DNA template and the newly synthesized RNA, and plays a key role in facilitating the formation of a phosphodiester bond between an incoming ribonucleoside triphosphate and the elongating RNA transcript. The studies presented here have shown that POLR2B is upregulated in the NM22B ovarian carcinoma cell line to the point that it exceeds the availability of the other subunits of RNA Polymerase II examined, and that knocking down the expression of this subunit via siRNA results in decreased rates of cell growth. These findings suggest that POLR2B has a role, separate from its functions as a subunit of RNA Pol II, as a Transcription Factor that promotes cancer cell growth and tumor progression.

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Asset Metadata

Creator Kohan, George (author)

Core Title POLR2B and its contributions to cancer cell growth

School Keck School of Medicine

Degree Master of Science

Degree Program Experimental and Molecular Pathology

Publication Date 02/21/2010

Defense Date 08/06/2009

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

Tag genetics,HEY/Chr6,NM22B,OAI-PMH Harvest,oncogene,ovarian cancer,ovarian cancer genetics,ovarian carcinoma,POLR2B,RNA polymerase II

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Dubeau, Louis (committee chair), Coetzee, Gerhard A. (committee member), Hofman, Florence M. (committee member)

Creator Email Gkohan@usc.edu,Masoud2001@aol.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m2573

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Legacy Identifier etd-Kohan-3217.pdf

Dmrecord 251783

Document Type Thesis

Rights Kohan, George

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