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University of Southern California Dissertations and Theses
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The role of microRNAs in cancer
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The role of microRNAs in cancer
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Content
THE ROLE OF MICRORNAS IN CANCER
by
Jeffrey Mathew Friedman
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(BIOCHEMISTRY AND MOLECULAR BIOLOGY)
August 2009
Copyright 2009 Jeffrey Mathew Friedman
ii
Acknowledgments
I would like to acknowledge the following people who helped me complete this thesis:
Peter A. Jones for your support, unwavering belief in my abilities, and subtle methods of
persuasion.
Gangning Liang for being interested and excited about microRNAs and my project.
Peter W. Laird and Gerry Coetzee for their invaluable advice during lab meetings and as
committee members.
Robert Maxson, Shao-yao Ying, Michael Stallcup, Peter Nichols, Mo-Lee Chen, Wei Ye,
Susan Groshen, Jasmine Zhou, Jim Lui, Ben Berman, Kim Siegmund, Joseph Hacia, Li
Jia, and Omar Khalid for their generosity, support and suggestions.
Past and present members of the Jones’ lab with whom I have had the pleasure of
working: Gerda Egger, Yoshimasa Saito, Connie Cortez, Einav Gal-yam, Shinwu Jeong,
Terry Kelly, Phillippa Oakford, Erika Wolff, Flora Han, Xiangning Qiu, Shikhar Sharma,
Daniel Carvalho, Joy Lin, Christine Yoo, Yvonne Tsai, Tina Miranda, Yoshitomo
Chihara, and Jody Chuang.
My friends and family including Mom, Dad, Brian, Rachel, Bosco and Rio, whose
support through this process has been unyielding and extraordinary.
iii
Table of Contents
Acknowledgments
ii
List of Tables
vi
List of Figures
vii
Abstract
ix
Chapter 1: MicroRNAs are Critical Mediators of Differentiation, Development
and Disease
1
Introduction 1
miRNA biogenesis and basic function 3
miRNAs regulate important biological processes 4
miRNAs involved in cancer 5
Epigenetics and miRNAs 10
The future of miRNAs in medicine 13
Summary 14
Overview of thesis research
15
Chapter 2: Stem-loop miRNA qPCR and Bladder Cancer miRNA Profiling 19
Introduction 19
Materials and Methods 23
Cell lines and primary tumors 23
Northern blots 24
5-aza-2 ′-deoxycytidine (5-Aza-CdR) and 4-phenylbutyric acid (PBA)
treatment
24
Stem-loop RT-PCR for miRNAs 25
miRNA microarray 25
Reverse transcription and Taqman qPCR 26
Expression vectors and transfections 26
Cell proliferation and colony formation assays 27
Results 28
Stem-loop RT-PCR validates miR-127 is silenced in cancer and re-
expressed after epigenetic treatment
28
Differential miRNA expression between primary TCCs and matched
normal urothelium
32
Restored expression of downregulated miRNAs in TCC cell lines reveals
novel putative tumor suppressors
35
Discussion
41
Chapter 3: The Functional Effects of miR-101 Misexpression in Bladder Cancer 47
Introduction 47
Materials and Methods 48
iv
Cell lines and tissues samples 48
Expression vectors and transfections 49
Reverse transcription and Taqman qPCR 49
Cell proliferation and colony formation assays 50
Western blot 50
Luciferase assay 51
mRNA microarray 52
Chromatin Immunoprecipitation assay (ChiP) 53
Results 53
miR-101 is also downregulated in colon and prostate cancer tumors 53
miR-101 represses the Polycomb group protein EZH2 and the Polycomb
Repressive Complex 2 histone modification H3K27me3
54
EZH2 is a direct target of miR-101 59
Knockdown of EZH2 shows phenotypic overlap with the restoration of
miR-101 expression in UM-UC-3 cells
62
Discussion
67
Chapter 4: Epigenetic Therapy Upregulates the Tumor Suppressor MicroRNA-
126 and Its Host Gene EGFL7 in Human Cancer Cells
70
Introduction 70
Materials and Methods 72
Cell lines and primary tumors 72
5-aza-2 ′-deoxycytidine (5-Aza-CdR) and 4-phenylbutyric acid (PBA)
treatment
72
5′-Rapid Amplification of cDNA ends (RACE) 72
Northern blots 73
RT-qPCR 73
DNA methylation analysis 74
Chromatin Immunoprecipitation assay (ChiP) 75
Results 75
miR-126 is downregulated in primary tumors and cancer cell lines but is
activated by treatment with 5-Aza-CdR and PBA
75
The primary transcripts of miR-126 correspond to multiple transcripts of
EGFL7
78
miR-126 and the alternative transcripts of EGFL7 are concomitantly
regulated in cancer cell lines and primary tumors
80
Epigenetic alterations around the CpG island promoter of the S2
transcript of EGFL7
81
Discussion
84
Chapter 5: Using a Flexible Pol II Driven Expression Vector to Generate
Multiple MicroRNAs by Linking Endogenous
87
Introduction 87
Materials and Methods 89
Cell lines 89
v
Expression vector construction and transfections 90
Reverse transcription and Taqman qPCR 90
Northern blot 91
Cell proliferation assay 91
Results 92
Discussion
96
Chapter 6: Summary
100
References 106
vi
List of Tables
Table 1.1. miRNAs that are implicated in human cancer
7
Table 2.1. RT-qPCR of differentially expressed miRNAs in TCC cell lines
36
Table 2.2. Summary of RT-qPCR of differentially expressed miRNAs in TCC
for 28 patient samples
42
vii
List of Figures
Figure 1.1. Genomic locations of miRNAs
2
Figure 1.2. The function of tumor suppressor miRNAs
8
Figure 2.1. Diagram of miRNA-specific stem-loop RT-qPCR
21
Figure 2.2. Diagram of miR-127-specific stem-loop RT-qPCR primers
30
Figure 2.3. Expression patterns of miR-127 in cancer cells and normal
fibroblasts treated with 5-Aza-CdR and PBA
31
Figure 2.4. miRNA microarray showing the differentially expressed miRNAs in
TCC
33
Figure 2.5. miRNA RT-qPCR of 28 clinical TCC samples and matched normal
urothelium
34
Figure 2.6. RT-qPCR confirms that pcDNA3.1(+) vectors express mature
miRNAs
37
Figure 2.7. RT-qPCR for miR-101 shows that miR-101 transfections restore
miR-101 to levels similar to those in normal tissues
38
Figure 2.8. Restored miRNA expression in TCC cell lines reveals novel tumor
suppressors
40
Figure 3.1. miR-101 is downregulated in colon and prostate tumors
55
Figure 3.2. RT-qPCR analysis of 20 TCC samples shows that EZH2 is
upregulated in tumors compared to adjacent normal tissue
56
Figure 3.3. Western blot analysis of TCC cell lines after transient transfection
with pre-miR-101
58
Figure 3.4. The highly conserved sequence of the 3 ′UTR of EZH2
60
Figure 3.5. Luciferase assay conducted in UM-UC-3 cells
61
Figure 3.6. Knockdown of EZH2 decreases cell proliferation and colony
formation in TCC cell lines
63
Figure 3.7. pre-miR-101 transfection and siRNA to EZH2 lead to the up-
regulation of overlapping genes
65
viii
Figure 3.8. miR-101 transfection decreases H3K27me3 enrichment in gene
promoters
66
Figure 4.1. Northern blot analysis of miR-126
77
Figure 4.2. 5 ′-RACE for the primary transcript of miR-126 and RT-qPCR
analysis of EGFL7 normalized to GAPDH
79
Figure 4.3. Epigenetic alterations around the CpG island promoter of the
alternative transcript of EGFL7
83
Figure 5.1. Strategy to create multiple miRNA expression vector
94
Figure 5.2. The miR-34abc vector expresses mature miR-34a, miR-34b, and
miR-34c at comparable levels to the individual miRNA expression
vectors alone
95
Figure 5.3. Cell proliferation assay shows enhanced growth inhibition of the
multiple miRNA expression vector when compared to single miRNA
vectors
97
ix
Abstract
MicroRNAs (miRNAs) are small non-coding RNAs that are expressed in higher
eukaryoates and have even been found in viral genomes. They usually act as endogenous
repressors of target genes by either inhibiting translation, causing mRNA degradation, or
by a combination of both mechanisms. More than 900 mature miRNA sequences have
been identified in humans, and although this accounts for less than 2% of human genes, it
is predicted that 30% of mRNAs are targeted by miRNAs. miRNAs play critical roles in
most cellular processes including development, differentiation, and the homeostasis of
both a cell and an organism. Moreover, many disease states, including cancer, occur or
are sustained by miRNA dysregulation. Here we will review the latest reports of miRNA
involvement and aberrant expression in human disease with an emphasis on cancer.
1
Chapter 1: MicroRNAs are Critical Mediators of Differentiation, Development and
Disease
Introduction
MicroRNAs (miRNAs) are ~22 nucleotide long small RNA molecules that
usually act as endogenous repressors of gene activity. Although miRNAs were initially
discovered in the nematode C. elegans, they have subsequently been found in various
organisms and are thought to be expressed in all metazoan eukaryotes (Cullen, 2004).
The importance of miRNAs in humans continues to become apparent and it is clear that
faithful miRNA expression is critical for a myriad of biological processes ranging from
differentiation and development to physiological homeostasis.
There are currently 969 mature human miRNA sequences in the Sanger database
version 12.0, many of which are highly conserved in other organisms (Berezikov et al.,
2005). miRNAs are either intergenic, located in non-coding regions between annotated
genes, or intronic, located within protein coding genes (Fig. 1.1) (Bartel, 2004). The
intergenic miRNAs are likely transcribed from their own promoters and many are located
in miRNA clusters that generate long polycistronic transcipts (Bartel, 2004). The intronic
miRNAs are usually coordinately expressed with their host genes and are therefore
regulated by the same factors as the host gene (Cullen, 2004). In addition, many
miRNAs are expressed in a tissue-specific or developmental stage-specific manner,
indicating the importance of coordinated regulation and function of miRNAs (Farh et al.,
2005; Stark et al., 2005; Zeng, 2006).
2
Figure 1.1. Genomic locations of miRNAs. miRNAs may be located in almost any
region of the genome. They may be grouped into clusters or situated alone. A, an
intergenic miRNA may be located many kb away from coding genes and transcribed as a
pri-miRNA, such as in miR-203. B, polycistronic miRNAs may be grouped into a cluster
and transcribed as a pri-miRNA, which yields several miRNAs. This occurs with the
miR-431~136 cluster. C, intronic miRNAs are located in canonical genes and are part of
an intron. The mature miRNA may be processed from the intron of the host gene
transcript. This occurs when miR-126 is processed from the EGFL7 transcript. Arrow,
transcription start site; rectangle, exon; hairpin, pre-miRNA.
Intergenic miRNAs
miRNA cluster
Intronic miRNA
chr14 q32.33
miR-203
chr14 q32.31
miR-431 miR-433miR-127 miR-432miR-136
chr9 q34.3
Single miRNA
miR-126
exon - TSS - pre-
miRNA -
A
B
C
EGFL7
3
miRNA biogenesis and basic function
Most miRNAs are transcribed by RNA polymerase II as long (>1 kb) primary
miRNAs (pri-miRNA) that contain a 5 ′ 7-methyl guanosine cap and a 3 ′ poly adenosine
tail, similar to mRNAs (Lee et al., 2004). However, miRNAs embedded in repetitive
elements such as Alus can be transcribed by RNA polymerase III (Borchert et al., 2006).
The hairpin structure in the pri-miRNA is normally recognized and cleaved by the
nuclear RNase III enzyme Drosha and its cofactor DiGeorge syndrome critical region 8
(DGCR8), although there are exceptions that bypass Drosha processing (Kim, 2005;
Ruby et al., 2007). Drosha/DGCR8 mediated pri-miRNA cleavage yields a precursor
miRNA (pre-miRNA) of ~70 nt that forms a hairpin, which is exported to the cytoplasm
via the nuclear transport receptor exportin-5 and the cofactor RanGTP (Kim, 2005).
Once in the cytoplasm, the pre-miRNA is cleaved by the RNase III enzyme Dicer into a
double stranded RNA of ~22 nt. The strand with the less stable 5 ′ hydrogen bonding is
usually selected as the mature miRNA, and is then incorporated into the RNA-induced
silencing complex (RISC) (Cullen, 2004).
RISC directs the miRNA to binding sites in the target mRNAs, which usually
leads to gene repression, although there have been some reports of gene upregulation
(Orom et al., 2008; Vasudevan et al., 2007). The miRNA binding sites of the target
mRNA are often perfectly complementary to the “seed” sequence (5 ′ nt 2-7) of the
miRNA and are located in the 3 ′ untranslated region (UTR), but many important targets
do not follow these rules (Brodersen and Voinnet, 2009; Orom et al., 2008; Tay et al.,
2008). The exact mechanisms of gene repression are still being elucidated, but there is
evidence for translational initiation inhibition, translational elongation inhibition,
4
premature translational termination, and cotranslational protein degradation (Eulalio et
al., 2008). In addition, several studies suggest that miRNA binding enhances mRNA
degradation, such that transcript levels decrease along with protein levels (Eulalio et al.,
2008). Transcriptomics and proteomics approaches indicate that there may be >200
targets per miRNA (Lim et al., 2005) and a miRNA can directly affect the translation of
hundreds of genes (Baek et al., 2008; Selbach et al., 2008b). These widespread effects of
miRNAs are not surprising considering the promiscuous nature of miRNA:mRNA
interactions.
miRNAs regulate important biological processes
The importance of faithful miRNA expression has been implicated in numerous
biological and cellular events. The miRNA let-7 is critical for developmental timing
(Reinhart et al., 2000), a developmentally regulated miRNA (bantam) controls cell
proliferation via regulation of apoptosis (Brennecke et al., 2003), and miRNAs control
embryonic stem cell differentiation (Tay et al., 2008) and stem cell division (Hatfield et
al., 2005). Other examples are miR-196, which is involved in hindlimb development
(Hornstein et al., 2005), and the brain-specific miR-134, which contributes to the
spatiotemporal control of mRNA translation that is necessary for synaptic development
and plasticity (Schratt et al., 2006). Skin differentiation is promoted by miR-203, which
represses p63 in stratified epithelial tissues (Yi et al., 2008), while precise levels of miR-
1 are critical in cardiogenesis (Zhao et al., 2005). Normal immune function is dependent
on miR-155 (Rodriguez et al., 2007) and B-cell differentiation is controlled by miR-150
mediated repression of the transcription factor c-Myb (Xiao et al., 2007). In addition, the
5
pancreatic islet cell-specific miR-375 regulates insulin secretion by inhibiting
Myotrophin, a component of the exocytosis pathway (Poy et al., 2004).
Recent studies have shown that miRNAs may play causative roles in several
diseases. In neurological diseases, the loss of the miR-20a/b-1 cluster has been
implicated in Alzheimer’s disease (Hebert et al., 2008) and the loss of miR-133b may
contribute to the decrease in dopaminergic neurons seen in Parkinson’s disease (Kim et
al., 2007). In heart disease, the expression of miR-21 in cardiac fibroblasts contributes to
interstitial fibrosis and cardiac hypertrophy (Thum et al., 2008), while miR-1 and miR-
133 in cardiomyocytes protect against hypertrophy (Care et al., 2007). As a defense
against viral infection, interferon- β upregulates miRNAs that target hepatitis C virus
RNA and decrease replication and infection (Pedersen et al., 2007). On the other hand,
during latent infection herpes simplex virus 1 expresses miRNAs that target viral
transcripts (Umbach et al., 2008), so miRNAs have evolved to play roles in both aiding
viruses and defending against them.
miRNAs involved in cancer
miRNA misexpression also has been well documented in cancer. The first high-
throughput study using 334 patient samples of various malignancies showed that miRNA
profiles can distinguish the developmental lineage and differentiation state of the tumors
(Lu et al., 2005a). Another report was even able to identify the tissue of origin of
metastatic tumors with unknown primary origin based on the miRNA profiles (Rosenfeld
et al., 2008). Profiling experiments have established miRNA deregulation in various
cancers including pancreatic cancer (Roldo et al., 2006; Szafranska et al., 2007), liver
6
cancer (Murakami et al., 2006), breast cancer (Iorio et al., 2005), colorectal cancer
(Cummins et al., 2006; Schepeler et al., 2008), neuroblastoma (Chen and Stallings,
2007), prostate cancer (Ambs et al., 2008; Porkka et al., 2007), bladder cancer (me),
cervical cancer (Lui et al., 2007; Wang et al., 2008b), leukemias (Calin et al., 2005; Calin
et al., 2004a), lung cancer (Yanaihara et al., 2006; Yu et al., 2008), esophageal cancer
(Guo et al., 2008), ovarian cancer (Zhang et al., 2008b), thyroid cancer (He et al., 2005a),
and sarcomas (Subramanian et al., 2008). Intriguingly, many of these studies show that
miRNA signatures have diagnostic and prognostic value, and may become valuable
clinical tools in cancer therapy (Calin and Croce, 2006).
Thorough elucidation of the impact each specific miRNA can have on neoplastic
processes will take many years. However, several examples of important oncogenic and
tumor suppressor miRNAs have been reported (Table 1.1) (Fig. 1.2). The first was the
frequent down-regulation and deletion of the miR15a/16-1 cluster at 13q14 in chronic
lymphocytic leukemia (CLL) (Calin et al., 2002). Subsequent work showed that both
miR-15a and miR-16-1 likely serve a tumor suppressor function by targeting the anti-
apoptotic protein Bcl2 (Cimmino et al., 2005). In addition, a recent report using a
prostate cancer model revealed that the miR-15a/16-1 cluster also regulates tumorigenic
activities such as survival, proliferation and invasion by targeting DDND1 and WNT3A
(Bonci et al., 2008).
7
Table 1.1. miRNAs that are implicated in human cancer.
miRNA Target
Function in
Cancer
References
miR-15a/16-1
cluster
BCL2,
DDND1,
WNT3A
Tumor
suppressor
(Bonci et al., 2008; Calin et al., 2002;
Cimmino et al., 2005)
Let-7 family HMGA2, RAS
Tumor
suppressor
(Johnson et al., 2005; Lee and Dutta,
2007; Mayr et al., 2007; Yu et al.,
2007a)
miR-34 family
CCNE2,
CDK4, MET
Tumor
suppressor
(Chang et al., 2007; He et al., 2007a;
Raver-Shapira et al., 2007; Toyota et
al., 2008)
BIC/miR-155 TP53INP1 Oncogene
(Costinean et al., 2006; Eis et al.,
2005; Gironella et al., 2007)
miR-17~92
cluster
HIF-1 α, Tsp1,
CTGF
Oncogene
(Dews et al., 2006; Hayashita et al.,
2005; He et al., 2005b; Matsubara et
al., 2007; Taguchi et al., 2008)
miR-221/222
p27(CDKN1B),
p57(CDKN1C)
Oncogene
(Fornari et al., 2008; le Sage et al.,
2007)
miR-127 BCL6
Tumor
suppressor
(Saito et al., 2006)
miR-124a CDK6
Tumor
suppressor
(Lujambio et al., 2007)
miR-223 NFI-A
Tumor
suppressor
(Fazi et al., 2007; Fazi et al., 2005)
miR-203
ABL1, BCR-
ABL1
Tumor
suppressor
(Bueno et al., 2008)
miR-1
FoxP1,
HDAC4, MET
Tumor
suppressor
(Datta et al., 2008)
miR-29 family
YYI,
DNMT3A/B
Tumor
suppressor
(Fabbri et al., 2007; Wang et al.,
2008b)
miR-101 EZH2
Tumor
suppressor
(Friedman et al., 2009; Varambally et
al., 2008)
miR-128 BMI1
Tumor
suppressor
(Godlewski et al., 2008)
8
Figure 1.2. The function of tumor suppressor miRNAs. A, normally, a tumor suppressor
miRNA is transcribed in the nucleus as a pri-miRNA, processed by Drosha/DGCR8 to a
pre-miRNA, exported to the cytoplasm by Exportin-5/RanGTP, processed by Dicer and
incorporated into RISC, which mediates translational repression of the target oncogene.
B, decreased levels of a tumor suppressor miRNA, whether by genomic loss or epigenetic
silencing as shown (processing defects and transcriptional blocks via trans acting factors
may also occur), de-represses the target oncogene, leading to aberrant oncogene
translation and tumorigenesis. In the case of miR-101, genomic loss decreases miR-101,
causing an increase in its target EZH2, which promotes tumorigenesis.
RISC
Normal tumor suppressor
miRNA function
Aberrant tumor suppressor
miRNA downregulation in
cancer
nucleus
5 ′ 3 ′
5 ′
3 ′
miRNA mediated
inhibition of oncogene
translation and/or
mRNA destabilization
ribosome
aberrant oncogene
translation
Drosha/
DGCR8
Exportin5/
RanGTP
Dicer
RISC
Target
oncogene
mRNA
5 ′
3 ′
ribosome
Genomic loss,
Epigenetic silencing
A
B
tumorigenesis
Target
oncogene
mRNA
X
9
Another well studied tumor suppressor miRNA family is the 11 member let-7
family, which is downregulated in lung cancer, and lower levels correlated with poor
prognosis (Table 1.1) (Takamizawa et al., 2004). Let-7 targets two important oncogenes,
HMGA2 (Lee and Dutta, 2007) and RAS (Johnson et al., 2005), and a common 12q15
translocation in cancer replaced the let-7 binding site in the HMGA2 mRNA, leading to a
loss of repression (Mayr et al., 2007). A recent study extended the realm of let-7 to
breast cancer by showing that let-7 decreased proliferation by targeting RAS and
increased differentiation by targeting HMGA2 in breast tumor-initiating cells (Yu et al.,
2007a). In 2007, three separate reports showed that miRNAs were intimately involved
with the tumor suppressor p53 (Chang et al., 2007; He et al., 2007a; Raver-Shapira et al.,
2007). These groups demonstrated that p53 transactivates the miR-34 family, which
causes apoptosis and decreases progression through the cell cycle by targeting CCNE2,
CDK4, and MET (Table 1.1) (He et al., 2007b).
The first oncogenic miRNA to be identified was miR-155, which is generated
from the B-cell integration cluster (BIC) non-coding RNA (Table 1.1) (Eis et al., 2005).
miR-155 levels were increased in lymphomas and overexpression of miR-155 promoted
B-cell proliferation and eventual malignancy in a transgenic mouse model (Costinean et
al., 2006). miR-155 may cause these effects by targeting TP53INP1, a p53 target gene
that mediates apoptosis and cell cycle arrest (Gironella et al., 2007).
Another well-studied oncogenic non-coding RNA is the miR-17-92 cluster, which
codes for 7 miRNAs (Table 1.1). The miR-17-92 cluster is frequently amplified in B-cell
lymphoma and its overexpression, along with c-myc, promoted tumor development in a
mouse model (He et al., 2005b). In addition, the miR-17-92 cluster is amplified and
10
upregulated in lung cancer and enforced expression of the miR-17-92 cluster enhanced
lung cancer cell growth (Hayashita et al., 2005), while administration of antisense
oligonucleotides promoted apoptosis (Matsubara et al., 2007). This group later identified
hypoxia inducible factor (HIF) 1 alpha as a target of the miR-17-92 cluster, elucidating a
mechanism for c-myc induced downregulation of HIF-1 alpha (Taguchi et al., 2008).
Using mouse colonocytes, another study showed that c-Myc induced expression of the
miR-17-92 cluster, which mediated tumor angiogenesis by targeting Tsp1 and CTGF
(Dews et al., 2006).
miR-221 and miR-222 are transcribed together and have also been identified as
oncogenic miRNAs (Table 1.1). Thyroid cancer miRNA profiling revealed that miR-
221/222 were upregulated in tumors and this correlated with a loss of KIT (He et al.,
2005a). A forward genetics approach showed that miR-221/222 target the tumor
suppressor and cell cycle regulator p27(Kip1), while miR-221/222 levels inversely
correlated with p27(Kip1) expression in glioblastoma (le Sage et al., 2007). A recent
study expanded the scope of miR-221 by showing that it targeted another cell cycle
regulator p57(CDKN1C) and that miR-221 levels inversely correlated with
p27(CDKN1B) and p57(CDKN1C) in hepatocellular carcinoma (Fornari et al., 2008).
Epigenetics and miRNAs
The causes of miRNA misexpression in cancer may be due to DNA copy number
amplification or deletion (Calin and Croce, 2006), inappropriate transactivation (Dews et
al., 2006), genetic mutation (Jazdzewski et al., 2008), altered post transcriptional
processing (Melo et al., 2009), or epigenetic mechanisms (Saito et al., 2006). Epigenetic
11
silencing of miRNAs could contribute to carcinogenesis by leading to the permanent
upregulation of the miRNA target genes. The first example of an epigenetically regulated
miRNA was the putative tumor suppressor miR-127, which is located in a CpG island
and is normally expressed as part of a miRNA cluster (Table 1.1). In cancer cells this
cluster is silent and miR-127 is methylated, but treatment with a DNA demethylating
agent and a histone deacetylase inhibitor induced miR-127 expression from its own
promoter (Saito et al., 2006). Further analysis showed that miR-127 may have a tumor
suppressor function by repressing the proto-oncogene BCL6 (Saito et al., 2006).
Subsequently, several reports have demonstrated that other tumor suppressor
miRNAs are epigenetically silenced in various cancers. miR-124a was silenced by DNA
methylation in cancer and targeted the oncogene cyclin D kinase 6, while leading to the
phosphorylation of the tumor suppressor retinoblastoma (Lujambio et al., 2007). The
most common acute myeloid leukemia-associated fusion protein AML/ETO aberrantly
epigenetically silences miR-223, which controls myelopoiesis by targeting NFI-A (Table
1.1) (Fazi et al., 2007; Fazi et al., 2005). Ectopic expression of miR-223, knockdown of
AML/ETO, or treatment with DNA demethylating drugs caused leukemia cells to
differentiate, revealing another mechanism by which AML/ETO promotes leukemia (Fazi
et al., 2007).
Another example of a miRNA that targets a fusion protein in hematopoietic
malignancies is miR-203 (Table 1.1). miR-203 is either genetically lost or epigenetically
silenced in leukemias and lymphomas and its re-expression directly repressed both ABL1
and BCR-ABL1 fusion protein (Philadelphia chromosome), causing an inhibition of
cancer cell proliferation (Bueno et al., 2008). A study showed that miR-1 is silenced by
12
hypermethylation in hepatocellular carcinoma and functions as a tumor suppressor by
targeting the oncogenes FoxP1, MET and HDAC4 (Datta et al., 2008). Moreover, the
p53 regulated miR-34b/c was frequently methylated in colorectal cancer and DNA
demethylating treatment re-expressed miR-34b/c in colon cancer cell lines (Toyota et al.,
2008).
In addition to DNA hypermethylation, repressive histone modifications may
epigenetically silence miRNAs in cancer as well. During skeletal myogenesis low NF-
κB and YY1 levels increase miR-29 expression, which targets its repressor YY1 in a
positive feedback loop (Wang et al., 2008a). The elevated NF- κB levels in
rhabdomyosarcoma (RMS) led to aberrant miR-29 silencing through YY1. The
expression of miR-29 inhibited RMS tumor growth and promoted differentiation,
implying that miR-29 acts as a tumor suppressor by promoting myogenesis (Wang et al.,
2008a).
miRNAs also control epigenetic mechanisms by targeting key chromatin
modifying proteins (Table 1.1). In lung cancer, the miR-29 family (miR-29a, -29b, -29c)
was downregulated and its expression inversely correlated with DNA methyltransferase
(DNMT) 3A and 3B levels (Fabbri et al., 2007). Enforced expression of miR-29s in lung
cancer cell lines inhibited tumorigenicity, decreased DNMT3A and DNMT3B levels,
restored normal DNA methylation patterns, and re-expressed hypermethylation-silenced
tumor suppressor genes (Fabbri et al., 2007).
The Polycomb group protein EZH2 is a histone methyltransferase that
epigenetically silences genes by trimethylating histone H3 lysine 27 (H3K27me3)
(Sparmann and van Lohuizen, 2006). EZH2 acts as an oncogene in various malignancies,
13
but the mechanism for EZH2 overexpression had not been elucidated (Varambally et al.,
2002). Two recent studies showed that miR-101, which is frequently downregulated in
cancer, targets EZH2 (Table 1.1) (Friedman et al., 2009; Varambally et al., 2008).
Ectopic expression of miR-101 decreased EZH2 levels, decreased global H3K27me3, re-
expressed aberrantly silenced Polycomb target genes, and inhibited cancer cell
proliferation (Friedman et al., 2009; Varambally et al., 2008).
Another Polycomb group protein BMI1 is involved in epigenetic gene silencing
and promotes tumorigenesis (Table 1.1) (Godlewski et al., 2008). miRNA profiling of
glioblastoma revealed that miR-128 is downregulated in the tumor tissues, which
inversely correlated with BMI1 expresssion (Godlewski et al., 2008). Inducing miR-128
expression inhibited glioma cell proliferation and self-renewal, decreased H3K27me3,
and increased p21(CIP1), all of which is consistent with BMI1 downregulation
(Godlewski et al., 2008).
The future of miRNAs in medicine
Because miRNAs play such important roles in disease, the development of
miRNA-based diagnoses and therapies is gaining traction. Techniques have been
established to isolate miRNAs from cell free bodily fluids such as serum and urine (Gilad
et al., 2008). The miRNA profiles generated from these samples are robust and could
discriminate between pregnant and non-pregnant women (Gilad et al., 2008). A recent
report demonstrated that miRNAs are present and very stable in plasma, and miRNAs
originating from prostate tumor xenografts are easily measured and discriminate tumor-
bearing mice from controls (Mitchell et al., 2008). In addition, the detection of miR-141
14
in plasma could distinguish prostate cancer patients from healthy controls, clearly
showing the potential for miRNA-based diagnosis (Mitchell et al., 2008).
miRNA-based therapies will be difficult to develop because of the inherent
instability of administered RNA. However, engineered oligonucleotides complementary
to endogenous miRNAs termed “antagomirs” were developed and are stable when
intravenously administered to mice (Krutzfeldt et al., 2005). The antagomir to the liver-
specific miR-122 caused a robust decrease in miR-122 levels and an increase in
transcripts with miR-122 binding sites (Krutzfeldt et al., 2005). Another group used
miR-122 as the target to validate systemic delivery of locked-nucleic-acid-modified
oligonucleotides (LNA-antimiR) in non-human primates (Elmen et al., 2008). The
intravenously administered LNA-antimiR was taken up into hepatocytes to form a stable
duplex with miR-122. This lead to a dose dependent depletion of mature miR-122 and a
decrease in plasma cholesterol, a marker of miR-122 downregulation (Elmen et al.,
2008). Moreover, there was no evidence of toxicity or histopathological changes from
the treatment, indicating that LNA-antimiRs could be valuable tools to both elucidate
miRNA function in animals and to treat disease in humans (Elmen et al., 2008).
Summary
miRNAs are a fundamental part of coordinated gene regulation in eukaryotic cells
and the recent explosion of reports on miRNA involvement in various biological
processes continues unabated. It now seems that miRNA involvement in a cellular
pathway or function is the rule rather than the exception, although the specific and
intricate roles of each miRNA will take some time to determine. Several human diseases,
15
from neurological disease to heart disease to cancer, are caused or propagated by miRNA
misexpression, which has generated great interest in therapies, diagnoses and prognoses
based on disease-specific miRNAs. Recent work in this regard has shown tremendous
promise and the successful translation of miRNA research from novel bench work to
medical practice and patients may open up a new avenue to treat disease in humans.
Overview of thesis research
When I began my thesis research in October of 2005, it was clear that miRNAs
were critical to fine-tuning gene regulation and cellular function. In addition, many
studies had shown that miRNA misexpression was not only a hallmark of cancer, but
may be a driver of tumorigenesis (Calin et al., 2002; Calin et al., 2005; Calin et al.,
2004a; Calin et al., 2004b; Lu et al., 2005a). However, the precise roles miRNAs play in
the cell will take many years to truly clarify and more specifically, miRNA function in
bladder cancer had not been thoroughly investigated. Moreover, miRNA misexpression
may be caused by the same mechanisms that would lead to the dysregulation of protein
coding genes, although epigenetic mechanisms had not been verified. This thesis
investigated techniques to measure miRNAs, miRNA misexpression in cancer, miRNA
function in cancer, and platforms for expressing miRNAs as possible therapeutics.
At the time I entered the Jones Lab, we were only able to use miRNA microarray
and Northern blot to measure mature miRNA levels. This became an issue when
reviewers for our miR-127 manuscript insisted on using a third method to verify that
miR-127 is upregulated upon epigenetic treatment of cancer cells (Saito et al., 2006). My
first task was to establish RT-qPCR for pre-miRNAs, and although I was successful, we
16
realized that pre-miRNA levels do not correlate with mature miRNA levels. Applied
Biosystems published a manuscript describing stem-loop RT-qPCR for miRNAs (Chen et
al., 2005), so I read the report and created a stem-loop RT primer for miR-127, which is
described in Chapter 2. The stem-loop RT-PCR results validated our Northern blot and
miRNA microarray results for miR-127. In addition, the stem-loop RT-PCR was
cheaper, used less material, and was very sensitive when compared to Northern blots or
miRNA microarrays.
There were TCC samples in our lab and there had not been a comprehensive
miRNA study done in TCC so I conducted a miRNA microarray on TCC samples. It
showed extensive differential miRNA expression between tumor and matched normal
tissue. At the time, Applied Biosystems had recently made their stem-loop RT-qPCR kits
commercially available, which allowed me to validate the miRNA microarray results. In
order to see if miRNA misexpression was a cause or consequence of TCC, I selected the
five most downregulated miRNAs in TCC and stably re-expressed them in TCC cell
lines. The results revealed novel putative tumor suppressor functions for several
miRNAs and expanded our understanding of TCC tumorigenesis.
I found that several miRNAs could function as tumor suppressors, but I did not
know the mechanism through which they worked. In Chapter 3 I focused on examining
the function of the most potent tumor suppressor miR-101. Recent studies had shown
miR-101 was downregulated in breast and lung cancers, so I used RT-qPCR to examine
miR-101 levels in prostate and colon cancer samples (Iorio et al., 2005; Yanaihara et al.,
2006). I found that miR-101 is downregulated in those cancers as well, indicating that
miR-101 downregulation is not specific to TCC, but may be a general property of solid
17
tumors. I used the most common miRNA target prediction algorithms to search for
potential miR-101 targets and found that the Polycomb group protein EZH2 was a
predicted target with two miR-101 binding sites in the 3 ′UTR. I confirmed that miR-101
decreases EZH2 levels and H3K27me3 levels in TCC cell lines, and showed that EZH2 is
a direct, sequence dependent target of miR-101. Because EZH2 catalyzes a repressive
histone mark, I felt that genes should be aberrantly repressed by elevated levels of EZH2
in TCC. Therefore, knocking down EZH2 by miR-101 or by siRNA should re-express
the same Polycomb-silenced genes, which I confirmed using chromatin
immunoprecipitation assay and expression microarrays.
Our manuscript describing the activation of miR-127 by chromatin-modifying
drugs was the first example of an epigenetically regulated miRNA (Saito et al., 2006).
To discover additional epigenetically regulated miRNAs, we looked at the overlap
between miRNAs that were downregulated in TCC and miRNAs that were upregulated in
TCC cells after epigenetic therapy. From this overlap, we chose to focus on miR-126
because it had recently been characterized as a metastasis suppressor (Tavazoie et al.,
2008). miR-126 is located in the intron of EGFL7, which plays an important part in
vasculogenesis and is normally expressed in endothelial cells. Interestingly, when miR-
126 is re-expressed upon epigenetic treatment in cancer cells, it is processed from an
alternative transcript of EGFL7, which has a CpG island promoter. Further experiments
revealed that miR-126 was controlled by repressive histone modifications rather than
DNA hypermethylation in cancer. This work showed an additional example of a tumor
suppressor miRNA that is silenced in cancer and re-expressed after epigenetic therapy.
18
Several studies have shown the potential utility of miRNA-based therapeutics in
cancer (Chang et al., 2007; Johnson et al., 2005; Mayr et al., 2007). In addition, it is well
accepted that several miRNAs are dysregulated in any particular tumor (Lu et al., 2005a).
However, there had not been a report using multiple miRNAs in a synergistic manner for
therapeutic effects. Therefore, in Chapter 5 I sought to determine if it would be possible
to express several miRNAs from a single expression vector using the same expression
vector backbone I used for restoring miRNA expression in Chapter 2. The process of
simply cloning a few bp surrounding the pre-miRNA sequence sequentially into the
multiple cloning site of the vector was very flexible and adaptable for any miRNA
combination. I confirmed robust miRNA expression from the multiple miRNA
expression vector, and I showed the multiple miRNA expression vector was more
effective at suppressing cancer cell growth than the individual miRNA vectors alone. My
work showed that miRNA vectors can be custom designed to include relevant miRNAs
for virtually any disease, which infinitely expands the potential of miRNA therapeutics.
This thesis examined various aspects of miRNA biology. My work was the first
to examine miRNA function in TCC and the results suggested a general mechanism for
EZH2-mediated tumorigenesis. Although epigenetic therapy is used for several
malignancies, the specific mechanisms for its efficacy are still under investigation. We
uncovered an additional functional consequence of epigenetic therapy by showing that
miR-126 is upregulated after epigenetic treatment. In addition, I showed the possible
therapeutic role miRNAs can play in cancer by developing a novel technique that easily
expresses multiple miRNAs from a single transcript.
19
Chapter 2: Stem-loop miRNA qPCR and Bladder Cancer miRNA Profiling
Introduction
Primary miRNAs (pri-miRNA) are usually long transcripts of over 1 kb and are
processed into precursor miRNAs (pre-miRNA), which are ~70 nt long. Both pri-
miRNAs and pre-miRNAs may be detected by relatively easy, conventional methods
such as PCR and Northern blot. However, both species exist transiently, such that the
levels of pri-miRNAs or pre-miRNAs often do not correlate with mature miRNA (~22 nt)
expression (Thomson et al., 2006). A pri-miRNA may accumulate to high levels while
the pre-miRNA and mature miRNA may not be expressed if the Drosha/DGCR8
processing step is blocked. This occurs in embryonic cells when the developmentally
regulated RNA binding protein Lin-28 impairs the processing of pri-let-7 (Viswanathan
et al., 2008). On the other hand, impaired Dicer processing leads to decreased miRNA
levels and may have severe functional consequences, which can occur in cancer due to
truncating mutations in TAR RNA-binding protein 2 (Melo et al., 2009). Examining the
expression of the pri-miRNA and pre-miRNA may elucidate valuable kinetic and
regulatory information, but will not determine functional effects, which are mediated by
the mature miRNA and RISC (Eulalio et al., 2008).
Because of the small size of miRNAs, miRNA microarrays, Northern blots or
RNase protection assays were the available methods for detection. miRNA microarrays
are very high throughput and can interrogate several hundred miRNA sequences, but
these experiments are subject to probe bias and replication difficulties (Esquela-Kerscher
and Slack, 2004). In addition, miRNA microarrays can be prohibitively expensive.
20
Northern blots and RNase protection assays are very sensitive, but can only measure the
levels of one miRNA at a time and use a relatively large amount (20 µg) of material,
which is not always available from tissue samples.
PCR typically uses primers that are 15-25 nt long, which would clearly be too
long for a miRNA after cDNA is made. Adding adaptors to the 3 ′ end of the small RNA
fraction and then using a universal reverse primer for the reverse transcriptase (RT) step
would create a much longer and more manageable cDNA, so that a miRNA-specific
forward primer and a universal reverse primer could be used during the PCR. However,
this would add a complicated ligation step that would create bias based on ligation
efficiency. Another possibility would be to design miRNA specific stem-loop primers
for the RT step (Fig. 2.1) (Chen et al., 2005). The 3 ′ end of each primer contains 6 nt that
are complementary to the last 6 nt of the 3 ′ end of the miRNA. The resulting cDNA
would have the miRNA sequence in the 5 ′ end and a universal sequence at the 3 ′ end.
The subsequent PCR step would use a miRNA-specific forward primer and a universal
reverse primer. The technique could be extended to a more quantitative method by using
Sybr green or a Taqman probe (Fig. 2.1).
21
Figure 2.1. Diagram of miRNA-specific stem-loop RT-qPCR.
Chen C et al. Nucleic Acids Res. 2005 33 (20) e179
5’
3’
5’
3’
SYBR
GREEN
16
o
C 30 min
45
o
C 30 min
85
o
C 5 min
miRNA
specific
cDNA
59
o
C and
reverse primer
placement
abrogates
stem structure
or
22
Our lab had discovered that the putative tumor suppressor miR-127 was
epigenetically silenced in cancer cells and could be re-expressed upon treatment with
chromatin-modifying drugs. However, we were only able to show this using a
microRNA microarray for T24 bladder cancer cells and Northern blots for several cell
lines including T24. It was critical for our lab to establish the stem-loop RT-PCR as an
additional method to validate our previous results for publication (Saito et al., 2006).
After we successfully validated our results and they were published, Applied Biosystems
made miRNA RT-qPCR kits commercially available, which only required 10 ng of RNA
for each assay, so we switched to the Applied Biosystems reagents.
miRNA involvement in cancer was well established and miRNA profiling
experiments in thyroid cancer (He et al., 2005a), breast cancer (Iorio et al., 2005), and
leukemia (Calin et al., 2005) had yielded signatures that correlated with diagnoses or
prognoses and identified tumor suppressor or oncogenic miRNAs. A study profiling
miRNA expression in human cancers included 8 TCC samples and one normal bladder
sample (Lu et al., 2005a). However, a comprehensive study with matched normal
bladder and tumor tissue and a functional study of differentially expressed miRNAs
remained to be conducted. Bladder cancers in the United States are almost exclusively
transitional cell carcinomas (TCC). In 2007 there were 67,160 new cases and 13,750
deaths making TCC the 5
th
most common cancer diagnosis according to the National
Cancer Institute (NCI).
Therefore, we sought to generate a miRNA expression profile for TCC by
comparing primary TCCs to their corresponding normal urothelium. We used a miRNA
microarray to generate preliminary results that were validated with stem-loop RT-qPCR.
23
We found many differentially expressed miRNAs, several of which showed putative
tumor suppressor functions.
Materials and Methods
Cell lines and primary tumors
T24, UM-UC-3, TCCSUP (bladder transitional cell carcinoma cells), HCT116
(colon carcinoma cells), NCCIT (embryonic carcinoma cells), Ramos (lymphoma cells),
HeLa (cervical carcinoma cells), CFPAC-1 (pancreatic carcinoma cells), MCF7 (breast
carcinoma cells), CALU-1 (lung carcinoma cells), and CCD-1070Sk (human normal
fibroblast cells) were obtained from the American Type Culture Collection. LD98 and
LD419 (human normal fibroblast cells) were established in our laboratory. T24,
HCT116, LD98, and LD419 cells were cultured in McCoy's 5A medium supplemented
with 10% fetal bovine serum (FBS). NCCIT and Ramos cells were cultured in
RPMI1640 medium supplemented with 10% FBS. HeLa and MCF7 cells were cultured
in MEM medium supplemented with 10% FBS. CALU-1 was cultured in McCoy's 5A
medium supplemented with 10% FBS and 1× glutamine. CFPAC-1 cells were cultured
in IMDM medium supplemented with 10% FBS and 1× glutamine. CCD-1070Sk cells
were cultured in MEM medium supplemented with 10% FBS, 1× sodium pyruvate, and
1× MEM nonessential amino acids. UM-UC-3 cells were cultured in DMEM
supplemented with 10% FBS. TCCSUP cells were cultured in MEM medium
supplemented with non-essential amino acids and 1mM sodium pyruvate.
24
RNA was extracted using Trizol (Invitrogen) according to the manufacturer’s
protocol. Slides were prepared from fresh frozen blocks of tumors and matched normal
tissue, stained with hematoxylin and eosin, and the epithelium was marked by a
pathologist. These slides were used as a guide to dissect the fresh frozen blocks and
RNA was extracted using the ToTALLY RNA Isolation Kit (Ambion) according to the
manufacturer’s protocol. The patient samples were obtained through USC/Norris Tissue
Procurement Core Resource after informed consent and Institutional Review Board (IRB)
approval (IRB #886005 and #926041) at the USC/Norris Comprehensive Cancer Center.
Northern blots
Total RNA (30 µg) was loaded onto a denaturing gel and transferred to a nylon
membrane. The StarFire radiolabeled probes (Integrated DNA Technologies, Coralville,
IA) were prepared by incorporation of [ α-32P] dATP 6000 Ci/mmol following the
manufacturer's recommendation. The sequences of the probes are available upon request.
Prehybridization and hybridization were carried out using ExpressHyb Hybridization
Solution (Clontech, Mountain View, CA). As a loading control, random primed labeling
probes specific for U6 RNA and GAPDH mRNA were generated using High Prime
(Roche, Indianapolis, IN). This was conducted by Yoshimasa Saito.
5-aza-2 ′-deoxycytidine (5-Aza-CdR) and 4-phenylbutyric acid (PBA) treatment
Cells were seeded at 5 × 10
5
cells per 100 mm dish 24 hr prior to treatment with
5-Aza-CdR (1 µM or 3 µM; Sigma-Aldrich, St. Louis, MO) and/or PBA (1 mM or 3 mM;
Sigma-Aldrich). 5-Aza-CdR was removed after 24 hr, while PBA was continuously
25
administered by replacing the medium containing PBA every 24 hr for 5 or 6 days.
Ramos cells were seeded at 2 × 10
6
cells per 100 mm dish 24 hr prior to treatment with 5-
Aza-CdR (0.1 µM) and/or PBA (1 mM). Treatments were done as described above for 4
days. This was conducted by Yoshimasa Saito.
Stem-loop RT-PCR for miRNAs
Stem-loop RT for mature miR-127 was performed as previously described (Chen
et al., 2005). All reagents for stem-loop RT were obtained from Applied Biosystems.
PCR products were analyzed on 3% agarose gels. U6 RNA was used as an internal
control. The primers used for stem-loop RT-PCR for miR-127 are as follows:
miR-127
RT, GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGAAGCCAA
Forward, GCGGCTCGGATCCGTCTGAGCT
Reverse, GTGCAGGGTCCGAGGT
U6
Forward, CTCGCTTCGGCAGCACA
Reverse, AACGCTTCACGAATTTGCGT.
miRNA microarray
miRNA microarray analysis was done as previously described (Saito et al., 2006).
Briefly, 1 µg of total RNA from each of 9 TCCs was pooled and labeled with Cy5 and 1
µg of total RNA from each of 9 matched normal tissues was pooled and labeled with
26
Cy3. RNA quality
control, labeling, hybridization, scanning, and statistical analysis were
performed
by LC Sciences using the probe content
in the Sanger miRBase 8.0.
Reverse transcription and Taqman qPCR
All reagents for miRNA Taqman assays to detect mature miRNAs were
purchased from Applied Biosystems and used according to the manufacturer’s protocol
(Chen et al., 2005). U6 was used as the internal control and all reactions were done in
duplicate.
For U6 primers
Forward CTCGCTTCGGCAGCACA
Reverse AACGCTTCACGAATTTGCGT
Probe FAM-AGATTAGCATGGCCCCTGCGCAA-BHQ
Expression vectors and transfections
Expression vectors were made by cloning ~250bp surrounding the precursor
miRNA into pcDNA3.1(+) (Invitrogen). The primers for PCR inserts are
miR-1
Forward TATTAAGCTTAGTTACACTGCCTCTGAGCT
Reverse ATATGAATTCAGTGACAGAACAATGCTGGC
miR-101
Forward ATATGAATTCATGACAGAGGTGCAGGGTAA
Reverse TAATAAGCTTGTCTCCAACCAGAAGGTGAT
miR-127
27
Forward TGATAAGCTTTCTGTTGGTCAGCATGTCCT
Reverse ATATGAATTCATGCATTGCCCTAGAGAGGC
miR-143
Forward GAACAAGCTTCAGTTGTGAGGAATTACAAC
Reverse TATAGAATTCTTGTGTAGAGGAACTTCCCCA
miR-145
Forward TATAAAGCTTACATCCGGCGACGTGT
Reverse TATAGAATTCTGGTTCATAAGCCCTCTTACCT
T24, UM-UC-3 and TCCSUP cells were seeded in 6-well dishes so that 24 hr later they
were 90% confluent. Cells were transfected using 10 µL Lipofectamine 2000
(Invitrogen) and 4 µg plasmid according to the manufacturer’s protocol.
Cell proliferation and colony formation assays
Cell proliferation assays were conducted in triplicate as described previously
(Robertson and Jones, 1999). Cells in each well were trypsinized 48 hr after transfection
and equal cell numbers plated in 10 cm dishes with medium containing G418 (Sigma)
(T24 400 µg/mL, UMUC3 and TCCSUP 1 mg/mL). Medium was changed every 3-4
days and total cell numbers were counted after 13 days using the Z1 Coulter Particle
Counter.
The colony formation assays were conducted as described previously (Kim et al.,
2006). Equal numbers of cells were plated in triplicate in 6-well dishes containing
medium with G418 at the same concentrations as above 48 hr after tranfection. Medium
28
was changed every 3-4 days and colonies were counted after 13 days by washing with
PBS, fixing with methanol and staining with Giemsa (Sigma).
The comparison of colony and cell counts between empty vector control and
miRNA expression vectors was done using Dunnet’s Method (Dunnet, 1955). The
analysis was based on log-transformed data where means and 95% confidence intervals
were calculated and transformed back to the original scale.
Results
Stem-loop RT-PCR validates miR-127 is silenced in cancer and re-expressed after
epigenetic treatment
(the following was adapted from (Saito et al., 2006))
We treated a panel of seven human cancer cell lines (HCT116, HeLa, NCCIT,
Ramos, CFPAC-1, MCF7, and CALU-1) as well as two normal human fibroblast cell
lines (LD98 and CCD-1070Sk) with 5-aza-2 ′-deoxycytidine (5-Aza-CdR) and the histone
deacetylase (HDAC) inhibitor 4-phenylbutyric acid (PBA). Expression patterns of miR-
127 in these cell lines were analyzed by Northern blot and stem-loop RT-PCR (Fig. 2.2)
(Chen et al., 2005). miR-127 was silenced in all the cancer cell lines examined but was
substantially induced after 5-Aza-CdR and PBA treatment in a dose-dependent manner in
HCT116, HeLa, NCCIT, and Ramos cells (Figs. 2.3A, 2.3B). CFPAC-1 showed only a
slight induction of miR-127 after treatment. MCF7 and CALU-1 showed no induction of
miR-127 by Northern blot analyses, whereas stem-loop RT-PCR showed a slight
induction, probably due to its higher sensitivity (Fig. 2.3A, 2.3B). On the other hand,
29
miR-127 was expressed substantially in normal fibroblasts and was slightly upregulated
after treatment (Fig. 2.3A, 2.3B). Therefore, our stem-loop RT-PCR technique validated
our Northern blot results, which led us to use this technique in further miRNA studies.
30
Figure 2.2. Diagram of miR-127-specific stem-loop RT-PCR primers.
Stem-loop RT primer
GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGAC
5’ stem loop stem 3’
miRNA specific extension
miR-127 –
UCGGAUCCGUCUGAGCUUGGCU
GTCGTATCCAGTGC
AACCGACAGCATAGGTCACG
PCR primers
Reverse primer - GTGCAGGGTCCGAGGT
Forward primer - (GCGGC)TCGGATCCGTCTGAGCT
PCR product ~ 60 bp
31
Figure 2.3. Expression patterns of miR-127 in cancer cells and normal fibroblasts treated
with 5-Aza-CdR and PBA. A, Northern blot analysis of miR-127 expression before and
after treatment with different doses of 5-Aza-CdR and PBA in a panel of cancer cell lines
(HCT116 colon carcinoma, HeLa cervical carcinoma, NCCIT embryonic carcinoma,
Ramos lymphoma, CFPAC-1 pancreatic carcinoma, MCF7 breast carcinoma, and CALU-
1 lung carcinoma cells) and normal fibroblasts (LD98 and CCD-1070Sk). U6 RNA
expression was used as a loading control. AP0.1, combination of 0.1 µM 5-Aza-CdR and
1 mM PBA; AP1, combination of 1 µM 5-Aza-CdR and 1 mM PBA; AP3, combination
of 3 µM 5-Aza-CdR and 3 mM PBA. B, Confirmation of expression patterns of miR-127
in cancer cells and normal fibroblasts treated with 5-Aza-CdR and PBA by stem-loop
RT-PCR analyses. U6 RNA expression was used as an internal control.
A
B
32
Differential miRNA expression between primary TCCs and matched normal urothelium
We used a miRNA microarray containing 328 miRNAs from the Sanger miRBase
8.0 to examine differentially expressed miRNAs in a pool of 9 TCCs and a pool of the
corresponding normal samples. Seventy-one transcripts showed greater than a 2-fold
difference in expression with miR-1, miR-101, miR-143, miR-145 and miR-29c the most
downregulated in the tumors and miR-182, miR-183, miR-203, miR-224 and miR-196a
the most upregulated (Fig. 2.4). The levels of the putative tumor suppressor miRNAs
were at least 9-fold lower in the tumor pool and the levels of the putative oncogenes were
at least 23-fold higher in the tumor pool. miR-127 was included because our previous
work revealed it is both downregulated in human cancers and a putative tumor suppressor
(Saito et al., 2006)
We conducted RT-qPCR for 12 differentially expressed miRNAs on 28 additional
TCC patients. miR-1, miR-101, miR-143, miR-145, miR-29c, and miR-127 were
significantly downregulated in the tumors, while miR-224, miR-182, and miR-183 were
significantly upregulated in the tumors using a 95% confidence interval (Fig. 2.5). miR-
196a, miR-10a and miR-203 showed no significant differences between normal and
tumor samples. Our miRNA microarray analysis and RT-qPCR results showed that there
is severe and consistent miRNA misexpression in TCC and our miRNA panel likely
constitutes a TCC miRNA signature.
33
Figure 2.4. miRNA microarray showing differentially expressed miRNAs in TCC. Total
RNA from 9 TCC samples was pooled and labeled with Cy5. Total RNA from 9
matched normal tissues was pooled and labeled with Cy3. The samples were hybridized
by LC Sciences to an array with probe content from Sanger miRBase 8.0 interrogating
328 miRNAs. Plot of the Tumor signal vs. Normal signal shows all transcripts with those
showing fold change > 8 in black and a table shows the most differentially expressed
transcripts (including miR-127) that were validated with RT-qPCR in additional patient
samples.
1
10
100
1,000
10,000
100,000
1 10 100 1,000 10,000 100,000
Normal (Cy3 signal)
Tum or (Cy5 signal)
`
-54 hsa-miR-1
-16 hsa-miR-101
-11 hsa-miR-143
-9 hsa-miR-145
-9 hsa-miR-29c
-3 hsa-miR-127
10 hsa-miR-10a
23 hsa-miR-196a
23 hsa-miR-224
36 hsa-miR-203
37 hsa-miR-182
38 hsa-miR-183
Fold Change
(Tumor/Normal)
miRNA
-54 hsa-miR-1
-16 hsa-miR-101
-11 hsa-miR-143
-9 hsa-miR-145
-9 hsa-miR-29c
-3 hsa-miR-127
10 hsa-miR-10a
23 hsa-miR-196a
23 hsa-miR-224
36 hsa-miR-203
37 hsa-miR-182
38 hsa-miR-183
Fold Change
(Tumor/Normal)
miRNA
34
Figure 2.5. miRNA RT-qPCR of 28 clinical TCC samples and matched normal
urothelium. All reactions were done in duplicate and U6 was the internal control. The
graph shows the ratio of miRNA expression of Tumor/Normal on a logarithmic scale. *
indicates statistical significance, error bars are the 95% confidence interval.
0.01
0.1
1
10
miR-1 miR-143 miR-145 miR-127 miR-101 miR-29c miR-196a miR-203 miR-10a miR-224 miR-182 miR-183
Ratio of miRNA Expression
Tumor/Normal
*
*
*
*
*
*
*
*
*
miR-101
miR-29c
miR-145
miR-127
miR-1
miR-143
miR-10a
miR-196a
miR-224
miR-203
miR-183
miR-182
35
Restored expression of downregulated miRNAs in TCC cell lines reveals novel putative
tumor suppressors
We examined the expression of the 10 miRNAs from our panel in 10 bladder
cancer cell lines using RT-qPCR to see if the cell line levels correlated with the TCC
profile. The miRNA levels in the cell lines were very similar between cell lines because
miR-1, miR-101, miR-127, miR-143, and miR-145 were barely expressed (Table 2.1).
These results were similar to those we obtained in patients as well. Therefore, these
miRNAs would be good candidates to examine tumor suppressor ability in a cell line
model. The miRNAs levels that were notably different than the TCC profile were miR-
29c which was highly expressed and miR-203 and miR-183 which were barely expressed
in the cell lines (Table 2.1).
To create expression vectors, we cloned approximately 250 bp surrounding the
pre-miRNA for miR-1, miR-101, miR-127, miR-143 and miR-145 into the multiple
cloning site of pcDNA3.1(+). T24, TCCSUP and UM-UC-3 cells were transfected with
the miRNA expression vectors and RT-qPCR confirmed the enhanced miRNA
expression from each vector (Fig. 2.6). The expression levels for miR-101 were found to
be of similar levels to those found in adjacent normal tissues (Fig. 2.7).
36
Table 2.1. RT-qPCR of differentially expressed miRNAs in TCC cell lines. All
reactions were done in duplicate and U6 was used as the internal control. All reactions
for each miRNA were done on the same qPCR plate. Data is presented as miRNA/U6 for
each miRNA and values less than 4 are considered low.
cell line miR-1
miR-
101
miR-
143
miR-
145
miR-
29c
miR-
127
RT4 0.0 1.8 0.0 0.0 103.5 0.1
LD611 0.0 1.2 0.0 0.0 12.8 0.0
LD137 3.3 1.5 0.1 0.1 6.3 0.0
TCCSUP 0.2 0.8 0.5 1.5 18.5 0.0
HT1376 0.0 1.5 0.0 0.0 11.9 0.0
LD71 0.0 1.5 0.0 0.0 27.7 0.0
LD605 0.1 0.7 0.0 0.0 10.3 0.0
SCABER 0.0 1.1 0.0 0.0 7.1 0.0
T24 0.0 0.9 0.0 0.0 22.3 0.0
UMUC3 0.2 1.2 0.0 0.0 13.0 0.0
cell line
miR-
203
miR-
224
miR-
182
miR-
183
RT4 0.2 9.1 35.8 3.1
LD611 0.2 6.6 10.6 1.0
LD137 0.2 2.8 36.3 4.4
TCCSUP 0.0 29.3 7.1 0.8
HT1376 0.5 2.8 8.5 0.8
LD71 0.0 33.0 9.5 0.6
LD605 0.0 7.5 5.8 0.5
SCABER 0.2 16.5 12.3 1.2
T24 0.0 7.9 4.9 0.9
UMUC3 0.0 4.0 5.3 0.8
37
Figure 2.6. RT-qPCR confirms that pcDNA3.1(+) vectors express mature miRNAs. RT-
qPCR was done in duplicate on total RNA isolated 48 hr after transfection in T24, UM-
UC-3, or TCCSUP cells. The miRNA expression vectors are compared to empty vector
controls and normalized to U6. All reactions were done in duplicate. Data is presented
as mean ± SEM.
T24
0
2
4
6
8
10
12
14
miR-1 miR-101 miR-127 miR-143 miR-145
average miR expression/U 6
control
miR
UM-UC-3
0
10
20
30
40
50
60
miR-1 miR-101 miR-127 miR-143 miR-145
average miR expression/U 6
control
miR
TCCSUP
0
5
10
15
20
25
30
35
miR-1 miR-101 miR-127 miR-143 miR-145
average miR expresion/U6
control
miR
38
Figure 2.7. RT-qPCR for miR-101 shows that miR-101 transfections restore miR-101 to
levels similar to those in normal tissues. All reactions were done in duplicate. Twenty
six TCC patient samples were used for Normal and Tumor. pcDNA3.1(+) miR-101
vector was used for cell line transfections except where 5nM of pre-miR-101 was used
for UM-UC-3 cells. Data is presented as mean ± SEM.
0
3
6
9
12
15
18
Normal
Tumor
T24 control
T24 miR101
TCCSUP control
TCCSUP miR101
UMUC3 control
UMUC3 miR101
UMUC3 control 5nM
UMUC3 miR101 5nM
miR-101/U6
39
To determine the functional effects of miRNA misexpression, proliferation assays
were done by counting final cell numbers after 13 days under selection with G418 after
transfection with the miRNA expression vectors. The results showed a dramatic
inhibition of cell proliferation by miR-101. In T24 cells, miR-101 suppressed
proliferation by 57% (Fig. 2.8A). Proliferation was inhibited 50% by miR-101, and 24%
by both miR-1 and miR-145 in UM-UC-3 cells. In TCCSUP cells, miR-1 showed the
highest suppression at 30% while miR-101 and miR-145 suppressed growth by 24% and
26%, respectively (Fig. 2.8A). miR-127 and miR-143 inhibited proliferation in all 3 cell
lines but the differences did not achieve significance. These results indicate that miR-101
is the most potent growth suppressor, although miR-1 and miR-145 also significantly
inhibited cell proliferation.
We determined the effect of restored miRNA expression on colony formation by
counting the number of colonies after 13 days of selection with G418 after transfection.
Again, the results varied depending on the cell line and miR-101 was the most potent
suppressor of colony formation. In T24 cells, miR-101 suppressed colony formation by
45% (Fig. 2.8B). miR-101 reduced colonies by 36% in UM-UC-3 cells while miR-127,
miR-143, and miR-145 suppressed colony formation by 28%, 30%, and 31%,
respectively. In TCCSUP cells, miR-101 suppressed colony formation by 35%, while
miR-1 and miR-143 showed 33% and 35% suppression, respectively (Fig. 2.8B).
Clearly, restored expression of miR-101 potently suppresses colony formation in these
cell lines while other miRNAs also suppress colony formation, although less substantially
and consistently.
40
Figure 2.8. Restored miRNA expression in TCC cell lines reveals novel tumor
suppressors. A, Cell proliferation assays were conducted by transferring equal cell
numbers to 10 cm dishes 48 h post-transfection with miRNA expression vectors or empty
vector (e.v.) control. After 13 days under G418 selection total cells were counted and
normalized to the empty vector. B, Colony formation assays were conducted by seeding
equal cell numbers 48 h post-transfection into 6-well plates. Colonies were stained and
counted after 13 days under G418 selection and normalized to the empty vector control. *
indicates p-value < 0.02 according to Dunnet’s method (except UM-UC-3 miR-145, p-
value = 0.044), data is presented as mean ± SEM.
T24 UM-UC-3 TCCSUP
T24
e.v.
m iR-145
p16
miR -1
miR -101
m iR-143
m iR-127
100
80
60
40
20
Relative cell num ber (% )
*
UM-UC-3
e.v.
miR -145
p16
miR -1
m iR-101
m iR-143
m iR-127
*
*
*
TCCSUP
e.v.
m iR-145
p16
miR -1
m iR-101
m iR-143
m iR-127
* *
*
T24 UM-UC-3 TCCSUP
T24
e.v.
m iR-145
p16
miR -1
miR -101
m iR-143
m iR-127
100
80
60
40
20
Relative cell num ber (% )
*
T24
e.v.
m iR-145
p16
miR -1
miR -101
m iR-143
m iR-127
100
80
60
40
20
Relative cell num ber (% )
*
UM-UC-3
e.v.
miR -145
p16
miR -1
m iR-101
m iR-143
m iR-127
*
*
*
UM-UC-3
e.v.
miR -145
p16
miR -1
m iR-101
m iR-143
m iR-127
*
*
*
TCCSUP
e.v.
m iR-145
p16
miR -1
m iR-101
m iR-143
m iR-127
* *
*
TCCSUP
e.v.
m iR-145
p16
miR -1
m iR-101
m iR-143
m iR-127
* *
*
e.v.
m iR-145
p16
miR -1
m iR-101
m iR-143
miR -127
100
80
60
40
20 Relative colony num ber (% )
*
e.v.
m iR-145
p16
miR -1
m iR-101
m iR-143
miR -127
*
*
*
*
e.v.
m iR-145
p16
miR -1
m iR-101
miR -143
m iR-127
*
*
*
T24 UM-UC-3 TCCSUP
e.v.
m iR-145
p16
miR -1
m iR-101
m iR-143
miR -127
100
80
60
40
20 Relative colony num ber (% )
*
e.v.
m iR-145
p16
miR -1
m iR-101
m iR-143
miR -127
100
80
60
40
20 Relative colony num ber (% )
*
e.v.
m iR-145
p16
miR -1
m iR-101
m iR-143
miR -127
*
*
*
*
e.v.
m iR-145
p16
miR -1
m iR-101
m iR-143
miR -127
*
*
*
*
e.v.
m iR-145
p16
miR -1
m iR-101
miR -143
m iR-127
*
*
*
e.v.
m iR-145
p16
miR -1
m iR-101
miR -143
m iR-127
*
*
*
T24 UM-UC-3 TCCSUP
A
B
41
Discussion
Engineering the miRNA RT-PCR for miR-127 was critical for our research and
enabled us to use a cheaper, higher throughput technique to study miRNAs. Establishing
this made it possible to validate the Northern blots for cell lines treated with epigenetic
drugs and the miRNA microarray for TCC and adjacent normal urothelium.
miRNA dysregulation has been implicated in various human cancers so we sought
to investigate the aberrant expression of miRNAs in TCC, the 5
th
most common cancer in
the United States. The miRNA microarray analysis and the RT-qPCR results showed that
there is extensive miRNA dysregulation in TCCs and our miRNA panel could constitute
a TCC miRNA signature. There was impressive consistency with 92% of tumors
showing downregulated levels of miR-1 and miR-143, while miRs -29c, -101, -127, and -
145 were downregulated in at least 70% of TCCs (Table 2.2). miRs-183, -182, and -224
were all statistically significantly upregulated in the tumors, with miR-183 being the most
consistent as it was upregulated in 84% of tumors (Table 2.2).
42
Table 2.2. Summary of RT-qPCR of differentially expressed miRNAs in TCC for 28
patient samples. Values are average normal sample, average tumor sample, % of samples
that showed up or down regulation, p-value from Student’s paired t-test.
Sample miR-1 miR-101 miR-143 miR-145 miR-29c miR-127
Avg N 505 136 636 802 725 105
Avg T 109 57 91 124 342 57
% 92 76 92 89 76 70
t-test 0.00146 0.00003 0.00028 0.00551 0.00040 0.00094
Sample miR-203 miR-224 miR-182 miR-183
miR-
196a miR-10a
Avg N 230 15 74 24 22 66
Avg T 429 35 150 63 24 67
% 46 57 73 84 35 45
t-test 0.01802 0.00191 0.00040 0.00134 0.75028 0.94192
43
There was remarkable similarity among miRNA expression patterns for TCC cell
lines and 5 of the putative tumor suppressor miRNAs from our clinical sample data were
expressed at extremely low levels or not at all. When we initiated our cell proliferation
and colony formation assays to determine the functional consequences of miRNA
misexpression, we expected miR-1, miR-143, and miR-145 to be the most dramatic
tumor suppressors because they were most frequently downregulated in TCCs. Instead
we found that miR-101 was the best suppressor of proliferation and colony formation.
The overexpression of miR-101, and not the saturation of the miRNA processing
machinery, caused the phenotype because expression of other miRNAs did not show such
dramatic tumor suppression.
Many of the miRNAs in our panel have been previously studied. A group
studying megakaryocytopoiesis found a significant upregulation of miR-101, but its
functional significance was not explored (Garzon et al., 2006). Although miR-101 was
upregulated in CLL, miRNA profiling of lung cancer and breast cancer revealed that
miR-101 was downregulated in tumors, indicating that miRNA misexpression is cell type
specific (Calin et al., 2004a; Iorio et al., 2005; Yanaihara et al., 2006).
The miRNA that was most downregulated in TCCs, miR-1, has been extensively
studied in the heart but there has been no evidence of its importance in carcinogenesis
until now (Yang et al., 2007; Zhao et al., 2007). Our results showed that miR-1
significantly inhibited growth and colony formation in TCCSUP cells while in UM-UC-3
cells it inhibited proliferation. In addition, our data support the results of normal tissue
miRNA profiling that showed miR-1 is strongly expressed in normal bladder (Baskerville
44
and Bartel, 2005). A recent report confirmed the tumor suppressor function of miR-1 in
hepatocellular carcinoma (Datta et al., 2008).
This study further supports the link between downregulation of miR-143 and
miR-145 and cancer which was previously shown in various malignancies (Gramantieri
et al., 2007; Iorio et al., 2005; Lui et al., 2007; Michael et al., 2003; Porkka et al., 2007;
Szafranska et al., 2007; Yanaihara et al., 2006). miR-145 significantly affected
proliferation in UM-UC-3 and TCCSUP cells while miR-143 suppressed colony
formation in these cell lines. In addition, miR-143 and miR-145 are located at the fragile
site 5q32 which is commonly deleted in myelodysplastic syndrome (Calin et al., 2004b).
A mechanism for the tumor suppressor function of miR-145 may be the direct targeting
of c-Myc. A recent report showed that p53 mediates repression of c-Myc through
upregulation of miR-145 (Sachdeva et al., 2009). In addition, studies in colorectal cancer
showed that miR-143 targets K-RAS (Chen et al., 2009).
We have previously shown that miR-127 was a putative tumor suppressor and that
it directly represses BCL-6 translation (Saito et al., 2006). Here we show that miR-127
overexpression significantly suppressed colony formation in UM-UC-3 cells, confirming
miR-127 may have a role as a tumor suppressor. The same previous study revealed that
miR-182 and miR-183 were upregulated in T24 cells upon treatment with 5-Aza-CdR
and PBA while another study showed that miR-182 was upregulated upon p53 activation,
indicating that it might be pro-apoptotic (Chang et al., 2007; Saito et al., 2006). Although
we grouped miR-182 as a potential oncogenic miRNA, these previous studies indicate
that further work must be done to determine the role of miR-182 in cancer, which may
also be tissue specific.
45
Conflicting results have also been obtained for miR-224, which was
downregulated in lung cancer, but overexpressed in hepatocellular carcinoma and
pancreatic cancer (Murakami et al., 2006; Szafranska et al., 2007; Yanaihara et al., 2006).
Previous studies in pancreatic cancer, papillary thyroid carcinoma and CLL all revealed
that miR-29c was downregulated in cancer (Calin et al., 2005; He et al., 2005a;
Szafranska et al., 2007). Our results were similar in patient samples but a surprising
result was that miR-29c was strongly expressed in bladder cancer cell lines which may be
an artifact of tissue culture.
Our future studies will investigate the functional targets of miR-101 in bladder
cancer cell lines. Although a strong repression of protein levels is the best indicator of
miRNA targets, analyzing differences in mRNA levels is very useful as well. We will
use an expression microarray to look for transcripts that are repressed after transfection of
cells with miR-101. This will allow us to determine the general effects of miR-101
overexpression on the transcriptome to clarify why miR-101 suppresses growth and
colony formation. By searching the downregulated transcripts for consensus miR-101
binding sites, we could find direct targets as well.
This is the first comprehensive examination of miRNA expression in TCC. We
used patient samples to generate a panel of significantly differentially expressed miRNAs
that could be used as a diagnostic tool for bladder cancer. Our transfections and cell line
data greatly enhanced our knowledge of the molecular biology of TCC and revealed that
miRNA dysfunction has dramatic functional consequences on tumor cell proliferation
and colony formation. Although not all of the miRNAs showed the dramatic effects of
46
miR-101, combining a few of the miRNAs in miRNA-based therapies for bladder cancer
could have synergistic effects by inhibiting several oncogenic pathways at once.
47
Chapter 3: The Functional Effects of miR-101 Misexpression in Bladder Cancer
Introduction
Polycomb group (PcG) proteins are chromatin modifying enzymes that were
discovered as homeotic regulators in Drosophila melanogaster. Subsequent work has
revealed that they are important in stem cell maintenance, X-inactivation, imprinting, and
development, and many PcG proteins are dysregulated in human cancer (Sparmann and
van Lohuizen, 2006). The PcG protein EZH2 is the catalytic subunit of the Polycomb
Repressive Complex 2 (PRC2), which is a critical part of the cellular machinery involved
in epigenetically regulating gene transcription (Pasini et al., 2004). PRC2 represses
genes by trimethylating the core histone H3 lysine 27 (H3K27me3) and to a lesser extent
H3 lysine 9 (H3K9me3) at and around the promoter regions of target genes (Sparmann
and van Lohuizen, 2006). In embryonic stem (ES) cells, pluripotency is sustained by
H3K27me3-mediated repression of genes that are important in development,
organogenesis and cell fate (Lee et al., 2006). Upon differentiation the H3K27me3 mark
is lost and these genes are activated (Lee et al., 2006). Ezh2 null mouse ES cells are not
viable, and Ezh2 is required for the growth of stem cells revealing its crucial role in stem
cell maintenance (O'Carroll et al., 2001).
EZH2 enhances neoplastic transformation (Kleer et al., 2003), is overexpressed in
many cancers, and is strongly associated with metastatic breast and prostate cancers
(Bracken et al., 2003; Kleer et al., 2003; Raman et al., 2005; Rhodes et al., 2004;
Varambally et al., 2002). However, the cause of EZH2 overexpression in cancer is not
clear. Recent work has shown that overexpression of EZH2 is directly responsible for the
48
de novo suppression of multiple genes in human cancer (Gal-Yam et al., 2008; Gal-Yam
et al., in press; Kondo et al., 2008). Intriguingly, a significant subset of PRC2 target
genes in cancer were also targets of PRC2 in ES cells (Yu et al., 2007b). This illustrates
a strong association between the function of PRC2 in cancer and stem cells which
represent de-differentiated and proliferative cell states. Therefore, EZH2 overexpression
might cause a normal cell to de-differentiate back to a stem-cell like state by
epigenetically repressing cell fate regulating genes and tumor-suppressor genes, which
initiates tumor development (Jones and Baylin, 2007; Kondo et al., 2008; Sparmann and
van Lohuizen, 2006).
Our miRNA expression profile for TCC found many differentially expressed
miRNAs, several of which showed putative tumor suppressor functions. The miRNA
that most consistently and dramatically suppressed growth was miR-101, which led us to
further investigate its role in cancer. We found that miR-101 is also downregulated in
prostate and colorectal cancer and it can directly target EZH2 and repress H3K27me3.
Furthermore, our results indicate that a significant subset of genes is regulated by both
miR-101 and EZH2.
Materials and Methods
Cell lines and tissue samples
T24, UM-UC-3, and TCCSUP cells were obtained from the American Type
Culture Collection. T24 cells were cultured in McCoy’s 5A medium supplemented with
10% fetal bovine serum (FBS). UM-UC-3 cells were cultured in DMEM supplemented
49
with 10% FBS. TCCSUP cells were cultured in MEM medium supplemented with non-
essential amino acids and 1mM sodium pyruvate. RNA was extracted using Trizol
(Invitrogen) according to the manufacturer’s protocol. Slides were prepared from fresh
frozen blocks of tumors and matched normal tissue, stained with hematoxylin and eosin,
and the epithelium was marked by a pathologist. These slides were used as a guide to
dissect the fresh frozen blocks and RNA was extracted using the ToTALLY RNA
Isolation Kit (Ambion) according to the manufacturer’s protocol. The patient samples
were obtained through USC/Norris Tissue Procurement Core Resource after informed
consent and Institutional Review Board (IRB) approval (IRB #886005 and #926041) at
the USC/Norris Comprehensive Cancer Center.
Expression vectors and transfections
shRNA to EZH2 vectors and control shRNA were purchased from Sigma. T24,
UM-UC-3 and TCCSUP cells were seeded in 6-well dishes so that 24 hr later they were
90% confluent. Cells were transfected using 2.5 µL PLUS reagent, 6.25 µL
Lipofectamine LTX and 2.5 µg shRNA vector. Cells at 60% confluence were transfected
with pre-miR-101, control precursors (Ambion), siRNA to EZH2 or control siRNA
(Dharmacon) at a final concentration of 50 nM or 5 nM using Oligofectamine
(Invitrogen) according to the manufacturer’s protocol.
Reverse transcription and Taqman qPCR
50
All reagents for miRNA Taqman assays to detect miR-101 were purchased from
Applied Biosystems and used according to the manufacturer’s protocol (Chen et al.,
2005). The same procedure was used for RT-qPCR for EZH2.
EZH2 primers
Forward ATTTTTGTGAAAAGTTTTGTCAATGTAGTTCAGAG
Reverse TCACACTCTCGGACAGCCAG
Probe FAM-CAACACCAAGCAGTGCCCGTGCT-BHQ
Cell proliferation and colony formation assays
Cell proliferation assays were conducted in triplicate as described previously (46).
Cells in each well were trypsinized 48 hr after transfection and equal cell numbers plated
in 10 cm dishes with medium containing puromycin (T24 2 µg/mL, TCCSUP 3 µg/mL,
UM-UC-3 2 µg/mL). Medium was changed every 3-4 days and total cell numbers were
counted after 13 days using the Z1 Coulter Particle Counter.
For colony formation assays, equal numbers of cells were plated in triplicate in 10
cm dishes containing medium with puromycin at the same concentrations as above 48 hr
after tranfection. Medium was changed every 3-4 days and colonies were counted after
13 days by washing with PBS, fixing with methanol and staining with Giemsa (Sigma).
Statistical analysis was conducted using an unpaired t-test.
Western blot
Cell pellets were lysed 48 or 72 hr after transient transfection in
radioimmunoprecipitation buffer (0.1% SDS, 0.5% NP40, and 0.5% sodium
51
deoxycholate) in PBS and incubated on ice for 10 min. Extracts were sonicated twice for
15 seconds and then 20 µg of protein was separated by SDS-PAGE on a Ready Gel 4-
15% gradient Tris-HCl Gel (Bio-Rad Laboratories) and transferred to a polyvinylidene
difluoride membrane using a Trans-Blot SD Semi-Dry Electrophoretic Transfer Cell
(Bio-Rad Laboratories). Membranes were incubated with antibodies against human
EZH2 (AC22; 1:1000; Cell Signaling Technology), H3K27Me3 (1:1000; Upstate
Biotechnology), and β-actin (1:1000, Sigma) in TBS-Tween (TBS-T) buffer (0.01 mol/L
Tris, 0.15 mol/L NaCl, and 0.1% Tween 20) with 5% nonfat dry milk overnight at 4°C.
The membranes were washed three times with TBS-T buffer at room temperature and
incubated with the secondary antibodies for one hour at room temperature. Secondary
antibodies used were anti-mouse-IgG-horseradish peroxidase (HRP) for EZH2 and β -
actin (1:7,500; Santa Cruz Biotechnology) and anti-rabbit-IgG-HRP for H3K27Me3
(1:7,500; Santa Cruz Biotechnology). The membranes were washed three times with
TBS-T at room temperature, incubated with the ECL Western Blotting Detection
Reagents (GE Healthcare Biosciences Corp.), and the signal was visualized by exposure
to Kodak X-OMAT AR film. Films were quantitated using Quantity One software (Bio-
Rad Laboratories).
Luciferase assay
Reporter vectors were created by cloning the wild type or mutated 3 ′UTR of
EZH2 into the XbaI site of the pGL3-control vector (Promega). UM-UC-3 cells were
seeded in a 24 well plate such that they were 90% confluent at the time of transfection.
Reporter vectors were co-transfected with pRL-SV40 (Promega) and pre-miR-101 using
52
Lipofectamine 2000 according to the manufacturer’s protocol. Firefly and renilla
luciferase activity determinations in cell lysates were conducted 24 hr later according to
the manufacturer’s protocol using the Dual Luciferase Reporter assay system (Promega).
Inserts for pGL3-control
EZH2 3'UTR WT
TAGCTTCTAGACTGCCTTAGCTTCAGGAACCTCGAGTACTGTGGGCAATTTAG
AAAAAGAACATGCAGTTTGAAATTCTGAATTTGCAAAGTACTGTAAGAATAA
TTTATCTAGATAGCT
EZH2 3'UTR MUT
TAGCTTCTAGACTGCCTTAGCTTCAGGAACCTCGACTAGTCTGGGCAATTTAG
AAAAAGAACATGCAGTTTGAAATTCTGAATTTGCAAACTAGTCTAAGAATAA
TTTATCTAGATAGCT
mRNA microarray
UM-UC-3 cells were transfected with pre-miR-101, control precursors, siRNA to
EZH2, and control siRNA in triplicate. GEO accession number GSE13674. Total RNA
was prepared 72 hr after transient transfection and was submitted to the Norris Cancer
Center CORE facility, which performed the amplification and hybridization according to
the manufacturer's protocol (Illumina). Illumina human 6 v 2 array was used for gene
expression analysis. The raw data of the spot density was extracted with Illumina
BeadStudio software. Gene expression data from individual arrays were normalized by
Quantile normalization. The criteria for significance were fold change > 1.5 and t-test p-
53
value < 0.05 and the p-value for the overlap of upregulated genes was based on
hypergeometric distribution.
Chromatin immunoprecipitation assay (ChIP)
ChIP assay was done as previously described (Saito et al., 2006). Antibodies
against H3K27me3 and CD8 were obtained from Upstate and Santa Cruz Biotechnology,
respectively. UM-UC-3 cells were treated with control precursors, pre-miR-101, control
siRNA, or siRNA to EZH2 at a final concentration of 50nM for 72 h.
ChIP primers
DDIT4
Forward GGTCGGTCCCCCTCTTGT
Reverse GGCGTTTGCTGATGAACTCA
Probe FAM-AGCGGCTTCTACGCTCCGGCA-BHQ
FAM84
Forward TTTCTCCATCCTTCCCCTGC
Reverse CTTCTCTTGCCTTGTCCCCA
Probe FAM-TCTTTGTTAGGTTATTTTAGACAGAGCAGCCTCGC-BHQ
Results
miR-101 is also downregulated in colon and prostate cancer tumors
To expand on our results from Chapter 2, we examined miR-101 expression in
colon and prostate cancers by RT-qPCR of 10 colon tumor and corresponding normal
54
sets and 7 prostate sets. The colon tumors showed a significant decrease in miR-101
expression when compared to the normal samples (6/10 samples) (Fig. 3.1). Similarly,
miR-101 expression was downregulated in prostate tumors (4/7 samples) (Fig. 3.1).
miR-101 represses the Polycomb group protein EZH2 and the Polycomb Repressive
Complex 2 histone modification H3K27me3
We used the prediction algorithm TargetScan (www.targetscan.org) to identify
targets of miR-101 and found the histone methyltransferase EZH2 had a very high score,
a highly conserved sequence, and two predicted sequence matches to the miR-101 seed.
To make a clear comparison, we plotted miR-101 RT-qPCR data from 20 individual
patient samples from Fig. 2.5 above the mRNA levels of EZH2 that were obtained by
RT-qPCR (Fig. 3.2). Our results showed that EZH2 was upregulated in the tumor
samples relative to the adjacent normal specimens while miR-101 is downregulated in
these same samples (Fig. 3.2).
55
Figure 3.1. miR-101 is downregulated in colon and prostate tumors. RT-qPCR for miR-
101 of 10 colon cancer patient sample sets and 7 prostate sets shows that miR-101 is
downregulated in colon and prostate cancer. All reactions were done in duplicate, the
miR-101 signal was divided by U6 and the average Normal value was normalized to 1. *
p-value = 0.01, ** p-value = 0.046, p-values were calculated using a 1-tailed paired t-test.
Prostate
0.0
0.5
1.0
Normal Tumor
miR-101/U6
Colon
0.0
0.5
1.0
Normal Tumor
miR-101/U6
56
Figure 3.2. RT-qPCR analysis of 20 TCC samples shows that EZH2 is upregulated in
tumors compared to adjacent normal tissue. The data from Fig. 2.5 showing miR-101
levels was modified to show individual patient samples and this was compared to EZH2
levels in these same samples. Each experiment was duplicated and the value for miR-101
or EZH2 was normalized to U6.
0
1
2
3
4
5
6
7
8
9
EZH2/U6
0
100
200
300
400
500
600
miR-101/U6
NT
(n=20)
57
We transiently transfected pre-miR-101 or control precursors into T24, TCCSUP,
and UM-UC-3 cells, and screened potential targets by Western blot. The Western blots
for TCCSUP and UM-UC-3 cells showed EZH2 levels decreased by 86% and 91%,
respectively, while the PRC2 repressive histone modification H3K27me3 decreased by
58% in both cell lines (Fig. 3.3). In T24 cells there was a decrease in EZH2 levels of
52% and the H3K27me3 levels remained the same, which may be due in part to
transfections that yielded 50% lower mature miR-101 levels when compared to UM-UC-
3 cells (data not shown). We determined the effect of physiological levels of miR-101 on
EZH2 by transfecting 5nM pre-miR-101 in UM-UC-3 cells. The results showed a 39%
downregulation of EZH2 (Fig. 3.3) and mature miR-101 levels comparable to the average
normal patient sample (Fig. 2.7). These results indicate that miR-101 represses EZH2
and causes a loss of the repressive PRC2 histone mark H3K27me3 in two of three TCC
cell lines (Fig. 3.3).
58
Figure 3.3. Western blot analysis of TCC cell lines after transient transfection with pre-
miR-101 or control precursors at a final concentration of 50 nM or 5nM where indicated.
Lysates were prepared 48 h after transfection and membranes were probed with
antibodies to EZH2, H3K27me3, and β-actin as a loading control. Bands were
quantitated by Quantity One software (Bio-Rad).
EZH2
β-Actin
H3K27Me3
T24
control
miR-101
TCCSUP
control
miR-101
UM-UC-3
control
miR-101
control
miR-101
(5nM)
EZH2
β-Actin
H3K27Me3
T24
control
miR-101
TCCSUP
control
miR-101
UM-UC-3
control
miR-101
control
miR-101
(5nM)
miR-101
(5nM)
59
EZH2 is a direct target of miR-101
To confirm that EZH2 is a direct target of miR-101, we created luciferase reporter
vectors by cloning either the wild type or a mutated portion of the 3 ′UTR of EZH2 into
the 3 ′UTR of the pGL3-control vector. The mutated 3 ′UTR had three bases changed,
from GUACUGU to CUAGUCU, at each of the two putative miR-101 binding sites (Fig.
3.4). We transfected these vectors into UM-UC-3 cells with pre-miR-101 and the Renilla
luciferase vector pRL-SV40 to control for transfection efficiency. The lysates were
analyzed 24 hr later and the results showed a 42% decrease in luciferase activity for the
wild type 3 ′UTR of EZH2, while the mutated 3 ′UTR showed no repression when
compared to the empty reporter (p-value < 0.01) as was also found previously (Lewis et
al., 2003) (Fig. 3.5). Therefore, miR-101 represses EZH2 by binding to the 3 ′UTR of
EZH2 in a direct and sequence specific manner, confirming that the oncogene EZH2 is a
direct target of the putative tumor suppressor miR-101.
60
Figure 3.4. The highly conserved sequence of the 3 ′UTR of EZH2 for human, mouse,
rat, dog, and chicken are shown. The nucleotides that were mutated for the luciferase
insert are marked with *.
58- C G A G U A C U G U G G G C A A U U U A G A A A A A G A A C A U G C A G U U U G A A A U U C U G A A U U U G C A A A G U A C U G U A A G A A - 124
-U G A G U A C U G U G G G C A A U U U A G A A A A C G G A A A U G C A G U U U G A A A U U C U G A A U U U G C A A A G U A C U G U A A C A G
-C G A G U A C U G U G G G C A A U U U A G A A A A A U A A A A U G C A G U U U G A A A U U C U G A A U U U G C A A A G U A C U G U A A G A A
-C U A G U A C U G U G G G C A A U U A ---A G A A A G A A A A A G C U A U U U G A A A U U C U G U G U U U G C A A A G U A C U G U A A C A G
-U G A G U A C U G U G G G C A A U U U A G A A A A A G G A A A U G C A G U U U G A A A U U U U G A A U U U G C A A A G U A C U G U A A C A G
mi R - 101
B in ding s ite
mi R -1 0 1
B indin g s ite
*** * ** Human Human
Mouse Mouse
Rat Rat
Dog Dog
Chicken Chicken
58- C G A G U A C U G U G G G C A A U U U A G A A A A A G A A C A U G C A G U U U G A A A U U C U G A A U U U G C A A A G U A C U G U A A G A A - 124
-U G A G U A C U G U G G G C A A U U U A G A A A A C G G A A A U G C A G U U U G A A A U U C U G A A U U U G C A A A G U A C U G U A A C A G
-C G A G U A C U G U G G G C A A U U U A G A A A A A U A A A A U G C A G U U U G A A A U U C U G A A U U U G C A A A G U A C U G U A A G A A
-C U A G U A C U G U G G G C A A U U A ---A G A A A G A A A A A G C U A U U U G A A A U U C U G U G U U U G C A A A G U A C U G U A A C A G
-U G A G U A C U G U G G G C A A U U U A G A A A A A G G A A A U G C A G U U U G A A A U U U U G A A U U U G C A A A G U A C U G U A A C A G
mi R - 101
B in ding s ite
mi R -1 0 1
B indin g s ite
*** * ** Human Human
Mouse Mouse
Rat Rat
Dog Dog
Chicken Chicken
61
Figure 3.5. Luciferase assay conducted in UM-UC-3 cells 24 h after cotransfection with
pre-miR-101, renilla luciferase vector pRL-SV40, and either the firefly luciferase reporter
pGL3-control containing wild type EZH2 3′UTR insert (GUACUGU) or mutated EZH2
3′UTR insert (CUAGUCU). Relative luciferase activity was normalized to the no insert
control (* p-value < 0.01). Data is presented as mean ± SEM.
0
0.2
0.4
0.6
0.8
1
wt EZH2 3'UTR mut EZH2 3'UTR
EZH2 3’UTR WT EZH2 3’UTR MUT
Normalized luciferase activity
0
0.2
0.4
0.6
0.8
1
wt EZH2 3'UTR mut EZH2 3'UTR
EZH2 3’UTR WT EZH2 3’UTR MUT
Normalized luciferase activity
62
Knockdown of EZH2 shows phenotypic overlap with the restoration of miR-101
expression in UM-UC-3 cells
After confirming that miR-101 leads to a decrease in H3K27me3 levels by
targeting EZH2, we examined if there was a phenotypic overlap between stable miR-101
transfection and knockdown of EZH2 by shRNA in TCC cells. We conducted cell
proliferation assays and colony formation assays in 3 TCC cell lines using 4 expression
vectors (clones 74, 75, 76, 77) containing distinct shRNAs targeting EZH2. The results
showed that 2 of 4, 1 of 4, and 4 of 4 shRNAs suppressed cell proliferation in T24,
TCCSUP, and UM-UC-3 cells, respectively (Fig. 3.6A). The colony formation results
were more striking as all 4 shRNAs suppressed colony formation in T24 and TCCSUP
cells, while 3 of 4 shRNAs suppressed colony formation in UM-UC-3 cells (Fig. 3.6B,
3.6C).
63
Figure 3.6. Knockdown of EZH2 decreases cell proliferation and colony formation in
TCC cell lines. A, Cell proliferation assays were conducted by transferring equal cell
numbers to 10 cm dishes 48 h post-transfection with 4 different expression vectors
(clones 74, 75, 76, 77) containing distinct shRNAs to EZH2 or control shRNA vector.
After 13 days under puromycin selection total cells were counted and normalized to the
empty vector. B, Colony formation assays were conducted by seeding equal cell
numbers 48 h post-transfection into 10cm dishes. Colonies were stained and counted
after 13 days under puromycin selection and normalized to the control shRNA vector. *
indicates p-value < 0.05 according to t-test, data is presented as mean ± SEM. C,
Photographs of representative colony formation assays.
EZH2-
76
shRNA
Control
shRNA
EZH2-
77
shRNA
Control
shRNA
EZH2-
75
shRNA
Control
shRNA
0
20
40
60
80
100
120
control 74757677
0
20
40
60
80
100
120
control 74 75 76 77
0
20
40
60
80
100
120
control 74757677
Rela tiv e cell num ber (% )
0
20
40
60
80
100
120
control 747576 77
Rela tiv e co lo ny num ber (%
0
20
40
60
80
100
120
control 74 75 76 77
0
20
40
60
80
100
120
control 74 75 76 77
Relative colony number (%)
T24
T24
UM-UC-3
UM-UC-3 TCCSUP
TCCSUP B
A
* *
* *
* *
* *
* *
* *
* *
* *
* *
* *
* *
* *
* *
* *
* *
* *
* *
* *
C
T24 UM-UC-3 TCCSUP
control
control
64
To examine additional phenotypic overlap, expression microarrays were
conducted on UM-UC-3 cells transfected with pre-miR-101 or siRNA to EZH2. We
identified a significant overlap of 43 upregulated genes, which suggests that restoring
miR-101 expression in cancer cells re-expresses a subset of genes that are repressed by
EZH2 (Fig. 3.7B). The siRNA to EZH2 caused a more efficient knockdown of EZH2
and H3K27me3 than the pre-miR-101 transfection (Fig. 3.7A). The extra decrease in
EZH2 and H3K27me3 from the siRNA to EZH2 may explain why there were 62
upregulated genes that did not overlap with the genes upregulated by pre-miR-101
transfection (Fig. 3.7B). In contrast, we expect the pre-miR-101 transfection to have
much wider effects on gene expression than the siRNA to EZH2 because miRNAs likely
repress several targets that influence the transcriptome. We conducted chromatin
immunoprecipitation analysis on the promoters for FAM84 and DDIT4 after treating UM-
UC-3 cells with siRNA to EZH2 and pre-miR-101 for 72 h. The results showed that both
treatments depleted the promoters of H3K27me3 (Fig. 3.8), indicating that miR-101
regulates histone methylation through EZH2.
65
Figure 3.7. pre-miR-101 transfection and siRNA to EZH2 lead to the up-regulation of
overlapping genes. A, Western blot analysis of UM-UC-3 cells transfected with siRNA
to EZH2, control siRNA, pre-miR-101, or control precursors to a final concentration of
50 nM. Total protein was extracted 72 h after transfection and membranes were probed
with antibodies to EZH2, H3K27me3, and β-actin as a loading control. B, Illumina
Human 6 v 2 chips were used to interrogate the mRNA levels from UM-UC-3 cells 72 h
after transfection with pre-miR-101, control precursors, siRNA to EZH2 and control
siRNA. Based on the criteria fold change > 1.5 and t-test p-value < 0.05, 1,092 genes
were up-regulated after pre-miR-101 transfection, while 105 genes were up-regulated
after treatment with siRNA to EZH2. There was an overlap of 43 genes (p-value < 10
-11
based on hypergeometric distribution).
EZH2
β-Actin
H3K27Me3
miR-101
control
pre-miR
EZH2
control
siRNA
A
1049 1049 43 43 62 62
EZH2 siRNA B
pre-miR-101
66
Figure 3.8. miR-101 transfection decreases H3K27me3 enrichment in gene promoters.
UM-UC-3 cells were treated with control precursors, pre-miR-101, control siRNA, or
siRNA to EZH2 at a final concentration of 50 nM for 72h. Fold enrichment was
calculated by (H3K27me3-CD8)/(input-CD8). FAM84 was chosen because it was
identified as a Polycomb target gene (Tan et al. Genes Dev. 2007 May 1;21(9):1050-63)
and DDIT4 was chosen because it was upregulated by both siRNA to EZH2 and pre-miR-
101 transfection.
DDIT4
0.00
0.05
0.10
0.15
0.20
control miR miR-101 control siRNA siRNA E ZH2
ChIP H3K27me3
Fold enrichment Fold enrichment
FAM84
0
0.4
0.8
1.2
control miR miR-101 control siRNA siRNA E ZH2
67
Discussion
There are a plethora of mechanisms that could lead to decreased miRNA
expression in cancer including copy number alterations (Calin and Croce, 2006),
epigenetic silencing (Brueckner et al., 2007; Lujambio et al., 2007; Saito et al., 2006) and
trans-acting factors (Taganov et al., 2006). There are two copies of miR-101, with miR-
101-1 located at chromosome 1p31 and miR-101-2 located at chromosome 9p24. The
two precursors have different sequences but the mature forms are identical. We found
that miR-101 silencing in TCC cell lines was probably not due to epigenetic phenomena
because treatment with the DNA demethylating agent 5-Aza-2 ′-deoxycytidine and the
histone deacetylase inhibitor 4-phenylbutyric acid did not induce expression of miR-101
in TCC cell lines (data not shown). Intriguingly, loss of heterozygosity (LOH) at
chromosome 1p occurs in many different solid tumors and is negatively associated with
survival (Ragnarsson et al., 1999), while LOH at chromosome 9p also commonly occurs
in cancer, particularly TCC (Calin et al., 2004b; Tsai et al., 1990; Wolff et al., 2005). A
recent report suggested that genomic loss may be a mechanism for miR-101
downregulation in prostate cancer (Varambally et al., 2008). This suggests that DNA
copy number may regulate miR-101 expression, although a trans-acting mechanism
should be investigated in the future.
The role of miRNAs in controlling epigenetics is just emerging. ES cell specific
miRNAs control de novo DNA methylation during differentiation by targeting Rbl2
(Benetti et al., 2008; Sinkkonen et al., 2008). A recent report suggests that the
downregulation of the miR-29 family in lung cancer could lead to the overexpression of
68
DNA methylatransferases 3A and 3B and subsequent DNA hypermethylation and gene
silencing (Fabbri et al., 2007). Our results show another instance in which miRNA-
mediated epigenetic mechanisms can be dysregulated in cancer with global
consequences. In addition, this study implies that the cause of EZH2 overexpression in
many cancers may be due to the downregulation of a miRNA that normally maintains
EZH2 at appropriate levels.
EZH2 is critical for the maintenance of proliferation and pluripotency in stem
cells (Sparmann and van Lohuizen, 2006). Global levels of Ezh2 and H3K27me3
decreased when mouse ES cells differentiated and PRC2 target genes specifically lost
Ezh2 binding and H3K27me3 enrichment (Lee et al., 2007). In addition, two groups
found that miR-101 was upregulated after differentiation of human ES cell lines (Bar et
al., 2008; Lakshmipathy et al., 2007). These reports present a strong association between
miR-101 activation and EZH2 repression upon differentiation of stem cells, suggesting
that miR-101 might be part of the complex network, which includes PcG proteins, that
determines developmental outcome. Therefore, in addition to its potential role in cancer,
miR-101 might be involved in normal differentiation by directly repressing EZH2 and re-
expressing cell fate regulating genes.
The prevalence of aberrant epigenetic events in cancer and other diseases has
created the impetus to develop therapies that reactivate silenced genes. Several
epigenetic drugs are FDA approved and others are being used in clinical trials for
myelodysplastic syndrome and other hematological malignancies (Jones and Baylin,
2007). Overexpression of EZH2 causes H3K27me3-mediated gene silencing of tumor
suppressor genes (Kondo et al., 2008) and this may be reversed by molecules that inhibit
69
histone modifying enzymes such as 3-Deazaneplanocin A (Tan et al., 2007). Creating
therapeutic regimens that combine epigenetic drugs with traditional chemotherapeutics is
intriguing and may provide a new paradigm for cancer therapy (Jones and Baylin, 2007).
Our study implicates miR-101 as a potential tumor suppressor and a powerful epigenetic
therapeutic target, by downregulating EZH2, decreasing H3K27me3, and re-expressing
aberrantly silenced Polycomb target genes in cancer. Our results and previously
published data examining miR-101 in lung cancer, breast cancer, colorectal cancer and
prostate cancer (Iorio et al., 2005; Porkka et al., 2007; Schepeler et al., 2008; Yanaihara
et al., 2006) indicate that miR-101 is downregulated in the 5 most frequently diagnosed
cancers in the U.S. (NCI), demonstrating that miR-101 might be part of a solid tumor
signature. This report suggests that aberrant silencing of miR-101 may be a cause of the
overexpression of EZH2 seen in cancer and that restoring miR-101 expression could
hinder EZH2-mediated neoplastic progression.
70
Chapter 4: Epigenetic Therapy Upregulates the Tumor Suppressor MicroRNA-126 and
Its Host Gene EGFL7 in Human Cancer Cells
Introduction
MicroRNAs (miRNAs) are ~22 nucleotide (nt) non-coding RNAs that function
as endogenous regulators of hundreds of target genes. Studies have shown that aberrant
expression of miRNAs is involved in the initiation and progression of cancer (Lu et al.,
2005a), and several miRNAs have been characterized as tumor suppressors or oncogenes
(Calin and Croce, 2006; Esquela-Kerscher and Slack, 2006). Recently, miR-126 was
identified as a metastasis suppressing miRNA that is downregulated in relapsing breast
cancer (Tavazoie et al., 2008). Subsequent reports showed that miR-126 targeted the
oncogene IRS-1 (insulin receptor substrate-1) in breast cancer cells (Zhang et al., 2008a)
and miR-126 was downregulated in cervical cancer (Wang et al., 2008b). In addition,
miR-126 was downregulated in leukemia and targets HOXA9, the overexpression of
which correlates with poor prognosis in acute myelogenous leukemia (Shen et al., 2008).
These studies showed that miR-126 not only plays a critical role in tumorigenesis but also
is important in tumor progression and metastasis.
The main mechanisms for successful cancer therapy are killing proliferating
tumor cells, inhibiting cell growth, inhibiting oncogenes or restoring the expression of
silenced tumor suppressor genes. A promising option for cancer treatment is the use of
epigenetic drugs which inhibit tumor growth by several mechanisms including restoring
the expression of epigenetically silenced tumor suppressor genes (Jones and Baylin,
2007). We and other groups have recently reported that specific miRNAs can be directly
71
regulated from their own promoters by epigenetic alterations induced by chromatin
modifying drugs, or by genetic disruption of key DNA methyltransferases (DNMT) in
human cancer cells (Brueckner et al., 2007; Lujambio et al., 2007; Saito et al., 2006).
These findings suggest that many miRNAs are under epigenetic control and could be
therapeutic targets of cancer (Saito and Jones, 2006).
Most human miRNAs are located within intronic regions in either coding or
noncoding transcription units (Baskerville and Bartel, 2005; Rodriguez et al., 2004). A
recent study demonstrated that intronic miRNAs are processed from unspliced introns
before splicing occurs, indicating that both the intronic miRNA and its host gene mRNA
are generated from the same primary transcript (Kim and Kim, 2007; Rodriguez et al.,
2004). These findings led us to investigate whether epigenetic therapy could restore the
expression of epigenetically silenced genes containing intronic tumor suppressor
miRNAs.
To address this issue, we focused on the epigenetic regulation of the tumor
suppressor miR-126 because our previous study suggested that miR-126 is upregulated
by chromatin modifying drugs (Saito et al., 2006). miR-126 is located within intron 7 of
EGFL7, an epidermal growth factor-domain gene, which is highly expressed in
endothelial cells and highly vascularized tissues, and it controls an important step in
vasculogenesis (Fitch et al., 2004; Parker et al., 2004). We examined expression levels
and epigenetic changes of miR-126 and EGFL7 in human cancer cells and our results
showed that miR-126 is downregulated in cancer cells but is upregulated together with its
host gene EGFL7 by epigenetic treatment. The experiments were primarily conducted by
Yoshimasa Saito and the manuscript was written by Jeffrey Friedman.
72
Materials and Methods
Cell lines and primary tumors
T24, HeLa, MCF7, and HUVEC cells were obtained from the American Type
Culture Collection (Rockville, MD). T24 cells were cultured in McCoy’s 5A medium
supplemented with 10% fetal bovine serum (FBS). HeLa and MCF7 cells were cultured
in MEM medium supplemented with 10% FBS. HUVEC cells were cultured in EGM-2
medium (Cambrex, Walkersville, MD).
Matched sets of primary bladder and prostate tumors and adjacent normal tissues
were obtained through the USC/Norris Tissue Procurement Core Resource after informed
consent and Institutional Review Board (IRB) approval (IRB # 886005 and # 926041) at
the USC/Norris Comprehensive Cancer Center.
5-aza-2 ′-deoxycytidine (5-Aza-CdR) and 4-phenylbutyric acid (PBA) treatment
Cells were seeded at 5X10
5
cells per 100 mm dish 24 hr prior to treatment with
5-Aza-CdR (1µM or 3 µM, Sigma-Aldrich, St. Louis, MO) and/or PBA (1mM or 3mM,
Sigma-Aldrich). 5-Aza-CdR was removed after 24 hr, while PBA was continuously
administered by replacing the medium containing PBA every 24 hr for 5 more days.
5′-Rapid Amplification of cDNA Ends (RACE)
73
The 5 ′ ends of the primary transcripts of miR-126 were determined using the
RLM-RACE kit (Ambion) according to the manufacturer’s instruction. Outer primer,
TCCAGGAAGGAAATCTGCTCGC; inner primer, CAGCACCAGCTGCAGCTTCT.
Northern blots
Total RNA (20 µg) was loaded onto a 15% denaturing polyacrylamide gel and
transferred to a nylon membrane. The StarFire radiolabeled probes (Integrated DNA
Technologies, Coralville, IA) were used according to the manufacturer’s instruction.
Probes for miR-126, GCATTATTACTCACGGTACGA and U6 loading control,
GCAGGGGCCATGCTAATCTTCTCTGTATCG.
RT-qPCR
Total RNA (5 µg) was used for reverse transcription using Superscript III
(Invitrogen) and random hexamers (Promega, Madison, WI). Then PCR was performed
with primers specific for EGFL7 mRNA
Primer set 1
Forward AGGGCTAGGGTCCATCTCCA
Reverse TGGCGGAGGAGAATCAGTCAT
Primer set 2
Forward CCCCGGATCCGGCGGCCA
Reverse TGCGGCGGTAGGCGGTCCTA
Primer set 3
Forward CAGACGGTACACTCTGTGTGC
74
Reverse CAGCACCAGCTGCAGCTTCT
GAPDH mRNA was used as an internal control.
GAPDH
Forward GAAGGTGAAGGTCGGAGTC
Reverse GAAGATGGTGATGGGATTTC
Quantitative analysis was performed by qPCR with CYBR green using the DNA Engine
Opticon System (MJ Research, Waltham, MA).
DNA methylation analysis
Genomic DNA (2 µg) was treated with sodium bisulfite. DNA methylation
levels were determined by bisulfite genomic sequencing, methylation-sensitive single-
nucleotide primer extension (Ms-SNuPE), and methylation-specific PCR (MSP) as
previously described (Herman et al., 1996; Saito et al., 2006).
Bisulfite sequencing primers
Forward GGTTTGAAAGTTAGTAAAGGGTT
Reverse AACAATAACTCTACTAAAACCC
MSP primers
M1
Forward TTGGCGGTCGGGTTTGGTC
Reverse TAAAACCCCGCGACGAACG
U1
Forward TTGGTTTTTGGTGGTTGGGTTTGGTT
Reverse CAAACAAAAAAACTAAAACCCCACAACAAACA
75
M2
Forward GCGGCGCGTGCGCGTTT
Reverse CCAACCCGAACGACGACCG
U2
Forward GTGGTGGTGGTGTGTGTGTGTTT
Reverse CTCAACCCAACCCAAACAACAACCA
Ms-SNuPE primers
S1 TTTGAAAGTTAGTAAAGGGTT
S2 GGTTTTTTTTGGTTTTTGG
Chromatin Immunoprecipitation Assay (ChIP)
ChIP analysis of the promoter region of the EGFL7 gene was performed as
previously described (Saito et al., 2006). Ten µL of anti-acetylated histone H3 antibody
(Upstate Biochemistry, Lake Placid, NY) was used. The fraction of immunoprecipitated
DNA was calculated as follows: (immunoprecipitated DNA – nonspecific antibody
control (NAC)) / (input DNA – NAC).
Forward CAGCTCAGTGCTAACCTGCG
Reverse TGCGGGCCCTTTGCTAGCTTT
Results
miR-126 is downregulated in primary tumors and cancer cell lines but is activated by
treatment with 5-Aza-CdR and PBA
76
We first performed Northern blot analysis for miR-126 expression in matched sets
of primary bladder and prostate tumors and adjacent normal tissues. miR-126 was highly
expressed in the normal bladder and prostate tissues and was downregulated in the
corresponding tumors in all cases except for case 2 of the prostate tumors, which showed
no change in expression (Fig. 4.1A). EGFL7 is highly expressed in HUVEC endothelial
cells so we used HUVEC cells as our positive control (Fitch et al., 2004). We found that
miR-126 is highly expressed in HUVEC cells but not in T24 (bladder cancer), HeLa
(cervical cancer), or MCF7 (breast cancer) cell lines (Fig. 4.1B). After treatment with the
DNA demethylating agent 5-Aza-CdR and the histone deacetylase (HDAC) inhibitor
PBA, miR-126 was strongly upregulated in these cancer cell lines (Fig. 4.1B). miR-126
was slightly upregulated after treatment with either 5-Aza-CdR or PBA alone (data not
shown), suggesting that 5-Aza-CdR and PBA act synergistically to induce miR-126
expression.
77
Figure 4.1. Northern blot analysis of miR-126. A, miR-126 expression in matched sets
of normal tissues and primary bladder and prostate tumors. B, miR-126 expression in
HUVEC, T24, HeLa, and MCF7 cells. tRNA and U6 RNA were used as loading
controls. N, normal; T, tumor; U, untreated; AP3, 5-Aza-CdR (3 µM) and PBA (3mM).
N T N T N T N T N T N T N T N T
Bladder Prostate
miR-126 21 nt
Case 1Case 2Case 3Case 4 Case 1Case 2Case 3Case 4
tRNA
A
B
U AP3
21 nt miR-126
U AP3 U AP3
HeLa MCF7 T24
U6
HUVEC
78
The primary transcripts of miR-126 correspond to multiple transcripts of EGFL7
In order to examine if miR-126 was coexpressed with EGFL7, we designed
primer set 1 for RT-qPCR to examine full-length EGFL7 (S1) expression (Fig. 4.2A). S1
expression correlated well with miR-126 expression in HUVEC cells, but we could not
detect appreciable levels of S1 in T24, HeLa, and MCF7 cancer cell lines even after
treatment. Bladder and prostate tumors and their matched normal tissues also failed to
show expression of S1 (Fig. 4.2B). To resolve this issue, we searched the UCSC
Genome Bioinformatics Site and found several potential alternative transcripts for
EGFL7. A CpG island was detected in intron 2 which contained the start site for an
alternative transcript, and another CpG island was located in intron 7 which contained
miR-126. To determine the start site of the primary transcript of miR-126 in cell lines,
we performed 5 ′-RACE analysis in T24 cells treated with 5-Aza-CdR and PBA. We
designed two primers immediately downstream of miR-126 with one located in exon 8
and the other in intron 7 (Fig. 4.2A). Two transcription start sites were found with the
exonic primer and no 5 ′-RACE product was detected with the intronic primer, indicating
that miR-126 does not have its own promoter (Fig. 4.2A). The longer alternative
transcript corresponds to human EST BC012377 (S2) which has its start site in the CpG
island of intron 2; the shorter transcript corresponds to human EST BF667512 (S3) which
starts at the beginning of exon 7 (Fig. 4.2A). These results suggest that miR-126 is
transcribed as part of these alternative transcripts of EGFL7 rather than from its own
promoter.
79
Figure 4.2. 5 ′-RACE for the primary transcript of miR-126 and RT-qPCR analysis of
EGFL7 normalized to GAPDH. A, 5 ′-RACE for the primary transcript of miR-126 in
T24 cells treated with 5-Aza-CdR and PBA. Two transcription start sites were found (S2
and S3). miR-126 (arrowhead) is embedded within intron 7 of the EGFL7 gene. The bent
arrows indicate transcription start sites determined by 5 ′-RACE (S2 and S3), whereas the
dotted bent arrow indicates the full length start site (S1) of EGFL7. The white box
indicates exon 1 of the S2 alternative transcript of EGFL7. The open arrowheads indicate
primers used for 5 ′-RACE. The black bars indicate CpG islands. B, RT-qPCR analysis
of EGFL7 normalized to GAPDH in HUVEC, T24, HeLa, and MCF7 cells and matched
sets of normal tissues and primary bladder and prostate tumors. The three different
primer sets described in Fig. 4.2A were used. The white and black bars indicate
untreated (U) and treated (AP3) T24, HeLa, and MCF7 cells, respectively. The white
bars indicate normal tissues (N) and the black bars indicate primary tumors (T) of bladder
(B) and prostate (P).
EGFL7/GAPDH EGFL7/GAPDH EGFL7/GAPDH
A
B
primer set 3 primer set 2 primer set 1
ATG
S2 S3 S1
100
600
1000
(bp)
S2
S3
5 5’ ’- -RACE RACE
Primer set 2
Primer set 1
Primer set 3
Bladder tumor samples
Cell lines
HUVEC T24 HeLa MCF7
U AP3
Prostate tumor samples
B1 B2 B3 B4
N T N T N T N T
B1 B2 B3 B4
N T N T N T N T
B1 B2 B3 B4
N T N T N T N T
P1 P2 P3 P4
N T N T N T N T
P1 P2 P3 P4
N T N T N T N T
P1 P2 P3 P4
N T N T N T N T
0
0.1
0.2
0.3
0.4
0.5
0.6
0
0.1
0.2
0.3
0.4
0.5
0.6
0
0.004
0.008
0.012
0.016
0.02
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0
0.004
0.008
0.012
0.016
0.02
0
0.01
0.02
0.03
0.04
0.05
0.06
U AP3 U AP3
0
0.01
0.02
0.03
0.04
0.05
0.06
HUVEC T24 HeLa MCF7
U AP3 U AP3 U AP3
0
0.004
0.008
0.012
0.016
0.02
HUVEC T24 HeLa MCF7
U AP3 U AP3 U AP3
80
miR-126 and the alternative transcripts of EGFL7 are concomitantly regulated in cancer
cell lines and primary tumors
To verify the 5 ′-RACE results and to determine the transcripts for miR-126
expression, we performed RT-qPCR analysis of EGFL7 using three primer sets to
distinguish between the different transcripts. Primer set 1 detects the full-length EGFL7
(S1); primer set 2 detects the longer alternative transcript of EGFL7 (S2); primer set 3
detects the shorter alternative transcript S3 in addition to S1 and S2. Results using primer
set 1 indicated that S1 was expressed in HUVEC cells but not in cell lines or in patient
samples as we mentioned above (Fig. 4.2B). On the other hand, expression data using
primer sets 2 and 3 showed that S2 was strongly upregulated after treatment of T24,
HeLa, and MCF7 cells with 5-Aza-CdR and PBA. S2 was also expressed at high levels
in normal bladder and prostate tissues, whereas it was remarkably downregulated in
bladder and prostate tumors except for case 2 of the prostate tumors (Fig. 4.2B).
In HUVEC cells all three EGFL7 transcripts (S1, S2, S3) are expressed because
primer set 3 levels are higher than the sum of primer sets 1 and 2, and miR-126
expression correlates with EGFL7 expression (Fig. 4.1B, 4.2B). In treated cancer cell
lines (T24, HeLa, and MCF7) S1 is expressed at extremely low levels; expression levels
were almost equal for primer sets 2 and 3 which indicated that there was no S3
expression so S2 was the major transcript activated by epigenetic treatment. Similarly
high levels of expression for primer sets 2 and 3 were also observed in normal bladder
tissues, but in prostate tissues expression levels for primer set 3 were greater than set 2,
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suggesting that both S2 and S3 were expressed (Fig. 4.2B). This indicated that there is a
tissue or cell specific expression pattern of EGFL7.
The results from the Northern blot, 5 ′-RACE, and RT-qPCR experiments are
consistent with each other and the expression patterns of miR-126 correlate closely with
the expression patterns of the EGFL7 transcripts in cell lines and patient samples.
Despite this, there seems to be a discrepancy in the magnitude of activation of miR-126
and S2 by 5-Aza-CdR and PBA treatment. Although the increases in the S2 expression
after treatment were ~5 fold in T24, HeLa, and MCF7 cells (Fig. 4.2B), the increases in
miR-126 expression were much higher than that of S2 (Fig. 4.1B). This is
understandable when one considers that the processing of intronic miRNAs precedes and
might be more efficient than the splicing of the mRNAs of their host genes (Kim and
Kim, 2007).
Epigenetic alterations around the CpG island promoter of the S2 transcript of EGFL7
After finding that miR-126 and S2 are upregulated after treatment with
chromatin modifying drugs, we examined the DNA methylation status around the S2
CpG island promoter. DNA methylation status of the promoter and exon 1 of S2 was
determined by methylation sensitive PCR (MSP) analysis (Fig. 4.3A). The results
showed there were no fully methylated strands in either region. We used bisulfite
genomic sequencing to validate the MSP results at the promoter and confirmed that there
are no fully methylated strands, but there are low levels of DNA methylation (Fig. 4.3A).
These results were also supported by Ms-SNuPE (Methylation-sensitive Single
Nucelotide Primer Extension) analysis which showed very low DNA methylation levels
82
in T24 cells and in matched primary bladder and prostate tumors and adjacent normal
samples (Fig. 4.3D).
83
Figure 4.3. Epigenetic alterations around the CpG island promoter of the alternative
transcript of EGFL7. A, Bisulfite genomic sequencing and MSP analysis of the CpG
island promoter region in T24 cells. The bent arrow indicates the transcription start site
of S2. The open arrowheads indicate the primers used for Ms-SNuPE analyses in Fig.
3D. Open circle, unmethylated CpG; filled circle, methylated CpG. The locations of the
primers used for MSP are described as arrows. M, methylation specific primers; U,
unmethylation specific primers. Sperm DNA and sperm DNA treated with SssI
methylase were used as unmethylated and methylated controls, respectively. B and C,
ChIP analysis of the CpG island promoter region in T24 (B) and HeLa (C) cells. The
levels of acetylated histone H3 were determined by (immunoprecipitated DNA –
nonspecific antibody control (NAC)) / (input DNA – NAC). U, untreated; AP3, 5-Aza-
CdR (3 µM) and PBA (3mM). D, Ms-SNuPE analysis of the CpG island promoter region.
The white and black bars indicate untreated (U) and treated (AP3) in T24 cells,
respectively. The white bars indicate normal tissues (N) and the black bars indicate
primary tumors (T) of bladder (B) and prostate (P).
A
B
D
C
0
1
2
3
U AP3
AcH3/Input
0
20
40
60
80
100
%Methylation
B1 B2 B3 B4
N T N T N T N T N T N T N T N T
P1 P2 P3 P4
U AP3
T24
0
1
2
3
4
5
UAP3
AcH3/Input
50 bp
Sperm SssI T24
M U M U M U
Sperm SssI T24
M U M U M U
S2
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Because our results showed S2 was not controlled by DNA methylation, we
analyzed alterations in chromatin structure around the S2 and S3 promoters by ChIP
analysis in T24 and HeLa cells. The levels of the active transcription mark acetylated
histone H3 were increased at both S2 and S3 in T24 and HeLa cells after treatment, but
the increase was much more dramatic at S2 (Fig.4.3B, 4.3C). This correlated well with
the expression pattern of miR-126 and S2 (Fig. 4.1B, 4.2B). These results suggested that
expression of S2 is regulated by histone modifications rather than by DNA methylation at
the CpG island promoter.
Discussion
In the short time after we published that miR-127 was epigenetically silenced in
cancer cells, several labs have shown additional examples of miRNA expression being
controlled by epigenetic mechanisms around miRNA promoters (Yang et al., 2008).
However, most miRNAs are intronic and an intronic miRNA tends to be co-expressed
with its host gene (Baskerville and Bartel, 2005). The mechanisms that control the
transcription of the host gene should be the same as those that control expression of the
intronic miRNA (Kim and Kim, 2007; Rodriguez et al., 2004). Elucidating these
mechanisms will give us a much clearer view of the roles miRNAs play in the cell, but
due to alternative splicing, it will be difficult to dissect the role each transcript has on
miRNA expression.
Here we show that the tumor suppressor intronic miRNA miR-126 is
downregulated in human cancer cell lines and bladder and prostate tumors, and is
activated by inhibitors of DNA methylation and histone deacetylation, suggesting that
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miR-126 could be a target of epigenetic therapy of cancer (Yoo and Jones, 2006). In
addition, we found that the primary transcript of miR-126 corresponds to an alternative
transcript of EGFL7 (S2) with a CpG island promoter and that miR-126 and S2 are
concomitantly regulated in cancer cell lines and bladder tumors. Our results indicate that
epigenetic therapy activates miRNA expression in two ways: by directly activating
miRNAs such as miR-127 from their own promoters as we previously reported (Saito et
al., 2006) and by activating intronic miRNAs such as miR-126 together with their host
genes.
Intriguingly, our data suggest that the CpG island promoter of S2 is regulated by
chromatin structural changes such as histone modifications rather than by DNA
methylation in cancer cells. However, treatment of cancer cell lines with the HDAC
inhibitor PBA alone was not able to activate miR-126 expression, indicating that the
expression of S2 is strongly suppressed in cancer cells. Our lab reported that 5-Aza-CdR
is highly effective not only at removing cytosine methylation but also at rapidly reversing
chromatin structural changes (Nguyen et al., 2002), while another study indicated that 5-
Aza-CdR can reactivate epigenetically silenced genes independent of its effects on DNA
methylation (Wozniak et al., 2007). Although this may be due to indirect effects of 5-
Aza-CdR, it seems that both inhibitors of DNA methylation and histone deacetylation are
necessary to activate miR-126 expression to a sufficient level.
Inhibitors of DNA methylation and histone deacetylation can work synergistically
to suppress growth of cancer cell lines both in vitro and in vivo. This effect may be
caused by inducing cancer cells to differentiate, re-expressing aberrantly silenced tumor
suppressor genes and re-expressing tumor antigens which would aid immune surveillance
86
(Jones and Baylin, 2007). Many epigenetic drugs have shown promising results in
clinical trials and our results suggest a new anticancer effect of this class of drugs. By
inducing expression of miR-126, epigenetic therapy not only inhibits the growth of
cancer, but may also inhibit the invasiveness and metastatic potential of cancer cells as
well. This work improves our understanding of the mechanisms by which miRNAs are
regulated and the effects of epigenetic drugs in cancer.
87
Chapter 5: Using a Flexible Pol II Driven Expression Vector to Generate Multiple
MicroRNAs by Linking Endogenous Precursor MicroRNA Sequences
Introduction
MicroRNAs (miRNAs) are ~22 nucleotide non-coding RNA molecules that
typically function as endogenous repressors of target genes. A miRNA is usually
transcribed by RNA Pol II as a primary transcript (pri-miRNA) which may be many
kilobases long. The pri-miRNA is processed in the nucleus by the RNAse III enzyme
Drosha, which uses the stem-loop secondary structure in the pri-miRNA to direct
cleavage (Han et al., 2006). The Drosha product is a ~70 nt stem-loop precursor miRNA
(pre-miRNA) that is exported to the cytoplasm. There, the RNAse III enzyme Dicer
cleaves the pre-miRNA to ultimately yield the mature miRNA (Bartel, 2004). In animals,
miRNAs can bind with imperfect complementarity to the 3 ′ untranslated region (3 ′UTR)
of the target mRNA via the RNA-induced silencing complex. The resulting gene
repression occurs by multiple mechanisms including enhanced mRNA degradation and
translational repression (Valencia-Sanchez et al., 2006).
Due to the promiscuity of miRNA binding to target mRNAs, each miRNA may
control numerous genes and each mRNA may be controlled by many miRNAs (Lim et
al., 2005). Developmental timing, cell death, proliferation, hematopoiesis, insulin
secretion, and the immune response are just a few examples of critical biological events
that depend on faithful miRNA expression (Ambros, 2004). miRNA profiling has
revealed extensive miRNA dysregulation in neurological diseases, cardiovascular
diseases and cancer (Soifer et al., 2007).
88
The analysis of miRNA expression profiles in cancer has revealed that many
tumor suppressor miRNAs (miRNAs that target oncogenes) are down-regulated in cancer
any may be therapeutic targets. It might be possible to manipulate miRNA expression to
inhibit cancer progression just as RNAi is being used in some approaches to gene
therapy. A few studies have shown the potential utility of miRNA-based therapies in
cancer. These include the induction of apoptosis by the miR-34 family in colon cancer
cell lines (Chang et al., 2007) and by miR-15a/16-1 in CLL (Cimmino et al., 2005),
growth inhibition of cancer cells by let-7 (Akao et al., 2006; Johnson et al., 2005; Mayr et
al., 2007), and reduced metastasis by miR-126 in breast cancer (Tavazoie et al., 2008).
Currently there are no reported studies using miRNAs for in vivo anti-cancer
therapy. However, the development of methods for in vivo delivery of siRNA and short
heteroduplex RNA (shRNA) to silence single target genes has established technical
approaches that could translate into miRNA therapy (Devi, 2006). Gene therapies based
on systemic delivery of siRNA/shRNA in preclinical models have made use of viral
vectors, liposomes, and nanoparticles (Abbas-Terki et al., 2002; Lu et al., 2005b; Tong,
2006), but the same challenges encountered with delivering antisense and siRNA into
cells will be faced with miRNA-based therapies. The primary obstacle is that introducing
a charged, linear polymer across the membrane of a cell is exceedingly difficult. The
clear advantage miRNA-based gene therapy will have over siRNAs, shRNAs, and
antisense oligonucleotides is that multiple miRNAs can be co-transcribed and each
miRNA has multiple targets, such as let-7 which down-regulates RAS, MYC, and
HMGA2 oncogenes (Johnson et al., 2005; Mayr et al., 2007).
89
The general miRNA hairpin structure has been used to develop short hairpin RNA
(shRNA) vectors for gene knockdown experiments or antagomir vectors to study miRNA
knockdowns (Scherr et al., 2007). These vectors show much promise for both functional
studies and for use in gene therapy (Marquez and McCaffrey, 2008). However, these
approaches use synthetic sequences and require many complicated cloning steps (Zhu et
al., 2007). Although miRNA profiling of disease states indicates that many miRNAs are
either up- or down-regulated, most studies have focused on the function of single
miRNAs or miRNA clusters. In addition, a recent report indicates that the miRNA-
mediated repression of a target mRNA is additive with respect to the number of miRNA
binding sites in the 3 ′UTR (whether they are for the same miRNA or multiple miRNAs),
while this effect is synergistic when the sites are within 40 bp (Selbach et al., 2008a).
These reports suggest that thorough functional investigations of miRNAs should analyze
the combinatorial effects of multiple miRNAs on target genes and pathways.
We developed a simple and flexible platform that can express multiple miRNAs
from a single transcript using endogenous pre-miRNA sequences. We show here that the
miRNA processing machinery can generate multiple mature miRNAs from a transcript
made of inserts that include ~60 bp surrounding the pre-miRNAs. This platform will be
invaluable as a tool to study the complex and synergistic interactions of aberrantly
expressed miRNAs in human diseases and may have applications in gene therapy.
Materials and Methods
Cell lines
90
T24, HCT116, and PC3 cells were obtained from the American Type Culture Collection.
T24 and HCT116 cells were cultured in McCoy’s 5A medium supplemented with 10%
fetal bovine serum (FBS). PC3 cells were cultured in RPMI supplemented with 10%
FBS.
Expression vector construction and transfections
Single miRNA expression vectors for miR-34a, miR-34b and miR-34c were made
by cloning ~60 bp 5 ′ and 3 ′ of the pre-miRNA into the multiple cloning site for
pcDNA3.1(+) (Invitrogen). The multiple miRNA expression vector was constructed by
sequentially cloning the miR-34b and miR-34c inserts into the miR-34a expression
vector. The primer sequences and restriction sites were
5′-miR-34a-KpnI TAATGGTACCAGGCAGGACAGGCCT,
3′-miR-34a-BamH1 TGAAGGATCCATCTCTCGCTTCATCTTC,
5′-miR-34b-EcoR1 TGTGGAATTCTCGTCCGGGAGCTGCA,
3′-miR-34b-EcoRV ATAGGATATCTCAGGCATCTTCTCTCGA,
5′-miR-34c-EcoRV TGCAGATATCCAACTTGAGACTGGAAT,
3′-miR-34c-NotI TATAGCGGCCGCTGCACAGGCAGCTCAT.
Cells were seeded in 6-well dishes so that 24 h later they were 90% confluent. Cells were
transfected using 10 µL Lipofectamine 2000 (Invitrogen) and 4 µg plasmid according to
the manufacturer’s protocol.
Reverse transcription and Taqman qPCR
91
RNA was extracted 48 h post transfection using Trizol (Invitrogen) according to
the manufacturer’s protocol. All reagents for miRNA Taqman assays were purchased
from Applied Biosystems and used according to the manufacturer’s protocol. All
reactions were done in duplicate and the primer sequences for the U6 internal control
were:
Forward – CTCGCTTCGGCAGCACA
Reverse – AACGCTTCACGAATTTGCGT
probe - FAM-AGATTAGCATGGCCCCTGCGCAA-BHQ.
Northern blot
Northern blots were done as described previously (Saito et al., 2006). Briefly, 10
µg of total RNA was loaded onto a denaturing gel and transferred to a nylon membrane.
The Star-Fire radiolabeled probes (Integrated DNA Technologies) were prepared by
incorporation of [ α-
32
P] dATP 6000 Ci/mmol according to the manufacturer’s protocol.
The probe sequences were:
miR-34a - ACAACCAGCTAAGACACTGCCA
miR-34b - CAATCAGCTAATGACACTGCC
miR-34c - CAATCAGCTAACTACACTGCCT
U6 - GCAGGGGCCATGCTAATCTTCTCTGTATCG.
Prehybridization and hybridization were carried out using ExpressHyb Hybridization
Solution (Clontech).
Cell proliferation assay
92
Cell proliferation assays were conducted in triplicate as described previously
(Robertson and Jones, 1999). Briefly, cells were transfected as described above. Cells in
each well were trypsinized 48 h after transfection and equal cell numbers plated in 10 cm
dishes with medium containing G418 (Sigma) (T24 400 µg/mL, HCT116 600 µg/mL and
PC3 750 µg/mL). Medium was changed every 3-4 days and total cell numbers were
counted after 13 days using the Z1 Coulter Particle Counter. Significance was
determined by p-value < 0.01 using a paired t-test.
Results
The key steps for the miRNA processing machinery to produce mature miRNAs
seem to be the recognition of both the hairpin structure and the junction between the
single-stranded and double-stranded region of the pri-miRNA (SD junction), implying
that the sequence requirement for mature miRNA expression from an expression vector
could be as little as a few base pairs in either direction of the pre-miRNA (Han et al.,
2006; Morlando et al., 2008). Recent studies suggest that the pri-miRNA needs to be at
least 110 nt to be efficiently processed (Han et al., 2006). Due to the small size of the
pre-miRNA genes, it is technically simple to clone many pre-miRNA genes into the same
expression vector. Therefore, it is possible to clone multiple tumor suppressor miRNAs
into one vector able to affect many different pathways involved in tumorigenesis,
creating a powerful miRNA-based cancer therapy.
As a proof of concept, we cloned the miR-34 tumor suppressor family (miR-34a,
miR-34b and miR-34c), which is regulated by p53, into a single expression vector in
order to determine whether it had a stronger inhibitory effect on cancer cell lines when
93
compared to the individual miRNAs. miR-34a is located at chromosome 1p36, while
miR-34b and miR-34c are located at chromosome 11q23, 418 bp apart (Fig. 5.1).
Previous studies have shown that restored expression of individual miRNAs from the
miR-34 family can induce apoptosis in cancer cell lines and inhibit cell growth (Raver-
Shapira et al., 2007). Because miR-34a, miR-34b, and miR-34c have similar roles when
they are activated by p53, we established a synergistic expression vector by expressing
three miRNAs (miR-34a, miR-34b, and miR-34c) from one single transcript.
To create a multiple miRNA expression vector, approximately 60 bp surrounding
the pre-miRNAs which included the SD junction for miR-34a, miR-34b, and miR-34c
were amplified by PCR and then cloned into pcDNA3.1(+) either individually or all three
together in one transcript of 600 bp (Fig. 5.1). When T24 bladder cancer cells, which
have low levels of miR-34a, miR-34b, and miR-34c, were transfected, the miR-34abc
vector yielded mature miRNAs at a level similar to each individual miRNA vector as
measured by Northern blot and RT-qPCR (Fig. 5.2A, 5.2B). The Northern blots showed
some cross-hybridization due to the high sequence similarity of the miR-34 family but
this was eliminated in the more specific RT-qPCR experiments. Therefore, we confirmed
that individual endogenous pre-miRNAs can be ligated into one expression vector that
produces multiple mature miRNAs from a single transcript.
94
Figure 5.1. Strategy to create multiple miRNA expression vector. Approximately 60 bp
surrounding pre-miR-34a, pre-miR-34b, and pre-miR-34c were PCR amplified and
sequentially cloned downstream of the CMV promoter in the pcDNA3.1(+) vector.
miR miR- -34a 34a
miR miR- -34b 34b
miR miR- -34c 34c
1p36
11q23
a
bc
pcDNA3.1 (+)
a
b c
EcoRI
KpnI EcoRV
NotI
BamH1
95
Figure 5.2. The miR-34abc vector expresses mature miR-34a, miR-34b, and miR-34c at
comparable levels to the individual miRNA expression vectors alone. Total RNA was
isolated from T24 cells 48 h after transfection with the indicated vector. A, Northern blot
was done to confirm that all 3 mature miRNAs were expressed from the miR-34abc but
not from each single vector. U6 was used as a control. There was some cross
hybridization of probes because of high sequence similarity among the miR-34 family.
B, RT-qPCR results validate the Northern blots. All reactions were done in duplicate.
There is no cross reactivity because of the increased specificity of the RT-qPCR assay.
Error bars are the SEM.
E
miR-34-
ab a b c
miR-
U6
miR-
U6
miR-
U6
qPCR of miR34a
0
20
40
60
80
100
E.V miR34abc-V miR34a-V miR34b-V miR34c-V
miR34a/U6X1000
qPCR of miR34b
0
40
80
120
160
E.V miR34abc-V miR34a-V miR34b-V miR34c-V
miR34b/U6X1000
qPCR of miR34c
0
50
100
150
200
250
E.V miR34abc-V miR34a-V miR34b-V miR34c-V
miR34c/U6X1000
96
Because the growth suppressive effects of the miR-34 family have been well
documented (Lujambio et al., 2007), we used a cell proliferation assay to examine the
effects of the miR-34abc vector when compared to each individual miR-34 vector. T24,
HCT116, and PC3 cells were transfected with the miR-34abc, miR-34a, miR-34b, miR-
34c vectors and the empty vector (Fig. 5.3). Cells were transferred to selection media 48
h after transfection and total cell numbers were counted after 13 days under G418
selection. Although there are cell line specific effects in these three cancer cell lines, the
miR-34abc vector inhibited cell proliferation more than each individual miR-34 vector.
These results indicate that although each miR-34 family member might not have a strong
effect individually, when expressed together they can have a synergistic or additive
effect.
Discussion
Our study shows for the first time that the cellular miRNA machinery can
recognize and process individual endogenous pre-miRNA sequences sequentially ligated
into a single transcript. The multiple miRNA expression vector miR-34abc generates all
three miR-34 family members at comparable levels to individual miRNA vectors and it
inhibited cell proliferation more than the individual miRNA vectors in three cell lines.
This platform can be used in any Pol II driven vector which would allow for tissue
specific or inducible miRNA expression (Marquez and McCaffrey, 2008). In addition,
the multiple miRNA expression vector should be applicable to lentiviral systems for use
in gene therapy and it may also be relevant to Pol III driven expression vectors which are
often used to generate shRNA (Marquez and McCaffrey, 2008).
97
Figure 5.3. Cell proliferation assay shows enhanced growth inhibition of the multiple
miRNA expression vector when compared to single miRNA vectors. T24, HCT116, or
PC3 cells were transferred to selection media 48 h after transfection with each vector.
Total cell numbers were counted after 13 days of selection. Error bars are the SEM, *
indicates p-value < 0.01 using a paired t-test.
T24
0
0.2
0.4
0.6
0.8
1
1.2
E.V. miR34abc-V miR34a-V miR34b-V miR34c-V
Relative cell number
PC3
0
0.2
0.4
0.6
0.8
1
1.2
E.V. miR34abc-V miR34a-V miR34b-V miR34c-V
Relative cell number
HCT116
0
0.2
0.4
0.6
0.8
1
1.2
E.V miR34abc-V miR34a-V miR34b-V miR34c-V
Relavtive cell number
∗
∗
∗
∗
∗
∗
98
There will be an experimentally optimal primary transcript length where adding
more inserts would decrease the processing efficiency and reduce mature miRNA
expression, though this would not decrease the functional and therapeutic applications for
the multiple miRNA expression vector. In addition, these results suggest that efficient
multiple shRNA processing can be achieved by simply ligating each hairpin in tandem
into a Pol II or Pol III driven vector without complicated microRNA backbone structures
or other sequence determinants.
The flexibility of the multiple miRNA expression vector makes it a critical tool
for the functional analysis of essentially any combination of miRNAs. This is critical to
determining synergistic or additive effects of physiologically relevant miRNA
dysregulation since human diseases are associated with extensive differences in the
expression of many miRNAs (Soifer et al., 2007).
For example, miR-1 and miR-133 have been implicated in cardiovascular
development and disease (Care et al., 2007; Yang et al., 2007; Zhao et al., 2007). Both
miRNAs are coexpressed as part of a pri-miRNA of at least 6 kb and are regulated by
SRF and MyoD. However, these miRNAs have opposing functions since miR-1
promotes myogenesis whereas miR-133 increases myoblast proliferation (Chen et al.,
2006). The above reports only examined each miRNA inidividually. We propose that
future studies may use the multiple miRNA expression vector to determine the
combinatorial effects of miR-1 and miR-133, thereby expanding our knowledge of the
intricate ways that miRNAs can affect cardiovascular development and disease.
Another example is the miR-17-92 cluster, which encodes six miRNAs (miR17,
miR-20a, miR-20b, miR-106a, miR-106b, miR-93), plays an essential role in the
99
development of the immune system, heart and lungs, and functions as an oncogene in
both hematologic malignancies and solid tumors (Mendell, 2008). The groups studying
this cluster have studied the entire cluster, but have not determined which individual
miRNAs or which miRNA combinations are critical for the functional effects of the miR-
17-92 cluster. The multiple miRNA expression vector would be an ideal platform with
which to perform these experiments.
Moreover, the multiple miRNA expression vector may lead to a robust class of
gene therapies that can target multiple genes or pathways in a disease-specific manner.
In cancer, many validated tumor suppressor miRNAs are found in clusters or families
which include the miR-34 family (Raver-Shapira et al., 2007), the let-7 family (Johnson
et al., 2005), and the miR-29 family (Fabbri et al., 2007). The flexibility of the multiple
miRNA expression vector would allow a gene therapy for cancer to have innumerable
miRNA combinations. These could include members of different miRNA families that,
for example, target the p53 pathway (miR-34) (Raver-Shapira et al., 2007), inhibit cell
growth (let-7) (Johnson et al., 2005), and even re-express epigenetically silenced tumor
suppressor genes (miR-29) (Fabbri et al., 2007). In conclusion, our simple technique
provides an avenue to study physiologically relevant miRNA functions and to generate
more potent and specific gene therapies.
100
Chapter 6: Summary
miRNAs were introduced to me in October 2005, and it was incredible that such a
fundamental level of gene regulation could go undiscovered until very recently. In fact,
the power that a miRNA could have in fine-tuning target gene expression was so
intriguing that I decided to focus our studies on miRNAs. I began by examining
epigenetically regulated miRNAs, but eventually I studied the functional effects of
miRNA misexpression in cancer and the potential for miRNA-based therapeutics. In the
years since my work began, several advances in the miRNA field have occurred, but
these seem to create more questions than they answer, and exceptions to general miRNA
rules for regulation, processing and function are common. This thesis examined several
aspects of miRNA molecular biology and advanced our understanding of miRNA
detection, miRNA function and miRNA therapeutics.
My first issue was a technical one. I was able to measure miRNAs using
microarrays and Northern blots, but microarrays were too costly, and Northern blots used
too much material and were low-throughput. At first, I used primer specific RT and
qPCR to detect pre-miRNAs, but I soon realized that the pre-miRNA levels did not
necessarily correlate with mature miRNA levels. Around that time, Applied Biosystems
published a paper describing stem-loop RT-qPCR that could detect mature miRNAs
(Chen et al., 2005). Unfortunately, they did not publish the sequences to detect miR-127,
which our lab had discovered was epigenetically silenced in cancer. The reviewers for
our miR-127 manuscript were insistent that we use another technique to show that miR-
127 is upregulated in cancer cells after epigenetic treatment, so I created a miR-127
101
specific stem-loop RT primer from the universal backbone that was published.
Fortunately, I succeeded and I was able to validate the Northern blot data showing miR-
127 upregulation in cancer cells treated with epigenetic therapy (Saito et al., 2006). In
fact, the stem-loop RT-PCR was more sensitive than Northern blot and made it possible
to detect miR-127 upregulation in additional cancer cell lines. Establishing RT-PCR to
detect mature miRNAs put our lab on the leading edge in miRNA research, although
shortly thereafter, Applied Biosystems made stem-loop RT-qPCR commercially available
for most miRNAs.
At that time, miRNA profiling in cancer was revealing diagnostic and prognostic
miRNA signatures, but no detailed study had been done for bladder cancer (Calin et al.,
2005; Iorio et al., 2005; Lu et al., 2005a). Because our lab had TCC samples readily
available and I would be able to validate results using RT-qPCR, I had a miRNA
microarray conducted on a pool of 9 TCC samples. The results were astounding and
showed clear and extensive miRNA misexpression in TCC. Ideally, I would have done
one microarray per matched patient sample and I would have replicated the experiment
after switching dyes, but due to the cost I did not. Instead, I used the RT-qPCR to
confirm the microarray results in 27 additional TCC patient samples. The results showed
that 5 miRNAs were downregulated and 3 miRNAs were upregulated in TCC. I did not
have established primary urothelial cells with which to transfect potential oncogenic
miRNAs, so I stably transfected the downregulated miRNAs into three TCC cell lines. I
found that the downregulated miRNAs caused a reduction in colony formation and cell
proliferation when re-expressed in the TCC cell lines. This confirmed that the extensive
102
miRNA dysregulation I found could have severe functional consequences in promoting
TCC tumorigenesis.
The miRNA that most consistently and significantly decreased cell proliferation
and colony formation when re-expressed in TCC cell lines was miR-101. At the time,
breast cancer and lung cancer miRNA profiles had shown that miR-101 was
downregulated in cancer, but no functional effects had been studied (Iorio et al., 2005;
Yanaihara et al., 2006). In Chapter 3, I used common prediction algorithms to identify
several potential targets for miR-101, but the only target that I was able to confirm by
Western blot was EZH2. This was very exciting because EZH2 is not only an important
oncogene, but is a critical mediator of development and differentiation by epigenetically
silencing Polycomb target genes (Sparmann and van Lohuizen, 2006). Therefore, it was
intriguing to relate stem cell biology with cancer biology. I confirmed that EZH2 is a
direct target of miR-101 by luciferase assays and showed that the same genes were
upregulated upon knockdown of EZH2 by miR-101 or by siRNA to EZH2. Before I was
able to submit my revised manuscript, miR-101 was shown to be downregulated in
prostate cancer due to genomic loss, which strengthened my case and validated my
results (Varambally et al., 2008). miR-101 now stands as a bona-fide tumor suppressor
that is downregulated in several solid tumors, so miR-101 downregulation may be a truly
critical aspect of tumorigenesis.
Our work showing that miR-127 was epigenetically silenced in cancer led us
(primarily Yoshimasa Saito) to examine if other miRNAs were similarly regulated in
Chapter 4. miR-126 was chosen because it was upregulated upon treatment with
epigenetic drugs in T24 cells and it was downregulated in TCC samples according to
103
miRNA microarray analysis. We found that miR-126 is located within an intron of the
EGFL7 gene and is expressed with EGFL7 in normal cells. However, in cancer cells,
both EGFL7 and miR-126 were silenced. The upregulation of miR-126 upon treatment
with epigenetic drugs did not coincide with increased EGFL7 expression, which led us to
search for alternative transcripts for EGFL7 that might produce miR-126. We found two
alternative transcripts and localized the transcription start site of one of these transcripts
to a CpG island. After detailed chromatin structural analysis, we determined that miR-
126 was not silenced by DNA hypermethylation, as was miR-127, but instead was
silenced by repressive histone modifications (Saito et al., 2009). Nevertheless, miR-126
is a well-studied tumor and metastasis suppressor and the re-expression of miR-126 by
epigenetic therapy revealed another potential benefit to using chromatin-modifying drugs
to treat cancer.
In our pursuit of potential miRNA-based therapeutics I examined the processing
of miRNAs in Chapter 5. It is clear that several miRNAs play important roles in each
disease process. However, studies have been done on only one miRNA at a time, which
neglects the physiological reality that miRNAs likely work in synergistic ways. When I
constructed miRNA expression vectors in Chapter 2, I simply ligated in ~100 bp around
the pre-miRNA sequence, and the miRNA was efficiently expressed. We felt it might be
possible to create a vector with several miRNAs in tandem that would effectively express
all of the miRNAs at once because the processing of the pri-miRNA depends primarily
on the secondary structure created by the pre-miRNA sequence. To examine this we
created expression vectors for miR-34a, miR-34b, and miR-34c, and a vector containing
all three miR-34 family members. Not only did I show that the miR-34abc vector
104
expresses all three miRNAs at similar levels to the single miRNA vectors, but I showed
that the miR-34abc vector was more effective at suppressing cell proliferation in three
different cancer cell lines. These results confirmed our hypothesis that it was possible to
generate multiple miRNAs from a single primary transcript. This innovation should be
an invaluable tool for interrogating cellular processes that have important roles for
several miRNAs. In addition, a multiple miRNA expression vector would be a promising
cancer therapeutic candidate as it could express several tumor suppressor miRNAs that
target different pathways, and as a result, deliver a synergistic inhibition of
tumorigenesis.
My work presented in this thesis is a thorough investigation of miRNA molecular
biology. I began by establishing a stem-loop RT technique to detect miRNAs and used
this technique to validate important results regarding the DNA hypermethylation-
mediated silencing of a miRNA in cancer. Additional work revealed that epigenetic
drugs can upregulate another tumor suppressor miRNA, which had been silenced by
repressive histone modifications in cancer, by re-expressing an alternative transcript of
the miRNA’s host gene. I shifted my focus to miRNA roles in cancer and, using my new
stem-loop technique, showed clear miRNA misexpression in TCC. Further experiments
confirmed that the miRNA misexpression in TCC had clear functional consequences and
contributed to tumorigenesis. In particular, a detailed study of miR-101 downregulation
in cancer revealed a novel mechanism that caused EZH2-mediated tumorigenesis. In our
search for flexible, customizable therapeutics, I showed that expressing several miRNAs
from a single transcript was possible and more beneficial than expressing a single
miRNA. Therefore, this thesis describes investigations into the technical aspects of
105
miRNA detection, miRNA misexpression in cancer, mechanisms for aberrant miRNA
silencing in cancer, and potential miRNA-based therapeutics for cancer.
106
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Abstract (if available)
Abstract
MicroRNAs (miRNAs) are small non-coding RNAs that are expressed in higher eukaryoates and have even been found in viral genomes. They usually act as endogenous repressors of target genes by either inhibiting translation, causing mRNA degradation, or by a combination of both mechanisms. More than 900 mature miRNA sequences have been identified in humans, and although this accounts for less than 2% of human genes, it is predicted that 30% of mRNAs are targeted by miRNAs. miRNAs play critical roles in most cellular processes including development, differentiation, and the homeostasis of both a cell and an organism. Moreover, many disease states, including cancer, occur or are sustained by miRNA dysregulation. Here we will review the latest reports of miRNA involvement and aberrant expression in human disease with an emphasis on cancer.
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Friedman, Jeffrey Mathew
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The role of microRNAs in cancer
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Biochemistry and Molecular Biology
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2009-08
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