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MicroRNAs in the Regulation of Cellular Stress Responses
by
Haoran Li
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy
Laboratory Medicine and Pathobiology University of Toronto
© Copyright by Haoran Li 2015
ii
MicroRNAs in the Regulation of Cellular Stress Responses
Haoran Li
Doctor of Philosophy
Laboratory Medicine and Pathobiology
University of Toronto
2015
Abstract
MicroRNAs are key regulators of cellular functions at post-transcriptional level. There is an
emerging concept that microRNAs are involved in the regulation of how cells respond to
changes in environment and stress conditions. Understanding the consequence of microRNA
regulatory network has the potential to answer a multitude of fundamental questions.
Dysregulation of these processes is associated with cancer development and drug resistance. In
this dissertation, four studies are presented. The first study demonstrated that microRNA-17
targets both oncogene MDM2 and tumor suppressor gene PTEN: it suppresses glioblastoma
tumor cell proliferation in favorable condition. However, when challenged by starvation or
chemotherapy, it induced angiogenesis and the generation of tumor stem-like cells, and helping
tumor cells survive in metabolic stress. The second study revealed the role of microRNA-17 in
the regulation of chemotherapy sensitivity. By analyzing tissue samples from colorectal cancer
patients, we found that microRNA-17 serves as a predictive factor of chemotherapy and
prognostic factor of overall survival. Overexpression of microRNA-17 in colorectal cancer cells
increased drug resistance and cell motility. The third study focused on the impact of microRNA
on antitumor immune response. We found vigorous anti-melanoma immune response in
microRNA-17 transgenic mice, which is characterized by CD8+ T lymphocytes infiltration. We
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further demonstrated the potential role of microRNA in the coordination of interaction between
tumor cells and microenvironment. The fourth study examined the function of microRNA in
tissue regeneration. We found an enhanced wound healing process in anti-microRNA-378
transgenic mice that have otherwise normal phenotype. Knocking down microRNA increased the
expression of its targets Vimentin and Integrin beta-3, helping wound healing. Conjugated gold
nanoparticle treatment delivered antisense oligos to the wound area and achieved therapeutic
effect. Taken together, these studies illustrate the multiplicity of microRNA in the coordination
of cellular stress responses.
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Acknowledgments
I would like to express my sincere gratitude to my supervisor—Dr. Burton B. Yang who has
provided me tremendous opportunities as well as challenges through various interesting projects.
His steadfast support of this project was greatly needed and deeply appreciated, and my research
career would never have started with such an enriching experience without Dr. Yang. I am also
thankful to my committee member Dr. Tianru Jin, Dr. David Spaner and Dr. Michael V. Sefton
for your keen advice, constructive comments and guidance throughout the years. My external
reviewer—Dr. Stephen Sims used to give me the best advice on my PhD journey. I sincerely
thank him for such direct, simple and useful suggestion.
During this work I have received great deal of support from many knowledgeable and skillful
people for whom I owe great gratitude. I would also like to acknowledge all the past and present
members of Dr. Yang’s laboratory. Some of them have already left our lab, and I will not forget
how much joy you brought to me: Dr. Samantha S. Shan, Dr. Zhaoqun Deng, Dr. Fengqiong Liu,
Dr. Xiangling Yang, Dr. Zina Rutman, Dr. Ling Fang, Dr. Tatiana Shatseva, Chunwei Jiao,
Tanvi Mehta, Li Lin, Leslie Chang, Diane Liu and Cindy Ma. Some of them are still in our lab
and I wish you all the best: Dr. William W. Du, Anna Khorshidi, Shaan Gupta, Yan Zeng, Lucy
Yang, Xiangmin Li, Weining Yang and Bing Yang. I also would like to thank Dr. LekunFang for
his collaboration on Chapter 3. His excellent work on clinical sample analysis contributes
successful publication of the paper.
I owe my deepest gratitude to Dr. Maureen Trudeau, Dr. Pak-Cheung Chan and Dr. Edward
Chow. They opened the window to let me explore the world outside and encouraged me to
follow my dream no matter what may come.
I would like to thank my family for their continued support and love. My parents give me their
whole heart and ask for nothing back. My cousin—Dr. Hongfei Wang has always been my role
model. His sage advice and insightful criticism help me in innumerable ways. Last but not the
least, my heart full of thanks go to my life partner and soul mate—Dr. Fang Zhu. Finding and
marrying you is the most successful project I have ever accomplished in my life. Your love has
been my inspiration and motivation. I will go on being the person you expect me to be.
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Table of Contents
Abstract……………………………………………………………………………………………ii
Acknowledgments.......................................................................................................................... iv
Table of Contents .............................................................................................................................v
List of Abbreviations ..................................................................................................................... xi
List of Tables .................................................................................................................................xv
List of Figures .............................................................................................................................. xvi
Chapter 1 Introduction and Literature Review ..............................................................................1
1 MicroRNA Regulated Stress Responses in Cancer ....................................................................2
1.1 Abstract ................................................................................................................................2
1.2 Introduction ..........................................................................................................................2
1.3 MicroRNA and metabolic stress in cancer ...........................................................................6
1.3.1 MicroRNA and oxidative stress ...............................................................................6
1.3.2 MicroRNA and starvation ........................................................................................9
1.3.3 MicroRNA and autophagy .....................................................................................11
1.4 MicroRNA and tumor microenvironment ..........................................................................13
1.4.1 MicroRNA and immune response .........................................................................13
1.4.2 MicroRNA and epithelial mesenchymal transition................................................16
1.5 MicroRNA regulation of chemotherapeutic drug resistance .............................................17
1.5.1 MicroRNA as a key regulator in cancer ................................................................18
1.5.2 MicroRNA and chemotherapy ...............................................................................19
1.5.3 MicroRNAs regulate drug resistance-related proteins ...........................................22
1.5.4 MicroRNAs alter drug targets ................................................................................24
1.5.5 MicroRNAs change drug concentration ................................................................25
1.5.6 MicroRNAs influence therapeutic induced cell death ...........................................26
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1.5.7 MicroRNAs promote angiogenesis ........................................................................27
1.5.8 MicroRNAs in the generation of tumor stem cells ................................................28
1.6 MicroRNA and Radiotherapy ............................................................................................31
1.6.1 Response to damaging radicals ..............................................................................31
1.6.2 Regulation of DNA histone modification ..............................................................31
1.6.3 Regulation of cell cycle .........................................................................................32
1.6.4 Regulation of repair process ..................................................................................32
1.7 Therapeutic influence and future perspective ....................................................................32
Chapter 2 MicroRNAs Regulate Metabolic Stress Response ......................................................34
2 Stress Response of Glioblastoma Cells Mediated by MiR-17-5p Targeting PTEN and the
Passenger Strand MiR-17-3p Targeting MDM2 .......................................................................35
2.1 Abstract ..............................................................................................................................35
2.2 Introduction ........................................................................................................................35
2.3 Materials and Methods .......................................................................................................37
2.3.1 Cell cultures ...........................................................................................................37
2.3.2 Construct generation ..............................................................................................37
2.3.3 RNA analysis .........................................................................................................39
2.3.4 Cell function test ....................................................................................................39
2.3.5 Cell migration assay ...............................................................................................39
2.3.6 Tube formation assay .............................................................................................40
2.3.7 Western blot analysis .............................................................................................40
2.3.8 Flow cytometry ......................................................................................................40
2.3.9 Colony formation and self-renewal assay ..............................................................40
2.3.10 MTT assay .............................................................................................................41
2.3.11 Luciferase activity assay ........................................................................................41
2.3.12 Statistical analysis ..................................................................................................41
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2.4 Results ................................................................................................................................41
2.4.1 MiR-17 prolongs glioblastoma cell survival and increases cell motility ...............41
2.4.2 MiR-17 regulates distinct response to starvation and chemotherapy ....................45
2.4.3 MiR-17 induces HIF-1α activation in response to stress by targeting PTEN ........48
2.4.4 MiR-17 promotes the generation of tumor stem-like cells ....................................48
2.4.5 MiR-17 reduces glioblastoma cell proliferation ....................................................55
2.4.6 MiR-17-3p targets MDM2 in glioblastoma cells ...................................................55
2.5 Discussion ..........................................................................................................................59
Chapter 3 MicroRNA Regulates Chemotherapeutic Drug Resistance ........................................63
3 MicroRNA-17-5p Promotes Chemotherapeutic Drug Resistance of Colorectal Cancer by
Regulating PTEN ......................................................................................................................64
3.1 Abstract ..............................................................................................................................64
3.2 Introduction ........................................................................................................................65
3.3 Materials and Methods .......................................................................................................66
3.3.1 Patients ...................................................................................................................66
3.3.2 Microarray..............................................................................................................66
3.3.3 RNA isolation and quantification of miRNA by qRT-PCR ..................................68
3.3.4 Tissue Microarrays.................................................................................................68
3.3.5 In situ hybridization and Immunohistochemistry ..................................................68
3.3.6 Cell cultures ...........................................................................................................69
3.3.7 Construct generation ..............................................................................................69
3.3.8 Real-time PCR analysis .........................................................................................70
3.3.9 Cell activity tests ....................................................................................................70
3.3.10 Western blot ...........................................................................................................71
3.3.11 Flow cytometry ......................................................................................................71
3.3.12 Luciferase activity assay ........................................................................................71
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3.4 Results ................................................................................................................................72
3.4.1 Expression of miR-17 in the course of colorectal cancer chemoresistance ...........72
3.4.2 MiR-17-5p induces drug resistance in colorectal cancer cells...............................77
3.4.3 PTEN as a target of miR-17-5p in colorectal cancer cells .....................................77
3.4.4 Relationship between miR-17-5p expression and overall survival of CRC patients80
3.4.5 MiR-17-5p promotes colorectal cancer cell migration ..........................................84
3.5 Discussion ..........................................................................................................................89
Chapter 4 MicroRNA Regulates Immune Response ...................................................................93
4 MicroRNA-17 Inhibits Tumor Growth by Stimulating T-cell Mediated Host Immune
Response ...................................................................................................................................94
4.1 Abstract ..............................................................................................................................94
4.2 Introduction ........................................................................................................................94
4.3 Material and Methods ........................................................................................................96
4.3.2 Generation of transgenic mice ...............................................................................96
4.3.3 Tumor formation assay ..........................................................................................96
4.3.4 Flow cytometry ......................................................................................................96
4.3.5 Immunohistochemistry ..........................................................................................97
4.3.6 Western blotting .....................................................................................................97
4.3.7 Luciferase assay .....................................................................................................97
4.3.8 Cell proliferation assay ..........................................................................................97
4.3.9 Statistical analysis ..................................................................................................98
4.4 Results ................................................................................................................................98
4.4.1 CD8+ cells increased in tumor-bearing miR-17 transgenic mice ..........................98
4.4.2 Tumor invasion was inhibited in miR-17 transgenic mice ..................................104
4.4.3 MiR-17 targets STAT3 in melanoma tumor microenvironment .........................104
4.4.4 MiR-17 promotes proliferation of Jurkat cells co-cultured with B16 cells .........108
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4.5 Discussion ........................................................................................................................111
Chapter 5 MicroRNA Regulates Wound Healing......................................................................115
5 Anti-microRNA-378a Enhances Wound Healing Process by Up-regulating Integrin beta-3
and Vimentin ...........................................................................................................................116
5.1 Abstract ............................................................................................................................116
5.2 Introduction ......................................................................................................................117
5.3 Materials and Methods .....................................................................................................118
5.3.1 Construct generation ............................................................................................118
5.3.2 Generation of transgenic mice and wound healing experiment ...........................119
5.3.3 Immuno-reaction assay ........................................................................................122
5.3.4 Cell culture ...........................................................................................................123
5.3.5 Confocal microscopy ...........................................................................................123
5.3.6 Cell adhesion test .................................................................................................123
5.3.7 Cell migration test ................................................................................................123
5.3.8 Cell differentiation assay .....................................................................................124
5.3.9 Oil-Red-O staining ...............................................................................................124
5.3.10 Real-time PCR .....................................................................................................124
5.3.11 Tube formation assay ...........................................................................................125
5.3.12 Luciferase activity assay ......................................................................................125
5.3.13 Nanoparticle synthesis and delivery ....................................................................125
5.3.14 Statistical analysis ................................................................................................125
5.4 Results ..............................................................................................................................126
5.4.1 Enhanced wound healing in miR-Pirate378a transgenic mice ............................126
5.4.2 MiR-Pirate378a accelerates fibroblasts migration, differentiation and tube
formation ..............................................................................................................129
5.4.3 MiR-Pirate378a counteracts miR-378a’s function by up-regulating vimentin
levels ....................................................................................................................133
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5.4.4 Integrin beta-3 is a target of miR-378a-5p ...........................................................136
5.4.5 MiR-Pirate378a enhanced wound healing ...........................................................140
5.5 Discussion ........................................................................................................................145
Chapter 6 General Discussion ....................................................................................................150
6 MicroRNA-regulated Stress Responses and Its Clinical Implications ...................................151
6.1 MicroRNA-regulated metabolic stress responses in glioblastoma ..................................151
6.2 MicroRNA-regulated drug resistance in colorectal cancer ..............................................154
6.3 MicroRNAs regulate inflammatory responses and tissue regeneration ...........................157
References ....................................................................................................................................161
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List of Abbreviations
1,25(OH)(2)D(3) = 1alpha,25-dihydroxyvitamin D(3)
5-FU = fluorouracil
3’UTR = 3’ untranslated region
5’UTR = 5’ untranslated region
ABC = ATP-binding cassette
AGO2 = argonaute 2
AICD = activation-induced cell death
AMOs = anti-miRNA oligonucleotides
BCRP = breast cancer-resistant protein
BCS = bovine calf serum
BE = bystander effect
BRCA1 = breast cancer 1early onset
BrdU = bromodeoxyuridine
CAT-1 = cationic amino acid transporter 1
Cdk = cyclin-dependent kinase
CMV = cytomegalovirus
COX10 = cytochrome c oxidase assembly protein
CR = complete response
CRC = colorectal cancer
CTL = cytotoxic T cells
Cx = connexins
CYP = cytochrome P450
DEDD = death effector domain-containing DNA binding protein
DGCR8 = Di George syndrome critical region 8
DMEM = Dulbecco’s modified Eagle’s medium
DMSO = dimethyl sulfoxide
DSBs = double stranded breaks
ds-RNA = double-stranded RNA
E-cadherin = epithelial cadherin
ECM = extracellular matrix
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EGF = epidermal growth factor
EGFR = epidermal growth factor receptor
EMT = epithelio-mesenchymal transition
EOC = epithelial ovarian cancer
ER = estrogen receptor
FBS = fetal bovine serum
FGF = fibroblast growth factor
GFP = green fluorescent protein
GJIC = gap junction intercellular communications
GNP = gold nanoparticle
GSC = glioblastoma stem-like cells
H&E = hematoxylin and eosin
HIF1 = hypoxia inducible factor-1α
HR = homologous recombination
HRP = horseradish peroxidase
IC50 = half maximal inhibitory concentration
IGF1 = insulin-like growth factor-1 receptor
IHC = immunohistochemistry
IMDM = in Iscove's Modified Dulbecco's Media
ISCU = iron-sulfur cluster scaffold homolog
ISH = in situ hybridization
LATS2 = large tumor suppressor homology 2
LNA = locked nucleic acids
Luc = luciferase reporter vector
Luc-mut = luciferase reporter the mutants
MAPK = mitogen-activated protein kinase
MDM2 = murine double minute 2
MDR = multiple drug resistance
MDSCs = myeloid-derived suppressor cells
miRNA = microRNA
mirsupps = tumor suppressor miRNAs
MRP1 = MDR-associated protein
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NHEJ = non-homologous end joining
OD = optical density
oncomirs = oncogenic miRNAs
PAGE = polyacrylamide gel electrophoresis
PBs = processing bodies
PBS = phosphate-buffered saline
PCR = polymerase chain reaction
PD = progressive disease
PFA = paraformaldehyde
PI3K = phosphatidylinositol-3 kinase
PKC = protein kinase C
pol II = polymerase II
PR = partial response
Pre-miRNAs = precursor miRNAs
Pri-miRNAs = primary miRNAs
PTEN = phosphatase and tension homolog
RCS = reactive chloride species
RECIST = response evaluation criteria in solid tumors
RISC = RNA induced silencing complex
RNS = reactive nitrogen species
ROS = reactive oxygen species
RSS = reactive sulfur species
RTQPCR = real-time quantitative polymerase chain reaction
SCLC = small cell lung cancer
SD = stable disease
SDS-PAGE = sodium dodecyl sulfate- polyacrylamide gel electrophoresis
SFM = serum-free medium
SIDT1 = systemic RNA interference-defective-1 transmembrane family member 1
siRNA = small interfering RNA
SP = side population
SQSTM1 = sequestosome 1
STAT3 = signal transducer and activator of transcription 3
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TGF = transforming growth factor
TGF-β = transforming growth factor-β
TICs = tumor initiating cells
TMA = tissue microarray
TRBP = transactivating response RNA-binding protein
TSCs = tumor stem cells
VEGF = vascular endothelial growth factor
VEGFA = vascular endothelial growth factor A
VHL = Von Hippel-Lindau
XPO5 = exportin-5
YB-1 = Y-box binding protein-1
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List of Tables
Table 1 The miRNAs in the regulation of MDR-1 ....................................................................... 23
Table 2 Correlation between expression of miR-17 and clinicopathological features in 295 cases
of colorectal cancer ....................................................................................................................... 67
Table 3 Univariate and multivariate analysis of different prognostic parameters in 81 colorectal
cancer patients with chemotherapy ............................................................................................... 76
Table 4 Univariate and multivariate analysis of different prognostic parameters in 295 patients
with colorectal cancer ................................................................................................................... 86
Table 5 Univariate and multivariate analysis of different prognostic parameters in 214 colorectal
cancer patients without chemotherapy .......................................................................................... 88
Table 6 Primer sequences used in the study ............................................................................... 121
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List of Figures
Figure 1.1 The mechanisms of microRNA biogenesis and regulation of gene expression ............ 3
Figure 1.2 Hallmarks of microRNA history ................................................................................... 5
Figure 1.3 MicroRNA-200 regulates oxidative stress responses .................................................... 8
Figure 1.4 MicroRNA-17 regulates starvation responses ............................................................. 10
Figure 1.5 MicroRNA regulates antitumor immune reactions ..................................................... 14
Figure 1.6 The role of microRNA in cancer ................................................................................. 20
Figure 1.7 MicroRNAs regulate chemotherapeutic drug resistance ............................................. 30
Figure 2.1 The primers’ sequence used in luciferase assay .......................................................... 38
Figure 2.2 MiR-17 enhances glioblastoma cell survival. ............................................................. 43
Figure 2.3 MiR-17 enhances glioblastoma cell survival, migration, and invasion....................... 44
Figure 2.4 MiR-17 stimulates angiogenesis upon starvation ........................................................ 46
Figure 2.5 MiR-17 regulates distinct response to starvation and chemotherapy .......................... 47
Figure 2.6 PTEN is one of miR-17’s targets................................................................................. 49
Figure 2.7 MiR-17 induces HIF-1α activation in response to stress by targeting PTEN ............. 50
Figure 2.8 MiR-17 promotes the generation of tumor stem-like cells .......................................... 52
Figure 2.9 MiR-17 promotes self-renewal and treatment resistance of tumor cells ..................... 53
Figure 2.10 Overexpression of miR-17 increases CD133 level ................................................... 54
Figure 2.11 HIF-1α overexpression increases cell survival and tumor stem-like cell generation 56
Figure 2.12 Expression of miR-17 reduces glioblastoma cell proliferation. ................................ 57
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Figure 2.13 MiR-17-5p and miR-17-3p target MDM2. ................................................................ 58
Figure 2.14 Confirmation of miR-17’s functions by silencing and rescue assays. ....................... 60
Figure 3.1 Comparison of miRNA expression in six CRC patients ............................................. 73
Figure 3.2 Validation of microRNA-17’s expression in fifteen CRC patients ............................. 74
Figure 3.3 Expression of miR-17 is associated with poor survival in colorectal cancer. ............. 75
Figure 3.4 MiR-17 overexpressing construct and its functions .................................................... 78
Figure 3.5 MiR-17 induces multiple drug resistance in colorectal adenocarcinoma cells. .......... 79
Figure 3.6 PTEN is targeted by miR-17-5p in colorectal adenocarcinoma cells .......................... 81
Figure 3.7 PTEN expression is negatively associated with miR-17-5 level in colorectal tissue .. 82
Figure 3.8 MiR-17-5p promotes multiple drug resistance by regulating PTEN ........................... 83
Figure 3.9 Overexpression of miR-17-5p is associated with tumor metastasis and poor survival 85
Figure 3.10 Overexpression of miR-17 increases cancer cell invasiveness ................................. 87
Figure 3.11 PTEN overexpression reversed miR-17’s function ................................................... 90
Figure 4.1 CD45+ cells in non-tumor-bearing mice ................................................................... 100
Figure 4.2 CD8+ expression in non-tumor bearing mice ........................................................... 101
Figure 4.3 CD45+ expression cells in tumor-bearing mice ........................................................ 102
Figure 4.4 CD8+ expression cell in tumor-bearing mice ............................................................ 103
Figure 4.5 Immunohistochemistry analysis in B16 grafted tumor and host spleen .................... 105
Figure 4.6 MiR-17 increases CD8+ expression by targeting STAT3 ......................................... 107
Figure 4.7 B16 and Jurkat cell co-culture assay ......................................................................... 109
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Figure 4.8 Cell cycle analysis in Jurkat cells with or without B16 co-culture ........................... 110
Figure 5.1 The construct structure of anti-microRNA-378a/miR-Pirate-378a ........................... 120
Figure 5.2 Enhanced wound healing in miR-Pirate378a transgenic mice .................................. 127
Figure 5.3 Wound healing pictures taken from mice .................................................................. 128
Figure 5.4 MiR-Pirate378a increases CD34 expression ............................................................. 130
Figure 5.5 Expression of miR-Pirate378a increases cell migration and adhesion ...................... 131
Figure 5.6 Typical photos of cell function test ........................................................................... 132
Figure 5.7 MiR-378a-5p targets vimentin .................................................................................. 134
Figure 5.8 Typical photos of Vimentin knocking down assay ................................................... 135
Figure 5.9 Overexpression of Vimentin increases cell motility and differentiation ................... 137
Figure 5.10 Typical photos of Vimentin overexpression assay .................................................. 138
Figure 5.11 MiR-378a-5p targets Integrin beta-3 ....................................................................... 139
Figure 5.12 Integrin beta-3 knocking down and overexpression assay ...................................... 141
Figure 5.13 Typical photos of Integrin beta-3 knocking down test ............................................ 142
Figure 5.14 MiR-Pirate378a increases expression of Vimentin and Integrin beta-3 .................. 143
Figure 5.15 Nanoparticle treatment ............................................................................................ 144
Figure 5.16 Typical photos of gold nanoparticle treatment ........................................................ 146
Figure 5.17 Anti-microRNA-378 enhances wound healing by rescuing Vimentin and Integrin
beta-3........................................................................................................................................... 149
Figure 6.1 MicroRNA-17 coordinates stress responses in cancer .............................................. 152
Figure 6.2 The multiplicity of microRNA targeted pathways .................................................... 156
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Figure 6.3 The mechanism of gold nanoparticle based oligonucleotide delivery ...................... 159
1
Chapter 1
Introduction and Literature Review
(A version of this chapter section is published in Acta Pharmacologica Sinica(1))
2
1 MicroRNA Regulated Stress Responses in Cancer
1.1 Abstract
Cancer cells often face unique challenges as they attempt to thrive in the human body, as a result
of internal or external stresses. They are often faced with two options—adapt or perish. These
responses are usually the manifestation of complex molecular signaling cascades, which are
attempting to maintain cellular homeostasis despite the increasingly harsh environment. Their
signaling cascades are fine-tuned through constant monitoring and regulation of genes,
transcripts and proteins. As research elucidates the participants in these complex networks,
microRNAs are emerging as key players in the regulation of stress responses in cancer;
highlighting a potential for the exploitation of these oligonucleotides for therapeutic use. There
are thousands of microRNAs, each regulating thousands of protein’s expression levels, thus this
review serves to elucidate the nature of microRNAs through selected examples, and to suggest
possible therapeutic opportunities.
1.2 Introduction
MicroRNAs (miRNAs) are single stranded, short sequence, non-coding RNAs that are broadly
conserved across species. So far, more than 1400 miRNAs have been identified in human
genome (2). Most miRNA loci are found within the introns of protein coding genes, while they
could be also embedded in exonic regions or separate transcriptional units (3). In most cases,
miRNA genes are transcribed by RNA polymerase II (pol II) in the nucleus, where they are then
processed by the complex containing RNase III enzyme Drosha and co-factor Di George
syndrome critical region 8 (DGCR8) (Figure 1.1). Drosha-DGCR8 complex trims the long
primary miRNAs (Pri-miRNAs) into 70-100 nt long precursor miRNAs (Pre-miRNAs), which
are subsequently exported out of the nucleus by exportin-5 (XPO5). In the cytoplasm, pre-
miRNAs hairpins are cleaved by a protein complex including RNase III-type enzyme Dicer and
the human immunodeficiency virus transactivating response RNA-binding protein (TRBP),
giving rise to double-stranded RNA (ds-RNA) approximately 22nt long. This dsRNA includes
two miRNA strands, known as miRNA-3p and miRNA-5p, in both arms of pre-miRNA.
3
Figure 1.1 The mechanisms of microRNA biogenesis and regulation of gene expression
MicroRNAs (miRNAs) are single stranded, short sequence, non-coding RNAs that are broadly
conserved across species. In most cases, miRNA genes are transcribed by RNA polymerase II
(pol II) in the nucleus, they are subsequently exported out of the nucleus by exportin-5. In the
cytoplasm, pre-miRNAs hairpins are cleaved by Dicer, giving rise to the double-stranded RNA.
The dsRNA includes two miRNA strands, known as miRNA-3p and miRNA-5p. It was used to
be thought that one strand is a mature miRNA and the other strand is subject to degradation, yet
the current evidence suggests that either arm can be selected as a mature miRNA in a tissue-
specific context. The mature single-stranded miRNAs are incorporated into the RNA induced
silencing complex (RISC), which is responsible for inducing posttranscriptional gene silencing
by base-pairing to partially complementary sequence motifs within 3’ untranslated regions (3’-
UTR) of target mRNAs. As such, they are able to cleave the mRNA directly, and enhancing
mRNA degradation or repressing its translation. Some studies also showed that RISC activated
mRNA translation by binding to the 5‘-UTR of target mRNA.
4
It is used to be thought that one strand is a mature miRNA and the other strand (the passenger
strand) is normally subject to degradation, yet the current evidence suggests that either arm can
be selected as a mature miRNA in a tissue-specific context (4). The mature single-stranded
miRNAs are incorporated into the RNA induced silencing complex (RISC), which contains core
components such as argonaute 2 (AGO2), Dicer and TRBP (5). RISC is responsible for inducing
posttranscriptional gene silencing by base-pairing to partially complementary sequence motifs
within 3’ untranslated regions (3’-UTR) of target mRNAs. As such, they are able to cleave the
mRNA directly, enhancing mRNA degradation or repressing its translation. Some studies also
showed that RISC activated mRNA translation by binding to the 5'-UTR of target mRNA (6).
More recently, some miRNAs have been found to bind decoy mRNAs in a RISC-independent
way (7).
The first miRNA, lin-4, was identified in 1993 by Victor Ambros and his colleagues in a study of
C. elegans development (8) (Figure 1.2). However, it was not until 1998 that the mechanism of
RNA interference was unprecedentedly illuminated by Craig C. Mello and Andrew Fire (9). In
this work, they found that double-stranded RNA was surprisingly more effective at producing
interference than either single-stranded mRNA or antisense RNA, and thereby they named this
phenomenon as RNA interference. This study is an important contribution to understanding how
the miRNA-RISC complex functions to inhibit gene expression. Soon after this study the RNA
interference (RNAi) pathways were found to play critical roles in development, cell proliferation,
differentiation and stress response. In 2000, the second, small regulatory RNA let-7 was
identified as a developmental regulator, intriguing explosive research interest in C. elegans,
plants and animals (10). More small expressed RNAs were found in 2001 and then the term
“microRNA” (miRNA) were coined (11). The roles of miRNAs in the development of human
cancer was not established until 2002, when Croce and his colleagues found that both miR-15
and miR-16 are located in chromosome 13q14, and they are down-regulated in approximately
68% of chronic lymphocytic leukemia patients (12). Over the last decade, many miRNAs have
been implicated in human cancer development. Interestingly, most their genes are located near
cancer susceptibility loci. Mapping of miRNA genes provides specific clue for the possible roles
of miRNA in tumorigenesis events (13).
5
Figure 1.2 Hallmarks of microRNA history
A brief history of microRNA research milestones
6
The function of miRNAs requires sequence specific match to their target mRNA. Majority of
match pairs are composed of 7-8 nucleotides in miRNA that are perfectly complementary to 3’-
UTR segments of target mRNA (14). The mechanistic model of “seed” pairing leads to the
possibility that miRNAs are influencing the expression or evolution of nearly all mammalian
mRNAs (15). It is well established that miRNAs are broadly involved in cancer cell
proliferation, tumorigenesis, metastasis, angiogenesis and drug resistance. Based on the influence
on cancer cell growth, they can be categorized into oncogenic or tumor-suppressive miRNA.
Oncogenic miRNAs (oncomirs) induce cancer cell proliferation by down-regulating expression
of tumor suppressor genes, whereas tumor suppressor miRNAs (mirsupps) inhibit cancer
progression by targeting oncogenes post-transcriptionally (1). However, this dichotomous
approach is challenged by growing evidence. A particular miRNA could be increased in some
cancers as an oncomir, but downregulated in other cancers. For example, miR-17 was found as a
mirsupps in breast cancer while it promotes development of hepatocellular carcinoma (16).
Moreover, as a single miRNA is able to target a host of mRNAs, studying miRNA’s function is
complicated by the enormous genetic diversity observed in cancers. Hence, miRNAs and their
related network more likely have a fine-tuning effect in cellular homeostasis.
1.3 MicroRNA and metabolic stress in cancer
The growth of cancer requires an increased supply of nutrition and oxygen, which permits rapid
expansion of the tumor. To adapt to the accelerated metabolic rate, cancer cells develop unique
genetic alterations that control cell proliferation. Perhaps one of the most significant adaptations
is Warburg effect, which is named after Dr. Otto Warburg. His discovered that cancer cells
harbor a highly glycolytic rate which increases glucose consumption and lactate production
regardless of the concentration of oxygen; this gives rise to a new era where detection and
treatment of cancer could be focused on its unique metabolic signature (17). Thus some
researchers suggest that cancer as a whole is a metabolic disease.
1.3.1 MicroRNA and oxidative stress
As a result of the Warburg effect and anaerobic respiration, several potential toxic compounds
are generated. These include reactive oxygen species (ROS), reactive nitrogen species (RNS),
reactive sulfur species (RSS) and reactive chloride species (RCS) (18). Of these, ROS are
7
produced most abundantly. These reactive species can cause damage to DNA structure and to its
repair mechanism. They can also initiate lipid peroxidation and increase permeability of the cell
membrane. Elevated concentration of ROS has been frequently found in cancer cells. Oxidative
stress affects several biochemical pathways, such as PTEN/PI3K/Akt and MAPK/ERK. Notably,
miRNAs also actively respond to intracellular change of ROS. It was first identified that ROS
accumulation in small cell lung cancer (SCLC) cells was linked with miR-17-92 (19).
Overexpression of miR-17-92 cluster counterbalances ROS generation in SCLC cells. It was
suggested that miR-17-92 plays a role in fine-tuning the effects of ROS-induced DNA damage,
maintaining genomic stability (19). Several ROS-related miRNAs have been described thereafter
(18). MiR-200 family—comprising miR-141, 200a, 200b, 200c and 429—has been shown as key
regulators of oxidative stress (20) (Figure 1.3). These miRNAs control cellular motility by
mediating epithelio-mesenchymal transition (EMT), and they also influent cellular stemness and
apoptosis by targeting p38α MAPK. High expression of miR-200s is often found in epithelial
ovarian cancer (EOC) and is correlated with a better outcome and early-stage disease (21). Based
on the level of miR-200, EOC can be stratified as “oxidative stress” and “fibrosis” signature
(22). “Stress” patients have a better response to chemotherapy and longer survival, compared to
“fibrosis” patients. There was an enhanced expression of miR-141 and miR-200a in ovarian
cancer cells exposed to oxidative stress, leading to down-regulation of p38α and increased ROS
production. The up-regulation of ROS level, in turn, augment expression of miR-200 family,
which together sensitize tumor cells to cisplatin or carboplatin treatment (23). This study
implicated that the signature of miR-200s can be used as a predictive biomarker for
chemotherapy response. Restoration of miR-200s level may be a new therapeutic approach in
drug resistant EOC patients.
Increased level of glycolysis and anaerobic respiration prevent tumor cells from entering
senescence and stimulate vascularization. Several studies have demonstrated the importance of
miRNAs in regulating cellular response to hypoxia. Most of these hypoxia-responsive miRNAs
are found to be associated with the hypoxia-inducible factor 1 (HIF-1α) signaling pathway. MiR-
210 is a robust target of HIF-1α, and its overexpression has been linked to adverse prognosis in
breast cancer and hepatocellular carcinomas (24). It is indicated that miR-210 activates the
generation of ROS, by targeting ISCU (iron-sulfur cluster scaffold homolog) and COX10
(cytochrome c oxidase assembly protein), two key factors of the mitochondrial electron transport
8
Figure 1.3 MicroRNA-200 regulates oxidative stress responses
Increased expression of miR-200 suppresses ROS inhibitor p38-alpha and EMT inducer ZEB,
which in turn regulates miR-200 in a feedback loop.
9
chain. It thus inhibits mitochondrial function and upregulates the level of glycolysis (25). ISCU,
which is also a target of HIF-1α, is a cofactor for enzymes involved in the TCA cycle and iron
metabolism. Through interfering with HIF-1α at multiple levels, miR-210 enhances cancer cell
survival in hypoxic conditions, but also makes cells more sensitive to glycolysis inhibitors (26).
1.3.2 MicroRNA and starvation
It is well known that tumor cells are perpetually nutritionally hungry. In response to nutritional
starvation, varied changes will occur at the genetic and epigenetic level to favor cell survival. It
was first found that miRNA was involved in starvation-induced alterations in human
hepatocarcinoma cells (27). When cells are growing under unstressed condition, miR-122 binds
to the 3’-UTR of cationic amino acid transporter 1 (CAT-1) mRNA. Nevertheless, this pairing
was reversed in cells subjected to starvation, by relocalization of CAT-1 mRNA from the
cytoplasmic processing bodies (PBs). As the scaffolding center of miRNA function, the activity
of PBs showed an on- and off- switch in a context-dependent manner. In a stressed state, such as
amino acid deprivation, 3’-UTR of CAT-1 binds to HuR, an ARE binding protein, relieving
CAT-1 from miR-122 suppression in PBs and recruiting it to polysomes for translation (27). This
model suggests a way that RNA-binding protein modulates the activity of miRNAs in tumor
cells under stressed conditions. Through regulation in the promoter region, miRNA activation is
closely affected by intracellular environment. It is found that glucose depletion-induced
oxidative stress inhibits histone deacetylation in the miR-466h-5p promoter region, which actives
miR-466h-5p, miR-669c and Sfmbt2 in a time-dependent manner (28). The author suggested that
miR-297-669 cluster, including miR-466h-5p, might play a role in cellular detoxification and
drug-induced injuries. During oncogenic transformation, induction of the miR-297-669 cluster is
inhibited by the loss of the oxidative stress defense mechanism (28).
Glioblastoma is characterized by aggressive growth pattern and the frequent cellular apoptosis,
making it an optimal model to test the nutrition-dependent functions of microRNA. In cultured
U87 cells deprived of serum, the level of miR-17 increased remarkably (Figure 1.4). By targeting
PTEN and stabilizing HIF-1α, miR-17 reduced cellular metabolic rate under unfavorable
conditions in order to protect them from starvation. Notably, miR-17 also inhibited tumor cell
proliferation under unstressed conditions through targeting MDM2, an oncogene often
overexpressed in cancer cells (29).
10
Figure 1.4 MicroRNA-17 regulates starvation responses
MicroRNA-17 increases expression under starved condition, which further facilitates tumor
survival by targeting MDM2 and PTEN.
11
Thus, miR-17-overexpressing cells became more resistant to chemotherapy, since most cytotoxic
reagents act by diminishing highly proliferative cells (29). This finding, in which miR-17 plays a
dual role in glioblastoma cells, provides a new perspective to our understanding of stress
responses in cancer. To function as a buffering role, miRNA network balances the opposite
signaling pathways by targeting both positive and negative regulators. Any change leading to
imbalance signaling might trigger the vigorous response of miRNAs (30).
In order to survive under nutritional hungry state, cancer cells heavily rely on aggressive
angiogenesis to permit ample blood supply and oxygen uptake. Therefore, “tumor-starving”
(anti-angiogenic) therapy has been employed to prevent tumor vascularization and deprive it
from nutrition. Initially, our lab found that miR-378 contributes to tumor angiogenesis in
transplanted glioblastoma, by targeting SuFu and Fus-1. As a result, miR-378 promotes tumor
cell survival and growth (31). We further suggested that miRNA-induced angiogenesis is a
common phenomenon observed in different types of tumor (32). MiR-93, a paralog of miR-17-
92, was found increased in human breast carcinoma. By modulating large tumor suppressor
homology 2 (LATS2), miR-93 enhances tumor angiogenesis and metastasis in a mouse lung
metastasis model (33). These findings highlight a promising role of miRNA as a predictor in
“tumor-starving” therapy. Since tumors harboring high expression of certain miRNAs often
show an excessively angiogenesis pattern, elucidation of the underlying cross-reaction between
miRNAs and anti-angiogenic treatment is likely uncover new opportunities for therapeutic
intervention.
1.3.3 MicroRNA and autophagy
Autophagy is a catabolic process which transports cellular components to lysosomes for self-
degradation. It is a cytoprotective mechanism in maintaining homeostasis and highly conserved
during evolution. Deregulation of autophagy has been implicated in a variety of cancers (34).
Due to elevated metabolic demand, aggressive tumor cells often harbor robustly activating
autophagy, to fuel mitochondrial metabolism. Autophagy may also limit ROS toxicity by
triggering mitophagy, wherein damaged mitochondria are eliminated (35). Beclin 1 (also known
as autophagy-related gene 6 or Atg 6) is a key autophagy-promoting player in the development
and progression of cancer, including breast cancer, ovarian cancer, glioblastoma and lymphoma
(36). It was first demonstrated that Beclin 1 is a potential target of miR-30a. Inhibition of beclin
12
1 expression by miR-30a blunted the activation of autophagy induced by rapamycin in tumor
cells (37). The miR-30 cluster contains five paralogs: miR-30a, b, c, d, e. The potential targets of
miR-30 subfamily also include B-Myb, a transcription factor that positively regulates cell
proliferation and cell cycle. By binding to the 3’-UTR of B-Myb, miR-30 is able to repress
endogenous expression of B-Myb and inhibit cellular senescence in Hela cells (38). More
investigations suggested miR-30 is a prominent tumor suppressor in prostate cancer, breast
cancer and glioblastoma (39). Through regulation of EMT-associated oncogenes, miR-30 in
prostate cancer cells suppresses EMT features and inhibits tumor cell migration and invasion
(39). Remarkably, miR-30 is also broadly involved in tumor cell apoptosis and stem-like cells
generation (40). Together, it makes miR-30 a bridge between apoptosis and autophagy (34).
Another well-studied miRNA is miR-17-92 cluster. The human miR-17-92 cluster locates at
13q31.3, a fragile region often amplified in hematopoietic malignancies. The function of this
cluster was first reported in B-cell lymphoma, where enforced expression of miR-17-92
accelerated tumor development by acting with c-myc (41). It’s not long before mounting
evidence has demonstrated a pivotal role of miR-17-92 in cancer. As a potential oncomir, miR-
17-92 was found abundantly expressed in immature hematopoietic cells. Sequestosome 1
(SQSTM1), an ubiquitin-binding protein associated with autophagy, was found inhibited by
miR-17-92 cluster in myeloid progenitors (42). SQSTM1 plays an important role in inclusion
body formation by binding to the autophagy regulator Atg8/LC3 (43). In tumor cells under stress,
accumulation of SQSTM1 caused persistent damage to mitochondria and cellular genome. It was
indicated that failure to eliminate SQSTM1 was sufficient to alter NF-kB pathway and contribute
to tumorigenesis (44). By interfering with SQSTM1-regulated pathways, miR-17-92 actively
modulates stress responses in tumor cells.
On the one hand, autophagy pathway is subject to regulation of miRNA network. On the other
hand, the biogenesis of miRNAs is closely linked with autophagy process (45). As a function
center of miRNA-RISC complex, DICER1 and AGO2 can be integrated in the autophagosome
after binding to the selective autophagy receptor NDP52 and GEMIN4 (45). It is eventually
leading to protein degradation in the autophagosome-dependent lysosomal way. Therefore,
autophagy is involved in maintaining miRNA biogenesis by removing inactive DICER1-AGO2
complex, preventing them competing for additional factors which are required for miRNA
maturation (46). In turn, miRNAs control the activity of core autophagy proteins. In chronic
13
lymphocytic leukemia cells, miR-130a inhibits autophagosome generation by targeting DICER1
and ATG2B (47). It was indicated that miR-130a and DICER1 form a regulatory feedback loop
that mediates tumor cell survival (47).
1.4 MicroRNA and tumor microenvironment
Tumor microenvironment comprises blood vessels, immune cells, fibroblasts and extracellular
matrix. Numerous signaling molecules and pathways are important in the interactions of the
tumor and its surrounding microenvironment. It is believed that such interplay is remolding
tumor microenvironment, which allows for tumor angiogenesis and metastasis. Meanwhile,
immune responses are often suppressed in the host, leading to tumor-tolerogenic macrophages,
NK/T cells and neutrophils. Any fluctuation in microenvironment could impact global signaling
of tumor cells, and thus influence the stress response through miRNA-regulated pathways.
1.4.1 MicroRNA and immune response
The puzzle that how tumor cells escape from natural immune surveillance has intrigued
extensive research into tumor mediated immune suppression. It is becoming increasingly clear
that dysregulation of immune response plays a critical role in cancer progression and therapeutic
resistance. Hence normalizing of the microenvironment can improve anticancer outcome.
Analysis of tumor infiltrating lymphocytes has demonstrated that many types of tumors show
evidence of T-cell infiltration (48). Of particular, activated CD8+ T cell responses have been
associated with a positive prognosis in tumors such as colorectal cancer (49). More studies are
underway to explore the prognostic value of cancer associated immune biomarkers. Recent
findings have suggested that miRNAs are greatly involved in modulating the proliferation,
differentiation and response of CD8+ T cells. Initial characterization of miRNA profile in CD8+
T cells provided insight into the understanding of miRNA’s role in a cell-specific setting (Figure
1.5). When compared between naïve, effector and memory CD8+ T cells, it was shown that 7
miRNAs (miR-16, miR-21, miR-142-3p, miR-142-5p, miR-150, miR-15b and let-7f) are most
frequent expressed in all the T cell subsets, whereas they tend to be down-regulated in effector T
cells and come back up in memory T cells (50). During the process of differentiation, some
miRNAs such as miR-21 and miR-155 are found up-regulated while the miR-17-92 cluster is
concomitantly decreased (51).
14
Figure 1.5 MicroRNA regulates antitumor immune reactions
MicroRNAs are involved in regulation of tumor tolerance and antitumor immune reaction by
mediating CD8+ T cells, NK cells and macrophages.
15
T cell tolerance to cancer is the characteristic of immune suppression in tumor microenvironment.
Rescuing tolerant T cells by lymphopenia-mediated homeostasis-driven proliferation may enable
development of new immunotherapeutic strategies. By analyzing genome-wide miRNA profile in
tolerant T cells, Greenberg, et al found that miR-21 and miR-184 are up-regulated after rescuing,
whereas miR-181a was decreased (52). Further studies revealed that miR-181a expression
inversely correlated with mRNA levels of 56 predicted target genes. The authors pointed out miR-
181a could be a possible key negative regulator of CD8+ T cells functions (52). By inhibiting
innate immune response, miR-181 may enhance tumor vascular invasion and metastasis. Over-
expression of miR-181 was found correlated with poor survival in oral squamous cell carcinoma,
suggesting it as a potential biomarker for cancer tolerance and prognosis (53). The understanding
of miRNA’s potent effects in tumor-mediated immunosuppression was driven by studies in
tumor-bearing mice. Increased expression of miR-15b was observed in isolated CD8+ T
lymphocytes in mice with Lewis lung carcinoma (54). Ectopic expression of miR-15b in CD8+ T
cells inhibits apoptosis by knocking down death effector domain-containing DNA binding protein
(DEDD). DEDD is a ubiquitous death effector domain containing protein which induces
apoptosis through its N-terminal DED motif. High expression of miR-15b is also associated with
inactivation of CD8+ T lymphocytes by repressing the production of cytokines such as IL-2 and
IFN-γ (54). Despite of its anti-apoptotic effect, miR-15b likely plays a negative role in the
activation of effector T cells and anti-tumor immune response. Dynamic change of tumor-
associated miRNA expression can be also observed in miR-17-92 cluster. In patients with
multiple myeloma, the miR-92a level in CD8+ T cells was significantly down-regulated
compared with normal subjects (55). With the remission of disease, the plasma miR-92a level
became normalized. Together, these findings suggest gain or loss of miRNAs may represent the
T-cell immunity status in tumor host.
Accumulating evidence has identified signal transducer and activator of transcription 3 (STAT3)
as a critical molecule in regulating tumor-associated immunosuppression by interfering with
multiple factors. Constitutively expression of STAT3 alters gene-expression programs, inhibits
expression of immune mediators and suppresses leukocyte infiltration into the tumor (56).
Blocking STAT3 in immune cells can generate diverse anti-tumor immunity by suppressing
negative regulators such as immature dendritic cells and regulatory T cells and activating CD8+
T cells, natural killer cells and neutrophils (56). Thus, STAT3 has emerged as a potential target
16
for tumor immunotherapy. Recent studies have demonstrated that the interplay between miRNAs
and STAT3 broadly exists in cancer development and progression. MiR-124 has been reported as
a potential tumor suppressor in diverse tumor types, such as colorectal cancer and prostate cancer
(57). In patients with glioblastoma, miR-124 expression is significantly reduced, compared to
normal brain tissues (58). Ectopic upregulation of miR-124 in glioma stem-like cell promoted T
cell proliferation and regulatory T cell induction. Moreover, treatment of T cells from
glioblastoma patients with miR-124 induced pro-inflammatory cytokines and chemokines (58).
As a result, systemic administration of miR-124 prolonged overall survival and decreased tumor
incidence in a murine glioma model. Such anti-tumor effects were proved to depend on the
presence of T cells. In tumor bearing mice depleted of CD4+ or CD8+ cells, the
immunotherapeutic effects of miR-124 was ablated (58). Activation of STAT3, in turn, can
modulate expression of several miRNAs. For example, there is a highly conserved STAT3-
binding site in the promoter of the miR-17-92 gene (C13orf25) (59). By modulating the
expression of IL-6, activation of STAT3 upregulates the entire miR-17-92 cluster. Interestingly,
there are two seed regions of miR-17-92 in STAT3 3’-UTR, and thereby miR-17-92 reversely
targets STAT3 expression, leading to reduced ROS generation (60). By modulating STAT3
associated immune tolerance in myeloid-derived suppressor cells (MDSCs), the negative
regulatory loop between miR-17-92 and STAT3 may be an important factor in tumor associated
immune response and a potential immunotherapeutic target against cancer.
1.4.2 MicroRNA and epithelial mesenchymal transition
Epithelial mesenchymal transition (EMT) is regarded as a key process of tumor invasion and
distant metastasis. It is essential for cancer cells to survive in hostile milieu and escape adverse
sites (61). As a major stress-adaptive strategy, EMT leads epithelial cells to lose their cell
polarity and cell-cell adhesion, and gain morphological and functional characteristics of
mesenchymal cells (61). A prominent marker of EMT is the loss of epithelial cadherin (E-
cadherin) expression. E-cadherin is a transmembrane glycoprotein that mediates intercellular
adhesion via hemophilic binding. Inactivation of E-cadherin has been found in most carcinomas
(62). Recently, miRNAs are emerging as potential regulators of E-cadherin. MiR-200 family is
the first miRNAs identified to be associated with E-cadherin expression (63). In breast cancer
cells with less invasive phenotype, there is endogenous expression of both miR-200c and E-
cadherin. However, in estrogen receptor negative cells, miR-200c as well as E-cadherin levels
17
are merely detectable. By targeting E-cadherin repressors ZEB1 and ZEB2, miR-200c was able
to restore E-cadherin function and therefore inhibit EMT (63). Most recent study revealed that
miR-200/ZEB interaction is crucial to breast cancer growth and metastasis (64). This network is
subject to the regulation of β1 integrin and transforming growth factor-β (TGF-β). In triple
negative breast cancer cells, knockdown of β1 integrin changed cell migration pattern and
induced distant metastasis by activating TGF-β. Reducing the abundance of TGF-β or restoring
the ZEB/miR-200 balance reestablished cell cohesion and reduced tumor dissemination (64).
Augmented evidence suggests miR-200 as a potential marker of metastasis capacity. MiR-
200/ZEB network is not only involved in EMT in breast cancer, but also a key regulator of
prostate cancer and gastric cancer (65). Imbalance of miR-200/ZEB is associated to invasive
subtype of gastric cancer and poor prognosis of patients (66). Notably, miR-200 family also
exerts their effects on cellular plasticity and metastasis by modulating additional signaling in
parallel to ZEB. Actin-associated gene moesin was inversely associated with miR-200
expression (67). In a similar pattern as miR-200/e-cadherin interaction, miR-200/moesin axis
regulates breast cancer cell metastasis in a context-dependent manner (67).
1.5 MicroRNA regulation of chemotherapeutic drug resistance
When a patient is first diagnosed with cancer, the common medical practice is to perform
surgical resection of the tumor, in an attempt to liberate the patient from the cancerous mass of
cells. Unfortunately, tumor resection is not always an optimal procedure for cancer on its own,
and despite the surgeon’s best efforts, cancer cells will still be present in the patient’s body, and
will continue to grow if left untreated. In an attempt to combat these remaining cells,
chemotherapy or radiotherapy is often used adjunctively. Each of these procedures induces a
molecular stress response, as the patient’s remaining tumor cells attempt to survive the poisons
and high-energy radiation that they are being bombarded with. The cells are faced with two
options—adapt or perish. These responses are usually the manifestation of complex molecular
signaling cascades, which are attempting to maintain cellular homeostasis despite the
increasingly stressed conditions. These signaling cascades are fine-tuned through constant
monitoring and regulation. In the recent decade, as efforts being made to elucidate the
participants in these complex networks, microRNAs are emerging as key players in the
regulation of stress responses to chemotherapy and radiotherapy; highlighting a potential for the
exploitation of these oligonucleotides for therapeutic use. There are thousands of microRNAs,
18
each regulating thousands of protein levels, thus the next will exploit the nature of microRNAs
through select examples, discussing possible therapeutic opportunities.
Chemotherapy is a cancer treatment generally involving the use of one or more cytotoxic drugs
with the aim of slowing and ideally stopping the growth of tumors. Chemotherapeutics generally
act by targeting rapidly dividing cells (which cancer cells are) and preventing cell division
through a variety of mechanisms including impairing the cell division machinery and damaging
DNA—often leading to programed cell death, known as apoptosis.
Chemotherapy can offer an excellent adjuvant treatment for killing cancer cells, however this
treatment often becomes less effective, as cancer cells acquire traits helping them to survive the
toxicity. Resistance to chemotherapy is believed to cause treatment failure in over 90% of
patients with metastatic cancer (68). Resistance to the stressors of chemotherapy can occur
through many different mechanisms, which are poorly understood. However, it is becoming
increasingly apparent that microRNAs serve a regulatory role in the molecular mechanisms
underlying drug resistance; and thus may hold the potential to be used to reverse
chemoresistance.
1.5.1 MicroRNA as a key regulator in cancer
MicroRNAs are a group of non-coding RNA with 20-22 bases in length, which is broadly
conserved across species. MiRNAs do not encode any proteins but regulate gene expression
post-transcriptionally. Most miRNA loci are found in non-coding intronic transcription regions,
but some of them are located in exonic regions (69). MiRNA genes are transcribed to primary
miRNAs (pri-miRNAs) by RNA polymerase II (pol II), which are then processed by Drosha-
DGCR8 complex to release hairpin intermediates precursor miRNAs (pre-miRNAs). Pre-
miRNAs hairpins will bind to exportin-5 and be exported to the cytoplasm, where pre-miRNAs
will be cleaved by RNase III-type enzyme Dicer. Normally, two miRNA strands are produced
from opposite arms of one pre-miRNA, and they are named miRNA-3p and miRNA-5p (69).
Previously it was thought that one of the strands is the mature miRNA and the other strand (the
passenger strand) will be degraded, but current theory indicates that both arms can be selected as
a mature miRNA in a tissue specific context (70). Mature miRNAs are incorporated into the
RNA-induced silencing complex (RISC) to cleave targeted mRNA or repress their translation by
binding to the 3’-untranslated region (3’-UTR) of mRNAs. However, some studies have shown
19
that miRNAs can activate mRNA translation by binding to 5’-UTR of their targets (6). More
recently, some miRNAs have been found to bind to decoy mRNAs in a RISC independent way
(7).
To date, there has been plentiful research conducted demonstrating that miRNAs are linked to
approximately 300 human diseases, especially cancer (71-74). MiRNAs have been shown to be
broadly involved in cancer development, metastasis, angiogenesis and drug resistance. Since
miRNAs are differentially expressed in human cancer, they can be grouped into oncogenic and
tumor suppressive miRNAs, according to their influence on cancer cell growth (33, 75-77).
Oncogenic miRNAs (oncomirs) induce cancer cell proliferation by down-regulating expression
of tumor suppressor genes, whereas tumor suppressor miRNAs (mirsupps) inhibit cancer
progression by targeting oncogenes post-transcriptionally (Figure 1.6). They can be distinguished
based on chromosome distribution, evolutionary rate and functions. Oncomirs tend to be
amplified in human cancers whereas mirsupps are frequently cleaved (78). However, this
dichotomous approach has its limitations. On the one hand, it is important to note that miRNAs
may act in a tissue-specific way, where single miRNA can be either oncomirs or mirsupps in
different types of tumors. For example, miRNA-17 was found to accelerate tumor development
in B-cell lymphoma, while it can suppress breast cancer growth by down-regulating AIB1
expression (41, 79). On the other hand, many studies were based on experiments conducted in
vitro, where the body’s immunity response and tumor micro-environment are overlooked.
Emerging models have already shown that some miRNAs sensitize tumors to treatment while
promoting tumor growth in vitro, and these miRNAs could even be used as predictive markers
for clinical outcome (23). In our lab, we exploited miR-17’s function in glioblastoma cells. We
found miR-17 targeted the oncogene MDM2 and the tumor suppressor gene PTEN
simultaneously, resulting in retardation of cell growth yet prolonged cell survival (80).
Interestingly, chemoresistance was also detected partly as a result of tumor stem cell generation
(80). Clearly the biological effects of miRNA’s participation in cancer is more complex than it
was once thought to be (Figure 1.6).
1.5.2 MicroRNA and chemotherapy
Chemotherapy, together with surgery and radiotherapy, has been a major approach to cancer
treatment. Most chemotherapeutic agents function by interfering with DNA replication and cell
20
Figure 1.6 The role of microRNA in cancer
The current theory suggests that microRNAs can be grouped into oncogenic and tumor
suppressive microRNAs, based on their functions in tumorigenesis. Oncogenic microRNAs
(oncomirs) have been associated with accelerated cell proliferation. On the other hand, tumor
suppressive microRNAs have long been considered to inhibit cancer development.
However, our data suggest that microRNAs could regulate both positive and negative signalings
to buffer their activity, which is critical to maintain homeostasis under stressed circumstances.
Here we show that miR-17 can target MDM2 and PTEN simultaneously, reducing proliferation
in unstressed condition but prolonging cell survival in stressed condition.
21
mitosis, inhibiting protein synthesis and inducing cell damage. Chemotherapy is often effective
in eliminating rapid growing tumor cells as well as minimal metastatic disease. In recent
decades, tremendous achievements have been made to improve the efficacy of anti-cancer
agents. For malignancies such as lymphoma, leukemia and small cell lung cancer, chemotherapy
has been used as first-line therapy. As adjuvant therapy, chemotherapy is widely used to prevent
tumor recurrence by eliminating residual lesions. When used solely or combined with
radiotherapy, neo-adjuvant chemotherapy can even reduce tumor size before surgery, curing
otherwise incurable patients. However, the development of drug resistance often results in the
failure of chemotherapy, especially in advanced patients. In general, there are two classes of drug
resistance: inherent (natural) resistance and acquired resistance. Inherent resistance can be
partially overcome by incorporating multiple agents into chemotherapy regimens, while acquired
insensitivity to chemotherapeutic drugs accounts for over 90%of unsuccessful treatments in
advanced patients (81). As a result of drug resistance, tumors often relapse more aggressively
and metastasize to distant organs, leading to devastating outcomes. Despite the extensive efforts
taken, the mechanisms of chemotherapeutic drug resistance still remain largely unknown. Based
on the response of cancer cells to treatment, chemotherapy resistance could be due to either
genetic or epigenetic reasons, including (1) overexpression of drug resistance-related proteins,
(2) altered drug targets, (3) decrease in drug concentrations, and (4) escaping from cell cycle
checkpoints. Emerging evidence indicates that tumor angiogenesis and stem cell development
are also responsible for chemoresistance.
It is known that cancer is a group of genetically heterogenetic cells. Chemotherapeutic drug
treatment transforms predominant cells from fast dividing cells to drug resistant ones. These cells
are thought to be the cause of tumor recurrence thereafter. During such transformation, tumor
cells undergo dramatic changes at the genetic and epigenetic level. Recently, microRNAs
(miRNAs) have evolved as a major force in regulating gene expression and hence the phenotype
of tumor cells, because miRNAs have diverse functions in cell proliferation (82-84), cell cycle
progression (85-87), survival (75, 88), invasion (89, 90), cell differentiation (91, 92), and
morphogenesis (93). The activities of miRNA are also regulated by non-coding RNAs. This was
initially demonstrated by us using the 3’UTR of versican which induces organ adhesion by
modulating miRNA function (94, 95). Further studies indicated that a number of 3’UTRs tested
possess the ability to regulate miRNA functions (96-98). In addition, pseudogenes and long non-
22
coding RNAs can also modulate miRNA functions (99, 100). This complicated network makes it
difficult to understand the intrinsic mechanisms. Hence, there is a pressing need to decipher the
molecular mechanism of microRNA-regulated drug resistance and its therapeutic implications.
In this review, the role of microRNAs in anticancer drug resistance will be explored in light of
current knowledge.
1.5.3 MicroRNAs regulate drug resistance-related proteins
The term multiple drug resistance (MDR) refers to the idea that resistance to one drug is
followed by resistance to multiple drugs which might be completely different. Most known MDR
proteins belong to the ATP-binding cassette (ABC) family, which includes P-glycoprotein (P-
gp/MDR-1/ABCB1/CD243), MDR-associated protein (MRP1/ABCC1) and breast cancer-
resistant protein (BCRP/ABCG2). With similar trans-membrane domains, they protect tumor
cells from the influx of harmful drugs and pump them out, thus shelter cells from cytotoxic
treatment (101). To mimic the chemoresistant phenotype in vitro, drug-resistant cancer cell lines
have been developed to study MDR mechanisms. Despite the change in protein levels,
microarray analysis disclosed the transition in miRNA expression. Some miRNAs, such as miR-
19, miR-21, and miR-34a (102-104), have been found elevated several folds in chemoresistance
cell lines, and have been thought to play a role in adapting cancer cells to chemotherapy.
Meanwhile, reduced expression of some miRNAs was also shown to be correlated with up-
regulation of MDR proteins. These miRNAs usually control the expression of MDR related
proteins, thus chemoresistance may result from down-regulation of these miRNAs. For example,
miR-298 directly targets MDR-1 in a dose-dependent manner, resulting in decreased level of P-
gp. Moreover, overexpression of miR-298 reversed chemoresistance in breast cancer cells (105).
It’s noted that miR-27a activated MDR-1 indirectly in ovarian cancer, whereas MDR-1 could be
directly targeted by miR-27a in leukemia (106, 107). The fact that miRNA has dual roles in
regulating the same target is reinforced by these findings, and more details will be yielded in the
future on how miRNAs respond to different signaling in various tumors. The miRNAs that are
reported to regulate MDR-1 are listed (Table 1). Identification of their function highlights a new
approach to the development of gene therapy.
23
Table 1 The miRNAs in the regulation of MDR-1
Tumor category MiRNA Mechanism Reference
Breast cancer miR-21 Actively regulate
MDR-1 and IAPs
(108)
miR-137 Target Y-box
binding protein-1
(YB-1) and
suppress MDR
(109)
miR-200c Target MDR-1 (110)
miR-298, miR-
1253
Target MDR-1
directly
(105)
miR-451 Target MDR-1 (111)
Glioblastoma miR-221 Target MMP-9 and
suppress MDR
(112)
Colon cancer miR-145 Target MDR-1
directly
(113)
Ovarian cancer Let-7 Target IMP-1
mediated
stabilization of
MDR-1
(114)
miR-27a Target HIPK2 and
increase MDR-1
(115)
miR-27a, miR-451 Activate MDR-1
indirectly
(106)
miR-130a Target PTEN and
activate MDR
(116)
Liver cancer miR-122 Target MDR-1 and
MRP
(117)
Leukemia miR-27a, miR-331-
5p
Target MDR-1
directly
(107)
miR-138 Suppress MDR-1 (118)
Prostate cancer miR-148a Target MSK1 and
suppress MDR
(119)
24
Other ABC family members such as MRP1 and BCRP also appear to be targets of miRNAs.
MiR-326 was reported to modulate expression of MRP1 in VP-16 resistant cell lines and
induction of miR-326 reversed the resistance of VP-16 as well as doxorubicin (120). BCRP is
another drug resistance-related protein which determines pharmacokinetic properties in breast
cancer cell lines. MiR-328 was found to target BCRP 3’-UTR and influence drug disposition
accordingly in human breast cancer cells (121). Since the MDR mechanism accounts for only a
fraction of drug resistance, more experiments will be needed to explore the actual function of
miRNA in different type of malignancies. Nevertheless, the findings of miRNA targeting drug
resistance-related proteins will undoubtedly shed light on the therapeutic value of miRNAs.
1.5.4 MicroRNAs alter drug targets
MicroRNAs not only act in a cell-specific manner but also influence drug resistance in a drug-
specific way. For example, elevated expression of miR-34a is found to be associated with
docetaxel resistance in breast cancer cell lines, while miR-34a conversely sensitizes Ewing’s
sarcoma cells to doxorubicin and vincristine (103, 122). Recent development of targeted
therapies is giving more hope to developing successful cancer treatments. MiRNAs have been
found to interfere with the specific molecular target that is intended to be blocked by
medications. In non-small cell lung cancer cells, miR-126 could efficiently bind to 3’-UTR of
vascular endothelial growth factor A (VEGFA), which is the very target of angiogenesis inhibitor
bevacizumab. Furthermore, restoration of miR-126 enhanced the sensitivity of tumor cells to
anticancer agents, which implied the possibility of a combined targeted therapy (123). Epidermal
growth factor receptor (EGFR/HER1) is a cell-surface receptor, and mutations of it have been
found to be associated with a number of cancers. Therefore, it serves as an important target for
anticancer drug therapy. Tyrosine-kinase inhibitors (e.g. Gefitinib, Erlotinib) and monoclonal
antibodies (e.g. Cetuximab, Panitumumab) have been developed to inhibit EGFR signaling and
approved to treat patients harboring EGFR mutations. It is notable that EGFR pathways crosstalk
with some miRNAs during carcinogenesis and drug treatment. For example, EGFR mutations
positively regulate miR-21, which in turn increases expression of EGFR (124, 125). A positive
feedback loop as such is critical in maintaining physical homeostasis, but could also be the cause
of drug resistance in EGFR inhibitor-treated patients. Similarly, miR-145 inhibits cancer cells
growth by targeting EGFR, whereas EGFR suppresses miR-145 to promote tumorigenesis in
25
animal models (126, 127). These findings reveal one aspect of the buffering role of miRNA that
is subject to the regulation of its own target, maintaining a balance between positive and negative
signaling.
In addition, miRNAs can inactivate drugs by up-regulating downstream effectors of the same
pathway. One cause of therapeutic resistance is inactivation of tumor suppressor PTEN which
allows over-activation of the PTEN/PI3K/AKT pathway. Numerous miRNAs target PTEN to
function as oncomirs, such as miR-17, miR-21, miR-144, and miR-214 (80, 128-130). Other
cases of bypassing growth inhibition include recruitment of insulin-like growth factor-1 receptor
(IGF1), which was found in miR-17-92 overexpressed tumors (131). Down-regulation of
miRNAs targeting IGF1 leads to tumorigenesis, and restoration of the miRNAs causes growth
inhibition of the tumor cells (132). Future studies should address the predictive value of miRNAs
expression in personalized medicine. It’s also promising to overcome drug resistance by using a
miRNA that shares the same targets of anticancer agents (133).
1.5.5 MicroRNAs change drug concentration
The development of chemoresistance is marked by loss of the drug transport system. It results in
a decline in drug concentration inside cells. Gap junction intercellular communications (GJIC)
are broadly involved in transportation of small molecules and second messengers. It is
constituted by transmembrane protein connexins (Cx), which are often lost in cancer cells.
Restoration of GJIC suppresses tumor progression and enhances drug sensitivity. The main
antitumor function relies on the bystander effect (BE), where cytotoxic molecules can be
transferred from targeted cells to neighboring cells through GJIC, exposing more cells to
chemotherapeutic agents (134). MiR-1 and miR-206 have been shown to target connexins, which
may lead to impaired GJIC (135, 136). Further study showed that RNA-binding protein Dnd1
counteracted the function of miR-1 and miR-206 by prohibiting them from associating with their
targets (137). These results once again verified that endogenous miRNAs are under regulation of
an intrinsic network. Consequently, systematic down-regulation of miRNAs also drives the
development of drug resistance. It was reported that systemic RNA interference-defective-1
transmembrane family member 1 (SIDT1) facilitated intercellular transfer of miR-21, which
promoted resistance to gemcitabine in human adenocarcinoma cells (138).
26
In addition to influencing bystander effect, miRNAs also have impact on cell receptors. Estrogen
receptor (ER), which serves as the target of endocrine therapeutic agents such as tamoxifen and
raloxifen, has been found to be regulated by let-7, miR-206 and miR-221 in breast cancer (139-
141). Interestingly, miR-206 and miR-221 were believed to be responsible for tamoxifen
insensitivity, while let-7 induced tamoxifen sensitivity which could be due to the different
binding region. Most recently, accumulating evidence suggests that 1alpha,25-dihydroxyvitamin
D(3) [1,25(OH)(2)D(3)] inhibits growth of many kinds of cancerous cells such as breast cancer
and colon cancer. It was identified that miR-125b recognized the 3’-UTR of the vitamin D
receptor and abolished its expression, resulting in a decrease in the anticancer effects of
1,25(OH)(2)D(3) (142).
In addition to changing drug concentration at the cellular level, miRNAs also influence the
pharmacokinetics process of the whole body. It was implied that cytochrome P450 (CYP), a
superfamily of drug-metabolizing enzymes, could be targeted by miR-27b (143). In breast cancer
tissues, decreased miR-27b was accompanied by a high level of CYP1B1 protein, which was
responsible for docetaxel resistance in cancerous cells (143, 144). Accumulating evidence
suggests miRNAs may exert profound physiological effects on the regulation of the CYP family.
For example, CYP1A1 was reported to be targeted by miR-892a and CYP2J2 was inhibited by
let-7b (145, 146). The most recent data illuminated that miRNAs repressed CYP in a dose-
dependent manner. In transgenic mice, knock-down of CYP3A by miRNA-based shRNA
dramatically reduced enzymatic activity (147). It is known that the liver plays a crucial role in
catalyzing drugs. We found that miR-17 impaired nonalcoholic hepatic steatosis in transgenic
mice by targeting PPAR-alpha, leading to damaged liver function [Liu et al., Unpublished data].
1.5.6 MicroRNAs influence therapeutic induced cell death
Various anticancer drugs function by inducing intrinsic and extrinsic apoptosis in tumor cells
(148). Cellular response to apoptotic signaling can determine the outcome of treatment. There
are two principal pathways leading to apoptosis: mitochondrial intrinsic pathway and
transmembrane extrinsic pathway. The former event is mainly under the control of Bcl-2 family,
which includes more than thirty apoptotic sensorial molecules (149). A number of miRNAs
participate in cell apoptosis via interaction with Bcl-2 family members. For example, miR-15/16,
miR-21 and miR-125b were all shown to regulate Bcl-2 protein, an anti-apoptotic factor. It was
27
discovered that miR-15/16 induced apoptosis by targeting Bcl-2, whereas suppressing miR-15/16
promoted up-regulation of Bcl-2 and resistance to tamoxifen in breast tumors (150). Although
miR-21 could bind to 3’-UTR of Bcl-2 mRNA, it ultimately has an anti-apoptotic role in most
tumors (151). The reason might be that miR-21 has another target in the same pathway: Bax,
which is a critical pro-apoptotic molecule. Down-regulation of Bax by miR-21 inhibited drug
induced apoptosis (152). These results highlight another aspect of miRNA’s buffering role,
which interacts with the whole signaling pathway by controlling both upstream and downstream
effectors at the same time. Another example is miR-125b, which targets anti-apoptotic Bcl-2 and
pro-apoptotic Bak1 simultaneously, conferring drug resistance and anti-resistance properties in
different cancers (153, 154). It is consistent with our findings that miRNAs could play an
opposite role in spatial and temporal specific manners (80) (Figure 1.6).
At the onset of apoptosis, multimedia pro-apoptotic proteins assemble into apoptosome that
mediates the activation of the caspase reaction. The formation of apoptosome is often inactivated
in tumor cells (149). Apaf-1 is an adaptor molecule which forms the backbone of apoptosome. It
was recently revealed that miR-155 negatively regulates Apaf-1 in lung cancer tissue, which
inhibits the sensitivity of cancer cells to cisplatin (155). Other factors may also take part in the
process of apoptosis. Experiments in our lab showed that miR-199a-3p transfected breast cancer
cells became significantly more sensitive to docetaxel treatment. This was accomplished by a
prominent increase in sub-G1 apoptotic cells. We then demonstrated that this effect was due to
the inhibition of caveolin-2, of which expression was reversed by anti-miR-199a-3p (83). Until
now, there are over thirty miRNAs reported participating in the regulation of cell cycle
progression by modulating various pathways such as RAS, AKT, E2F1 and p53 (86). This
research provides a new version of miRNA-mediated drug resistance in cancer cells.
1.5.7 MicroRNAs promote angiogenesis
We initially illustrated that miRNAs expressed endogenously could play an important role in
tumor angiogenesis. In glioblastoma cells, miR-378 contributes to cell survival in vitro and
tumor growth and vascularization in vivo by targeting SuFu and Fus-1 (31). It is apparent that
aggressive angiogenesis helps tumor cells escape treatment and metastasize to distant organs.
Recent studies have shown that a variety of miRNAs termed angiomiRs regulate tumor
angiogenesis, such as miR-126, miR-130a, miR-210, and miR-296 (156). For example,
28
overexpression of miR-93 in U87 cells increases tube formation in vitro and neovascularization
in vivo (157).
To block vascular supply to tumor, a number of therapeutic approaches (bevacizumab, sorafenib,
sunitinib, etc.) have reached in clinic. However, only a fraction of patients benefit from
treatment, as tumors develop resistance to vascular endothelial growth factor (VEGF) inhibitors
(158). Computational analysis predicted at least 96 miRNAs were directly involved in VEGF
regulation (159). These miRNAs were shown to be associated with efficacy of anti-VEGF
treatment (160). Apart from binding the 3’-UTR of VEGF mRNA, many other miRNAs can
mediate VEGF signaling pathway indirectly. It was demonstrated that aberrant regulation of
VHL induced HIF-1α activation, which promoted autocrine VEGF secretion in leukemia (161).
Overactivation of tumor-derived VEGF could be responsible for treatment failure. In
glioblastoma cells, miR-17 was responsible for the activation of VEGF by activating its upstream
factor HIF-1α. Interestingly, such effects became dramatically significant when the tumor cells
are under starvation or chemotherapy (80). These findings favor the application using anti-
angiogenesis therapy combined with chemotherapeutic agents. It’s currently unclear how anti-
VEGF therapy alone influences tumor growth. The involvement of miRNAs with tumor
angiogenesis might provide more clues and further optimize the selection of anti-angiogenesis
treatment.
1.5.8 MicroRNAs in the generation of tumor stem cells
Tumor stem cells (TSCs) have long been considered as a hidden snake in the grass during the
treatment of cancer. They are thought to be responsible for therapeutic resistance, tumor
metastasis and relapse. Since they were found in acute myeloid leukemia cells in 2003, TSCs
have been reported in most tumors (162). The relationship between miRNAs and TSCs has been
confirmed over the last few years, by which several miRNAs control the key biological
properties of TSCs in breast cancer, prostate cancer and glioblastoma (163). Song’s group was
the first to examine the relationship between miRNAs and breast cancer stem cells (164). They
analyzed the expression of let-7 in breast tumor-initiating cells and found that let-7 was
dramatically reduced in TSCs. They then identified let-7 as a key regulator in mediating tumor
stem cell characteristics by silencing H-RAS and HMGA2 (164). Though it’s controversial about
how to define stem cells in cancer, CD44 and CD133 have been widely used as surface markers
29
of TSCs (164). Interestingly, a recent study suggested that miR-34a inhibited TSCs formation in
prostate cancer by directly repressing CD44, which highlighted a potential that miRNAs might
take part in the regulation of TSC in more common ways (165). In addition to a negative
mediator, some miRNAs possess the ability to promote the generation of TSCs by down-
regulating tumor suppressors. In hepatocellular carcinoma, miR-130b accounted for the growth
of TSCs, which was associated with worse overall survival and more frequent recurrence of
cancer in patients. The increased miR-130b paralleled the reduction of tumor protein 53-induced
nuclear protein 1, a known miR-130b target. Furthermore, miR-130b transfected cells
demonstrated higher resistance to chemotherapeutic agents (166).
Tumor stem cells are believed to be capable of self-renewal and give rise to tumorigenesis. In
glioblastoma cells, we found miR-378 transfected cells contained a large group of side
population (SP) cells which have higher density of TSCs (167). Overexpression of miR-378
enhanced colony formation and cell survival, which was due to the up-regulation of stem cell
marker Sox-2 (167, 168). More interestingly, cells harboring higher percentages of TSCs grew
slower in normal condition, but displayed significant survival advantage under stressed
circumstances, when treated with anticancer agents (80). Therefore, it’s more likely that
miRNAs control the development of TSCs at multiple levels (Figure 1.7).
30
Figure 1.7 MicroRNAs regulate chemotherapeutic drug resistance
MicroRNAs change drug sensitivity of cancer cells by promoting angiogenesis, inducing
therapeutic cell death, regulating drug resistance-related proteins, changing drug concentration,
generating tumor stem cells and altering drug targets.
31
1.6 MicroRNA and Radiotherapy
Radiation therapy is a cancer treatment that involves subjecting a patient’s tumor to ionizing
radiation to kill malignant cells. Ionizing radiation damages cells by producing intermediate ions
and free radicals which cause double stranded breaks (DSBs). If left unfixed, this DNA damage
leads to the death of the cells. Subjecting cells to ionizing radiation stimulates a stress response,
whereby the cell undergoes a battery of molecular changes in attempts to mitigate the damage
and repair damaged DNA (169). Many of the molecular processes in this stress response have
been shown to be regulated by microRNAs, which opens the possibility for them to be exploited
as radiosensitizers in the future.
1.6.1 Response to damaging radicals
As previously mentioned, the ionizing radiation produces free radicals, which exert their lethal
effect on cancer cells by inducing double strand breaks, which may eventually lead to cell death.
A radical is an atom that contains an unpaired valence electron, making the atom highly unstable
and chemically reactive. These radicals can then attack the deoxyribose DNA backbone and
cause DSBs. Thus, in attempt to mitigate these damaging effects, cells have developed
mechanisms to metabolize harmful radicals. For example, the superoxide dismutase family of
proteins catalyzes the degradation of the free radical superoxide anion (•O−2
) to hydrogen
peroxide. Studies have shown that miR-21 to targets and downregulates superoxide dismutase 3
protein expression. It also indirectly lowers superoxide dismutase 2 protein levels, and ultimately
leads to higher levels of superoxide levels, which may act as a radiosensitizer by permitting
higher levels of DSBs (169, 170).
1.6.2 Regulation of DNA histone modification
DNA is usually tightly coiled and packaged into a nucleosome, which can be thought of as a
thread tightly wrapped around a spool. In order for the DNA repair machinery to physically
access the DSB site, the DNA must first be unpackaged. H2AX is member of the histone protein
family, and phosphorylation of this protein leads to DNA that is less condensed to permit DSB
repair (171). Both miR-24 and miR-138 have been shown to target H2AX, and overexpression of
these microRNAs results in H2AX protein downregulation, more DSBs and radiosensitivity
(172, 173).
32
1.6.3 Regulation of cell cycle
Cell cycle checkpoints are mechanisms that allow cells to ensure the integrity of their genome. In
these highly regulated processes, DNA damage leads the cell to undergo cell cycle arrest, which
allows the cell time to repair the DSB. The cyclin-dependent kinase (Cdk) family of proteins
function to regulate the cell cycle by promoting passage through cell cycle checkpoints. DNA
damage leads to inhibition of Cdks, which allows the cell to undergo cell cycle arrest and repair
itself. The Cdc25 protein family re-activates Cdks and allows re-entry into the cell cycle. MiR-21
has been shown to directly target Cdc25 in cancer cell lines and miR-21 inhibitors have shown
enhanced apoptosis in glioblastoma cells treated with ionizing radiation, elucidating a potential
role of miR-21 as a radiosensitizer in these cells (174, 175).
1.6.4 Regulation of repair process
Finally, repair of DSBs ultimately occurs through two mechanisms: homologous recombination
(HR) and non-homologous end joining (NHEJ). In HR, the repair proteins use undamaged sister
chromatid as a template to reconstruct the damaged region, and in NHEJ, the repair proteins
simply rejoin the DNA fragments. MicroRNA regulation occurs in both of these mechanisms,
but to briefly exemplify this, consider the HR protein breast cancer 1 early onset (BRCA1),
which is targeted by miR-182. Overexpression of miR-182 leads to decreased HR-mediated
DNA repair and renders the cells hypersensitive to ionizing radiation in breast cancer cells; thus
revealing a potential role as a radiosensitizer (176).
1.7 Therapeutic influence and future perspective
Are miRNAs friends or foes in cancer treatment? This question might be too broad to answer
concisely. As discussed above, the function of miRNAs in drug resistance could be positive,
negative and even opposite under different circumstances. Taking the evolutionary conservation
into consideration, the nature of miRNAs in physiological condition could be more like
buffering. Emerging data suggest miRNAs are important in balancing different signaling,
helping maintain homeostasis (30). It has been well-established that cancer is a heterogeneous
group of diseases, thus personalized medicine has evolved as a future direction in clinical
oncology. Down-regulation of miRNA networks has been shown to be the root of cancer
development. Therefore, the therapeutic strategy should focus on re-balancing miRNA networks.
33
Meanwhile, disorganized miRNA profiling will have promising diagnostic and prognostic
values.
Through this review, we have seen that microRNAs serve complex, diverse and sometimes
seemingly contradictory regulatory roles in stress response signaling pathways during cancer.
Through processes still not fully understood, microRNAs are able to exert cell-specific and
sometimes environment-specific effects. Nonetheless, these small molecules seem to serve an
important role in maintaining homeostasis, and acting as buffers to balance signaling networks;
and thus have great therapeutic promise. MicroRNA-based therapies are progressing, and
miravirsen, an inhibitor of the liver-specific miR-122, is already in Phase IIa trials for the
treatment of hepatitis C (177).
In the following chapters, the roles of microRNA network will be examined on several models in
vitro and in vivo. I hypothesized that miR-17 has a dual role in the regulation of stress responses.
The changes of its concentration and target preference lead to stress tolerance and immune
suppression. Specifically, four pathophysiological aspects will be addressed: stem cell generation,
drug resistance, immune surveillance and tissue regeneration. Each of them is closely related to
stress responses and regulations. The development of tumor stem cells help tumor cells escaped
from hostile environment and it is a key factor for tumor recurrence in glioblastoma patients. The
first chapter will provide evidence that miR-17 is involved in this process. In addition to that,
selected and general drug resistances also contribute to therapeutic failure and worse prognosis.
The second chapter will link the miR-17 regulated drug resistance together with poor clinical
prognosis in colorectal cancer. It highlights the potential of microRNA-17 monitoring in clinical
settings. The third chapter will look into stress resources in a different way—the internal stress
from immune system. The effort immune cells made to eliminate malignant cells will be
jeopardized/enhanced when there is a variation of microRNA. The goal of the third chapter is to
demonstrate how miR-17 influence immune system by shifting its target preference, and promote
cytotoxic T cell infiltration into tumor. Animal models may not have phenotypical change until
they are challenged by pathophysiological stress such as tissue regeneration. Thus the fourth
chapter will focus on the role of miR-378 in wound healing and angiogenesis. I hypothesized that
miR-378 overexpression will pose a risk of delayed tissue repair on mice while knocking-down
miR-378 will enhance wound healing.
34
Chapter 2
MicroRNAs Regulate Metabolic Stress Response
(A version of this chapter section is published in Oncotarget(29))
35
2 Stress Response of Glioblastoma Cells Mediated by MiR-
17-5p Targeting PTEN and the Passenger Strand MiR-17-
3p Targeting MDM2
2.1 Abstract
Tumor development not only destroys the homeostasis of local tissues but also the whole body,
and thus the tumor cells have to face the body’s defense system, a shortage of nutrition and
oxygen, and chemotherapeutic drug treatment. In response to these stresses, tumor cells often
alter gene expression and microRNA levels to facilitate survival. We have demonstrated that
glioblastoma cells deprived of nutrition or treated with chemotherapeutics drugs expressed
increased levels of miR-17. Ectopic transfection of miR-17 prolonged glioblastoma cell survival
when the cells were deprived with nutrition or treated with chemotherapeutic drugs. Expression
of miR-17 also promoted cell motility, invasion, and tube-like structure formation. We found that
these phenotypes were the results of miR-17 targeting PTEN. As a consequence, HIF-1 and
VEGF were up-regulated. Ectopic expression of miR-17 was found to facilitate enrichment of
stem-like tumor cells, since the cells became drug-resistant, showed increased capacity to form
colonies and neurospheres, and expressed higher levels of CD133, a phenotype similar to ectopic
expression of HIF-1. To further confirm the phenotypic property of stem cells, we
demonstrated that glioblastoma cells transfected with miR-17 proliferated slower in different
nutritional conditions by facilitating more cells staying in the G1 phase than the control cells.
Finally, we demonstrated that miR-17 could repress MDM2 levels, resulting in decreased cell
proliferation and drug-resistance. Our results added a new layer of functional mechanism for the
well-studied miRNA miR-17.
2.2 Introduction
Glioblastoma is the most common primary brain tumor, accounting for nearly 40 percent of all
central nervous system malignancies (178). It is characterized by an aggressive growth pattern
and a resistance to conventional therapy. Despite extensive efforts, the prognosis is still very
poor, with a median survival of approximately 14 months (178). Although some advanced cancer
patients can benefit from chemotherapy, residual tumors often recur soon after treatment. It is
36
believed that a sub-population of tumor cells is not sensitive to treatment, and might be the cause
of tumor relapse (179, 180). The characteristics of these cells, however, remain largely unknown.
MicroRNAs are a group of small non-coding RNAs that are transcribed in the nuclei and
transported to the cytoplasm, each precursor miRNA can be processed to produce a mature
miRNA and a passenger strand (181). Usually, the mature miRNA is the guide strand for
regulation of gene expression, while the passenger strand is believed to be degraded and
inactivated (182, 183). The mature miRNAs regulate gene expression by targeting mRNAs post-
transcriptionally A great deal of evidence has indicated that microRNAs play a crucial role in
regulating tumor proliferation, apoptosis, angiogenesis and metastasis (31, 82, 184-193). They
also play important roles in development of glioblastoma (157, 194, 195). Through the down-
regulation of target proteins, microRNAs can function as oncomirs or tumor suppressors in a
cell-specific context. MiR-17-92 is one of the most extensively studied clusters. This cluster and
its paralogs have been shown to be associated with many malignancies such as breast cancer,
liver cancer, colon cancer, lung cancer and lymphoma (33, 196). The miR-17-92 cluster has six
components which share common characteristics in structure but differ in functions (197). Since
each member in this cluster can mediate multiple pathways and act diversely, there is a pressing
need to explore the precise role of each component. There are documented evidences that
dysfunctions of microRNA are associated with the development of glioblastoma (112). Elevated
levels of miR-17 were found in glioblastoma samples and was negatively related to patients’
survival (198). MiR-17 is also increased in glioblastoma spheroids, which are enriched in tumor
initiating cells (TICs) or stem-like cells (TSCs) (131). Thus, miR-17 has emerged as a critical
regulator in mediating the cellular function of glioblastoma.
Emerging studies suggest that many stress signals are responsible for altered microRNA
expression and functions (199-201). Some microRNAs can modify gene expression by cross-
talking with the tumor micro-environment, and their expression can be altered in turn by distinct
stress conditions such as hypoxia, oxidative stimulation or radiation (202-210). In response to
stress, tumor cells often change gene expression to facilitate their survival (211). For example,
the up-regulation of hypoxia inducible factor-1α (HIF-1α) to adapt to oxygen and nutritional
shortage is essential for inducing tumorigenesis and angiogenesis. HIF-1α is generally subjected
to the negative regulation of tumor suppressors such as Von Hippel-Lindau (VHL) and
phosphatase and tension homolog (PTEN). Notably, HIF-1α is often found overexpressed in
37
glioblastoma (212). Our findings identified that, due to suppression of PTEN by miR-17, HIF-1α
was stabilized when tumor cells were under starvation or chemotherapy, and its elevation
promoted survival, motility and angiogenesis. Furthermore, HIF-1α overexpression contributed
to the generation of tumor stem-like cells. Interestingly, such effects could be only achieved in
stressed conditions such as serum deprivation or chemotherapeutic drug treatment, yet miR-17
reduced tumor growth by targeting murine double minute 2 (MDM2) under normal
circumstances. Because the retarded proliferation rate often decreases chemo-sensitivity, miR-
17-transfected cells develop resistance to chemotherapy. Hereby we show miR-17 has a dual
function in glioblastoma: it suppresses tumor cell growth in normal conditions, and it also
promotes tumor cell survival in unfavorable conditions. This highlights a potential mechanism in
the response of tumor cells to stress and chemotherapy.
2.3 Materials and Methods
2.3.1 Cell cultures
Human glioblastoma cell lines U87 (HTB-14) and U343 were cultured in DMEM media
supplemented with 10% fetal bovine serum (FBS), penicillin (100 U/mL) and streptomycin (100
U/mL). Serum-free medium (SFM) was prepared by using DMEM-F12 medium supplemented
with glucose (4.5 g/L), epidermal growth factor (EGF) (20 ng/mL) and fibroblast growth factor
(FGF) (10 ng/ mL) (213). Cells were maintained in a humidified incubator containing 5% CO2 at
37℃ and passaged every 3-4 days as described (91).
2.3.2 Construct generation
A cDNA sequence, containing two human pre-miR-17 units, a CMV promoter driving
expression of GFP and an H1 promoter, was inserted into a mammalian expression vector
pEGFP-N1 between the restriction enzyme sites BglII and HindIII (70). Green fluorescence was
used to monitor transfected cells.
The primers’ sequences which were used in luciferase activity assay are listed in Figure 2.1. The
3’-untranslated region (3’UTR) of MDM2 contains four potential binding sites for miR-17 while
the 3’UTR of PTEN contains two. For each binding site, two pairs of primers were used to clone
the fragments of 3’UTR and mutant controls.
38
Figure 2.1 The primers’ sequence used in luciferase assay
The list of sequences of primers used in luciferase assay to verify the targeting PTEN and
MDM2.
39
The PCR products were digested with SacI and MluI, followed by insertion into a SacI- and
MluI-digested pMir-Report vector (Ambion) to obtain a luciferase construct or a mutant
counterpart (77).
The PTEN cDNA with coding region was purchased from Origene and the HIF-1α is a generous
gift from Dr. Peng at York University. The MDM2 cDNA was amplified by using two primers:
MDM2-Kozak-BamHI (5’cccggatccgccaccatgtgcaataccaacatgtctgtacc) and MDM2-CMyc-Xbal
(5’ctatctagacaggtcctcctcggagatcagcttctgctccatggggaaataagttagcacaatcatttg). Then the PCR
product was cloned into pCR3.1 vector (Invitrogen), and the identity of the insert was confirmed
by DNA sequencing.
2.3.3 RNA analysis
Total cell RNA was extracted using mirVanaTM
miRNA isolation kit (Ambion). RT-PCR was
performed as described previously (7). The primers specific for mature miR-17 were purchased
from Qiagen. Human U6 RNA was used as control.
2.3.4 Cell function test
In proliferation assay, transfected U87 and U343 cells were plated onto 100 mm tissue culture
plates at a density of 1 x 105 cells/well in DMEM containing 2.5%, 5% or 10% FBS and
maintained for 5 days. Similarly, a survival assay was performed by starving the cells (1 x 106
cells/well) in serum-free medium for up to 2 weeks. The cells were harvested and cell numbers
were counted in different time points.
To test drug sensitivity, Docetaxel (Sanofi-Aventis), Temozolomide (Merck) and Carmustine
(Bristol-Myers Squibb) were applied to adhered cultures. All of the drugs were purchased from
the Pharmacy Department at Sunnybrook Health Sciences Centre. The cell number was counted
every other day after Trypan Blue staining.
2.3.5 Cell migration assay
Migration studies were performed by wound scratch tests and transwell invasion tests
respectively. In the scratch test, different serum concentration (0%, 2.5%, 5%, 10%) were
applied in culture medium. The monolayer of cells was scraped linearly with pipette tips, washed
to remove cell debris and replenished with fresh media. Microscope images of the scratch test
40
were captured at the beginning and at different intervals later. In the transwell invasion assay,
24-transwell (Coster) was coated with 100 l BD MatrigelTM
(BD Biosciences) at a density of 1
mg/mL. 1 x 106 of cells were suspended in DMEM containing 1% FBS and 100μL were
transferred into the upper chamber of the transwell. The lower chamber was filled with 600 L
DMEM containing 10% FBS. After incubation for 24 hours, MatrigelTM
was removed with a
cotton swab and invaded cells were stained with Diff-Quick solution (Fisher Scientific).
2.3.6 Tube formation assay
YPEN cells were mixed with miR-17-transfected cells or control cells and cultivated with BD
MatrigelTM
in 48-well plates. As described previously, the tube-like structures were observed and
recorded by microscopic examination after 24 hours (96).
2.3.7 Western blot analysis
Western blot was performed as previously described (214).
2.3.8 Flow cytometry
For cell cycle analysis, cells in the logarithmic phase were harvested and washed twice in PBS.
Following adjustment of cell concentration to 2 x 106 cells/mL in 50 µL PBS/HBSS with 2% calf
serum, 1 mL 80% ice cold ethanol was added and incubated for 30 minutes. The cells were re-
suspended in 500 µL HBSS containing 0.1 mg/mL of Propidium Iodide (Sigma) and 0.6% of
NP-40. The DNA content was measured by flow cytometry (Beckman Coulter).
For antibody staining, 1 x 106
cells were washed twice in PBS before re-suspension in 50 µL
HBSS with 2% calf serum. Anti-CD133 antibody (Abcam, 1:20 dilution) was added and stained
on ice for 30 minutes. The cells were pelleted, and 1 µL of cy5-conjugated goat-anti-mouse
(Jackson ImmunoResearch) was added into each tube. Flow cytometry analysis was conducted
after 30 minutes and CD133 ratio was examined. The data was analyzed using FlowJo 9.1
software.
2.3.9 Colony formation and self-renewal assay
Colony formation was assessed by mixing 1000 cells with 0.33% low-melting agarose in DMEM
supplemented with 5% FBS and plated on 0.66% agarose-coated 6-well tissue culture plates.
41
After four weeks, colonies were stained by Coomassie blue (Bio-Rad) and photographed. Self-
renewal was measured as previously described (215). Cells were cultured in serum-free medium
for two weeks before spheroid formed. Individual spheroids were plated at clonal density in non-
adherent culture. Secondary spheroids were counted 5 days later.
2.3.10 MTT assay
Ten thousand cells in 200 µL media per well were seeded and cultured in a 96-well plate for 24
hours. Two micro liters of drug in sequential diluted concentrations were added to each well and
incubated overnight. Thiazolyl blue tetrazolium bromide (MTT) was diluted to 5 mg/mL in PBS
and 20 µL were added to each well. After 3 hours, the cells were re-suspended in 200 µL of
Dimethyl sulfoxide (DMSO) and shaken for 15 minutes. The absorbance value was recorded at
570 nm using a microplate reader (Perkin Elmer).
2.3.11 Luciferase activity assay
Luciferase activity assays were performed as previously described (98). In brief, U87 cells were
seeded onto 12-well tissue culture dishes at a density of 1 x 105 cells/well and co-transfected
with the luciferase reporter constructs and miR-17 plasmid or positive control sequences with
Lipofectamine 2000. After 12 hours, cell lysate was prepared by employing Dual-Luciferase®
Reporter Assay Kit (Promega) and luciferase activity was detected using microplate scintillation
and a luminescence counter (Perkin Elmer).
2.3.12 Statistical analysis
All experiments were performed in triplicate and numerical data were subjected to independent
sample t test (unless otherwise specified). The levels of significance were set at *p<0.05 and
**p<0.01.
2.4 Results
2.4.1 MiR-17 prolongs glioblastoma cell survival and increases cell motility
To test how glioblastoma cells responded to nutrition deprivation, we cultured U87 and U343
cells in serum-free medium or medium containing 10% FBS, followed by analysis of miR-17
levels. We found that cells expressed higher levels of miR-17-5p when nutrition was deprived
than that cultured in medium containing serum (Figure 2.2a). The cells were also treated with the
42
chemotherapeutic Temozolomide, followed by analysis of miR-17-5p levels. Treatment with
Temozolomide promoted expression of miR-17-5p (Figure 2.2a).
To determine the role of miR-17 in glioblastoma cells, U87 and U343 cells were stably
transfected with miR-17 expressing plasmid. Control cell lines were also established by using a
plasmid without the miR-17 precursor sequence. The levels of miR-17 were detected by real-
time PCR, which confirmed that the expression of miR-17-5p in the transfected cells was higher
than that in the control cells (Figure 2.2b).
We then tested the roles of miR-17 in regulating cell survival. When U87 (Figure 2.2c) and U343
(Figure 2.3a) cells were starved in serum-free medium, there was an increased amount of
survived miR-17-transfected cells compared to the control.
The abilities of survival and metastasis to large distance are often associated with tumors that are
resistant to chemotherapeutic drug treatment. In order to evaluate metastasis potential, cell
migration and invasiveness were measured by wound scratch assay and transwell test. In cell
migration assay, miR-17-transfected cells migrated faster than the control cells (Figure 2.3b).
Transwell test was also performed in different serum combination inside and outside of
chambers. The experiments showed that more cells in the miR-17 group invaded through the
membrane pores, which confirmed that over-expression of miR-17 could increase cell
invasiveness (Figure 2.3c). In addition, our findings suggested that miR-17 conferred survival
advantage to glioblastoma cells in an unfavorable condition and increased cell motility
accordingly.
43
Figure 2.2 MiR-17 enhances glioblastoma cell survival.
(a) U87 cells were cultured in serum-free or FBS containing medium, followed by analysis of
miR-17 levels. Nutrition deprivation increased miR-17 levels.U87 and U343 cells were also
treated with chemo-drug Temozolomide, followed by analysis of miR-17 levels. Temozolomide
treatment increased miR-17 levels. n = 3 independent experiments.
(b) Real-time PCR was performed to detect the relative mRNA levels in transfected cells. n = 3
independent experiments.
(c) U87 cells were cultured in serum-free DMEM for survival assay. The miR17-overexpression
cells displayed higher ability of survival than the control cells. **p<0.001, Error bars indicate SD,
n = 3 independent experiments. Scale bar = 20 µm.
44
Figure 2.3 MiR-17 enhances glioblastoma cell survival, migration, and invasion.
(a) U343 cells were cultured in serum-free DMEM for survival assay. The miR17-
overexpression cells displayed higher ability of survival than the control cells. **p<0.001, Error
bars indicate SD. n = 3 independent experiments.
(b) The cells were seeded onto 6-well dishes and the monolayers were wounded with a pipette
tip and cultured in 10% FBS/DMEM medium containing 2 μM mytomycin. The distances
between the wounding center and the front of the migrating cells (vertical axis) were measured
for statistical analysis. **, p< 0.01. Error bars indicate SD (n = 10 independent experiments).
(c) The cells were loaded into the insert with 100 l serum-free DMEM medium and then
incubated at 37°C for 24 hours. The invasive cells were stained blue and were counted in 6
randomly selected fields under a light microscope. Expression of miR-17 promoted cell invasion.
**, p< 0.01. Error bars indicate SD (n = 6 independent experiments.). Scale bar, 15 µm.
45
2.4.2 MiR-17 regulates distinct response to starvation and chemotherapy
Tumor expansions rely on sufficient supply of oxygen and other essential nutrients. By inducing
angiogenesis, tumor cells avoid being starved and escape chemotherapy. Emerging data suggest
that angiogenesis of glioblastoma involves the interactions between endothelial cells and tumor
cells (216). Tube-like structure formation is an assay widely used to study angiogenesis in vitro.
When co-cultured with endothelial cell line, YPEN, in low serum medium, the miR-17-
transfected cells induced formation of more tube-like structures than the control cells, but there
was no significant difference when the cells were cultured in medium containing 10% FBS
(Figure 2.4). This led us to explore the expression of HIF-1α and vascular endothelial growth
factor (VEGF), which are the major driving forces of vascularization. Interestingly, HIF-1α was
suppressed in cells cultured in medium containing 10% FBS, but was highly expressed in the
miR-17-transfected cells cultured in serum-free medium (Figure 2.5a). These findings suggest
that HIF-1α could only be activated in starved cells expressing miR-17. HIF-1α is a downstream
factor subjected to the regulation of PTEN, which highlights the possibility that miR-17 might
dominate the PTEN-HIF-1α-VEGF pathway. Once PTEN was down-regulated in cells
overexpressing miR-17, HIF-1α was activated in response to serum deprivation stress. HIF-1α
activation also facilitated up-regulation of VEGF, which was elevated in miR-17-transfected
cells during serum deprivation (Figure 2.5a).
We further found that miR-17 regulated cell response under chemotherapy. When glioblastoma
cells were treated with Docetaxel, miR-17 over-expressed cells survived better than the control
cells (Figure 2.5b). Herein, the half maximal inhibitory concentration (IC50) was calculated and
applied to long-term chemotherapy. Notably, HIF-1α was induced within 1 day in the miR-17-
transfected cells, which was similar to what we found during serum deprivation. However,
activation of HIF-1α could not be maintained after 4 days, which might be due to reduced cell
viability after prolonged treatment (Figure 2.5c). HIF-1α was also reported to be negatively
regulated by VHL, but we did not detect any change of VHL expression levels in either 10%
FBS or serum-free conditions (Figure 2.5d). Given that VHL is specifically sensitive to oxygen
concentration changes, PTEN-HIF-1α-VEGF pathway was shown to mainly mediate
glioblastoma cells’ response to starved conditions (217).
46
Figure 2.4 MiR-17 stimulates angiogenesis upon starvation
The miR-17- and mock-transfected U87 cells were mixed with Ypen cells (1:1) and inoculated in
Matrigel, followed by examination of formation of tube-like structures. The miR-17 expressing
U87 cells formed larger complexes and longer tubes when cultured in medium containing 1%
FBS, but little difference could be seen when cultured in medium containing 10% FBS. Lower,
formation of the tube-like structures was quantified. Scale bars, 20 µm. n = 3 independent
experiments.
47
Figure 2.5 MiR-17 regulates distinct
response to starvation and
chemotherapy
(a) Expression of HIF-1α and VEGF was
elevated in starved miR-17-transfected
U87 cells. Re-probing of beta-actin was
served as loading control.
(b) Cell viability was analyzed in cells
treated with Docetaxel. Increased survival
was seen in the miR-17-transfected cells.
n = 5 independent experiments.
(c) Expression of HIF-1α was elevated one
day after Docetaxel treatment in the miR-
17-transfected U87 cells. Re-probing of
beta-actin was served as loading control.
(d) Expression of VHL in the GFP-mock-
and miR-17-transfected U87 cells. Re-
probing of beta-actin was served as
loading control.
48
Since HIF-1α is involved in response to drug treatment in glioblastoma (212), our data suggested
that miR-17 could confer drug resistance to the cells by regulating the PTEN/HIF-1α pathway.
2.4.3 MiR-17 induces HIF-1α activation in response to stress by targeting
PTEN
PTEN is a tumor suppressor which dominates the PTEN/HIF-1α pathway. Inactivation of PTEN
often allows for the over-expression of HIF-1α, leading to cascade reactions in angiogenesis and
migration. It has been reported that PTEN is a target of the miR-17-92 cluster, and indeed we
detected two potential binding sites for miR-17 in PTEN 3’UTR (Figure 2.6a). Western blot was
employed to analyze PTEN levels in the miR-17-transfected cells. Compared with the control
cells, PTEN was down-regulated in cells over-expressing miR-17 (Figure 2.6b). The luciferase
assay was then employed to determine whether miR-17 could target PTEN directly. Fragments in
PTEN 3’UTR containing the binding sites of miR-17 were cloned into the pMir-report vector.
Constructs with mutated binding sites were also generated to serve as controls (Figure 2.6c). U87
cells were co-transfected with miR-17 plasmid and one of the luciferase constructs. The
experiments showed that luciferase activities were repressed when the luciferase constructs were
co-transfected with miR-17 plasmid, and the inhibitory effect of miR-17 was abolished when the
binding sites were mutated (Figure 2.6d). We then transfected U87 cells with siRNA targeting
PTEN, which confirmed silencing of PTEN expression (Figure 2.7a, left). Down-regulation of
PTEN led to increased expression of HIF-1α (Figure 2.7a, right), and thus prolonged the survival
of the cells (Figure 2.7a, lower).
To confirm that PTEN played an important role in mediating miR-17 function, we transfected
the miR-17-expressing cells with PTEN expression construct or a vector control. After
confirming expression of the ectopic expression of PTEN (Figure 2.7b, upper panel), we
performed cell survival assay. Ectopic expression of PTEN reversed the effect of miR-17 on cell
survival (Figure 2.7b, lower panel).
2.4.4 MiR-17 promotes the generation of tumor stem-like cells
It is generally thought that TSCs play a major role in tumor re-vascularization and re-
aggregation, eventually leading to tumor relapse.
49
Figure 2.6 PTEN is one of
miR-17’s targets
(a) Computational analysis showed
that miR-17 potentially targeted
PTEN at two different sites. (b)
Cell lysate prepared from miR-17-
or mock-transfected U87 cells was
analyzed on Western blot for PTEN
expression to confirm targeting.
Re-probing of beta-actin was
served as loading control. (c) Two
luciferase constructs were
generated, each containing a
fragment harboring the target site
of miR-17, producing Luc-Pten-1
and Luc-Pten-2. Mutations were
generated on the seed regions (red
color), resulting in two mutant
constructs Luc-Pten-1mut and Luc-
Pten-2mut. (d) U87 cells were co-
transfected with miR-17 and each
of the luciferase reporter constructs
or the mutants. The luciferase
reporter vector (Luc) and the vector
harboring a non-related region
(G3R) were used as controls. miR-
17 repressed the activity of Luc-
Pten-1 and Luc-Pten-2 but had no
effect on that of Luc-Pten-1mut and
Luc-Pten-2mut. Error bars, SD (n =
3 independent experiments).
50
Figure 2.7 MiR-17 induces HIF-1α
activation in response to stress by
targeting PTEN
(a) Upper, Cell lysates prepared from U87
cells transiently transfected with siRNA
targeting PTEN or a control oligo were
subjected to Western blot analysis to
confirm PTEN silencing. Re-probing of
beta-actin was served as loading control.
Lower, the cells were grown on 6-well
tissue culture dishes. Cell survival was
determined. n = 3 independent experiments.
(b) Upper, Cell lysate prepared from cells
transiently transfected with PTEN
expression construct or the control vector
was subjected to Western blot analysis to
confirm expression of the construct.
Probing of -actin from the same
membrane confirmed equal loading.
Lower, U87 cells stably transfected with
miR-17 were transiently transfected with
PTEN expression construct or the control
vector and cultured for different days as
indicated for survival assay. *p < 0.05.
Error bars indicate SEM (n=3 independent
experiments.).
51
Although the definition of TSCs is still controversial, CD133, a cell surface glycoprotein, has
been used extensively as a marker of glioblastoma stem-like cells (GSC). GSCs significantly
increase their number in neurospheres when cultivated in SFM containing EGF and FGF. In
order to get the neurospheres, U87 and U343 cells were cultured in SFM for two weeks, and the
sizes of neurospheres formed in cells overexpressing miR-17 were much larger than those
formed in control cells (Figure 2.8, upper panel). To confirm that these spheres were alive, we
continued to maintain the spheres in serum-free medium or serum-containing medium. When
serum was included in the cultures, the spheres adhered to the culture plates, and this is an
indication of cell survival (Figure 2.8, lower panel). Another prominent character of GSCs is that
they can undergo self-renewal and differentiate. We thus tested the self-renewal ability of
glioblastoma cells in SFM and found that the number of secondary spheres formed in cells over-
expressing miR-17 was significantly higher than those formed in the control cells (Figure 2.9a).
We then examined the tumorigenesis of glioblastoma spheroid using the colony formation assay.
After the cells have been grown on agarose-containing plates for three weeks, more colonies
could be seen in miR-17-transfected cells (Figure 2.9b).
GSCs are thought to play an important role in drug resistance. Therefore, we investigated the
effects of chemotherapeutic agents on glioblastoma cells. As expected, overexpression of miR-
17 facilitated cell survival after treating the U343 cells with Docetaxel (Figure 2.9c). We also
treated the miR-17- and vector-transfected U87 cells with Docetaxel, Carmustine and
Temozolomide, followed by analysis of sensitivities of the cells to these drugs. We confirmed
that the cells transfected with miR-17 displayed resistance to all of these drugs (Figure 2.9d).
Additionally, we examined the expression of CD133 using flow cytometry. The percentage of
CD133 positive in the miR-17-transfected cells was much higher than that in the control cells
(Figure 2.10a). Moreover, when plated in serum, these floating neurospheres could differentiate
to adherent cells again. The miR-17-transfected adhesive cells still expressed higher levels of
CD133 than the control cells (Figure 2.10b).
Since we have shown that HIF-1α was up-regulated by miR-17 expression, we explored its
involvement in the generation of GSCs. U87 cells were stably transfected with HIF-1α construct
and plated into serum-free medium. Similar to what we observed in miR-17-transfected cells,
52
Figure 2.8 MiR-17 promotes the generation of tumor stem-like cells
U87 and U343 cells stably transfected with miR-17 or the control vector were cultured in serum-
free medium for two weeks. Cells expressing miR-17 formed significantly larger spheres than
those transfected with the mock control (upper). The sphere cultures were continued to be
maintained in serum-free medium, which induced extensive cell death in the control cells, but
not in the miR-17-transfected cells. Addition of FBS into the cultures induced cell adhesion to
the plate, displaying survivability of the spheres (lower). Scale bars, 15 µm. n = 3 independent
experiments.
53
Figure 2.9 MiR-17 promotes self-renewal and treatment resistance of tumor cells
(a) The numbers of spheres were counted and passaged to new plates for continuing culture.
Spheres formed in the secondary plates were divided by the numbers formed in the primary
plates to evaluate the formation of spheres in the secondary plates. n = 3 independent
experiments. (b) In colony formation assays performed in soft agar, miR-17-expressing cells
form more colonies with larger sizes. Scale bar, 4 mm. n = 3 independent experiments. (c) The
miR-17- and vector-transfected U343 cells were cultured and treated with Docetaxel.
Sensitivities of the cells to the drug were tested. Cells transfected with miR-17 displayed
resistance to Docetaxel-induced cell death. n = 3 independent experiments. (d) The miR-17- and
vector-transfected U87 cells were cultured and treated with Docetaxel, Carmustine and
Temozolomide, followed by analysis of cellular viability. Cells transfected with miR-17
displayed resistance to all drugs. n = 3 independent experiments.
54
Figure 2.10 Overexpression of miR-17 increases CD133 level
(a) The miR-17- and vector-transfected U87 cells were subjected to flow cytometry to measured
CD133 expression. CD133 expression was higher in the miR-17-transfected cells than the
control cells in serum-containing medium (0.31% vs. 0.14%) or serum-free medium (30.6% vs.
0.26%). n = 3 independent experiments. Representative data are shown.
(b) Flow cytometry analysis of CD133 expression level. n = 3 independent experiments.
Representative data are shown.
55
HIF-1α over-expression increased the number of survival cells compared with the control
(Figure 2.11a). Moreover, CD133+ ratio also increased in HIF-1α transfected cells (Figure
2.11b).
2.4.5 MiR-17 reduces glioblastoma cell proliferation
In order to examine the effect of miR-17 on glioblastoma cell growth, a cell proliferation assay
was performed and miR-17-overexpressing cells were found to have a significantly reduced
growth rate (Figure 2.12a). This was in line with cell cycle analysis, in which the percentage of
cells in G1 phase was much higher in miR-17-overexpressed cells as compared with the control
(Figure 2.12b). Our findings indicated that miR-17 inhibited glioblastoma cell proliferation,
which is in agreement with other studies revealing similar results on breast cancer cells (79).
Taken together, these results suggest that miR-17 suppresses glioblastoma cell growth under
normal circumstances.
2.4.6 MiR-17-3p targets MDM2 in glioblastoma cells
We then sought to identify the targets that mediated miR-17 suppressing glioblastoma cell
growth. Taking advantage of the online databases and computational algorithms, we screened a
series of genes that could promote cell proliferation. In silico analysis, MDM2 revealed three
potential binding sites for miR-17-3p in its 3’UTR (Figure 2.13a). MDM2 is an oncogene which
is highly expressed in glioblastoma and it widely participates in tumorigenesis and progression.
It is thought to inhibit the activation of p53, but it can also regulate tumor cell proliferation
independently (218). We found a decreased level of MDM2 in miR-17-overexpressed cells
(Figure 2.13b), but there was no change in p53 expression, which suggests that miR-17 may
function in a p53-independent pathway. To confirm whether miR-17-3p targeted MDM2
directly, we generated three reporter constructs, each containing a fragment of wild-type or
mutated MDM2 3’UTR sequence downstream of a luciferase coding sequence (Figure 2.13c).
U87 cells were co-transfected with miR-17 plasmid and one of the constructs. There was a
decrease in luciferase activities in the cells transfected with the MDM2 3’UTR construct, but the
inhibitory effect was abolished when the miR-17-3p binding sites were mutated (Figure 2.13d).
56
Figure 2.11 HIF-1α overexpression increases cell survival and tumor stem-like cell
generation
(a) Left, U87 cells were transfected with HIF-1 or the mock vector, followed by analysis of cell
survival. Transfection of HIF-1α mimicked miR-17’s function in survival. n = 3 independent
experiments. Right, typical photos are shown. Scale bars, 20 µm.
(b) The HIF-1- and vector-transfected U87 cells were analyzed for CD133 expression.
Transfection of HIF-1α increased CD133 level (2.8% vs. 0.68%). n = 3 independent
experiments. Representative data are shown.
57
Figure 2.12 Expression of miR-17 reduces glioblastoma cell proliferation.
(a) Cell proliferation was inhibited in miR-17-transfected U87 and U343 cells in different fetal
bovine serum (FBS) concentrations. n = 3 independent experiments.
(b) Cell cycle analysis was performed by flow cytometry, which showed that miR-17
overexpression increased the distribution of the cells in G1 phase. n = 3 independent
experiments. Representative data are shown.
58
Figure 2.13 MiR-17-5p and miR-17-3p target MDM2.
(a) Computational analysis showed that miR-17-5p and miR-17-3p potentially targeted MDM2
at three different sites. (b) Cell lysate prepared from miR-17- or mock-transfected U87 cells was
analyzed on Western blot for MDM2 protein expression. MDM2 level was down-regulated in
miR-17-transfected cells. Re-staining of -actin from the same membrane confirmed equal
loading. (c) Three luciferase constructs were generated, each containing a fragment harboring the
target site of miR-17-3p, producing Luc-Mdm2-1, Luc-Mdm2-2, and Luc-Mdm2-3. Mutations
were generated on the seed regions of each target sequence (red color), resulting in four mutant
constructs Luc-Mdm2-1mut, Luc-Mdm2-2mut, and Luc-Mdm2-3mut. (d) U87 cells were co-
transfected with miR-17-3p and each of the luciferase reporter constructs or the mutants. The
luciferase reporter vector (Luc) and the vector harboring a non-related region (G3R) were used
as controls. Asterisks indicate significant differences. Error bars, SD (n = 3 independent
experiments).
59
We then validated whether MDM2 played an essential role in modulating U87 cell activities.
The cells were transfected with siRNA complementary to MDM2. Silencing of MDM2 was
confirmed using Western blotting (Figure 2.14a), and knockdown of MDM2 reduced cell
proliferation (Figure 2.14b). To corroborate this result, we performed rescue experiments by
transfecting U87 cells with MDM2 expression construct. After confirming up-regulation of
MDM2 (Figure 2.14c), the effect of MDM2 on cell proliferation was tested, and we found that
over-expression of MDM2 in the miR-17-transfected cells resulted in enhanced cell growth
(Figure 2.14d).
2.5 Discussion
Given the fact that tumors often develop as a result of an aberrant response to a stress signal, it is
important to determine the molecular biological mechanism involved. The theory of “tumor-
starving therapy” suggests that tumor vascularization is critical to its survival. Therefore,
bevacizumab, a monoclonal antibody against VEGF, has been approved to treat glioblastoma. It
is believed to be able to starve tumors by blocking their blood supply. Nevertheless, highly
penetrant tumor growth patterns in bevacizumab-treated patients have been repeatedly
documented (219). It is believed that a subpopulation of cells is resistant to “starving” treatment.
Here we identify that miR-17-transfected glioblastoma cells survived longer under starved stress,
with the potential to develop the tube-like structures of endothelial cells and to enrich GSCs.
These may facilitate angiogenesis and increase the number of TSCs.
Our results revealed the unique response of HIF-1α to stimuli, suggesting a role of HIF-1α in
mediating miR-17 functions. As a key transcription factor evoked upon exposure to hypoxia,
HIF-1α can be observed best at a distance from blood vessels in tissue, but is absent immediately
when oxygenated. In general, HIF-1α is ubiquitinated and degraded by VHL under normoxia but
activated under hypoxia. In addition to that, it can be regulated by other suppressors such as
PTEN and MDM2 (220). PTEN’s loss of function results in HIF-1α activation by dysregulation
of the PI3K/AKT pathway, especially in glioblastoma cells (221). The PTEN/PI3K/AKT
pathway has been experimentally shown to be associated with stress adaptation, such as serum
deprivation (222). We showed that PTEN was one of the targets of miR-17 in glioblastoma cells.
MiR-17 could respond to stress signals by targeting PTEN, suggesting our findings might be of
60
Figure 2.14 Confirmation of miR-17’s functions by silencing and rescue assays.
(a) Cell lysates prepared from U87 cells transiently transfected with siRNA targeting MDM2 or
a control oligo were subjected to Western blot analysis probed with anti-MDM2 antibody to
confirm silencing of MDM2. Re-probing of beta-actin was served as loading control. (b) U87
cells transiently transfected with different amount of the siRNA or the control oligo were grown
on 6-well tissue culture dishes. Cell proliferation was recorded accordingly. n = 3 independent
experiments. (c) Western-blot analysis of cells transiently transfected with MDM2 expression
construct or the control vector. Re-probing of beta-actin was served as loading control. (d) U87
cells stably transfected with miR-17 were transiently transfected with MDM2 expression
construct or the control vector and cultured for different days as indicated for proliferation assay.
n = 3 independent experiments. (e) Proposed signal transduction showing the pathway by which
miR-17 functioned.
61
clinical implication. Firstly, because glioblastoma is characterized by its uncontrolled
vascularization and high expression of miR-17 in tumor samples, miR-17 may take part in the
process of glioblastoma angiogenesis by activating HIF-1α and VEGF indirectly. Secondly, since
miR-17 endows cells with the ability to escape “tumor-starving therapy” by increasing survival
and motility, cautions should be taken when treating patients with anti-angiogenesis therapy,
especially for those who have tumors that are over-expressing miR-17.
We also demonstrated that miR-17 has dual roles in cell growth: it reduces the tumor
proliferation rate, but protects cells from cytotoxic agents’ treatment. This is consistent with our
previous data that elucidated that slower growing cells are more resistant to chemotherapy-
induced cell death (83). Currently, chemotherapeutic agents that are commonly used in treating
glioblastoma act by interfering with DNA replication, such as temozolimide and carmustine. It is
conceivable that fast growing tumor cells are much easier suffered from cytotoxic agents
compared with slower growing cells. MiR-17 therefore can induce chemo-resistance on
glioblastoma cells by slowing down their proliferation. In addition, a reduced cell proliferation
rate also benefits cells under starved conditions because a slower metabolic rate requires limited
nutritional supply. Thus, by targeting both MDM2 and PTEN simultaneously, miR-17 could act
through several modes to regulate stress response. Very recently, similar finding were reported
on other microRNAs (miR-141 and miR-200a) which potentially modulate the oxidative stress
response in ovarian carcinogenesis (23). It was concluded that miR-141 and miR-200a promoted
tumor growth but sensitized tumors to chemotherapy, which was in agreement with our
perspectives. These data support the emerging model of microRNA: a buffering function. This
refers to a microRNA’s ability to target several pathways as both a positive and a negative
regulator (30). Documented examples have shown that the buffering function of microRNA is
critical to maintain homeostasis in the systemic network (201, 207). It has been proposed that
MDM2 can also ubiquitinate and degrade HIF-1α through the proteasome pathway, which raises
the possibility that miR-17 mediates cellular response to diverse stimuli by targeting closely
related signaling pathways (223).
The ability of miR-17 to induce generation of glioblastoma stem-like cells is another interesting
finding of our work. Although the role of microRNAs in the development of TSC has been
studied extensively, there is still no general agreement on the definitions of TSCs in vitro (163,
62
164). It is known that TSCs can both undergo self-renewal and differentiate into a spectrum of
mature cells. Moreover, recent discoveries indicate that they are widely involved in tumor
progression, therapy resistance and distant metastasis. In glioblastoma, serum-free medium is a
well-established method to enrich GSCs which can be detected by CD133 expression (224, 225).
Serum contains essential nutrition factors for tumor cell growth. During tumor progression to an
advanced stage, it could be deprived of serum, under the stress of growth factor deficiency. In
this study we reported that miR-17 not only increased CD133 positive cells when cultured in
SFM, but also increased capacities of self-renewal and colony formation ability. This may be due
to the activation of HIF-1α, which was documented to promote neurosphere formation in SFM
(226). To support this, we over-expressed HIF-1α in glioblastoma cells and measured the
changes of GSCs. Not surprisingly, there was increased number of GSCs in HIF-1α-transfected
cells compared with that of the control cells. Our findings confirm the critical role of HIF-1α in
GSCs development and maintenance. More importantly, GSCs are often thought to be
responsible for drug resistance, which may be another potential mechanism accounting for
chemo-resistance in tumor cells over-expressing miR-17. At last, we found that miR-17
increased tumor cell migration and invasiveness, which can also be found in neural stem cells
(225). Taken together, miR-17 induced the generation of GSCs which display stem-like
behaviors in multiple ways.
In summary, our findings reveal a novel mechanism of stress response in glioblastoma cells.
During serum deprivation, miR-17 prolonged tumor cell survival, induced angiogenesis and
promoted stem-like cell aggregation by repressing expression of MDM2 and PTEN and
modulating HIF-1α levels. We thus proposed a signal pathway delineating miR-17 activities
(Figure 2.14e). This adds new insights to our knowledge about microRNAs as mediators in
tumor development. It has practical implications on clinical diagnosis and treatment. In
glioblastoma patients, miR-17 could be used as a predictive marker of response to chemotherapy
and anti-angiogenesis treatment.
63
Chapter 3
MicroRNA Regulates Chemotherapeutic Drug Resistance
(A version of this chapter section is published in Oncotarget(227))
64
3 MicroRNA-17-5p Promotes Chemotherapeutic Drug
Resistance of Colorectal Cancer by Regulating PTEN
3.1 Abstract
Backgrounds: Colorectal cancer (CRC) is one of the most common cancers worldwide,
especially in Western countries. Although chemotherapy is used as an adjuvant or as a palliative
treatment, drug resistance poses a great challenge. In previous studies, we demonstrated that
dysregulation of the microRNA (miRNA) functional network could be responsible for drug
resistance in cancer treatments.
Methods: By microarray analysis, we studied miRNAs expression profiles in CRC patients,
comparing chemoresistant and chemosensitive groups. The miRNAs of interest were validated
and the impact on clinical outcomes was assessed in a cohort of 295 patients. To search for
potential targets of these miRNA, tissue samples were subject to in situ hybridization and
immunohistochemistry analysis. Colorectal adenocarcinoma cells were also used for in vitro
experimentation, where cellular invasiveness and drug resistance were examined in miRNA-
transfected cells.
Results: The expression level of miRNA-17-5p was found increased in chemoresistant patients.
Significantly higher expression levels of miR-17-5p were found in CRC patients with distant
metastases and higher clinical stages. Kaplan-Meier analysis showed that CRC patients with
higher levels of miR-17-5p had reduced survival, especially in patients who had previously
received chemotherapy. Overexpression of miR-17-5p promoted COLO205 cell invasiveness.
We found that PTEN was a target of miR-17-5p in the colon cancer cells, and their context-
specific interactions were responsible for multiple drug resistance. Chemotherapy was found to
increase the expression levels of miR-17-5p, which further repressed PTEN levels, contributing
to chemo-resistance.
Conclusions: MiR-17-5p is a predictive factor for chemotherapy response and a prognostic factor
for overall survival in CRC, which was due to its regulation of PTEN expression.
65
3.2 Introduction
Colorectal cancer (CRC) is one of the leading causes of cancer mortality worldwide. It is
estimated that over one million people develop colorectal cancer every year, especially in
western countries (228). Current guidelines recommend that treatments should be considered
based on tumor stages. In potentially curable patients, surgery remains the mainstream treatment
course, with or without adjuvant radiation and chemotherapy. In patients at advanced stagestu,
palliative chemotherapy has been demonstrated to improve survival, by preventing tumor
invasion or downsizing distant metastatic lesions. In the past three decades, the use of
fluorouracil (5-FU), combined with irinotecan and oxaliplatin has been shown to double overall
survival (229). However, drug resistance poses a great challenge in treating chemorefractory
patients. One of the most challenging tasks is to identify patient subpopulations that are most
likely to respond to specific therapies. Therefore, understanding the mechanisms underlying
chemoresistance may help identify subgroup of patients who may benefit from chemotherapy
and avoid over-treatment. Despite enormous efforts, only a few predictive and prognostic
biomarkers have been validated clinically (230). Studies have shown that multiple cellular
processes including DNA repair, cell apoptosis and proliferation may play important role in
chemoresistance (231-233). Several clinical studies have been performed in an attempt to find
biomarkers predicting benefit from chemotherapy. However, with the exception of KRAS
mutations, none of these studied markers have entered into the clinical management of colorectal
cancer (234). Given that complex signaling pathways and their cross-talk contribute to
chemoresistance in a temporal- and spatial-specific manner, single molecular markers might not
be sufficient to predict entire clinical outcomes. Thus, there is a great demanding to identify
better markers that can enhance the prognostic strength in the clinical setting.
In recent years, microRNAs (miRNAs) have been recognized as key regulators of gene
expression at the post-transcriptional level (235). They are broadly involved in tumor
proliferation, invasion and angiogenesis (1). High-frequency miRNA dysfunction is also
associated with colorectal cancer development and progression (236). It has been shown that
miRNAs can be used as biomarkers for cancer detection. One miRNAs may be able to target
several pathways, facilitating tumor cells evasion of drug treatment and generating stem-like
cells (237). Therefore, it is of value to illuminate whether dysregulation of these miRNAs-
regulatory networks are also responsible for chemorefractory colorectal cancer.
66
3.3 Materials and Methods
3.3.1 Patients
Fifteen patients with primary colorectal cancer who underwent neoadjuvant chemotherapy
containing fluorouracil (5-FU) at the Department of Colorectal Surgery, the Sixth Affiliated
Hospital of Sun Yat-Sen University, were enrolled into the present study. Tumor specimens were
obtained by colonoscopy prior to starting therapy. The effect of chemotherapy on the tumors was
assessed as the three-dimensional volume reduction rate or tumor response rate. The tumor
response was evaluated by the Response Evaluation Criteria in Solid Tumors (RECIST), which
is defined as the following: complete response (CR; disappearance of the disease), partial
response (PR; reduction of ≥30%), stable disease (SD; reduction <30% or enlargement ≤20%),
or progressive disease (PD; enlargement ≥20%). Among them, 7 patients were defined CR/PR,
and 8 patients were defined SD/PD.
Paraffin-embedded samples of primary colorectal adenocarcinomas were included from 295
patients, who underwent tumor resection between 2001 and 2005 at the First Affiliated Hospital
of Sun Yat-Sen University. This cohort of patients with CRC included 153 (51.9%) men and 142
(48.1%) women, with a median age of 59 years, and their clinic-pathological characteristics are
summarized in Table 2. The cases selected were based on a distinctive pathological diagnosis of
CRC, undergoing primary and curative resection for CRC, availability of resection tissue,
follow-up data, and had not received preoperative anticancer treatment. Our study protocol was
approved by The Ethics Committee of the First Affiliated Hospital of Sun Yat-sen University.
3.3.2 Microarray
Total RNAs were extracted from tissues of six primary colorectal cancer patients using the
mirVana miRNA extraction kit (Ambion) according to the manufacturer’s instructions. The
quality control of RNA was performed by a 2100 Bioanalyzer using the RNA 6000 Pico
LabChip kit (Agilent Technologies, Santa Clara, CA). The microarray was performed at the
Shanghai Biochip Company by using the Agilent Human miRNA microarray Kit version 12.0.
Total RNA (100 ng) derived from each of the specimens were used as inputs for labelling via
67
Table 2 Correlation between expression of miR-17 and clinicopathological features in 295
cases of colorectal cancer
Mir-17
All cases Low
expression
Overexpression P Value
Sex 0.423
Male 153 (51.9) 110 (53.4) 43 (48.3)
Female 142 (48.1) 96 (46.6) 46 (51.7)
Age 0.536
<58.8 134 (45.5) 96 (46.6) 38 (42.7)
>58.8 161 (54.5) 110 (53.4) 51 (57.3)
Tumor location 0.732
Colon 148 (49.8) 104 (50.5) 43 (48.3)
Rectum 149 (50.2) 102 (49.5) 46 (51.7)
Histological
grade
0.353
G1 24 (8.1) 17 (8.3) 7 (7.9)
G2 225 (76.3) 161 (78.2) 64 (71.9)
G3 46 (15.6) 28 (13.6) 18 (20.2)
pT status 0.443
1 8 (2.7) 5 (2.4) 3 (3.4)
2 41 (13.9) 30 (14.6) 11 (12.4)
3 241 (81.7) 166 (80.6) 75 (84.3)
4 5 (1.7) 5 (2.4) 0 (0)
pN status 0.874
0 181 (61.4) 127 (61.7) 54 (60.7)
1 114 (38.6) 79 (38.3) 35 (39.3)
pM status 0.004
pM0 265 (89.8) 192 (93.2) 73 (82.0)
pM1 30 (10.2) 14 (6.8) 16 (18.0)
Clinical stage 0.030
I 32 (10.8) 22 (10.6) 10 (11.2)
II 129 (43.4) 94 (45.2) 35 (39.3)
III 106 (35.7) 78 (37.5) 28 (31.5)
IV 30 (10.1) 14 (6.7) 16 (18.0)
Chemotherapy 0.657
No 214 (72.5) 151 (73.3) 63 (70.8)
Yes 81 (27.5) 55 (26.7) 26 (29.2)
68
Cy3 incorporation. Microarray slides were scanned by XDR Scan (PMT100, PMT5). The
labelling and hybridization were performed according to the protocols in the Agilent miRNA
microarray system.
3.3.3 RNA isolation and quantification of miRNA by qRT-PCR
RNA samples were isolated from harvested cells using Trizol reagent (Invitrogen) according to
the manufacturer’s instructions. miRNA expression was quantified by two-step quantitative RT-
PCR, beginning with first-strand cDNA synthesis using the One-step primeScript miRNA cDNA
Synthesis Kit (Takara), followed by quantitative real-time PCR using the miRscript SYBR Green
PCR kit in a 7500 Real-Time PCR system. The mature miRNA-specific forward primer was
purchased from Takara (DHM0136) and the universal reverse primer was provided by the
manufacturer. RNA quantity was normalized using U6 snRNA, and fold change of expression
was calculated according to the 2-△△ct
method.
3.3.4 Tissue Microarrays
The tissue microarray (TMA) was conducted using paraffin-embedded tissues. In brief, the
paraffin-embedded tissue blocks and the corresponding histological H&E stained slides were
overlaid for tissue TMA sampling. Duplicate of 0.6 mm diameter cylinders were punched from
representative tumor areas of individual donor tissue block, and re-embedded into a recipient
paraffin block at a defined position, using a tissue arraying instrument (Beecher Instruments,
Silver Spring, MD).
3.3.5 In situ hybridization and Immunohistochemistry
For in situ hybridization, tissue slides were deparaffinized and digested with proteinase K for 30
min. The slides were then prehybridized in a hybridization solution at 57℃ for 2 hours. Ten
picomoles of digoxingenin-labeled miRCURY LNA detection probes (Exiqon) complementary
to U6 or miR-17-5p or scrambled microRNA were added and hybridized at 55℃ for 1 hour.
After stringent washes, an immunologic reaction was carried out by using the biotinylated sheep
antibody against digoxingenin (Roche) and with alkaline phosphatase streptavidin (Zhongshan
Golden Bridge Biotechnology Company) to detect biotinylated probes.
69
For immunohistochemistry, the paraffin sections were incubated with primary antibody against
PTEN (1:100, CST, USA). For negative control, isotype-matched antibodies were applied. Each
slide was assigned a score for density and intensity. Slides were mounted with mounting medium
and analyzed using a Leica DMI4000B microscope. Each slide was assigned a score for intensity
and staining positive pattern.
The percentage of positive tumor cells was set as follows: 1 (up to 25% of positive cells), 2 (25%
to 50% of positive cells), 3 (50% to 75% of positive cells) and 4 (more than 75% of positive
cells). Intensity scores ranged from 0-3: 0, no staining; 1, weak staining; 2, moderate staining,
and 3, strong staining. Multiplication of the two scores resulted in a final score ranging from 0 to
12. Under these conditions, samples with score 0-6 and score 8-12 were defined as low and high
expression.
3.3.6 Cell cultures
Human colorectal adenocarcinoma cell lines COLO205 (CCL-222) and SW480 (CCL-228) were
cultured in Dulbecco's Modified Eagle's Medium (DMEM) supplemented with 10% fetal bovine
serum (FBS), penicillin (100 U/mL) and streptomycin (100 U/mL). Cells were allowed to grow
in a humidified incubator containing 5% CO2 at 37℃ and subcultured every 3-4 days.
3.3.7 Construct generation
We generated a cDNA sequence which contains a pair of human pre-miR-17 units, a CMV
promoter driving expression of green fluorescence protein (GFP) and an H1 promoter. It was
then inserted into an expression vector pEGFP-N1 between the restriction sites BglII and
HindIII. Successful transfected cells were screened by using green fluorescence and cultured in
media with G418 at the concentration of 1 mg/ml.
For luciferase assay, computational analysis showed two potential binding sites for miR-17-5p in
the 3’-untranslated region (3’UTR) of PTEN. Thus, two pairs of primers were used to clone the
fragments as well as mutant controls. The PCR products were then digested with SacI and MluI,
followed by insertion into a SacI- and MluI-digested pMir-Report vector (Ambion) to obtain a
luciferase construct or a mutant counterpart. In PTEN rescue test, the PTEN cDNA with coding
region was purchased from Origene.
70
3.3.8 Real-time PCR analysis
For real-time PCR analysis, total cellular RNA was extracted by using the mirVana miRNA
Isolation Kit (Ambion) according to the manufacturer’s instructions. The cDNA products were
synthesized by using 1 μg RNA in successive reverse transcription PCR, which was performed
using miScript Reverse Transcription Kit (Qiagen). The primers specific for mature miR-17-5p
were purchased from Qiagen and real-time PCR was performed by using miScript SYBR
GreenPCR Kit (Qiagen). The primers used as controls for real-time PCR were Human-U6RNA.
3.3.9 Cell activity tests
In cell proliferation assay, transfected COLO205 and SW480 cells were plated onto 12-well
tissue culture plates at a density of 1x105 cells/well for 5 days. Meanwhile, survival assay was
performed by keeping the cells (1x106 cells/well) in serum-free medium for 10 days. The cells
were harvested and cell number was counted in different time points.
To test drug sensitivity, fluorouracil (Valeant Pharmaceuticals), eloxatin (Oxaliplatin) (Sanofi-
Aventis) and irinotecan (Pfizer) were applied to adhered cell cultures. These drugs were
purchased from the Pharmacy Department at Sunnybrook Health Sciences Centre. The cell
number was counted 12 hours after drug loading to the cultures by Trypan Blue staining. They
were also subjected to apoptosis assay by flow cytometry.
For wound scratch assay, monolayer of cells was scraped linearly with micropipette tips
(BioMart) and washed to remove cell debris. To diminish the impact of proliferation, the cultures
were treated with Mitomycin C (Sigma) at 200 µg/mL for two hours beforehand. Microscopic
images were captured at the beginning, 24 hours and 48 hours intervals, and the migrated
distance was quantified. In the transwell invasion assay, 24-transwell (Coster) was coated with
100 μL BD MatrigelTM (BD Biosciences). COLO205 cells at a density of 1x105/100 μL were
suspended in DMEM media and transferred into the upper chamber of the transwell. The lower
chamber was filled with 600 μL DMEM media containing 10% FBS. After incubation for 12
hours, non-migrated cells were removed with cotton swab and invaded cells were stained with
Coomassie brilliant blue (Bio-Rad).
71
3.3.10 Western blot
In Western blot analysis, cell lysates were collected from the cultured cells, which were subject
to sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE). The proteins
separated on SDS-PAGE were transferred onto a nitrocellulose membrane (Bio-Rad). The
membrane was then blocked in Tris-Buffered Saline and Tween 20 (TBST: 10 mM Tris-Cl, 150
mM NaCl and 0.05% Tween 20) containing 10% skim milk powder for 30 minutes. It was then
incubated at 4℃ overnight with mouse monoclonal anti-PTEN antibody (Abcam). After washing
for 30 minutes, secondary goat anti-mouse IgG (Vector) was applied to nitrocellulose membrane
in TBST for 1 hour. After washing for 1 hour, the proteins of interest were visualized by using
Chemiluminescent HRP Antibody Detection Kit (Denville Scientific).
3.3.11 Flow cytometry
For cell cycle analysis, cells in the logarithmic phase of growth were harvested and washed twice
in PBS. Following adjustment of a cell concentration to 2x106 cells/mL in 50 µL PBS/HBSS
with 2% calf serum, 1 mL 80% ice cold ethanol was added and incubated for 30 minutes. The
cells were re-suspended in 500 µL HBSS containing 0.1 mg/mL of Propidium Iodide (Sigma)
and 0.6% of NP-40. The DNA content was measured by flow cytometry (Beckman Coulter).
Cell apoptosis was detected by using Annexin V-FITC Apoptosis Detection Kit (BD
Pharmingen). According to the manufacture’s instruction, 1x106 cells were washed twice in PBS
before re-suspension in 50 µL HBSS with 2% calf serum. Annexin V-FITC and Propidium
Iodide of 5 µL respectively were added and stained on ice for 30 minutes. The cells were re-
suspended to 500 µL HBSS and flow cytometry analysis was conducted within 30 minutes. The
data were analyzed using FlowJo9.1 software.
3.3.12 Luciferase activity assay
Luciferase activity assays were performed as previously described (237). COLO205 and SW480
cells were seeded onto 12-well tissue culture dishes at a density of 1x105 cells/well and co-
transfected with the luciferase reporter constructs and miR-17-5p mimic with Lipofectamine
2000. After 12 hours, cell lysate was prepared by using Dual-Luciferase® Reporter Assay Kit
(Promega) and luciferase activity was detected by microplate luminescence counter (Perkin
Elmer).
72
3.4 Results
3.4.1 Expression of miR-17 in the course of colorectal cancer chemoresistance
To search for potential miRNA targets in the course of colorectal cancer (CRC) chemoresistance,
we started with the analysis of the miRNA expression profiles of CRC tissues collected before
neoadjuvant chemotherapy. A comparison of miRNA expression levels between chemoresistant
and chemosensitive groups are shown (Figure 3.1). There were six miRNAs (miR-17-5p, miR-
19b, miR-20a, miR-592, miR-7 and miR-93) showing consistently elevated levels in
chemoresistant patients. Among them, miR-17-5p, miR-19b, miR-20a, miR-93 belonged to the
miR-17~92 cluster and one of its paralogous clusters, miR-106b~25. Their overexpression has
shown to be associated with many malignancies such as leukemia, liver and prostate cancer
(238). To confirm their potential roles in chemoresistance, validation experiments were carried
out by qRT-PCR in seven chemoresistant and eight chemosensitive colorectal cancer samples.
We found that the chemoresistant colorectal cancer samples had a significantly higher level of
miR-17-5p than those obtained from chemosensitive colorectal cancer patients (Figure 3.2,
p=0.001, Mann Whitney test).
We further analyzed the association between miR-17-5p expression and therapeutic outcomes in
CRC patients treated with adjuvant chemotherapy. The chemotherapy regimens were primarily
fluorouracil-based, with leucovorin and oxaliplatin. Kaplan-Meier analysis demonstrated that
high miR-17-5p expression was associated with a worse prognosis in CRC patients with
chemotherapy (p=0.001), further indicating its potential as a predictive biomarker for
chemotherapy (Figure 3.3). Multivariate Cox regression showed increased miR-17-5p expression
was predictive of a worse prognosis in CRC patients receiving chemotherapy (Table 3, HR 4.06,
95% CI 1.24 to 13.36, p=0.021). Therefore, miR-17-5p expression emerged as a predictive factor
in the clinical outcomes of CRC patients treated with chemotherapy. We then analyzed
association between miR-17-5p expression and survival in both early stage (Stage I and II) and
late stage (Stage III and IV) CRC patients. A significant relationship between expression of miR-
17-5p and overall survival rate in early stage CRC patients was not found. However, Kaplan-
Meier analysis indicated that in late stage CRC patients, high miR-17-5p expression levels were
associated with a worse prognosis, especially for patients who had received chemotherapy
(Figure 3.3).
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Figure 3.1 Comparison of miRNA expression in six CRC patients
Compare miRNA expression of 3 chemoresistant and 3 chemosensitive patients samples by
using the Agilent Human miRNA microarray. Results showed that the expression of miR-17
levels in chemosensitive patients samples were higher.
74
Figure 3.2 Validation of microRNA-17’s expression in fifteen CRC patients
A validation experiment was carried out using qRT-PCR. Expression of mir-17 from fifteen
primary colorectal cancer samples from patients who consecutively underwent neoadjuvant
chemotherapy were analyzed. Among them, 7 patients were defined CR/PR, 8 patients were
defined SD/PD. Chemoresistant cancer samples have significantly higher expression of mir-17
(p=0.0012, Mann Whitney Test).
75
Figure 3.3 Expression of miR-17 is associated with poor survival in colorectal cancer.
Association between miR-17-5p expression and overall survival in 81 patients with
chemotherapy and 214 patients without chemotherapy: high levels of miR-17-5p were associated
with worse survival in colorectal patients, especially in those who received chemotherapy. For
patients with cancer stages Ⅲ and Ⅳ, high levels of miR-17-5p were significantly associated
with poor survival, especially among those who received chemotherapy (p=0.002, Kaplan-Meier
log rank test).
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Table 3 Univariate and multivariate analysis of different prognostic parameters in 81
colorectal cancer patients with chemotherapy
Univariate analysis Multivariate analysis
Variable All
cases
Mean survival
(years)
P
Value
HR (95% CI) P
Value
Sex 0.091 0.019
Male 45 7.026 1
Female 36 6.122 4.371(1.272 to 15.020)
Age 0.896 0.292
<58.8 48 6.668 1
>58.8 33 6.563 1.826(0.595 to 5.601)
Tumor location 0.032 0.019
Colon 43 7.166 1
Rectum 38 6.002 4.085(1.264 to 13.199)
Histological grade 0.991 0.573
G1-G2 59 6.652 1
G3 22 6.539 0.711(0.217 to 2.331)
pT status 0.803 0.999
T1-T2 6 6.987 1
T3-T4 75 6.613 1.001(0.162 to 6.184)
pN status 0.317 0.211
N0 37 6.911 1
N1 44 6.363 2.176(0.643 to 7.364)
pM status <0.001 <0.001
pM0 73 7.009 1
pM1 8 3.147 20.494 (4.657 to
90.297)
miR-17
expression
0.001 0.021
Low expression 55 7.286 1
Overexpression 26 5.257 4.062 (1.235 to
13.355)
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3.4.2 MiR-17-5p induces drug resistance in colorectal cancer cells
To further dissect the function of miR-17-5p’s function in colorectal cancer, we stably
transfected a miR-17 overexpression plasmid and its control vector expressing a non-related
sequence into colorectal cancer cell lines COLO205 and SW480. The construct we developed
contained a pair of human pre-miR-17 units, which were used to generate over expression of
mature miR-17-5p (Figure 3.4a). RT-PCR was used to verify increased levels of miR-17-5p in
the transfected cells, as compared with the control cell lines (Figure 3.4b). As mentioned above,
miR-17-5p is negatively related with chemosensitive status in CRC patients. Based on MTT
assay, we applied cytotoxic drugs (Oxaliplatin, Irinotecan, and Fluorouracil) at the half maximal
inhibitory concentration (IC50) to cultured COLO205 cells. After 12 hour treatment, miR-17-
transfected cells showed greater resistance towards these chemotherapeutic agents, with more
cells surviving after the treatment (Figure 3.4c, d). We then conducted an apoptosis assay to
verify our findings through flow cytometry and found that miR-17 overexpression decreased
cellular apoptosis induced by chemotherapeutic treatments (Figure 3.5a).
In a previous study, we found that the loss of PTEN resulted in activation of downstream
signaling pathways, which accounted for the drug resistance observed in cancer cells (237). To
trace the change of PTEN during the course of chemotherapy, we analyzed the levels of PTEN
expression by Western blot assay. Although PTEN was down-regulated in the miR-17-
transfected cells before Irinotecan treatment, a much more drastic decrease was observed
following Irinotecan treatment (Figure 3.5b). We found a concomitant up-regulation of miR-17-
5p, which was substantially increased in response to chemotherapeutic treatment (Figure 3.5c). It
appears that targeting of PTEN by endogenous miR-17-5p became a prominent factor in cellular
stress induced by the chemotherapeutic regimens. We hypothesize that miR-17-5p is a central
mediator of chemoresistance, enabling colorectal cancer cells to escape chemotherapy.
3.4.3 PTEN as a target of miR-17-5p in colorectal cancer cells
PTEN is a tumor suppressor which dominates the PTEN/AKT/PI3K pathway. Loss of PTEN and
activation of AKT has been reported in many types of cancers, including hepatocellular
carcinoma, prostate adenoma and colorectal cancer (239). Through computational analysis, we
found that the 3’-untranslated region of PTEN mRNA contained two binding sites for miR-17-5p
78
Figure 3.4 MiR-17 overexpressing construct and its functions
(a) Structure and sequence of miR-17 expression construct. (b) Real-time PCR was performed to
measure miR-17-5p levels in transfected cells. Increased RNA levels were observed in the miR-
17-transfected cells compared to vector control. n = 3 independent experiments. (c, d) COLO205
cells were treated with Oxaliplatin, Irinotecan and fluorouracil (5-FU) overnight, followed by
counting cell number. More cells survived in miR-17 overexpression group. Scale bar, 20 µm. n
= 3 independent experiments.
79
Figure 3.5 MiR-17 induces multiple drug resistance in colorectal adenocarcinoma cells.
(a) COLO205 cells were treated with Oxaliplatin, Irinotecan and fluorouracil overnight,
followed by analysis of apoptosis. There were fewer cells undergoing apoptosis in the miR-17
overexpression group. n = 3 independent experiments. Representative data are shown. (b) Cell
lysate prepared from miR-17- or mock-transfected COLO205 cells was analyzed on Western blot
for PTEN expression. While cells transfected with miR-17 expressed lower level of PTEN than
the control, treatment with Irinotecan further decreased PTEN levels, especially in cells
overexpressing miR-17. Re-probing of beta-actin was served as loading control. (c) COLO205
cells were cultured in medium with or without Irinotecan, followed by analysis of miR-17-5p
levels. Irinotecan treatment increased miR-17-5p levels, especially in the cells transfected with
miR-17 overexpression plasmid. n = 3 independent experiments.
80
(Figure 3.6a). Western blot analysis was thereby performed and PTEN was to be found
decreased in miR-17-transfected cells (Figure 3.6b). We then generated firefly luciferase reporter
constructs with the 3’UTR of PTEN mRNA, and transfected them into colorectal cancer cells
with miR-17-5p mimics. We found that co-transfection with miR-17-5p in SW480 and
COLO205 cells decreased luciferase activity when the construct contained the 3’UTR of PTEN
(Figure 3.6c, d). Mutation of the binding sites reversed the observed inhibitory effects.
Next we conducted In Situ Hybridization (ISH) assays to detect miR-17-5p expression in
colorectal cancer tissues. PTEN expression was also analyzed by immunohistochemistry (IHC)
in these samples (Figure 3.7a). In cancer tissues where miR-17-5p was overexpressed (Figure
3.7aV), PTEN was down-regulated (Figure 3.7aVI). Consistent with this, low expression of miR-
17-5p was correlated with high PTEN expression (Figure 3.7aVII vs. Figure 3.7aVIII). We
further validated the association between miR-17-5p and PTEN expression levels in 295
colorectal cancer specimens. MiR-17-5p was found elevated in 89 samples, 53 of which showed
reduced expression levels of PTEN. By Pearson Chi-square test, it was shown that miR-17-5p
was inversely correlated with PTEN expression (p=0.006) (Figure 3.7b).
We then tested whether PTEN mediated the survival effects observed in cancer cells treated by
chemotherapy. When treated with siRNA against PTEN, more cells survived after
chemotherapeutic treatment (Figure 3.8a). More importantly, reconstruction of PTEN expression
sensitized these cells to cytotoxic drugs, with more cells undergoing apoptosis and cell death
(Figure 3.8b). By complementary binding to miRNA, antagomir or antisense small RNAs can
arrest miRNA’ functioning by preventing further processing (167). When we transiently
transfected antisense oligos against miR-17-5p into COLO205 cells, we found that the cells
became more sensitive to drug treatment than control cells (Figure 3.9a). Increased drug
sensitivity was observed in anti-miR-17-transfected cells, co-cultured overnight with
fluorouracil, irinotecan and oxaliplatin. These results suggested that miR-17 could be a
therapeutic target in the treatment of chemorefractory colorectal cancer.
3.4.4 Relationship between miR-17-5p expression and overall survival of CRC
patients
We assessed the impact of mir-17 expression on overall survival in a patient cohort. The
clinicopathological characteristics of the CRC patients are summarized in Table 2. The testing
81
Figure 3.6 PTEN is targeted by miR-17-5p in colorectal adenocarcinoma cells
(a) Computational analysis showing that miR-17-5p targets PTEN at two different sites. (b)
Western blot showing repression of PTEN in the miR-17-transfected cells. Re-probing of beta-
actin was served as loading control. (c) SW480 cells were co-transfected with miR-17 and each
of the luciferase reporter constructs or the mutants. The luciferase reporter vectors (Luc) were
used as controls. n = 3 independent experiments. (d) COLO205 cells were co-transfected with
miR-17 and each of the luciferase reporter constructs or the mutants. The luciferase reporter
vectors (Luc) were used as controls. MiR-17-5p repressed the activity of Luc-Pten-1 and Luc-
Pten-2 but had no effect on that of Luc-Pten-1mut and Luc-Pten-2mut. Error bars, SD (n = 3
independent experiments).
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Figure 3.7 PTEN expression is negatively associated with miR-17-5 level in colorectal tissue
(a) In Situ Hybridization (ISH) of miR-17-5p expression and immunohistochemistry (IHC) of
PTEN in colorectal cancer specimens. The positive ISH staining was expressed as blue-violet
and the positive IHC staining was brown. (I) Staining of U6 in cancer sample (positive control).
(II) Staining of U6 in normal colon tissue. (III) Staining of scramble control probe in cancer
sample (negative control). (IV) Staining of scramble control in normal colon tissue. (V and VII)
Representative staining of miR-17-5p in patient 1 (P1 showing high level of miR-17-5p) and
patient 2 (P2 showing low level of miR-17-5p). (VI and VIII) Representative staining of PTEN
in patients 1 and 2. Top panel:×200; middle panel: ×100. Scale bars, 50 µm.
(b) Mir-17-5p expression was inversely associated with expression of PTEN. P value was
calculated by Pearson Chi-square test.
83
Figure 3.8 MiR-17-5p promotes multiple drug resistance by regulating PTEN
(a) COLO205 cells transiently transfected with siRNA targeting PTEN or a control oligo were
subject to apoptosis assay after cytotoxic drug treatment. Down-regulation of PTEN decreased
cell sensitivity to multiple chemotherapeutic agents. n = 3 independent experiments.
Representative data are shown. (b) COLO205 cells stably transfected with miR-17 were
transiently transfected with PTEN expression construct or the control vector. Up-regulation of
PTEN increased cell sensitivity to multiple chemotherapeutic agents. n = 3 independent
experiments. Representative data are shown.
84
cohort consisted of 153 men and 142 women, with a total of 81 CRC patients, who were treated
by adjuvant chemotherapy. High expression levels of miR-17-5p were found in 89/295 (30.17%)
of patients. Significantly higher miR-17-5p expression levels were found in CRC patients with
distant metastasis and higher clinical stages (Table 2, Figure 3.9b). Kaplan-Meier analysis
showed that N status, distant metastasis, clinical stage and miR-17-5p expression were correlated
with poor overall survival (Table 4). CRC patients with high expression levels of miR-17-5p had
reduced survival than patients with low expression levels of miR-17-5p (p=0.001, log-rank test,
Figure 3.9a). Further multivariate Cox regression analysis determined that tumor location, N
status, distant metastasis and expression of miR-17-5p were independent prognostic factors for
the poor survival of CRC patents (Table 4). The results also demonstrated that there was no
significant association between miR-17-5p expression and other clinicopathological features,
such as patient gender, age, tumor location, T classification, N classification and chemotherapy.
3.4.5 MiR-17-5p promotes colorectal cancer cell migration
Previous studies have shown that miR-17 overexpression is related to tumor cell growth (240). In
our study, we found that neither cell survival nor cell proliferation was altered by miR-17
transfection (Figure 3.10a, b). However, scratch wound assays performed on cancer cell
monolayers revealed that the miR-17-transfected cells migrated faster than the control cells
Figure 3.10c). Moreover, when seeded on the upper chamber of trans-well plates, more cells in
the miR-17 group were able to migrate through to the other side of the chamber (Figure 3.10d).
Taken together, the miR-17-transfected colon cancer cells showed greater motility in culture
conditions, which suggested higher metastatic potential in vivo. These results were in line with
our clinical findings, showing that patients with metastatic disease had higher expression levels
of miR-17-5p (Table 5).
To validate miR-17’s function in colorectal cancer cells, we employed siRNAs against PTEN to
simulate miR-17-5p overexpression (Figure 3.10e). Down-regulation of PTEN would result in
activation of the AKT/PI3K/HIF-1α pathway, which contributed to cancer cell migration (241).
As expected, we detected increased cell motility (Figure 3.10f) and cell invasion (Figure 3.10g)
in the siRNA treated cells.
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Figure 3.9 Overexpression of miR-17-5p is associated with tumor metastasis and poor
survival
(a) The miR-17-, vector- and antisense oligonucleotides-transfected COLO205 cells were
cultured and treated with Oxaliplatin, Irinotecan, and Fluorouracil, followed by MTT analysis of
cellular viability. Cells transfected with miR-17 displayed resistance to all drugs, yet anti-miR-
17-5p treatment arrested miR-17-5p’s function. Error bars, SD (n = 3 independent experiments).
(b) Association between miR-17-5p expression in colorectal cancers and overall survival in 295
patients with colorectal cancer. For all of the colorectal patients, Kaplan-Meier test showed that
high miR-17-5p expression associated with poor overall survival (P<0.001, Kaplan-Meier log
rank test).
(c) Among the patients with stage Ⅰand Ⅱ, there is no statistically significant association
between miR-17-5p expression and prognosis (p>0.05, Kaplan-Meier log rank test).
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Table 4 Univariate and multivariate analysis of different prognostic parameters in 295
patients with colorectal cancer
Univariate analysis a Multivariate analysis b
Variable All
cases
Mean
survival
(years)
P
Value
HR (95% CI) P
Value
Sex 0.493 0.359
Male 153 6.638 1
Female 142 6.352 1.236(0.786 to 1.944)
Age 0.158 0.080
<58.8 134 6.694 1
>58.8 161 6.340 1.523(0.951 to 2.439)
Tumor location 0.022 0.004
Colon 147 6.841 1
Rectum 148 6.170 2.040 (1.263 to 3.295)
Chemotherapy 0.580 0.306
No 214 6.463 1
Yes 81 6.621 0.748(0.429 to 1.304)
Histological
grade
0.193 0.498
G1-G2 249 6.596 1
G3 46 5.982 1.227(0.679 to 2.216)
pT status 0.415 0.869
T1-T2 49 6.924 1
T3-T4 246 6.417 1.058(0.541 to 2.067)
pN status 0.018 <0.00
1
N0 181 6.795 1
N1 114 6.024 2.634(1.603 to 4.329)
pM status <0.001 <0.00
1
pM0 265 6.907 1
pM1 30 2.942 11.683(6.513 to
20.959)
miR-17
expression
<0.001 0.007
Low expression 206 6.885 1
Overexpression 89 5.635 1.900(1.195 to 3.022)
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Figure 3.10 Overexpression of miR-17 increases cancer cell invasiveness
(a, b) In the absence of drug, there is little difference between cell survival and proliferation. n =
3 independent experiments. (c) In wound scratch assay, the distances between the wounding
center and the front of the migrating cells (vertical axis) were measured for statistical analysis. n
= 3 independent experiments. (d) Expression of miR-17-5p promoted cell tanswell invasion.
Scale bar, 15 µm. n = 3 independent experiments. (e) Western blot analysis confirmed silencing
of PTEN. Beta-actin was served as loading control. (f) Cells transfected with siRNA against
PTEN migrated faster than control. n = 3 independent experiments. (g) Trans-well invasion assay
showed that down-regulation of PTEN promoted cell invasion. n = 3 independent experiments.
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Table 5 Univariate and multivariate analysis of different prognostic parameters in 214
colorectal cancer patients without chemotherapy
Univariate analysis a Multivariate analysis b
Variable All
cases
Mean
survival
(years)
P
Value
HR (95% CI) P
Value
Sex 0.816 0.887
Male 108 6.492 1
Female 106 6.434 0.963(0.572 to 1.620)
Age 0.139 0.085
<58.8 86 6.707 1
>58.8 128 6.292 1.632(0.935 to 2.850)
Tumor location 0.153 0.046
Colon 104 6.715 1
Rectum 110 6.228 1.754(1.011 to 3.045)
Histological
grade
0.053 0.226
G1-G2 190 6.580 1
G3 24 5.500 1.538(0.766 to 3.045)
pT status 0.289 0.855
T1-T2 43 6.949 1
T3-T4 171 6.342 1.072(0.509 to2.256)
pN status 0.019 0.001
N0 144 6.765 1
N1 70 5.825 2.617(1.480 to 4.627)
pM status <0.001 <0.00
1
pM0 192 6.874 1
pM1 22 2.859 11.537 (5.883 to
22.626)
miR-17
expression
0.023 0.075
Low expression 151 6.740 1
Overexpression 63 5.829 1.647 (0.951 to 2.853)
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To corroborate these results and counteract miR-17’s effect, we overexpressed PTEN in
COLO205 cells (Figure 3.11a). As a consequence, we detected decreased cell migration in the
PTEN-overexpressing group by both scratch wound (Figure 3.11b, d) and trans-well migration
assays (Figure 3.11c). Therefore, it was confirmed that miR-17-5p enhanced invasiveness of
colorectal cancer cells by targeting the PTEN pathway. The addition of cytotoxic drugs in culture
media beforehand was not found to counteract these aggressive migration phenotypes. Given that
increased motility is often associated with higher metastatic capacity (242), our data suggests
that miR-17-5p promoted colorectal cancer cell metastasis in a treatment-independent manner. In
81 colorectal patients with chemotherapy and 214 patients without chemotherapy, miR-17-5p
overexpression was found to be predictive of worse overall survival (Table 3, Table 5). Given
our in vitro and in vivo results, we concluded that miR-17 overexpression contributed to tumor
metastasis, leading to decreased overall survival in CRC patients.
3.5 Discussion
Currently, fluorouracil based chemotherapy remains a standard treatment course for patients with
advanced CRC. While improving patient survival and reducing recurrence, chemotherapy
resistance leading to treatment failure and local recurrence is still a critical problem. One of the
biggest challenges is to identify patient subpopulations that are most likely to respond to specific
therapies. If one or more biomarkers could predict patient’s response to chemotherapy, we could
more effectively treat these patients, while redirecting other groups to alternative strategies that
could be more effective. Considering that the poor prognosis in CRC patients is typically due to
late diagnosis and low chemotherapy response, it is of importance to identify predictive markers
of therapeutic response.
In the present study, microRNA expression profile was first examined in CRC samples from
patients who received neoadjuvant chemotherapy. We discovered that miR-17-5p was capable of
conferring a responder or nonresponder status in colorectal cancer patient samples. Further
results showed that miR-17-5p was an independent predictive factor in patients who received
chemotherapy. We also demonstrated that miR-17-5p might induce chemoresistance by
regulating PTEN expression. In CRC samples, the expression levels of miR-17-5p were found to
be correlated inversely with PTEN expression. Subsequent analysis indicated that miR-17-5p
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Figure 3.11 PTEN overexpression reversed miR-17’s function
(a) Cell lysate prepared from cells transiently transfected with PTEN expression construct or the
control vector and subject to Western blot analysis probed with anti-PTEN antibody to confirm
expression of the construct. Staining of -actin from the same membrane confirmed equal
loading. (b) Wound scratch assay showed that overexpression of PTEN retarded cell migration.
**, p<0.01. Error bars indicate SD (n = 3 independent experiments). (c, d) Trans-well invasion
assay showed that up-regulation of PTEN inhibited cell invasion. **, p<0.01. Error bars indicate
SD (n = 6 independent experiments). Scale bars, 20 µm.
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was significantly correlated with tumor metastasis and advanced clinical stage. This suggested
that the overexpression of miR-17-5p in CRC may facilitate the invasive/metastatic phenotype.
Taken together, overexpression of miR-17-5p in CRC was a strong and independent predictor of
chemotherapy response and a prognostic biomarker for worse survival. Examination of miR-17-
5p expression levels could be used as an additional tool in identifying CRC patients who are in
need of chemotherapy or are at a risk of tumor metastasis.
Resistance to chemotherapy may arise from inherent genetic instability or through selection of
environmental stress. Recently, miRNAs have emerged as crucial mediators in regulating the
cellular responses of cancer cells to therapy. Patient response to chemotherapy has shown to be
closely correlated to the functional status of microRNAs (243-245). Although the mechanisms of
miRNA-regulated drug resistance are still largely unknown, current evidence suggest several
roles for miRNA, including influence of therapeutic induced cell death, alteration of drug targets,
regulation of multiple drug resistance (MDR)-related proteins, change in bioavailable drug
concentration and promotion of angiogenesis and tumor stem-like cells (TSC) (1). Some
miRNAs are capable of conferring drug resistance by targeting PTEN. For example, it has been
reported that miR-214 induces cell survival and chemoresistance, by binding the 3’UTR of
PTEN mRNA (246). In our previous study, we found that miR-17-5p targeted an oncogene,
MDM2 and a tumor suppressor PTEN simultaneously, resulting in chemoresistance and
generation of TSCs in glioblastoma (237). Loss of PTEN is a very frequent genetic aberration in
malignant tumors such as breast cancer, gastric cancer and glioblastoma. Various studies have
suggested that PTEN loss is significantly associated with cytotoxic drug resistance (247, 248).
In this study, we found that miR-17-5p negatively regulated PTEN expression in colorectal
carcinoma cell lines COLO205 and SW480. As a result, these cells became more aggressive and
invasive after transfected with the miR-17 expression construct. Experiments in vitro showed
that the miR-17-transfected cells migrated faster than control cells in both two- and three-
dimensional environments, which could be linked to more distant metastasis in vivo. This finding
is consistent with clinical observations, which revealed that more advanced patients expressed
higher levels of miR-17-5p. There is growing evidence suggesting that dysfunction of PTEN has
prognostic importance in several malignancies, including colorectal cancer (249). Our findings
reveal that targeting PTEN at the post-transcriptional level by miRNAs such as miR-17-5p are
also responsible for PTEN inactivation, and are thereby associated with reduced survival in CRC
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patients. PTEN down-regulation is closely correlated with PI3K/Akt activation, and this cascade
pathway has profound effects on tumorigenesis, proliferation, migration, and apoptosis. We did
not observe a difference in cell growth, which could be due to minimal repression of PTEN
translation in normal conditions. Interestingly, we found that miR-17-5p levels were elevated
upon chemotherapeutic stress, leading to increased knock-down of PTEN. As a result, cells
overexpressing miR-17-5p survived better than the controls. PTEN exerts an essential role in
maintaining chromosomal integrity and cell cycle progression (250). In response to DNA
damage, cancer cells often activate PI3K/Akt pathway, which modulate cell survival signaling
and regulate DNA repair machinery directly (251). Moreover, inactivation of PTEN also has a
positive effect on cancer cell proliferation, which can contribute to therapeutic resistance and
tumor recurrence (252). Our studies suggest that the miRNA-regulatory network might be the
first responder in face of DNA damaging signaling, and overexpression of miRNAs trigger
various response cascades for cell survival.
In summary, we identified miR-17-5p as a chemotherapy response predictor and prognostic
biomarker in colorectal cancer. Furthermore, we found that miR-17-5p responded to
chemotherapy by changing the levels of both itself and its target, PTEN. Up-take of antisense
oligo against miR-17-5p could successfully sensitize cancer cells to chemotherapy. Future
therapeutic strategies could be developed based on the predictive value of miR-17-5p.
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Chapter 4
MicroRNA Regulates Immune Response
(A version of this chapter section is published in Oncoscience(253))
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4 MicroRNA-17 Inhibits Tumor Growth by Stimulating T-
cell Mediated Host Immune Response
4.1 Abstract
Background: Melanoma is one of the fastest-rising types of cancer in North America.
Accumulating evidence suggests anti-tumor immune tolerance plays a critical role in tumor
development.
Methods: B16 melanoma cells were injected into wild type and miR-17 overexpressing
transgenic mice. Tumor growth was monitored and tumor bearing mice were sacrificed by the
end of the forth week. Peripheral blood and spleen cells were subject to flow cytometry analysis
and tumor samples were subject to immunohistochemistry staining. Meanwhile, Jurkat cells
transfected with mock-control or miR-17 overexpressing plasmid were co-cultured with B16
cells. The influence of miR-17 on cell cycle, proliferation and survival was evaluated.
Results: The melanoma tumors formed in mice overexpressing miR-17 were less than that in
wild type mice. It was also associated with less invasiveness and angiogenesis phenotype. The
percentage of CD8+ T cells was suppressed in miR-17 transgenic mice before melanoma cell
injection. Its level was significantly increased upon tumor grafting. More tumor infiltrating
CD8+ cytotoxic T lymphocyte could be found in transgenic mice. Luciferase assay indicated that
STAT3 was the target of miR-17. Decreased levels of STAT3 were associated with miR-17
over-expression. Down-regulation of STAT3 in Jurkat cells promoted cell proliferation and
mitosis.
Conclusions: MiR-17 inhibits melanoma growth by stimulating CD8+ T cells mediated host
immune response, which is due to its regulation of STAT3.
4.2 Introduction
Melanoma is the most aggressive skin cancer, and is characterized by its rapid growth and early
metastasis. It accounts for over 75% of deaths related to skin cancer. Melanoma has one of the
fastest growing incidences in North America, and it has been steadily increasing for the past 30
years. It is estimated that 2% of Caucasian people will develop melanoma in their lifetime (254).
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In 2014, approximately 76,100 new cases will be diagnosed and about 9,710 individuals will die
from melanoma in the United States (254). Until 2011, there was no single agent available for
the successful treatment of this disease. Owing to enormous progress made in immunotherapy,
many treatment options have emerged in recent years and the overall survival of patients with
advanced melanoma has been significantly prolonged (255).
Immunotherapeutic drugs function by stimulating the host immune system, which recognizes and
targets tumor cells in the tumor microenvironment. The tumor microenvironment has a pivotal
role in the development and progression of tumors. The microenviroment comprises stromal
cells, cytokines, signaling molecules and extracellular matrix. The interplay between the tumor
and its surrounding microenvironment determines the balance between tumor growth and
antitumor immune responses. Tumor cells are good at camouflage: they modify or shed their
surface antigen to escape from immune surveillance. Therefore, overcoming immune tolerance
will increase the effect of the antitumor immune response. By targeting molecules capable of
manipulating the microenvironment, immunotherapy has emerged as a novel method to treat
melanoma.
Melanoma cells harbor a multitude of gene mutations which favor tumor cell proliferation,
invasion and metastasis. The signal transducer and activator of transcription (STAT3) protein is
constitutively activated in approximately 50 to 90% of human cancers, including melanoma
(256, 257). Accumulating evidence suggests that elevated activity of STAT3 pathway is essential
for the ability of melanoma cells to evade the immune system (258, 259). STAT3 participates in
tumor immune tolerance by inhibiting proinflammatory mediators and stimulating immune
suppressing factors. As a result, T-cell functionality is suppressed and its immune response
against tumor antigens is impaired. It is still poorly understood how T-cells, arisen from the
human host, become tolerant to tumor cells. The restoration of infiltrative T-cell function in the
tumor microenvironment may provide a potential therapeutic opportunity for overcoming the
immune evasion of melanoma cells from immune surveillance.
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4.3 Material and Methods
4.3.1.1 Cell culture
Jurkat cells (TIB-152) were cultured in RPMI-1640 medium with 10% fetal bovine serum (FBS).
B16 cells (CRL-6475) were cultured in DMEM medium with 10% FBS. Cells were maintained
at 37°C with 5% of carbon dioxide. Fresh medium was added/changed every 2 to 3 days.
4.3.2 Generation of transgenic mice
The transgenic mice were developed by the microinjection of a microRNA-17 overexpression
plasmid into C57BL/6 mice zygotes. Then the fertilized embryo was implanted into a female
recipients’ uterus. F1 mice were backcrossed with wild type C57BL/6 mice and positive
offspring were identified by genotyping PCR. All animal experiment protocols were approved by
the Animal Care Committee of Sunnybrook Research Institute, Ontario, Canada.
4.3.3 Tumor formation assay
Mouse melanoma cell line B16 cells at the concentration of 1 x 105 cells/200 µL were injected
into peritoneal cavity of C57BL/6 wild type and miR-17 transgenic mice. General performance
of mice was closely monitored and all the mice were euthanized by the end of 28th
days. The
number and size of seeded tumor were examined. Tumor size was determined with measurement
obtained from a caliper using the equation (π/6 x height x length x width). Tumor samples were
fixed in 10% formalin solution for further IHC study. All of the methods were performed
following a protocol approved by the Animal Care Committee of Sunnybrook Research Institute.
4.3.4 Flow cytometry
Peripheral blood cells were obtained by heart puncture and spleen cells were isolated by using a
cell strainer (Fisherbrand). Live cells were suspended in phosphate buffered saline (PBS) and
counted using a hemocytometer (Bright-Line). Cells were incubated with FITC-conjugated anti-
mouse CD4 (Caltag Laboratories), PE-conjugated anti-mouse CD8 (BD Biosciences) and PerCP-
conjugated anti-mouse CD45 (BD Biosciences) for 30 minutes before resuspension for analysis.
FACScan flow cytometer (BD Biosciences) were used and the data were analyzed using FlowJo
software.
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In the cell apoptosis assay, 1 x 106 cells were washed twice in PBS before re-suspension in 50
µL of HBSS with 2% calf serum. 5 µL of Annexin V-FITC and Propidium Iodide (BD
Pharmingen) was added and then placed on ice for 30 minutes. The cells were re-suspended to
500 µL of HBSS, followed by flow cytometry analysis within 30 minutes.
In cell cycle analysis, co-cultured cells were harvested and washed twice with PBS. Cell number
was adjusted to 2 x 106/mL in 50 µL of HBSS with 2% calf serum. The cells were then incubated
with 1 mL of 80% ice cold ethanol for 30 minutes. Propidium Iodide (Sigma) and 0.6% of NP-40
were next added into the cell suspension, followed by DNA content analysis by flow cytometry.
4.3.5 Immunohistochemistry
Tumor xenograft and spleen were harvested from mice after B16 cell intraperitoneal injection.
All of the antibodies were purchased from Abcam. Mouse antibodies against CD4, CD8 and
STAT3 were employed as primary antibodies and biotinylated goat anti mouse IgG was used as
secondary antibody. Each slide was assigned a score for density and intensity.
4.3.6 Western blotting
Cultured cells or animal tissue lysates were prepared for SDS-PAGE electrophoresis. Western
blotting was subsequently performed as previously described (29).
4.3.7 Luciferase assay
Luciferase activity assays were performed as previously described (237). In brief, U343 cells
were seeded onto 12-well tissue culture dishes at a density of 1 x 105 cells/well and co-
transfected with the luciferase reporter constructs and miR-17-5p mimic with Lipofectamine
3000 (Life Technologies). After overnight incubation, cell lysate was prepared with buffer from
Dual-Luciferase® Reporter Assay Kit (Promega). Luciferase activity was detected by a
microplate luminescence counter (Perkin Elmer).
4.3.8 Cell proliferation assay
B16 cells were co-cultured with Jurkat cells transfected with GFP mock control or miR-17
overexpression plasmid. Cells were plated at a density of 1 x 105 cells/well in DMEM containing
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10% FBS and maintained for 5 days. The cells were harvested and cell number was counted at
different time points.
4.3.9 Statistical analysis
All experiments were performed at least three times. Numerical data were subject to independent
sample t test. Categorical data were subject to Pearson’s chi-squared test. The statistical
significance was set at *p<0.05 and **p<0.01.
4.4 Results
4.4.1 CD8+ cells increased in tumor-bearing miR-17 transgenic mice
Previous work from our lab showed that miR-17 is essential for hematogenesis and
differentiation (70). We therefore evaluated the influence of miR-17 on lymphopoiesis. CD45 is
expressed on most hematolymphoid cells. We examined the number of CD45+ cells in peripheral
blood and spleen. A lower percentage of CD45+ cells was detected in the miR-17 transgenic
mice as compared with wild type (58.23% vs. 30.80%, p=0.03) (Figure 4.1). Since patients with
melanoma containing a higher number of T lymphocytes show longer overall survival than those
bearing tumors without T lymphocytes infiltrations (260), we analyzed the subpopulation of T
lymphocytes, including the number of CD8+ and CD4+ T cells in CD45+ cells (Figure 4.2).
C57BL/6 mice have a higher percentage of CD8+ cells, compared to other strains. The CD8/CD4
ratio was close to 1 in both wild type and miR-17 transgenic mice (1.17 vs. 0.88, p=0.21), which
was consistent with previous findings (261). However, the number of CD8+ cells was
significantly less in the transgenic mice than that in wild type (9.12% vs. 14.07%, p<0.01). The
number of CD4+ cells also decreased in the miR-17 transgenic mice compared to wild type
(8.05% vs. 16.33%, p=0.02).
We next injected mouse melanoma B16 cells intraperitoneally into wild type and miR-17
transgenic mice. On the 28th
day, we collected blood in the periphery and the spleen from tumor-
bearing mice. Compared to the mice without tumors, mice with grafted tumors had a higher
number of CD45+ cells (Figure 4.1 and Figure 4.3). There was an 8% increase in tumor-bearing
wild type mice compared to tumor-free mice (58.23% vs. 66.43%, p=0.21). In the miR-17
transgenic mice, an increase of 10% after melanoma implantation was detected (30.80% vs.
40.90%, p=0.40). In line with what we have seen in non-tumor-bearing mice, the population of
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CD45+ cells was relatively lower in tumor-bearing mice with miR-17 overexpression (40.90%
vs. 66.43%, p=0.04) (Figure 4.3).
Analysis of subpopulation of T cells showed that CD8+ cells were significantly increased in
miR-17 transgenic mice after tumor implantation compared to tumor-free mice (9.12% vs.
27.43%, p=0.03). Nevertheless, there was little change of CD8+ cells in wild type mice (14.07%
vs. 14.40% p=0.83). The ratio of CD8/CD4+ cells in transgenic mice increased from 1.17 to 1.92
after tumor injection, while it only slightly increased from 0.88 to 0.99 in wild type controls
(Figure 4.4). In summary, compared to the mice without tumor, a significant increase in CD8+
cells was observed in miR-17 overexpressing mice, but not in the wild type controls.
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Figure 4.1 CD45+ cells in non-tumor-bearing mice
When injected with B16 cells, CD45+ cells decreased in percentage was associated with miR-17
overexpression in transgenic mice. n = 10 independent experiments. Representative data are
shown.
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Figure 4.2 CD8+ expression in non-tumor bearing mice
To analyze the subpopulation of T lymphocytes, we identified the number of CD8+ and CD4+ T
cells in CD45+ cells. The number of CD8+ cells was significantly less in transgenic mice than
that in wild type. The number of CD4+ cells also decreased in miR-17 transgenic mice. n = 10
independent experiments. Representative data are shown.
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Figure 4.3 CD45+ expression cells in tumor-bearing mice
When injected mouse melanoma B16 cells intraperitoneally into wild type and transgenic mice,
mice with grafted tumor have higher number of CD45+ cells. Consistent with what we have seen
in non-tumor-bearing mice, the population of CD45+ cells was relatively lower in tumor-bearing
mice with miR-17 overexpressed. n = 10 independent experiments. Representative data are
shown.
103
Figure 4.4 CD8+ expression cell in tumor-bearing mice
CD8+ cells were significantly increased in miR-17 overexpressing mice after tumor
implantation. Nevertheless, there was little change of CD8+ cells in wild type mice. n = 10
independent experiments. Representative data are shown.
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4.4.2 Tumor invasion was inhibited in miR-17 transgenic mice
When B16 cells were injected into the mouse peritoneal cavities of miR-17 transgenic and wild
type mice, they were capable of seeding on the surface of internal organs such as liver, bowels
and omentum. In the wild type group, implantation metastasis was found in 84.6% of mice,
while only 40.0% of transgenic mice had seeded tumor (Chi square test, p=0.03). Tumor sections
were stained with hematoxylin and eosin (H&E) after the mice were sacrificed by the end of
fourth week. In the wild type mice, massive necrosis and internal bleeding could be found in the
B16 melanoma, and tumor cells frequently invaded into stromal tissue (Figure 4.5). In the miR-
17 transgenic mice, grafted tumors were still surrounded by an intact plasma membrane and less
hemorrhagic necrosis can be found inside tumor (Figure 4.5). Accordingly, the sizes of tumors
formed in the transgenic group were much smaller than that in the control group. Taken together,
grafted melanoma cells were less invasive in miR-17 transgenic mice than in the wild type mice.
We previously reported that decreased numbers and sizes of germinal centers were observed in
non-tumor-bearing miR-17 transgenic mice (70). We next examined the paraffin sections of
spleen in tumor-bearing mice. By using H&E staining, enlarged white pulps could be seen in the
transgenic spleen of tumor bearing mice (Figure 4.5). Immunohistochemistry (IHC) analysis
showed that more CD8+ cells were in the spleens of transgenic mice than in wild type mice
(Figure 4.5). We further examined the expression of MAP3K14 and STAT3 in transgenic spleen.
Compared to the wild type mice, miR-17 overexpression in spleen was associated with reduced
expression of MAP3K14 and STAT3 (Figure 4.5). Overall, provocative reactions were observed
in the spleens of mice with miR-17 overexpression.
4.4.3 MiR-17 targets STAT3 in melanoma tumor microenvironment
Computational analysis showed that STAT3 is a candidate for miR-17 targeting. Its 3’-
untranslated region (3’-UTR) contains base a pairing sequence complementary to the seed region
of miR-17 (Figure 4.6a). We thereby designed a luciferase reporter construct which has a miR-17
binding site in the 3’-UTR of STAT3. In luciferase assay, miR-17 was able to bind to its
complementary base pairing in luciferase reporter, and reduced luciferase activity. We confirmed
that mutation of the miR-17 binding site interfered with miR-17-target interaction, which led to
105
Figure 4.5 Immunohistochemistry analysis in B16 grafted tumor and host spleen
(Continued on next page)
106
In the wild type mice, massive necrosis and internal bleeding could be found in the B16
melanoma, and tumor cells frequently invaded into stromal tissue. Meanwhile, intact plasma
membrane and less hemorrhagic necrosis was seen in the miR-17 transgenic mice. Scale bars,
100 m.
Enlarged white pulps could be seen in the transgenic spleen of tumor bearing mice (H&E
staining). More CD8+ cells were in spleens of transgenic mice than that in the wild type mice.
Compared to the wild type mice, miR-17 overexpression in spleen was associated with reduced
expression of MAP3K14 and STAT3. Scale bars, 100 m.
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Figure 4.6 MiR-17 increases CD8+ expression by targeting STAT3
(a) STAT3 is a potential target of miR-17.
(b) Luciferase assay to analysis the interaction between 3’UTR and miR-17 mimic. n = 3
independent experiments.
(c) STAT3 expression are decreased in miR-17 transgenic mice and miR-17 overexpressing
cells. Re-probing of beta-actin was served as loading control.
(d) CD8+ expression are increased in miR-17 over-expressed transgenic mice. Scale bar, 50 µm.
108
restoration of luciferase activities (Figure 4.6b). As a result of miR-17 overexpression, the levels
of STAT3 were suppressed in spleens of transgenic mice (Figure 4.6c). Moreover, decreased
expression of STAT3 was also detected in human T lymphocyte Jurkat cells transfected with the
miR-17 overexpression plasmid (Figure 4.6c). Stable overexpression of miR-17 could be
observed in these cells for two weeks after transfection. Notably, the positive rate of CD8 was
increased in these cells overexpressing miR-17 (Figure 4.6c). We next examined the existence of
CD8+ cells in a grafted tumor microenvironment. In tumor infiltrating T cells, we found higher
percentages of CD8+ cells in the miR-17 transgenic mice compared with the wild type (Figure
4.6d).
4.4.4 MiR-17 promotes proliferation of Jurkat cells co-cultured with B16 cells
When Jurkat cells were co-cultured with B16 cells, they benefited each other in proliferation
(Figure 4.7a). Jurkat cells overexpressing miR-17 grew significantly faster when co-cultured
with B16 cells (Figure 4.7a). These cells showed greater resistance to activation-induced cell
death (AICD) as well (Figure 4.7b). When miR-17 transfected Jurkat cells were treated with
cholera toxin, there was a smaller number of cells undergoing apoptosis compared to controls
(Figure 4.7b). Similarly, these cells survived better in serum-free media (Figure 4.7b).
Cell cycles were assayed in the miR-17 transfected Jurkat cells with or without B16 co-culture.
When they grew independently, miR-17 overexpression in Jurkat cells increased the cell number
in G1 phase (50.24%), compared to that in control group (42.84%) (Figure 4.8a). Consistently,
miR-17 overexpressing cells in S phase also decreased to 13.89%, compared to 23.41% of
control group (Figure 4.8a). However, when co-cultured with B16 cells, more cells
overexpressing miR-17 were detected in S phase (34.22%). But there was only slightly increase
in control cells (25.91%) (Figure 4.8a). To mimic the function of miR-17 in vitro, we further
knocked down the expression of STAT3 by using siRNA against STAT3. As opposed to miR-17,
knocking down STAT3 reduced the cell population in S phase (13.13%) and increased it in G1
phase (52.23%), compared to 21.46% in S phase and 38.04% in G1 phase of negative control
oligos (Figure 4.8b). When these cells were co-cultured with B16 cells, suppression of STAT3
was associated with an increased percentage of cells in S phase (26.45%) and decreased in G1
phase (40.09%) (Figure 4.8b). There was no significant change observed in control cells.
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Figure 4.7 B16 and Jurkat cell co-culture assay
(a) When B16 cells co-cultured with Jurkat cells, they benefited each other in proliferation. n = 3
independent experiments.
(b) MiR-17 over-expression promoted resistance to activation-induced cell death. n = 3
independent experiments. Representative data are shown.
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Figure 4.8 Cell cycle analysis in Jurkat cells with or without B16 co-culture
When B16 co-cultured with Jurkat cells, miR-17 over-expression cells increased in S phase. n =
3 independent experiments. Representative data are shown. (b) When B16 cells co-cultured with
Jurkat cells, STAT3 knock-down cell increased in S phase. n = 3 independent experiments.
Representative data are shown.
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4.5 Discussion
The tumor microenvironment comprises blood vessels, immune cells, fibroblasts and the
extracellular matrix. Numerous signaling molecules and pathways influence the interactions
between the tumor and its surrounding microenvironment. It is believed that such interplay
remolds the tumor microenvironment, permitting for tumor angiogenesis and metastasis.
Meanwhile, immune responses are often suppressed in the host, leading to tumor-tolerogenic
macrophages, NK/T cells and neutrophils. Any fluctuation in the microenvironment could
impact the global signaling of tumor cells, and thus influence the stress response through
miRNA-regulated pathways. In our study, we found that microRNA-17 was able to target
STAT3 in tumor microenvironment, thus inhibiting melanoma tumor growth by stimulating the
tumor infiltrating CD8+ T cells response.
There has been extensive research into the molecular mechanisms of tumor-mediated immune
suppression, in an attempt to explain how tumor cells are able to escape the natural immune
surveillance. It is becoming increasingly clear that the dysregulation of the immune response
plays a critical role in cancer progression and therapeutic resistance. Hence normalizing of the
microenvironment can improve the body’s ability to fight off cancer. Analysis of tumor
infiltrating lymphocytes has demonstrated that many types of tumors show evidence of T-cell
infiltration (48). Of particular interest, activated CD8+ T cell responses have been associated
with a positive prognosis in tumors such as colorectal cancer (49). More studies are underway to
explore the prognostic value of cancer associated immune biomarkers. Recent findings have
suggested that miRNAs are greatly involved in modulating the proliferation, differentiation and
response of CD8+ T cells. Initial characterization of the miRNA profile in CD8+ T cells
provided insight into the understanding of the role miRNAs play in a cell-specific setting. Our
previous study showed that CD8+ cells differentiation was impaired in miR-17 overexpression
mice (70). It could also be partially attributed to suppression of STAT3 (262). In the absence of
STAT3, T cells failed to mature into protective memory T cells (262). Thus it is suggested that
STAT3 drives a feedback loop to establish CD8+ T cells and other functional cell differentiation.
In addition, many other signaling pathways are also actively involved in the regulation of T cell
differentiation and clonal expansion, such as PTEN/PI3K/Akt and Wnt signaling (263, 264).
Since both pathways are under regulation of miR-17, the global immune suppression we
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observed in mice with miR-17 overexpression could be also the result of a vastly complex
mechanism of interconnected regulatory networks.
Interestingly, when melanoma cells were growing in the mice, effective immune response was
observed in miR-17 overexpressing mice, leading to inhibited tumor development. Recent
evidence has indicated microRNAs exert a fining tuning function to maintain cellular internal
homeostasis (32). MicroRNA-regulated stress response not only happens at the cellular level, but
also mediates systemic reactions. In miR-17 transgenic mice, high levels of CD8+ T cells were
detected in spleen as well as peripheral blood. More importantly, they infiltrated into grafted
tumor. It is generally recognized that CD8+ T cells play an important role in attacking tumor
cells and impeding tumor growth. They directly mediate the death of tumor cells, and also
produce inhibiting factors such as IFN-γ, TNF-α and IL-2. The combined effect is a driving
force of anti-tumor immunity, especially in melanoma (265).
The understanding of the potent effects of the miRNAs in tumor-mediated immunosuppression
was driven by studies in tumor-bearing mice. However, the impact of microRNA on anti-tumor
immune response could be a double-edged sword. Increased expression of miR-15b was
observed in isolated CD8+ T lymphocytes in mice with Lewis lung carcinoma (54). Ectopic
expression of miR-15b in CD8+ T cells inhibits apoptosis by knocking down death effector
domain-containing DNA binding protein (DEDD). High expression of miR-15b is also
associated with inactivation of CD8+ T lymphocytes by repressing the production of cytokines
such as IL-2 and IFN-γ (54). Despite its anti-apoptotic effect, miR-15b likely plays a negative
role in the activation of effector T cells and anti-tumor immune response. Dynamic changes in
tumor-associated miRNA expression has also been observed in the miR-17-92 cluster. In patients
with multiple myeloma, the miR-92a level in CD8+ T cells was significantly down-regulated
compared with normal subjects (55). With the remission of disease, the plasma miR-92a level
became normalized. Given the fact that miR-92a and miR-17 belong to a same microRNA
cluster, their role in immune mediation could be alike. It is notable that miR-17-92’s function in
tumor growth and progression still remain controversial, which mainly display in a cell-specific
context. Their levels are generally elevated in leukemia but suppressed in breast cancer (266). In
contrast, both miR-17 and miR-92a promote immune cell mediated anti-tumor response. It is
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therefore suggested their regulations of tumor development and progression are multilayered and
through different mechanisms.
Accumulating evidence has identified STAT3 as a critical molecule in regulating tumor-
associated immunosuppression by interfering with multiple factors. Constitutive expression of
STAT3 alters gene-expression programs, inhibits expression of immune mediators and
suppresses leukocyte infiltration into the tumor (56). Blocking STAT3 in immune cells can
generate diverse anti-tumor immunity by suppressing negative regulators such as immature
dendritic cells and regulatory T cells, and activating CD8+ T cells, natural killer cells and
neutrophils (56). Thus, STAT3 has emerged as a potential target for tumor immunotherapy.
Recent studies have demonstrated that the interplay between miRNAs and STAT3 broadly exists
in cancer development and progression. MiR-124 has been reported as a potential tumor
suppressor in diverse tumor types, such as colorectal cancer and prostate cancer (57). In patients
with glioblastoma, miR-124 expression is significantly reduced, compared to normal brain
tissues (58). Ectopic up-regulation of miR-124 in glioma stem-like cell promoted T cell
proliferation and regulatory T cell induction. Moreover, treatment of T cells from glioblastoma
patients with miR-124 induced pro-inflammatory cytokines and chemokines (58). As a result,
systemic administration of miR-124 prolonged overall survival and decreased tumor incidence in
a murine glioma model. Such anti-tumor effects were shown to be dependent on the presence of
T cells. In tumor bearing mice depleted of CD4+ or CD8+ cells, the immunotherapeutic effects
of miR-124 was ablated (58). Jurkat cell is a well-established model to investigate microRNA
function. Our findings demonstrate that forced expression of miR-17 in Jurkat cells promoted
cell proliferation and survival in the presence of B16 cells. Moreover, inhibition of STAT3
expression can achieve the same effect as miR-17 over-expression. The STAT3 pathway has
been extensively studied in Jurkat cells, and these cells have the potential to differentiate into
subtypes of T cells (267). Upon differentiation, there was a significant down-regulation in the
expression of STAT3 (268). Thus it is suggested that miR-17 promotes Jurkat cell differentiation
in vitro, by targeting STAT3.
Activation of STAT3, in turn, can modulate expression of several miRNAs. For example, there is
a highly conserved STAT3-binding site in the promoter of the miR-17 (C13orf25) (59). By
modulating the expression of IL-6, activation of STAT3 upregulates the entire miR-17-92
cluster. Our finding also confirmed that the 3’-UTR of STAT3 harbors a miR-17 binding site and
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is subject to negative regulation of miR-17. By modulating STAT3 associated immune response
in tumor microenvironment, the negative regulatory loop between miR-17 and STAT3 may be an
important factor in tumor associated immune tolerance and a potential immunotherapeutic target
against cancer.
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Chapter 5
MicroRNA Regulates Wound Healing
(A version of this chapter section is published in Molecular Therapy(269))
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5 Anti-microRNA-378a Enhances Wound Healing Process by
Up-regulating Integrin beta-3 and Vimentin
5.1 Abstract
Background: Delayed or impaired wound healing is a major public health issue worldwide,
especially in patients with diabetes mellitus and vascular atherosclerosis. Wound healing is
achieved by complex physiological processes, including homeostasis, inflammation, re-
epithelialization, vascularization, and tissue remolding. Many factors affect these processes.
MicroRNA has emerged as a key regulator of wound healing. Our previous studies revealed that
microRNA-378 (miR-378) plays a role in modulating cell proliferation, apoptosis, migration and
invasion.
Methods: In this study, we developed an anti-miR-378 sponge construct expressing multiple
tandem microRNA binding sites. With highly matched sequence, this homological antisense
transcript sufficiently blocked the process of precursor microRNA. CD1 transgenic mice were
generated to express the anti-miR-378 unit by microinjection of transgene fragments into
fertilized zygotes. Positive transgenic mice along with control group were subject to skin biopsy,
causing a pair of full-thickness, excisional wound on the back of neck. Wound sizes were
measured everyday thereafter, and tissue samples were collected for immunohistochemistry
examination. Meanwhile, mouse fibroblast cell line NIH/3T3 was transfected with anti-miR-378
and subject to migration, differentiation and angiogenesis assays.
Results: Anti-miR-378 sponge could block mature miR-378 functions in vitro and in vivo.
Compared to wild type mice, enhanced wound healing process was seen in anti-miR-378
transgenic mice. In addition, we found that levels of vimentin and integrin beta-3, two
modulators that are important in wound healing process, elevated remarkably in the transgenic
mice. Wound scratch and transwell migration assays showed a greater mobility in the anti-miR-
378-transfected NIH/3T3 cells, which was due to up-regulation of vimentin and integrin beta-3.
Both molecules were confirmed as targets of miR-378, and thus their expression could be
rescued by anti-miR-378. Overexpression of vimentin could also contribute to fibroblast
differentiation, and up-regulation of integrin beta-3 by anti-miR-378 induced angiogenesis.
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Conclusion: We demonstrated that knockdown of miR-378 by endogenous integrated antisense
fragments could increase the expression of its target proteins, vimentin and integrin beta-3,
which enhanced wound healing in vivo and accelerated fibroblast migration and differentiation in
vitro. These results add a new layer of knowledge in wound repair by microRNA regulation.
5.2 Introduction
As the largest organ of human body, the skin acts as the first line of protection against
environmental hazards. Dysfunctions of the skin’s wound healing process can result in cosmetic
problems, metabolic disorders, and lethal infection. Cutaneous wound healing is a complex
biological process which consists of homeostasis, inflammation, re-epithelization,
vascularization, and tissue remolding. Delayed or impaired wound healing has been a major
public health issue worldwide, especially in patients with diabetes mellitus and vascular
atherosclerosis. It is estimated that as many as 15% of the population with diabetes are at the risk
of nonhealing ulcers, and that the cost of treating these patients is about 10 billion dollars each
year (270).
The human genome encodes 1048 microRNAs (miRNAs), and some are involved in the tissue
repair process such as inflammation, angiogenesis, cell differentiation and migration (271).
Although dysregulation of miRNAs are often shown to be related with compromised wound
healing, the intrinsic mechanisms remain to be fully understood.
There are two main approaches to studying miRNA function: gain-of-function and loss-of-
function tests. Gain-of-function studies are performed by introducing a particular miRNA
molecule into cells or animal genomes, and observing the biological phenotype. By contrast,
loss-of-function studies can be used to silence a miRNA’s functions, thereby evaluating the
corresponding changes in vitro and in vivo.
Reverse genetic approaches that inhibit miRNA functions have widely been used to facilitate
functional studies. To date, many efforts have been made to successfully silence miRNAs. The
development of anti-miRNA oligonucleotides (AMOs) technology has opened up vast
opportunities for miRNA silencing. Developmental defects in Drosophila embryos were
observed by injecting antisense oligonucleotides to suppress miR-13 (272). However,
unmodified AMOs, such as the one used in this study, can be degraded by nucleotidase, limiting
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its application in vivo (272). Chemical modifications of AMOs may confer resistance to
degradation and increase target affinity. For example, 2'-O-methyl oligoribonucleotides were
shown to specifically inactivate miRNA-protein complexes in cultured human cells (273). These
modified AMOs display higher melting temperature and greater liver microsomal stability when
bound to miRNA than their unmodified counterparts. Locked nucleic acids (LNA) are another
modification used to optimize the chemical structure of AMOs, significantly increasing target
affinity by introducing LNA substitutions into AMO backbones (274). Although the use of
AMOs may be a good strategy for therapeutically inhibiting miRNAs, challenges in reaching
sufficient transfection rates ramain. Therefore, the endogenous expression of antisense miRNAs
builds a more stable system for comprehensive studies in vivo. The first endogenous antisense
miRNA (anti-miRNA) was reported by Carè and colleagues (275). They developed a construct
with a 3’-untranslated region (3’-UTR) designed to bind cellular miR-133, and found that a
single infusion this antagomir construct led to cardiac hypertrophy in mouse (275). To enhance
inhibition potency, anti-miRNA sponges were made by inserting multiple tandem miRNA
binding sites into vectors with a cytomegalovirus (CMV) promoter. These stably expressed
sponges can also be used to block an entire miRNA family, which contain identical seed
sequences (7, 276). This is advantage over traditional gene knock-out technologies, which have
been shown to be less efficient in silencing multiple genomic loci within one miRNA family
such as those in the let-7 and miR-17-92 clusters. Therefore, the use of stably integrated anti-
miRNA sponges provides a new tool for studying miRNA function in animal models.
Our previous studies revealed that microRNA-378a (miR-378a) plays a role in modulating cell
migration and differentiation in vitro, and we further demonstrated that the function of miR-378a
was subject to complex regulation in differentiated MC3T3 cells (92, 238). This led us to
investigate the role of miR-378a in tissue remodeling, using a miR-Pirate378a (anti-miR-378a)
construct.
5.3 Materials and Methods
5.3.1 Construct generation
The design of miR-378a expression plasmid was described previously (31). In brief, two human
pre-miR-378a units were inserted into a mammalian expression vector pEGFP-N1 driven by an
H1 promoter, between the restriction enzyme sites BglII and HindIII (Figure 5.1). To suppress
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the expression and function of endogenous miR-378a, we generated a construct that produced
RNA transcripts containing 16 repeats. Each repeat can play two functional roles. (1) It can
interfere with normal processing of endogenous miR-378a, producing imperfect truncated miR-
378a. (2) It can bind and arrest the functions of endogenous mature miR-378a-5p, which were
processed through the normal miRNA biogenesis pathway. Since the RNA transcript could
interact with up to sixteen miRNAs, it can form large complexes with miRNAs and thereby
arrest the functions of the mature miR-378a-5p. The construct was named miR-Pirate378a,
meaning microRNA-interacting RNA—Producing imperfect RNA and tangling endogenous miR-
378a (miR-Pirate). The miR-Pirate378a transcript could bind and block miR-378a-5p function.
For luciferase assay, two pairs of primers were used to clone the fragments of each binding site
and its mutant control. The PCR products were then digested with SacI and MluI and inserted
into a SacI- and MluI-digested pMir-Report vector (Ambion), producing a luciferase construct
and a mutant counterpart (277). The vimentin cDNA was amplified using two primers,
Vimentin-Kozak-BamHI and Vimentin-CMyc-Xbal. The PCR product was cloned into pCR3.1
vector (Invitrogen), which was confirmed by DNA sequencing (167). All the primers’ sequences
are listed in Supplementary Information (Table 6). The integrin beta-3 cDNA was a generous gift
of Dr. Ni from St. Michael's Hospital (Toronto).
5.3.2 Generation of transgenic mice and wound healing experiment
An anti-miR-378 sponge was generated by digestion of anti-miR-378 plasmid with Bg1II and
StuI. The transgene fragment was then purified from agarose gel electrophoresis and suspended
at a concentration of 2 ng/μL. Transgenic anti-miR-378 mouse strains were developed by
microinjection of anti-miR-378 sponge into fertilized zygotes of CD-1 mouse. Injected eggs
were then implanted into oviduct of female mouse. Transgenic strains were maintained by
backcrossing with CD-1 mouse (238, 278). Hemizygous positive transgenic mice were selected
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Figure 5.1 The construct structure of anti-microRNA-378a/miR-Pirate-378a
Generation of miR-378a and miR-Pirate378a (anti-miR-378a) expression construct.
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Table 6 Primer sequences used in the study
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by genotyping. And homozygous negative mice derived from same founders were used as
controls. At 4 weeks of age, 10 transgenic and 10 wild type control mice were subject to skin
biopsy using a punch (Miltex) of 5 mm in diameter. A pair of full-thickness, excisional wounds
were created on the dorsal region of each mouse. Wound size was measured by multiplying
longest length by greatest width, and all mice were sacrificed on the seventh day. Tissue samples
were collected for further study. All of the methods were performed following a protocol
approved by the Animal Care Committee of Sunnybrook Research Institute.
5.3.3 Immuno-reaction assay
Immuno-reaction assay was performed as previously described (29). Western blot and
immunohistochemistry assay were conducted by using antibodies against vimentin (Cell
Signaling) and integrin beta-3 (Santa Cruz Biotechnology). Bromodeoxyuridine (BrdU) (BD
PharmingenTM) was used to label cell proliferation in vivo. Mice were injected with 1 mg BrdU
solution intraperitoneally 12 hours prior to sacrifice. Antibody against BrdU (Biodesign) was
used to detect cellular incorporated BrdU in immunohistochemistry assay. Anti-CD34 antibody
(Santa Cruz Biotechnology) was used to probe blood vessel density in tissue samples and anti-
VEGF antibody (BD Bioscience) was used for Western blotting.
Wound tissue samples were freshly fixed in 10% neutral buffered formalin overnight, and
embedded in paraffin. Vertical section through the center of wound was conducted by microtome
(Leica RM2255). Immuno-reaction assay was performed as previously described (29).
Quantification of Ki67/BrdU was performed by ImageJ software (NIH). In brief, 20 stained
tissue sections were scanned initially under the low objective in order to select the suitable fields
that accurately represent the density and distribution of positive staining. Positively stained cells
were seen in the basal region of epithelium. Four pictures were taken from each slide. A total
eighty images were analyzed using a color subtractive technique, as previously described (277).
For immunostaining of Vimentin and Integrin beta-3, the percentage of positive tumor cells was
assigned as follows: 1 (up to 25% of positive cells), 2 (25% to 50% of positive cells), 3 (50% to
75% of positive cells) and 4 (more than 75% of positive cells). Intensity scores ranged from 0-3:
0, no staining; 1, weak staining; 2, moderate staining, and 3, strong staining. Multiplication of
the two scores resulted in a final score ranging from 0 to 12. 20 samples were scored on the
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grading system with score 0-6 defined as low expression and score 8-12 defined as high
expression.
5.3.4 Cell culture
Mouse fibroblast cell line NIH/3T3 (CRL-1658) was cultured in Dulbecco's Modified Eagle's
Medium (DMEM) supplemented with 10% bovine calf serum (BCS), penicillin (100 U/mL) and
streptomycin (100 U/mL). G418 (500µg/mL) was added into culture media after cells were
transfected with plasmids. Endothelial cell line YPEN-1 (CRL-2222) was cultured in Iscove's
Modified Dulbecco's Media (IMDM) media supplemented with 10% fetal bovine serum (FBS),
penicillin (100 U/mL) and streptomycin (100 U/mL). Cells were maintained in a humidified
incubator containing 5% CO2 at 37℃.
5.3.5 Confocal microscopy
NIH/3T3 cells were fixed with 4% paraformaldehyde (PFA) in PBS for 30 minutes, and then
permeabilized with 0.1% Triton-X-100 for 20 minutes at room temperature. After blocking with
10% goat serum for 60 minutes, primary antibody against vimentin and integrin beta-3 were
applied at a concentration of 1:200 and 1:100, respectively. Cy5- or Fitc-conjugated goat anti-
mouse secondary antibodies (Jackson ImmunoResearch) were then incubated for one hour and
subject to fluorescence confocal microscopy examination (Zeiss Axiovert).
5.3.6 Cell adhesion test
In cell adhesion assay, NIH/3T3 cells were incubated on Petri dish at a density of 1x106
cells/well. Images were taken in a consequent time points at 0, 2, 4 hours to test adhesion ability.
5.3.7 Cell migration test
Cell migration was tested by scratch assay and transwell assay. In the scratch assay, NIH/3T3
cells were plated in 6-well plates at a density of 1x106 cells/well for 12 hours. To diminish the
influence of proliferation, the cells were treated with Mitomycin C (Sigma) at 10 µg/mL for two
hours before being changed to serum-free media. The cultures were then scraped linearly with
micropipette tips (BioMart). Cell migration patterns were recorded by light microscopy at 0, 18,
and 24 hours. Migrated distance was measured and quantified. To detect cell motility in a three-
dimensional way, transwell chambers (Coster) were placed in 24-well tissue culture dish and
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1 × 105 of cells with 100 μL media were loaded into the upper chamber of the transwell. The
lower chamber was filled with 600 μL DMEM containing 10% FBS. After 12 hour incubation at
37ºC, non-migrated cells were removed with a cotton swab and invaded cells were stained with
Coomassie brilliant blue (Bio-Rad) for 5 minutes. Photos were taken under a light microscope
(Zeiss).
5.3.8 Cell differentiation assay
NIH/3T3 cells were grown to confluence in DMEM supplemented with 10% FBS for two days.
MDI (MIX, Dex, Insulin) induction media was prepared by adding 1% Isobutylmethylxanthine
(Sigma), 0.1% Dexamethasone (Sigma) and 0.1% insulin (Lilly) into DMEM media with 10%
FBS. NIH/3T3 cells were stimulated with MDI media for seven days before being replaced by
DMEM media supplemented with 0.1% insulin (Lilly). Differentiated cells were subject to Oil-
Red-O staining.
5.3.9 Oil-Red-O staining
Differentiated NIH/3T3 cells were washed twice with PBS before incubation in 10% formalin
for two hours. Cells were washed with 60% isopropanol for 5 minutes and dried at room
temperature. 1 mL of Oil-Red-O solution (Sigma) was then added and incubated for 10 minutes.
Images were captured by light microscopy after washing with distilled water. To measure the
optical density (OD), cells were washed with 1 mL of 100% isopropanol and the OD was
recorded at 500 nm using isopropanol as control.
5.3.10 Real-time PCR
Total RNA from 1 x 106 cells or approximately 0.05 g tissues was extracted by using mircury
TM
RNA isolation kit (Exiqon). Reverse transcript PCR was performed by using miscript II RT kit
(Qiagen). Mature miR-378a levels were measured using SYBR® green PCR kit (Qiagen) in real
time PCR (Applied Biosystem) as described (4, 279). Primers used as controls were mo-
Gapdh1F and mo-Gapdh250R (for mouse tissues). All the primer sequences are provided in
Table 6.
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5.3.11 Tube formation assay
BD MatrigelTM
was loaded in 48-well plates at 200 µL/well and allowed to settle for 30 minutes.
YPEN cells were labeled with Dil (Invitrogen) and NIH/3T3 cells were labeled with DiO
(Invitrogen) for 1 hour before mixed together. These cells were diluted to 1 x 105/mL and 200
µL were loaded into each well, followed by 12 hour incubation. The tube-like structures were
examined by fluorescence microscopy at 6, 12, and 24 hours. The intersections linked with more
than three tubes will be counted, and four fields will be chose to accurately represent each well.
5.3.12 Luciferase activity assay
NIH/3T3 cells were seeded onto 12-well tissue culture dishes at a density of 1 x 105 cells/well.
The cells were co-transfected with the luciferase reporter constructs and miR-378a/miR-
Pirate378a plasmid, using Lipofectamine 2000. Firefly reporter plasmids (Ambion) with or
without an unrelated fragment insert (G3R) served as positive controls. After 12 hours, cell
lysate was prepared by using Dual-Luciferase® Reporter Assay Kit (Promega) and luciferase
activity was detected by luminescence counter (Perkin Elmer) as previously described (91).
5.3.13 Nanoparticle synthesis and delivery
For synthesis of anti-miR-PEG conjugate, 20 nmol thiol modified miR-Pirate378a fragments
(GenePharma) were dissolved in 800 µL of RNase-free water. The mPEG-SH (PG1-TH-2k,
Nanocs) were mixed with the miR-Pirate378a fragments at a 1:20 molar ratio. Then 10 nm gold
nanoparticles (Cytodiagnostics) were mixed with 1 µg anti-miR-PEG at weight ratio of 1:1 for
conjugation. The mixture was gently shaken at 60℃ for 30 minutes and transferred into a
syringe. Upon wounding by skin punch, the nanoparticles with miR-Pirate378a or blank control
were administered intradermally in a volume of 100 µL as previously described (280).
5.3.14 Statistical analysis
All experiments were performed in triplicate and numerical data were subject to independent
sample t test. The levels of significance were set at *p<0.05 and **p<0.01.
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5.4 Results
5.4.1 Enhanced wound healing in miR-Pirate378a transgenic mice
CD1 miR-Pirate378a (anti-miR-378a) transgenic mice were generated by microinjection of
transgene fragments into fertilized zygotes (Figure 5.1). Newborns were screened for the
presence of the miR-Pirate378a sequence and positive ones were intercrossed with CD1 wild
type mice to obtain F1 generation. Tail clips were used for PCR genotyping to identify positive
transgenic mice. Real-time PCR was employed to confirm the miR-378a and miR-Pirate378a
levels. The sequences of primers used in this study are provided in Supplementary Information
(Table 6). We previously showed that miR-Pirate378a transcript could interfere with miR-378a
by targeting precursor miR-378a as well as arresting mature miRNA (278). Detecting the levels
of miR-Pirate378a allowed us to estimate mis-processing of endogenous miR-378a. We detected
high levels of truncated miR-378a as compared with wild type mice (Figure 5.2a). It was
anticipated that the mis-processed miR-378a could not be recognized by Dicer, since it lacked
the intact “seed” regions (278). As a result, mature miR-378a expression was repressed due to
the introduction of miR-Pirate378a fragments.
MiRNA’s function to maintain physical homeostasis, and are also subject to the regulation of
other signaling networks (1). For example, expression of miR-378a changes during the
differentiation of MC3T3 cells (92). We previously demonstrated that vimentin, one of the
cytoskeletal proteins which are crucial to wound healing, could mediate miR-378a’s expression
and function (238, 281). To study how miR-378a influences tissue repair and wound healing,
miR-Pirate378a transgenic and wild type mice were subject to a cervical dermal punch biopsy,
which left full-thickness excisional wounds around 5 mm on both sides of the neck. One week
after wounding, miR-Pirate378a transgenic mice showed enhanced healing as compared to the
wild type mice (Figure 5.3). Studies have shown that genders and sex steroids might impact
tissue repair and regeneration (282). In our studies, both male and female transgenic mice
displayed accelerated wound healing. The difference in wound area between two groups was
statistically significant after six days (Figure 5.2b). Measurements of wound area revealed that
the ratios of unhealed space (Day 6: Day 1) were significantly smaller in miR-Pirate378a group
than that in the wild type mice (Figure 5.2b).
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Figure 5.2 Enhanced wound healing in miR-Pirate378a transgenic mice
(a) RNAs isolated from transgenic mice were subject to real-time PCR to measure levels of miR-
Pirate378a and miR-378a. Expression of miR-Pirate378a was significantly higher in transgenic
mice, while expression of mature miR-378a-5p was significantly lower. n = 3 independent
experiments.
(b) Left, graphical representation of each wound size during one week. On the sixth day, the
wound size in transgenic mice was significantly smaller than that in wild type mice. Right, the
ratio of wound size on the sixth day to that on the first day indicated faster wound healing
process in the miR-Pirate378a transgenic mice. n = 3 independent experiments, a total of 48 mice.
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Figure 5.3 Wound healing pictures taken from mice
MiR-Pirate378a transgenic and wild type mice were subject to wound healing tests. Picture taken
from sixth day showed that miR-Pirate378a transgenic mice had enhanced wound healing
compared with the wild type. Scale bar, 2 cm. n = 3 independent experiments. Representative
photos are shown.
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On the seventh day, tissues of wound area were biopsied for histological examination and
immunohistochemistry staining. Wound healing is driven by myofibroblast migration and
transition, which is marked by expression of alpha-smooth muscle actin (283). Confocal
microscope showed that there was increased alpha-smooth muscle actin expression in the miR-
Pirate378a transgenic mice, as compared with that in wild type (Figure 5.4a). We also found that
there were more new blood vessels generated in situ in the miR-Pirate378a mice, as evaluated by
CD34 levels (Figure 5.4b). Nevertheless, there was no apparent difference in epithelial cell
proliferation in both groups, as indicated by BrdU and Ki67 staining (Figure 5.4b).
5.4.2 MiR-Pirate378a accelerates fibroblasts migration, differentiation and
tube formation
Fibroblasts are known to be essential in tissue repair. They move to the wound area upon wound
formation and synthesize collagen together with other extracellular matrix (ECM), generating the
force required to contract the wound. To study the function of miR-378a on fibroblast activities,
NIH/3T3 cells were stably transfected with plasmids containing GFP as a mock control, the pre-
miR-378a coding sequence or miR-Pirate378a fragments. Real time PCR was used to confirm
the expression of miR-378a in transfected cells. There was an elevation of mis-processed miR-
378a in cells overexpressing miR-Pirate378a (Figure 5.5a). As a result, miR-378a-transfected
cells expressed higher levels of mature miR-378a-5p, whereas miR-Pirate378a-transfected cells
expressed significantly lower levels of miR-378a-5p than the control (Figure 5.5a).
We performed a number of cell activity assays to test the effects of miR-378a on cell biology
associated with wound repair. In cell migration assay, the miR-Pirate378a-transfected cells
showed a greater ability to migrate, as compared to miR-378a-transfected and GFP-control cells
(Figure 5.5b, Figure 5.6a). The locomotion of fibroblasts during wound healing includes
migration as well as deformation. Thus, transwell migration assay was performed to test both
functions. After being placed above a cell permeable membrane for eight hours, more miR-
Pirate378a-transfected cells migrated through microspores of the membrane (Figure 5.5c, Figure
5.6b). In cell adhesion assay, NIH/3T3 cells were incubated on Petri dish for two hours to test
adhesion ability.
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Figure 5.4 MiR-Pirate378a increases CD34 expression
(a) Wound tissue samples were subject to H&E staining. Faster close-up of the wound was
detected in the miR-Pirate378a transgenic mice. Scale bars = 50 µm.
(b) Wound tissue samples were subject to immunohistochemistry analysis. Expressions of alpha
smooth muscle actin increased in miR-Pirate378a transgenic mice samples. There was no
difference in F-actin expression between these two groups. Scale bars = 50 µm.
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Figure 5.5 Expression of miR-Pirate378a increases cell migration and adhesion
(a) Real-time PCR was used to confirm increased expression of mature miR-378a-5p and miR-
Pirate378a in miR-378a-, and miR-Pirate378a-transfected cells respectively. n = 3 independent
experiments. (b) Scratch wound healing test showed that overexpression of miR-Pirate378a
increased cell migration while overexpression of miR-378a-5p inhibited cell motility. n = 6
independent experiments. (c) Transwell migration test showed that there were more miR-
Pirate378a-transfected cells migrated through the membrane than the other two groups. n = 6
independent experiments. (d) Cell adhesion test showed fewer miR-378a cells adhered while
more miR-Pirate378a cells adhered than the control. n = 6 independent experiments. (e)
NIH/3T3 cells were induced to differentiate and subject to Oil-Red-O staining, and analyzed
with optic density (OD) absorbance. There was higher OD reading in miR-Pirate378a group. n =
3 independent experiments.
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Figure 5.6 Typical photos of cell function test
Typical photos of scratch wound healing assay (a), transwell migration test (b), cell adhesion test
(c), 3D tube formation assay (d) and oil red staining (e). Scale bars = 20 µm. (n = 6)
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It was found that more miR-Pirate378a-transfected cells were able to attach to the surface of
Petri dish (Figure 5.5d, Figure 5.6c). By co-culturing NIH/3T3 cells with YPEN endothelial
cells, the cells formed tube-like structures, mimicking angiogenesis. There were more tube-like
structures formed in miR-Pirate378a-transfected cells, while miR-378a expression largely
inhibited tube formation (Figure 5.6d).
Tissue repair requires the differentiation of fibroblasts into functional mature cells. Thus,
differentiation of fibroblasts is believed to be responsible for wound healing. NIH/3T3 cells have
a tendency to differentiate into adipocytes (284), which allows us to test the capability of
differentiation in NIH/3T3 fibroblasts. After being incubated in stimulation media for two weeks,
more miR-Pirate378a-transfected cells were differentiated to adipocytes, as detected by Oil Red
O staining (Figure 5.5e, Figure 5.6e). The solutions extracted from stained cells were subject to
optic density (OD) absorbance measurement, and it was confirmed that miR-Pirate378a
transfection enhanced oil red uptake (Figure 5.5e). In summary, we found that the suppression of
miR-378a promoted migration, differentiation and tube formation in NIH/3T3 cells.
5.4.3 MiR-Pirate378a counteracts miR-378a’s function by up-regulating
vimentin levels
MicroRNA is thought to function by repressing the translation of its targeted mRNAs. In our
previous work, we reported that vimentin was down-regulated in miR-378a-overexpressed cells
(167). Vimentin is a major intermediate filament expressed in fibroblasts, which constitutes
cytoskeletal systems in eukaryotic cells. It has long been considered as a driving force of cell
strength and tissue integrity (281). To test the effect of miR-378a on vimentin expression in the
NIH/3T3 fibroblasts, a pair of luciferase reporter, which contained a fragment of the miR-378a
binding site or a mutated counterpart, was developed (Figure 5.7a, upper). We confirmed that
miR-378a transfection decreased luciferase activity, while such effect was abolished when the
binding sites were mutated or additional miR-Pirate378a was added (Figure 5.7a, lower). As a
result, the expression of vimentin was elevated in miR-Pirate378a transfected fibroblasts (Figure
5.7b, upper). We then transfected NIH/3T3 cells with siRNAs against vimentin and confirmed
the silencing of vimentin (Figure 5.7b, lower). Knockdown of vimentin inhibited cell adhesion
(Figure 5.7c, Figure 5.8a) and decelerated migration (Figure 5.7d, Figure 5.8b), when compared
with vector-transfected cells. Moreover, a lower velocity of migration of the siRNA-transfected
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Figure 5.7 MiR-378a-5p targets vimentin
(a) Upper, computational analysis showed that vimentin is a target of miR-378a. Lower,
luciferase assay confirmed Vimentin is a target of miR-378-5p. n = 3 independent experiments.
(b) Upper, transfection of miR-Pirate378a plasmid increased the expression of Vimentin. Lower,
transfection of siRNA against vimentin decreased its level. Re-probing of beta-actin was served
as loading control. (c) Adhesion test showed that there were fewer cells adhered in siRNA
against Vimentin group than that in the control group. n = 6 independent experiments. (d)
Scratch wound healing test showed that down-regulation of vimentin resulted in a lower
migration rate in NIH/3T3 cells. n = 6 independent experiments. (e) Transwell invasion test was
applied to detect motility of NIH/3T3 cells in three-dimensional way. After Coomassie blue
staining, quantification of migrated cells showed there were more NIH/3T3 cells in control group
migrated through membrane than the cells transfected with siRNA against vimentin. (n = 3).
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Figure 5.8 Typical photos of Vimentin knocking down assay
(a) Adhesion test was applied to NIH/3T3 cells transiently transfected with siRNA against
Vimentin or a control oligo. There were fewer cells adhered in siRNA group. Scale bar = 20 µm.
n = 6 independent experiments. (b) NIH/3T3 cells transfected with siRNA against vimentin or a
control oligo were subject to scratch wound healing test. Down-regulation of vimentin resulted in
a slower migration. Scale bars = 20 µm. n = 6 independent experiments. (c) Transwell invasion
test showed there were more NIH/3T3 cells in control group migrated through membrane than
the cells transfected with siRNA against vimentin. Scale bar = 20 µm. n = 6 independent
experiments.
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cells was observed in the transwell assay (Figure 5.7e, Figure 5.8c).
To confirm the effects of vimentin on mediating miR-378a-5p functions, we transfected
NIH/3T3 fibroblasts with a vimentin expression construct. Over-expression of vimentin was
confirmed through Western blotting (Figure 5.9a, left), which led to increased cell adhesion
(Figure 5.9a, right) and migration (Figure 5.9b, Figure 5.10a). We also found that over-
expression of vimentin increased cell migration in the transwell assay (Figure 5.9c, Figure 5.10b)
and promoted cell differentiation (Figure 5.9d, Figure 5.10c). Interestingly, the levels of
vimentin increased drastically in the differentiated NIH/3T3 cells (Figure 5.9e, left), which was
in accordance with the decrease in miR-378a levels (Figure 5.9e, right).
5.4.4 Integrin beta-3 is a target of miR-378a-5p
By using an overlapping analysis of three miRNA target prediction alogthrims (Pictar,
TargetScan and MiRBase), in silico analysis revealed that integrin beta-3 as a miR-378a targets.
Integrin beta-3 is an integral cell surface protein which participates in cell adhesion and signal
transduction. Dysregulation of integrin beta-3 has been linked to impaired endothelial cell
migration (285). To exploit the role of integrin beta-3 in wound healing, we tested the targeting
of integrin beta-3 by generating a luciferase reporter construct containing a fragment of the
integrin beta-3 3’UTR and a mutant construct (Figure 5.11a). NIH/3T3 cells were co-transfected
with miR-378a/miR-Pirate378a plasmid and one of the constructs. There was a decrease in
luciferase activity in the cells transfected with the integrin beta-3 3’UTR construct, but this
inhibitory effect was abolished when the miR-378a binding sites were mutated or when the cells
were co-transfected with miR-378a and miR-Pirate378a (Figure 5.11a).
Western blot analysis confirmed that transfection with miR-Pirate378a in NIH/3T3 fibroblasts
increased integrin beta-3 expression (Figure 5.11b, left, upper), which promoted VEGF
expression (Figure 5.11b, left, lower). Integrin beta-3 has been implicated in angiogenesis
through stimulating of vascular endothelial growth factor (VEGF) expression, thus increasing
neovascularization (286). Consistent with these findings, we found that VEGF expression was
elevated in the miR-Pirate378a-transfected cells. To test the effect of integrin beta-3 on cell
activities, we employed an siRNA approach. Western blot analysis showed that expression of
integrin beta-3 decreased when the cells were transfected with siRNA against integrin beta-3
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Figure 5.9 Overexpression of Vimentin increases cell motility and differentiation
(a) Left, Western blot showed that transfection of vimentin expression construct increased its
level. Re-probing of beta-actin was served as loading control. Right, adhesion test showed that
more cells were adhered in vimentin overexpression group than that in the control group. (b)
NIH/3T3 cells transiently transfected with vimentin expression construct or the control vectors
were subject to scratch wound healing test. Overexpression of vimentin increased cell motility. n
= 6 independent experiments. (c) Transwell migration test was applied to NIH/3T3 cells
transiently transfected with vimentin expression construct or the control vector. There were more
cells migrated through membrane in vimentin rescue group than that in the control group. (d)
NIH/3T3 cells transiently transfected with vimentin expression construct or the control vectors
were subject to oil red staining. There were more differentiated cells in vimentin overexpression
group. n = 6 independent experiments. (e) Left, NIH/3T3 cells were induced to differentiate and
subject to Western blot analysis. Differentiated cells increased expression of vimentin. Right,
Differentiated cells had decreased levels of mature miR-378a. Re-probing of beta-actin was
served as loading control. n = 3 independent preparations.
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Figure 5.10 Typical photos of Vimentin overexpression assay
(a) NIH/3T3 cells transiently transfected with vimentin expression construct or the control
vectors were subject to scratch wound healing test. Overexpression of vimentin increased cell
motility. Scale bar s= 20 µm. n = 6 independent experiments.
(b) Transwell migration test was applied to NIH/3T3 cells transiently transfected with vimentin
expression construct or the control vector. There were more cells migrated through membrane in
vimentin rescue group than that in the control group. Scale bars = 20 µm. n = 6 independent
experiments.
(c) NIH/3T3 cells transiently transfected with vimentin expression construct or the control
vectors were subject to oil red staining. There were more differentiated cells in vimentin
overexpression group. Scale bar = 20 µm. n = 6 independent experiments.
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Figure 5.11 MiR-378a-5p targets Integrin beta-3
(a) Upper, Computational analysis showed that integrin beta-3 was a potential target of miR-
378a. Constructs containing mutated/unmutated binding sites of integrin beta-3 were generated
for luciferase assay. Lower, NIH/3T3 fibroblasts were co-transfected with miR-378a (Mi378)
and luciferase reporter constructs (Luc-Int) or the mutants (Luc-mut). The luciferase reporter
vector (Luc) and the vector harboring a non-related region (G3R) were used as controls. MiR-
378a repressed the activity of the constructs containing the target sites, which was reversed when
the target sites were mutated. Co-transfection with the luciferase construct and miR-Pirate378
(Pi378) also reversed the inhibitory effect. ** p<0.01, SD (n = 3 independent experiments).
(b) Cell lysates prepared from NIH/3T3 cells were subject to Western blot analysis. Left,
Transfection of miR-Pirate378a plasmid increased the expression of integrin beta-3 and VEGF.
Right, Transient transfection of siRNA targeting integrin beta-3 decreased levels of integrin beta-
3 and VEGF. Re-probing endogenous beta-actin was served as loading control.
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(Figure 5.11b, right, upper), which led to decreased VEGF expression (Figure 5.11b, right,
lower).
As a transmembrane receptor, integrin beta-3 mediates cell-cell and cell-ECM interaction (287).
We found that silencing integrin beta-3 led to impaired both cell invasion, as assessed by
transwell-Matrigel assay (Figure 5.12a, Figure 5.13a), and cell migration, as assessed by scratch
assay (Figure 5.12b, Figure 5.13b). In cell adhesion assays, we found that silencing integrin beta-
3 reduced the adhesive capacity of the cells (Figure 5.12c, Figure 5.13c).
To confirm that integrin beta-3 played roles in mediating miR-378a’s effects, we over-expressed
integrin beta-3 in NIH/3T3 fibroblasts. After confirming the elevated expression of integrin beta-
3 (Figure 5.12d, left), the cells were subject to migration assay. Integrin beta-3 overexpression
promoted cell migration in the wound healing assay (Figure 5.12d, right). Over-expression of
integrin beta-3 also increased cell invasion in transwell-Matrigel assay (Figure 5.12e). Together,
these results suggest that ectopic expression of integrin beta-3 might rescue the inhibitory effects
of miR-378a on cell migration, and invasion.
5.4.5 MiR-Pirate378a enhanced wound healing
We then confirmed that both vimentin and integrin beta-3 were targets of miR-378a. The levels
of vimentin and integrin beta-3 in NIH/3T3 cells were analyzed by confocal microscopy. As
expected, increased levels of vimentin and integrin beta-3 expression were observed in the miR-
Pirate378a-transfected cells while they were decreased in miR-378a-transfected cells (Figure
5.14a). Their expression levels were also examined in tissue samples obtained from the wound
healing assay. Compared to wild type mice, miR-Pirate378a transgenic mice showed higher
expression levels of vimentin and integrin beta-3 around the wound area (Figure 5.14b).
Our finding that down-regulation of endogenous miR-378a could facilitate tissue repair led us to
exploit its therapeutic application. Several studies have demonstrated the utility of knocking-
down of miRNAs by using anti-miRNA molecules in vivo (288, 289). By loading anti-miRNA
oligo into PEG conjugated gold nanoparticles as indicated (Figure 5.15a), we were able to
administer a single dose of miR-Pirate378a to adjacent wound area by intradermal injection. We
found that nanoparticle treatment significantly reduced open wound areas over the course of 2-4
day treatments in wild type CD-1 mice (Figure 5.15b).
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Figure 5.12 Integrin beta-3 knocking down and overexpression assay
(a) Transwell migration test was applied to NIH/3T3 cells transiently transfected with two
siRNAs against integrin beta-3 or a control oligo. There were fewer cells migrated through
membrane in the siRNA groups than that in the control group. n = 6 independent experiments.
(b) NIH/3T3 cells transiently transfected with siRNA against integrin beta-3 or a control oligo
were subject to scratch wound healing test. Down-regulation of integrin beta-3 inhibited cell
migration. n = 6 independent experiments. (c) Adhesion assay was performed on NIH/3T3 cells
transiently transfected with siRNAs against integrin beta-3 or a control oligo. There were less
cells adhered in siRNA groups than that in the control group. n = 6 independent experiments. (d)
Transfection of integrin beta-3 construct increased integrin beta-3 expression. Right, Up-
regulation of integrin beta-3 increased cell migration compared to control oligo. Re-probing of
beta-actin was served as loading control. (e) Transwell migration test was performed and showed
that more NIH/3T3 cells transfected with integrin beta-3 construct migrated through MatrigelTM
.
n = 6 independent experiments.
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Figure 5.13 Typical photos of Integrin beta-3 knocking down test
Typical photos of transwell migration test (a), scratch wound healing test (b), and cell attachment
test (c). Scale bars = 20 µm. n = 6 independent experiments.
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Figure 5.14 MiR-Pirate378a increases expression of Vimentin and Integrin beta-3
(a) NIH/3T3 fibroblasts stably transfected with miR-378a, miR-Pirate378a expression plasmid,
or mock control were subject to confocal microscopic analysis. Vimentin and integrin beta-3
were down-regulated in miR-378a transfected cells but up-regulated in miR-Pirate378a-
transfected cells compared to the control. Scale bar s= 15 µm.
(b) Immunohistochemistry analysis indicated that expressions of vimentin and integrin beta-3
increased in miR-Pirate378a transgenic mice compared to wild type mice. Scale bars = 50 µm.
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Figure 5.15 Nanoparticle treatment
(a) Major steps involved in skin wound healing assay
(b) Wide type CD-1 mice were treated with miR-Pirate378a conjugated to gold nanoparticles.
Compared to blank control, treatment with miR-Pirate378a nanoparticle enhanced wound
healing (n = 3 independent experiments, a total of 24 mice, ** p<0.01)
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Compared to the wounds on the left of the neck which were treated with blank vector loaded
nanoparticles, miR-Pirate378a treatment (right side) showed a narrowed size and better healing
course (Figure 5.16).
5.5 Discussion
We reported a novel transgenic anti-miRNA mouse model used to study tissue regeneration. We
demonstrated that the knockdown of miR-378a by an endogenous integrated antisense approach
increased the expression of its targeted proteins, vimentin and integrin beta-3, which accelerated
fibroblast migration and differentiation in vitro and enhanced wound healing in vivo.
Various attempts have been made to silence microRNA in vivo. However, successfully
delivering anti-miRNA fragments into mammalian cells remains a challenge. Genetically
modified mice offer insight into the constitutive repression of individual miRNAs. MiRNAs
contain highly conserved seed regions, which could be identical among different paralogs. These
miRNAs are believed to exert similar functions through their common seed regions, which could
target similar mRNAs. Therefore, the effects of knocking-out single miRNA could be
jeopardized by other paralogs which target the same mRNAs. The anti-microRNA construct used
in this study diminishes such influence from other miRNAs by binding the central loop of the
miRNA precursor, in addition to the seed region. Thus, this approach can be used to specifically
knock down an individual member from a miRNA cluster. With highly matched sequences, this
homological antisense transcript can sufficiently block the downstream processing of specific
precursor miRNA, thus preventing them from becoming functional. Also, the sixteen copies of
the anti-miRNA sequence in the vector result in amplified silencing of the targeted miRNA.
MicroRNAs have recently emerged as key regulators of physical homeostasis. The regulatory
network consisting of miRNAs and their targets, maintain a stable internal environment. Any
changes in homeostasis activate the response of this regulatory network, leading to modification
of gene expression. In this study, we found that the down-regulation of miR-378a did not cause
any apparent changes in the phenotype of transgenic mice, but displayed a function during
wound healing. These findings highlight the possibility
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Figure 5.16 Typical photos of gold nanoparticle treatment
Typical picture taken from the second and the fourth days showed that miR-Pirate378a
nanoparticle treatment had enhanced wound healing (right side) compared with blank control
(left side).
147
that miRNAs are integrated into a complex network which maintains normal physiological
conditions, while their dysregulations in response to intrinsic or extrinsic stimulations could
result in pathophysiological dysfunction (290). Recent findings illuminated the important role of
miRNAs in wound healing. For example, miR-210 was found to be elevated in ischemic wounds,
where hypoxia inducible factor-1α (HIF-1α) was stabilized, and this accounted for attenuated
keratinocyte proliferation and impaired wound re-epithelization (291).
Wound healing is achieved by complex physiological processes: monocytes and neutrophils are
responsible for immune reaction, keratinocytes regenerate cutaneous epithelial cover, and
fibroblasts exert contractile forces between cell-cell and cell-ECM conjunctions (292). It also
varies among species, for example, human wound healing predominantly relies on re-
epithelization while wound contraction is more important in mice (293). This is why we chose
mouse fibroblasts in studying wound contraction in vitro. We observed that miR-Pirate378a
contributed to fibroblast migration in cultured NIH/3T3 cells, which was due to elevated
expression of vimentin and integrin beta-3. It has been reported that vimentin is required to
generate traction forces during wound healing, and also that vimentin deficient mice showed
impaired wound healing (281). Comparatively, integrin beta-3 is an integral cell-surface protein
which participates in cell adhesion as well as bidirectional signal transmission. It has been shown
that the inhibition of integrin beta-3 expression in endothelial cells resulted in impairment of cell
migration (285). Moreover, by interplaying with VEGF signaling, integrin beta-3 has been
shown to control tumor growth through the promotion of tumor vascularization (286). In this
study, we observed that elevated levels of vimentin and integrin beta-3 contributed to accelerated
fibroblasts migration, which is critical in the early stage of wound healing (294).
We also discovered enhanced differentiation in NIH/3T3 cells transfected with miR-Pirate378a.
Interestingly, during the process of differentiation, expression of vimentin was evoked, which
underlined the importance of vimentin in fibroblast differentiation. Since vimentin is targeted by
miR-378a, it highlights the role of miR-Pirate378a in inducing cell differentiation by rescuing
vimentin expression. When NIH/3T3 cells were originally obtained by Green and his colleagues
from mouse cells, they found that NIH/3T3 cells had the potential to differentiate into adipose
cells (284). Herein, we took advantage of this to detect the differentiation capacity of NIH/3T3
cells. We demonstrated that expression of miR-Pirate378a promoted adipogenesis by up-
regulation of vimentin expression. Although the intricate mechanism of wound healing is not
148
completely understood, adipocytes and adipose derived cells have been regarded as important
mediators in tissue regeneration (295). Furthermore, we found that the levels of mature miR-
378a decreased in differentiated NIH/3T3 cells, which was in agreement with increased vimentin
expression upon differentiation. Finally, we confirmed the increased differentiation of
myofibroblasts in tissue samples, as we detected higher levels of alpha-smooth muscle actin
expression in the miR-Pirate378a transgenic mice during wound healing.
The process of wound healing requires epithelial cell regeneration and proliferation. However,
we did not detect any difference in BrdU and Ki67 expression. We also assessed the proliferation
of NIH/3T3 cells in vitro, which showed little difference between miR-378a- and miR-
Pirate378a-transfected cells. This might be due to the overall activation of cellular regeneration
mechanism, which leads to a fast growing pace of epithelial cells in both the control and
experimental groups. Notably, we found that the overexpression of integrin beta-3 promoted
tube-like structure formation in vitro and angiogenesis in vivo, probably through the activation of
VEGF signaling. These findings suggest that miR-378a regulates single physical process (wound
healing) by interfering with multiple pathways (cell migration, differentiation and angiogenesis)
(Fig 7).
In summary, we have shown a novel wound healing model in miR-Pirate378a transgenic mice.
The investigation of miRNA in regulating tissue repairing can open up vast opportunities.
Further diabetic animal models could be developed based on our current transgenic mice, and
more clinically oriented research could be performed. Collectively, our data have shown that
targeting miR-378a could accelerate wound healing in a murine model. Our novel approach to
miRNA inhibition adds a new layer of knowledge in this area and warrants further investigation.
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Figure 5.17 Anti-microRNA-378 enhances wound healing by rescuing Vimentin and
Integrin beta-3
Flow chart is showing miR-378 regulates wound healing by mediating multiple pathways.
150
Chapter 6
General Discussion
(A version of this chapter section is published in Cell Cycle(32))
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6 MicroRNA-regulated Stress Responses and Its Clinical
Implications
6.1 MicroRNA-regulated metabolic stress responses in glioblastoma
During the process of tumorigenesis, the microenvironments of cancer cells are constantly
undergoing changes and remodeling. Such changes and remodeling can lead to shortage of blood
supply, reactive immune responses and damage to cellular components (Figure 6.1). Any
environmental fluctuations leading to deviations from physiological homeostasis are considered
as stress to cancer cells. It is well-known that strategies taken to modulate stress signaling are
critical to tumor development. This also marks a distinction of malignant cells from normal ones.
Currently, evolving evidence suggest that microRNAs play key roles in stress response
mediation (296). MicroRNAs have been shown to exert diverse functions in cancer cell
proliferation, cell cycle progression, invasion and angiogenesis (7, 33, 77). Notably, microRNAs
regulate cellular metabolism in a cell-specific and context-dependent manner.
Studies in the first chapter have gained insight into this issue, using glioblastoma cells as a model
to test the context-dependent functions of microRNA. Glioblastoma is characterized by
aggressive angiogenesis and the generation of tumor stem-like cells (TSCs), making it an optimal
candidate to test TSC-related phenotypes. Initially, we found that microRNA miR-378
accumulated in glioblastoma U87 cells when deprived of serum in vitro, and miR-378 in turn
contributed to tumor angiogenesis in vivo (31). This led us to further examine alterations to the
microRNA network when cancer cells were starved. Under these conditions, we found a group of
microRNAs up-regulated therein, including miR-17 (297). MiR-17 has a controversial role in
different cancers: it can function either as an oncomir or as a tumor-suppressor depending on the
tumor type. Glioblastoma cells over-expressing miR-17 appeared “highly adaptive” as compared
to the other cancerous cells. Under favorable conditions, the proliferative capacity of miR-17-
expressing cells decreased. By reducing their metabolic rate, such growth retardation could
protect them from serum-starvation. As a result, these cells showed increased survival under
serum-free conditions. Moreover, miR-17-expressing cells became more resistant to treatments
with cytotoxic reagents, since most chemotherapeutic drugs function by diminishing highly
proliferative tumor cells. These effects appeared to be the consequence of miR-17 targeting
MDM2 and PTEN. Through the negative regulation of p53, MDM2 acts as an oncogene and
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Figure 6.1 MicroRNA-17 coordinates stress responses in cancer
By targeting multiple pathways, microRNA networks such as miR-17-associated pathway play a
key role in regulating stress response of cancer cells. These stresses may come from
chemotherapy treatment, lack of blood supply, cell apoptosis and immune attack. To respond to
these stresses, miR-17 could mediate drug resistance, angiogenesis, cell survival and immune
evasion.
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suppression of MDM2 resulted in reduced proliferation. However, PTEN is a tumor suppressor
gene which dominates the PTEN/Akt/HIF-1α a pathway. Down-regulating PTEN caused
activation of HIF-1α, which contributed to tumor survival and angiogenesis. Interestingly, HIF-
1α expression was only stabilized under stressed conditions, and acted as a sensor to detect
environmental fluctuation. Activation of HIF-1α in response to chemotherapy not only prolonged
glioblastoma cell survival, but also accelerated the transformation of TSCs. Tumor stem-like
cells have been determined as one of the most important causes of tumor recurrence. It is
believed that a sub-population of cancer cells is capable of preserving their tumorigenicity after
cytotoxic chemotherapy. But how these cells remain undamaged after treatment is not readily
explained by current theory.
The glioblastoma TSCs show characteristic over-expression of miR-17, which restrict cell
growth to an indolent pattern. Interestingly however, these cells were more able to resist drug-
treatment and generate secondary colonies. Particularly under stressed conditions, TSCs were
enriched in glioblastoma cells overexpressing miR-17. These cells showed a greater ability to
induce angiogenesis when the nutritional supply was decreased, which may contribute to evasion
of traditional chemotherapeutic treatment. Thus the effects of miR-17 in glioblastoma have two
sides. First, by shifting the metabolic requirements during periods of tumor growth, these
malignant cells can evade traditional chemotherapy regimens. Secondly, increased angiogenic
capacity allows these cancer cells to rapidly regrow through increased tumor vascularization.
The realization that microRNAs play a dual role in glioblastoma cells will provide a new
perspective to our understanding of stress responses in cancer. To adapt to fluctuations in
environmental stress, microRNA networks can balance signalings by targeting both positive and
negative regulators of tumor progression (30). Any changes leading to imbalanced signaling
might trigger the responses of microRNAs accordingly. The heterogeneity of cancer lies not only
in its genetic diversity but also in its wide array of modifications at the post-transcriptional level,
indeed posing a new challenge in developing cancer therapeutics. For example, traditional
therapy may fail to eliminate miR-17-overexpressing cancer cells which are inherently resistant
to current drug-treatments. Targeted therapy might also lead to acquired drug-resistance if
microRNA altered the therapeutic target secondary to survival pressure. Anti-angiogenic therapy
is commonly used in treating advanced glioblastoma patients, but drug-resistance has been
observed frequently. The finding that miR-17 contributes to glioblastoma angiogenesis by over-
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inducing expression of VEGF provides another possible mechanism of resistance to anti-
angiogenic therapy.
Sub-populations of cancer cells with stem cell-like properties have been shown to give rise to
secondary tumors following traditional chemotherapy. Understanding the contributions of
miRNA to these phenotypes will be valuable. For example, glioblastoma patients with high
levels of miR-17 might benefit more from surgical resection, instead of chemotherapy. To
address microRNA-induced drug-resistance, our lab has developed an anti-miRNA sponge
which can efficiently decrease specific microRNA activity in vitro and in vivo (7). The ability of
microRNAs to mediate TSC functioning highlights the importance of understanding microRNA
networks in cancer progression. Much work needs to be done to uncover the intricacies of
miRNA functioning. Understanding the mechanism may provide unprecedented opportunity in
targeted cancer therapy.
6.2 MicroRNA-regulated drug resistance in colorectal cancer
Colorectal cancer (CRC) is one of the leading causes of cancer mortality worldwide. Over the
last three decades, considerable progress has been made on the treatment of CRC. For example,
it has been estimated that over 80% of patients diagnosed with CRC after 2010 received
chemotherapy (298). Despite considerable success however, resistance to chemotherapeutic
treatment has emerged as an obstacle to effective treatment. Thus, there is a growing need in
identifying critical molecular biomarkers for predicting both the clinical outcome of
chemotherapy as well as patients at risk of developing drug resistance. Recently, it has become
clear that multiple drug resistance (MDR) arises as a consequence of an accumulation of genetic
and epigenetic alternations. Among them, the microRNA (miRNA) network has been identified
as a master regulator of MDR.
Currently, several laboratories are exploring how microRNAs manipulate drug resistance to
cause CRC tumor relapse through epigenetic modulations. Studies in the second chapter
endeavored to elucidate the underlying mechanism responsible for acquired drug resistance and
distant metastasis in CRC patients. Tumor samples from patients undergoing neoadjuvant
chemotherapy were collected and microarrays were conducted by an independent group.
Corresponding clinical outcomes were recorded according to RECIST 1.1 criteria and the
samples were categorized into either chemosensitive (CR or PR) or chemoresistant (SD or PD)
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groups. By comparing miRNA expression patterns between these two groups, it was shown that
microRNA-17 (miR-17) was consistently elevated in the chemoresistant group. We hypothesized
that miR-17 might be a predictive factor of chemotherapeutic response in colorectal cancer. We
found that high levels of miR-17 expression were closely correlated with a worsened long-term
survival in 81 patients receiving chemotherapy (5.26 vs. 7.29 years). To confirm the role of miR-
17 in inducing MDR, we stably transfected the CRC cell lines COLO205 and SW480 cells with
a miR-17 overexpression plasmid. Indeed, MDR was correlated with miR-17 expression in a
dose-dependent manner. Less drug-induced apoptosis was noted in CRC cells which highly
expressed miR-17. In addition, knocking down miR-17 by antisense oligo was found to sensitize
cells to cytotoxic agents’ treatment. This finding, in line with clinical data, provided direct
insight into how miR-17 confers a poor prognosis by affecting tumor sensitivity to
chemotherapy.
It has been long thought that resistance to chemotherapy can be divided into two categories:
innate and acquired (299). Now this theory is facing challenge with the emerging of new
evidence. In this study, we reported that the levels of miR-17 were dramatically increased under
chemotherapeutic agents’ treatment, especially in those transfected with miR-17 overexpressing
plasmid. We believed that such a change confers increased capability of tumor cells to survive in
stressed condition. Thus miR-17 overexpressing tumor cells have an innate survival advantage.
Following the selective pressure of chemotherapy, this eventually leads to the accumulation of
miR-17 in the survived fraction. We found that high expression of miR-17 completely knocked
down its target PTEN, leading to excessive activation of downstream components such as AKT
and HIF-1α. HIF-1α is capable of promoting miR-17 transcription, which in turn increases miR-
17 accumulation. (237). Given the positive feedback loop, miR-17 concentration is continually
increased after drug treatment, leading to a subsequent decrease in PTEN expression. These
findings, in line with clinical data, provided direct insight into how miR-17 confers a poor
prognosis by affecting tumor sensitivity to chemotherapy. Adding another layer of complexity
however, single microRNAs can also act pleiotropically to target several pathways. Our
understanding of these microRNA networks will help us bridge the link between innate and
acquired drug resistance, and illuminate how this transition can occur at the post-transcriptional
level. (Figure 6.2).
156
Figure 6.2 The multiplicity of microRNA targeted pathways
Accumulating evidence suggests that microRNA networks are involved in the interactions
between tumor cells and the tumor microenvironment, and play a role in drug resistance.
157
There is now growing evidence that miR-17 plays a key role in determining the prognosis of
colorectal cancer. Yu G and colleagues reported that high miR-17 expression was associated
with reduced overall survival in 96 colon cancer patients (300). These findings were in
agreement with the results published by Ma Y et al (301). Transferring miR-17 oligo mimic into
LoVo cells, the authors showed that miR-17 regulated CRC tumorigenesis by targeting P130.
This study was an important contribution to our understanding of miRNA in colon cancer. To
further reveal the crosstalk between the microRNA network and tumor microenvironment, we
generated stably transfected cell lines and showed temporal changes in miR-17 expression in
CRC cells exposed to chemotherapy. With extensive investigation, PTEN/PI3K/AKT/HIF-1α
cascade has been shown as one of the most crucial pathways which are responsible for therapy
response and oxidative stress (302). Therefore, it is with great value to decipher how epigenetic
alterations of PTEN pathway can result in chemotherapeutic drug resistance.
Given its inherent genomic instability, CRC is able to maintain growth and proliferation through
cross-talk between several signaling pathways. This level of complexity makes it more
challenging to successfully treat patients. In recognition of the important role of microRNAs in
drug resistance, future research should be focused on therapeutic strategies that target this
dysfunctional network.
6.3 MicroRNAs regulate inflammatory responses and tissue
regeneration
Through the development of cancer, inflammatory responses play decisive roles at different
levels. On the one hand, chronic inflammation increased certain cancer’s risk, such as gastric
cancer, colorectal cancer and hepatocellular carcinoma (303). On the other hand, the existence of
tumor infiltrated immune cells revealed a dynamic dialog between malignant cells and tumor
microenvironment. It is now well established that an inflammatory environment is essential
characteristic of all tumors. Anti-tumor host immune response influences tumor development,
invasion and metastasis, and it is closely correlated with the effectiveness of chemotherapy.
Almost all of the immune cells can be found in tumor microenvironment. The functions of some
of them, such as B lymphocytes, still remain largely unknown. However, there is more evidence
that many of the T cell subsets such as CD8+ cytotoxic T cells (CTLs) are able to induce direct
158
lysis of cancer cells or produce cytotoxic cytokines. In breast cancer, the presence of high level
of CD8+ T cells is indicative of better prognosis (304).
The third study focused on the influence of tumor microenvironment on tumor formation in
microRNA-17 transgenic mice. Skin melanoma B16 cells are capable of forming grafted tumors
in C57BL/6 mice. It is one of the most common used animal models in tumor formation study.
Tumor seeding on visceral organs requires aggressive tumor cells and permitted host
environment, which gave rise to the “seed and soil” theory (305). Tumor cells as seeds have to
adapt themselves to new environment. Meanwhile, stromal tissue as soil provides metastasis-
friendly condition. Both of them are essential for tumor survival. We found that, compared to
wild type mice, microRNA-17-overexpression mice showed more resistance to tumor
development. It was not due to the intrinsic change of tumor cells, since un-modified tumor cells
were used in both groups. Interestingly, more tumor infiltrative CD8+ cytotoxic T lymphocytes
were found in transgenic mice. It is increased level of inflammatory response that retarded tumor
growth. In the new era of immune therapy, our findings illustrated that breakthrough of immune
tolerance is the key to treat some aggressive tumors such as melanoma. MicoRNAs network
might be a driving force of tumor surveillance.
Chronic inflammation not only relates to cancer development, but also associates with other
pathophysiological process such as delayed wound healing. It is often happened to patients with
diabetes. The prevalence of diabetes is increasing remarkably in recent decades. By 2025, it is
expected to be 380 million, or 7.1% of the adult population who will be affected by diabetes
worldwide. The largest increase will take place mostly in developing countries. Rising level of
blood glucose is not harmful to human body until it develops complications. Thus there is a
growing need to treat diabetes related complications.
In the fourth study, we tried to understand microRNA regulated stress response at organ level. In
microRNA-378 knocking down mice, we found wound healing process was enhanced. Since
these mice were genetically modified, we need to explore a method to deliver RNA oligos for
therapeutic purpose. Gold conjugated nanoparticle (GNP) meets the requirement for several
reasons: It enters into cells without causing further damage; It has constant transfection
efficiency regardless of different cellular status; It is easy to be modified. The concept of
nanoparticle based nucleotide delivery has been demonstrated in previous studies (Figure 6.3).
159
Figure 6.3 The mechanism of gold nanoparticle based oligonucleotide delivery
Gold nanoparticle could become a useful tool to deliver oligonucleotide into targeted cells.
160
In our study, we also proved that GNP is superior to lipofectamine in transfection of antisense
microRNA in vivo. The future direction will be optimization of GNP cell specificity. Using
certain antibody modification will enable GNP reach targeted cells at higher delivery rate.
Taken together, these studies examine the role of microRNA in regulation of metabolic stress,
drug resistance, immune response and tissue regeneration. It highlights the importance of
microRNA in controlling homeostasis and stress responses. MicroRNA expression profiles are
likely served as indicators for the dysregulated stress response. More research needs to be done
to provide further clues in order to elucidate which phenotype is associated better clinical
outcome. Our findings suggest new therapeutic potential in microRNA based treatment.
161
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