MicroRNAs, SNPs and cancer
Angela V. Vitale,1 Huiping Tan,1,2
Peng Jin1
1Department of Human Genetics, Emory
University School of Medicine, Atlanta,
GA, USA; 2Division of Histology and
Embryology, Tongji Medical College,
Huazhong University of Science and
Technology, Wuhan, People's Republic
of China
Abstract
MiRNAs are probable regulators of cell
events such as differentiation, propagation
and apoptosis. These cellular phenomena are
also associated with benign and malignant
tumor cells, therefore, it is presumed that
miRNAs act as natural oncogenes or tumor
suppressor genes. Whether a particular miRNA
serves as either could almost be moot when
the additional problems of SNPs enter the fray.
A miRNA involved with SNPs (miR-SNPs) on
any regulatory level, whether naturally cancerinducing
or not, could easily undergo an oncogenic
transformation. This work reviews targets
of miRNAs and the miRNAs themselves
frequently containing SNPs reflecting different
risks and markers of cancer with emphasis on
familial groups and populations of shared
heredity.
Introduction
MiRNAs are short (19 to 25 nucleotides
long), evolutionarily conserved RNA structures
that can bind to the mRNA of protein coding
genes.1-3 Most often miRNAs bind within the 3’
untranslated region (UTR),4,5 though there are
cases in which miRNAs can bind the 5’ UTR6
and even within coding regions of mRNA.6,7
MiRNAs, like mRNAs, possess 5’ phosphate
groups and 3’ hydroxyl termini. They are often
found within introns of coding genes, but
some miRNAs have their expression driven by
a separate promoter. Nucleotides 7 to 8 bases
in length, often referred to as seed sites, are
located at the 5’ end of the mature form of
miRNA.8 The seed sites are usually defined by
evolutionary comparison; they are generally
conserved among distantly related species,
though there is a weaker evolutionary conservation
with the 3’ end of miRNAs as the tail is
marginally involved in binding to the target
site.9 It has been computationally estimated
that up to 30-60% of genes can have their
expression altered by the presence or absence
of miRNAs that bind to the seed site target
located on the mRNA.10,11 Single nucleotide
polymorphisms (SNPs) are base pair changes
with DNA that occur with a frequency of about
1 in 12,500 base pair or at approximately 99%
of the sites in which the same residue is present
on both homologues of chromosomes.12
SNPs are by far the most common form of
mutation in the human genome. SNPs serve as
guides to delineate possible markers for disease
causing loci, or the loci themselves in
databases such as HapMap. SNPs have typically
been used for cancer-association studies in
different ways. One involves direct examination
of genes known to be involved in the cancer
pathway; these studies are not always fruitful
as they lack statistical power and are limited
to a few genes known to interact with a specific
oncogene or tumor-suppressor gene.13
The other uses genome-wide association studies
(GWAS) in order to examine cancer association
within a large population or SNPs can
work with and within miRNAs to influence
translational control of mRNAs.13-15 SNPs are
able in some cases to generate or abolish
miRNA binding sites.16,17 SNPs have also been
credited as activating miRNAs to become oncogenes
or tumor-suppressors.18,19
These SNP base pair changes, whether
within the target site of the miRNA or the
miRNA itself have been associated with many
cancers, both in vitro and in vivo.20-22 It is not
likely coincidental that about half of all
miRNAs are located at fragile sites as well as
sites known to be involved in cancer.23 This
review largely covers the interaction of
miRNAs with their target sites, but it should be
noted that miRNA containing polymorphic
SNPs can affect transcription of the primary
transcript, and additionally, how the precursormiRNA
interacts with downstream miRNA processing
proteins. After screening more than a
hundred tumor tissues representative of 20
cancers, the expression of one miRNA, let-7e,
was significantly downregulated in vivo when
a SNP transforming an A to a G (A>G) 17bp
downstream of the miRNA was examined.24
Though this was not a bioinformatics study it
demonstrated that SNPs within the pri- or preregions
of miRNA could affect miRNA processing.
Exact knowledge on the manufacture of
the atypical expression remains elusive.24
Currently, the in silico prediction of miRNA
interaction with a purported target site does
not always agree with in vivo studies, though
these predictions do lead to further avenues of
exploration via in vivo studies and effective
case control studies.25 The association of population
based SNPs with cancers, however, is a
somewhat contested issue. It has been suggested
that many of the population sizes used
to measure the connotation with SNPs and
cancer are not large enough to make some of
the claims of association and as such more
careful case control studies are needed.26 Also
imperative is the need to link bioinformatics,
in vitro examination, in vivo research and
large case control studies.27
Canonical pathway of mammalian
miRNA biogenesis
The diminutive miRNA strands are first synthesized
as longer structures encoded for by
RNA polymerase II (RNA Pol II)28 in the typical
pathway for mRNA biogenesis. These primary
miRNA structures, termed pri-miRNA, can be
up to 3 kilobases long. Pri-miRNAs have a 5’
cap, a 3’ polyadenylated tail29,30 and have significant
secondary structure.31 Two RNA polymerase
III proteins, Drosha and Dicer, are
responsible for cleavage of the pri-miRNA into
its subsequent form.32 Before leaving the
nucleus the pri-miRNA structures are cleaved
by a complex containing Drosha and another
associated protein, DGCR833 DGCR8 is a double
stranded RNA binding protein that plays a
critical role within the microprocessor complex.
DGCR8 simultaneously binds the primiRNA
at a single stranded and double stranded
form. DGCR8 recognizes these regions
while Drosha is then free to excise a 60 to 70
base pair stem loop structure (pre-miRNA)
from the preceding form of miRNA by cleaving
single stranded RNA tails near the major stem
loop structure.34 Gregory et al.35 found that
almost 20 other proteins associate with the
microprocessor complex, though they also
showed that the Drosha/DGCR8 complex is
necessary and sufficient for correct cleavage of
pri-miRNA into pre-miRNA. Several proteins,
including the DEAD box helicases p68 and p72,
and hnRUP1-like were found to somewhat
Journal of Nucleic Acids Investigation 2011; volume 2:e6
Correspondence: Peng Jin, Department of
Human Genetics, Emory University School of
Medicine, 615 Michael Street, Rm 323, Atlanta,
GA 30322, USA
Tel. +1.404.727.3729 - Fax. +1.404.727.3949.
E-mail: peng.jin@emory.edu
Key words: MicroRNAs, SNPs, cancer, miR-SNPs.
Conflict of interest: the authors report no conflicts
of interest.
Received for publication: 23 December 2010.
Revision received: 16 March 2011.
Accepted for publication: 21 March 2011.
This work is licensed under a Creative Commons
Attribution 3.0 License (by-nc 3.0).
©Copyright A.V. Vitale et al., 2011
Licensee PAGEPress, Italy
Journal of Nucleic Acids Investigation 2011; 2:e6
doi:10.4081/jnai.2011.e6
Non-commercial use only
[Journal of Nucleic Acids Investigation 2011; 2:e6] [page 33]
lower the amount of pre-miRNA cut correctly,
suggesting there is a larger role for them in
the microprocessor machinery. In order to
escape the nucleus, correctly spliced premiRNA
binds with exportin-5 with assistance
by Ran-GTP.36 Incorrectly spliced pre-miRNA
has a lower efficiency of transfer to the cytoplasm.
36
Once successfully passed into the cytoplasm
pre-miRNA is processed into an RNA duplex.37
The strands of the miRNA duplex are cleaved
by a second RNase III enzyme, Dicer,38 which
works alongside TAR-RNA-binding-protein
(TRBP) to remove the terminal stem-loop
structure.39 This cleavage releases two strands
of miRNA. The most thermodynamically stable
strand, or guide strand, will become the
mature miRNA and complex with the
Argonaute-2 (AGO2) containing RNA-inducing
silencing complex (RISC) and the less stable
secondary strand (denoted miR*) is degraded.
40 The mRNA target is found by the complimentary
mature miRNA via RISC. The mature
miRNA and mRNA contain limited base-pairings
along the target site. This imperfection
could thus allow a single miRNA to potentially
interact with hundreds of mRNAs.11 The mRNA
target is then translationally repressed and
often slated for mRNA degradation.9
MiRNAs and their relationship to
cancer
Many miRNAs have been associated with
certain cancer phenotypes. The first known
reporting of miRNAs and their association
with some cancers was shown in Calin et al.41
This study showed a deletion of miR-15a and
miR-17-92 in chronic lymphocytic leukemia
(CLL). This group further demonstrated that a
mutation in the pri-miR-16-1 results in downregulation
of the miRNA.41 Other studies have
also shown linkage between specific and nonspecific
cancers.21 For instance, the miR-19-92
cluster is frequently found rearranged within
lymphomas29 and the miR-17-92 cluster is
found to be highly expressed in a variety of
tumors42,43 and is associated with the binding
of c-myc to E-boxes for activation of transcription.
44 In vivo and in vitro studies confirm
miR-130a targets transcription factor V-maf
musculoaponeurotic fibrosarcoma oncogene
homolog B (MAFB) and that depletion of miR-
10a upregulates HOXA1 expression. It was also
shown that miR-10a directly targets the 3’UTR
of HOXA1 RNA.44
Conversely, leukemic megakaryocytes show
upregulation of miR-101, miR-126, miR-99a,
miR-135, miR-20.44 Additional works have
pointed to miRNA differential expression leading
to context dependent effects in some cancers.
Expression signatures of cancer gene targets
within solid tumors are also beginning to
be explored45 and recently solid tumors were
used for deep sequencing and discovery of new
miRNA SNP regions.46 However it is unknown
whether these novel sequences will shed light
on SNP regions that are differentially
expressed across cancers within the same
familial clades.
Breast Cancer
A SNP in the precursor form of miR-146a
could be a target for predicting age of onset for
both ovarian and breast cancer47 though there
is some doubt about the case control methodologies.
48 A SNP in the gene antecedent
(rs2910164) changing a G>U pair to a C>U
pair in the stem region was recently associated
with age of onset of breast cancer (BC) and
ovarian cancer (OC) in unrelated groups.47 In
vitro analysis demonstrated that the rare SNP
variant binds the 3’UTR of BRCA1 more commonly
than the more common allele. This
study suggests that the miR-146a mutant precursor
may be concomitant with ovarian cancer
and breast cancer.47 A later study showed
that the miR-146a pre-miRNA rs2910164 C>G
allele was in Hardy-Weinberg equilibrium with
the rest of the comparative population with in
a case control study among Chinese women.48
Other studies point toward bioinformatics
methodologies that could shed light on both
miRNAs and their target sites with a role in
cancer.49-51 Recently, in a case control study
involving unrelated Chinese women of Han
ethnicity, two out of four pre-miRNAs studied
were shown to have significance with
increased risk of BC. The Hu et al. study indicated
that hsa-mir-196a2 rs11614913: T>C and
hsa-mir-499 rs3746444: A>G were distributed
more heavily in women of like descent.48 The
research also points out two genes, LSP1 and
TOX3, according to GWAS studies, are associated
with hsa-mir-196a2-3p and hsa-mir-
196a2-5p as newly identified BC susceptibility
markers.48
In a smaller case study, the estrogen receptor
1 (ESR1) protein product has been shown to
affect BC risk in women; based on a study predicting
polymorphic SNPs effect on gene
expression52 an ESR1 miRNA binding site was
examined for association with BC onset.53 The
populations amassed for the study included
familial BC cases and isolated cases of early
onset BC. A minor allele of ESR1 (ESR1
rs2747648T>C) within a predicted miR-453
binding site was negatively correlated with
premenopausal women and the onset of BC.53
The allele (T>C) has a protective affect
against BC, even more so in cases of familial
BC and when the C allele was present in the
homozygous condition.
BRCA1 and BRCA2 gene mutations are
involved in a majority of BCs and OCs,54,55 however,
both their penetrance and expressivity
are questioned as neither gene (or both genes
together) can truly predict an accurate outcome
of patient disease onset.56,57 Kontorovich
et al examined a population of Jewish women
at risk for BC and OC in a case control study.58
Specifically they address both miRNA binding
site SNPs as well as SNPs with the miRNAs
themselves. This is an interesting revelation
in that three BRCA2 SNPs within miRNA binding
sites were found to have different modalities
in their effect on BC and OC onset.58 Two
miRNA precursor SNPs, rs6505162 and
rs895819 are associated weakly with cancer
risk. The hsa-mir-423 SNP rs6505162 is unusual
in that it is located outside of the mature
product, but various RNA folding programs are
unable to predict any other genes with which
this miRNA with its mutant SNP interact.58
Another SNP within the activating transcription
factor 1 (ATF1) gene miRNA-binding site,
rs11169571 is strongly associated with onset of
cancer, but its mechanism is also unknown.
Rs11169571 has an affinity for binding the hsamir-
320 family and the heterozygote SNPs
have an approximately 2-fold risk for developing
BC and OC.58 One line of reasoning suggests
that the miR-320 family binds a particular
SNP blocking access to many other miRNAs
that could in theory seek presentation to ATF1.
The rs895819 SNP in its heterozygous form
has a much lower rate of cancer and is located
within the has-mir-27a pre-miRNA. Once
again, RNA fold programs cannot predict the
relevance of this particular SNP and its attachment
to BC and OC.58 Nicoloso et al. looked at
SNPS that interrupt miRNA target sites.20 The
study found that BC associated SNPs within
different populations at risk for developing BC
(BCRA1 rs799917 and TGFR1 rs334348) present
in differing amounts within somatic DNA.
TGFB1 SNP rs982073, associating with miR-
187 and XRCC1 rs1799782, associating with
miR-138 possess the ability to alter expression
by changing the target sites of each miRNA.20
An A>G SNP is also found related BC, though
its exact mechanism of action is unknown.59
Another SNP, rs89519, was assessed with a
reduction in BC within related individuals,
though again the achievement of this SNP to
aid in circumventing BC is a quandary.60
Lung cancer
Lung cancer is the third largest cause of
cancer-related deaths among men and women
in the United States.61 Let-7 has been implicated
as an oncogene in many human cancers.
Let-7 is a direct downstream target of the RAS
gene family and a recent report by Chin et al.
examines the connection between Let-7 and
KRAS, a gene within the RAS superfamily.62
LCS6 is a newly found SNP in the 3’ UTR of
KRAS, a target of Let-7. Expression of KRAS,
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and a consequent lowering of expression of
Let-7, was found to be significantly associated
with non-small lung cancer.62 Shortly after
LCS6 was shown to be tied to lung cancer
involving low-dose smokers, a reexamination
of the data cast doubt on the association.16
Though involvement of KRAS as a lung cancer
oncogene and lowered Let-7 expression is not
in doubt, the LCS6 SNP is not found to be
involved with greater risk of lung cancer.16 The
second study, involving the same populations
as the Chin et al. paper uses a slightly different
analysis of the data and the authors discuss
that the use of a smaller subset of cases coupled
with a very low association of LCS6 with
lung tumors may play a role in the most current
study negating the former study.16
Other extremely important genes that
require deeper investigation are those directly
responsible for of miRNA processing. It cannot
be ignored that any polymorphisms including
SNPs within miRNA biosynthesis genes can
have a direct effect on an individual’s cancer
susceptibility. In a two stage study using a
Sequenome mass spectrometry-based genotyping
assay for stage 1, 11 miRNA were examined
for lung cancer association.63 The intronic
AGO1 rs636832A>G was found to be a good
candidate for further study using a larger population
for analysis in a case-control study
investigating a Korean population with a little
over both 500 cancer patients and control
healthy patients. Interestingly, individuals
with at least one AA allele at rs636832 have a
higher risk of lung cancer while those with an
AG or GG alleles have a protective effect
against lung cancer.63 A possible link between
cancer risk of smokers and non-smokers was
examined with regards to AGO1 rs636832. The
AA allele was found to be initially correlated to
lung cancer prediction in heavy smokers, but
in a multivariate logistic regression this correlation
was not found.63 Further study on this
AGO1 SNP in larger case-control studies and in
different ethnic groups is needed to elucidate
its relationship with lung cancer.
Hepatocellular carcinoma
Hepatocellular carcinoma (HCC) is responsible
for the majority of liver cancers64 with the
prevalence occurring in China.65 Worldwide,
HCC is the fifth most widespread cancer and is
responsible for a third of cancer deaths.66 Mir-
146a rs2910164 SNP GG genotype was coupled
to hepatocellular carcinoma (HCC) in males.64
This is in contrast to another SNP change in
the miR-146a, a G>U pair to a C>U pair.47 This
case control study used male and female unrelated
Han Chinese participants, 479 HCC
patients and 504 controls without occurrence
of HCC.64 Hepatitis B Virus (HBV) was found
in a large cohort of the HCC patients (88.9%)
suggesting that HBV plays a role in cancer
onset of HCC and may have some interaction
with the miR-146a variant allele. Production of
mature miR-146a was also studies by transiently
transfecting 293T cells with either the
GG or CC allele. The cells transfected with the
GG allele produced more mature miR-146a.
Also discovered was the ability of the GG allele
to promote colony formation and proliferation
in transfected NIH/3T3 cells.64
Two recent studies investigated origins of
HCC and found that miR-196a2, coupled with
cirrhosis of the liver, has prognostic implications
for HCC.67,68 Using a Han Chinese population,
310 HCC patients with cirrhosis and
222 individuals with cirrhosis but without
HCC, were examined for an rs11614913 miR-
196a2 polymorphism in the first study.67
Patients with HCC and cirrhosis had a higher
level of the rs11614913 CC genotype. Various
stages of tumor tissue were collected from 59
HCC patients and the expression levels of miR-
196a were examined. No significant differences
between rs11614913 phenotypes were
seen among the different grades and stages of
tumors, though a slight association with the T
allele was shown with tumor progression.67
Patients with a CC or CT genotype overall had
a higher preponderance of HCC. Because miR-
196a2 has been previously shown to effect
expression of mature miR-196a it was thought
that levels of miR-196a2 might increase levels
of miR-196a. Indeed miR-196a expression levels
were increased in patients with a CC or CT
genotype in miR-196a2 suggesting these
miRNA polymorphisms play a role in HCC
onset in patients also displaying cirrhosis.67 In
the second study 560 patients examined had
HCC and 391 individuals without HCC were
used as the control population.68 As in the previous
study males with miR-196a2 rs11614913
CC genotype had higher levels of HCC diagnosis.
This case-control study also examined
miR-196a2 expression in different tumor
stages and concluded that the miR-196a2
rs11614913 C allele was indicative of patients
with certain types of tumors but not in patients
with large tumor, advanced-stage tumor or
lymphatic metastasis thus suggesting differential
gene regulation is playing a role in HCC
stages.68
Other cancers
Other miR-SNPs, through case control studies,
have been found to amplify or diminish
risk of other cancers. For instance, cervical
cancer is the second most globally reported
cancer for which Human Papilloma Virus
(HPV) is responsible.69 Han Chinese women
were used in a case control study recently and
a miR-SNP was examined in the LAMB3 pathway.
70 HPV through genes E6 and E7 blocks the
expression of miR-218. LAMB3 expresses
laminin-5 and this protein is greatly reduced in
the absence of miR-218. The lack of laminin-5
then further stimulates the HPV. The study
yielded an interesting result, SNP rs11134527
within pri-miR-218 has a variant linked to
increased cervical cancer.70 It is even postulated
that the variant may play a role in increased
risk of HPV infection. LAMB3 was shown to be
a direct target of miR-218 through this work.
The study could, by the author’s admission, be
expanded as the numbers involved in the case
study were rather low and the controls were
women who has self-reported to have no cancers,
but may have been harboring other
unknown cancers.70
A non-synonymous substitution in GEMIN3
has been coupled with increased bladder cancer
risk.71 This mutation is somewhat similar
to the AGO1 SNP as there is an increased risk
of lung cancer which examines an miRNA
biosynthesis gene’s relationship with cancer.63
GEMIN3 codes for a core protein of a larger
complex that plays a role in pre-miRNA splicing;
72 the protein is also in a 15S ribonucleoprotein
complex containing eIF2C, another
protein that is of great consequence with
regard to miRNA processing.73 The population
was a large and homogenous, composed of
Caucasian patients diagnosed with bladder
cancer and a control group.71 This analysis
once again points to the importance of further
study of miRNA processing genes that may
alter expression of a myriad of miRNAs potentially
involved in tumorgenesis.
Also targeting MiR-SNPS for targeted exploration
of linkage in an effort to aid in identification,
early-stage head and neck cancer
patients with high and low risk secondary primary
tumor (STP) and high- and low-risk cancer
reoccurrence.74 The population contained
only 150 patients and 300 controls matched by
age, gender and ethnicity.74 Though 18 miRSNPs
were found to be associated with STP
and/or reoccurrence, one miR-SNP in particular,
rs3747238, is located in a miRNA binding
site within SMC1B.74 The 18 miR-SNPs were
examined and found to be tied to STP/reoccurrence
in a dose dependent fashion.74Almost
half of the SNPs were located in RNASEN
(DROSHA).74 Though mutations in the
RNASEN are likely to equally affect the processing
of all pri-mRNA equally, it is postulated
that since miRNAs are expressed differentially
in tissue the RNASEN would then differentially
affect tumorgenesis.74 SMC1B is suggested
to play a role in chromosome structure during
meiosis and mitosis.75 Polymorphism in
microRNA Target Site (PolymiRTS) is a database
of DNA changes in presumed microRNA
target sites.76 PolymiRTS found that a SNP
within SMCB1 is likely to create miRNA binding
sites for miR-609 and miR-124a.75 This
SNP is thought to lower expression of SMC1B
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leading to increased carcinogenic potential via
further genome volatility.75
Responsible for a third of deaths among
genitourinary malignant cancers, renal cell
carcinoma (RCC) causes 40% mortality among
these patients.77 Though surgery is still the
best therapy for RCC, reoccurrence will arise
in 20-40% of patients.78 Because this cancer
has such a high rate of mortality it is imperative
that biological markers predictive of clinical
outcome, including miR-SNPs be recorded.
Seven miR-SNPs were found linked with cancer
survival, however five miR-SNPs were
associated with an additional RCC episode.79
GEMIN4, a protein functionally coupled with
GEMIN3, has two SNPs, rs7813T>C and
rs91025G>C associated with almost 1.75% risk
of mortality.79,80 SNP rs3744741C>T was found
concomitant with decreased risk of mortality.79
MiR-146a, miR-196a-2, miR-423, miR-608 and
miR-601 are also concomitant with RCC recurrence.
79 All of the SNPs found in the miRNAs
are located in the pre-miRNA form.79
There is a scenario in which the heterozygosity
of the SNP within a miRNA area can
lead to greater likelihood of disease. SNP
rs2910164 located in the 3 prime strand of
miR-146a can lead to an increased risk of papillary
thyroid carcinoma especially when present
as a heterozygote.81 It is suggested that the
heterozygosity somehow leads to a gestalt phenomena
wherein the sum of the parts is less
than equal to the whole via an epistatic effect
between the two alleles.81 The same group then
showed that the SNP produces three miRNAs
unlike the normal two produced in homozygous
affected individuals. Unlike the phenotype
normally seen with heterozygous individuals,
two of the mature miRNAs are produced
from the 3 prime end of miR-146a and a third
is produced from the leading strand.82 These
three mature miRNAs have the ability to bind
various mRNAs thus interrupting the normal
miR-146a interaction with a predicted variety
of mRNAs. It is thought that DNA-damage
response pathways acting on cell death signals
are invoked within the SNP heterozygote.82
This group demonstrates the genetic complexity
of miRNA interactions with target site, and
the importance of somatic mutation with
regards to an oncogenic phenotype.82
As related with BC risk and HCC, miR-146a
rs2910164 is found once again to be associated
with a distinct cancer, this time esophageal
squamous cell carcinoma (ESCC) within a
case control study among the Chinese Han.83
In this case the GG genotype was attached to
the ESCC state83 rather than a change from the
G>U pair to a C>U.47
Like HCC patients, a North Indian population
was shown to have a significant risk of
developing prostate cancer with a polymorphism
in miR-196a2 (rs11614913).84 In this
candidate gene study, miR-499 (rs3746444)
also demonstrated significant association with
prostate cancer in this case-controlled study
which examined 159 prostate cancer patients
and 230 controls.84 In this case the heterozygote
allele CT in miR-196a was associated with
disease outcome and interestingly a heterozygote
CT genotype in miR-499 also showed linkage
to prostate cancer. MiR-196a and miR-499
may work in concert to produce influence the
onset of prostate cancer and my serve as prognostic
and diagnostic indicators.84
MiRNAs: Clinical outcome predictors?
Discussed above are some of the miRNA
binding sites and miRNA SNPs that putatively
affect the outcome of BC. In silico scenarios
suggests that miR-453 binds more strongly to
an ESR1 SNP and may thus effectively lower
the amount of estrogen produced.53 Intere -
stingly the majority of BCs do express estrogen
receptors, though the cancers that do not are
more difficult to treat.85,86 The facts that these
estrogen receptor positive cancers, though
more easily treated with certain drugs, do
become easily resistant. It is suggested that
hormone replacement therapy would be a valuable
variable to study in addition to familial
cancer patients and sudden onset patients.53 It
would be invaluable to know if those patients
with the ESR1 SNP allowing more dynamic
binding of miR-453 would positively respond to
endocrine treatment, thus leading to an individualized
plan of treatment.53 The Konto -
rovich et al. study addresses their shortcomings.
58 More affected and unaffected individuals
need to be included in the study, especially
in light of the preliminary BRCA2 data suggesting
that this particular population contains
a mutant SNP possibly affecting regulatory
actions leading to BC.58 Again, with more
case control studies focusing on larger and
more diverse populations (this initial study
only focused on an Ashkenazi population displaying
little heterozygosity at the SNP mutation
sites), the possibility arises that personal
treatment plans could be designed for
patients.58 Yet another study involves integrins
which dictate cell adhesion to the extracellular
matrix.87 In a large case control study 746
Swedish patients with current or former
instances of BC were examined along with
1493 individuals without BC as controls.
Probable target sites of miRNA SNPs were
examined in integrin genes and a strong association
between the ITGB4 rs743554 A allele
and aggressive tumor formation was discovered.
87 This allele could be a strong predictive
indicator of BC risk.
It has also been shown that several cancer
cell lines will alter protein expression based on
differential regulation of miR-638 and miR-
628-5p and was concluded that small differences
in protein expression caused by the
interaction of certain regulatory genes SNPs
and miRNA will influence the onset of certain
cancers.20 In one case control study miR-21
was discovered to be involved with lung cancer
and proved a chemotherapy response marker.62
MiRNA related SNPs have also been associated
with colon cancer in patients treated with 5-
flurouracil and irinotecan.88 These SNPs were
associated with various genes, including
rs1834306, within pri-miR-100 and rs7372209
also located in a pri-miRNA, pri-miR-26a.88
Investigation of SNPs directly involved with
deleterious effects of cancer drugs would
greatly facilitate basic research studies for
cancer. Further studies involving GWAS and
large case control studies could certainly go a
long way to advancing these research studies
into something that could be used to tailormake
a treatment plan for cancer.
A significant movement advocates personalized
medicine.89,90 This group feels that much
can be done to assist individuals with a particular
SNP (or greater than one SNP) that may
leave them more likely for cancer onset.
Foremost amongst this concern is the large
number of adverse drug reactions among cancer
patients. Dihydrofolate reductase (DHFR),
when overexpressed, leads to methotrexate
resistance, a drug primarily used to treat cancer
but is also used to treat such conditions as
psoriatic arthritis.91 SNP 892C>T mutation
near the 3’UTR of DHFR hinders miR-24 from
binding its target site located within the
3’UTR. This causes upregulation of DHFR
along with its consequent drug resistance
leads to recurrence or even inability to fight
cancer. Acknowledging that much more can be
done to identify and validate particular miRSNPs
and their association to a diseased state
a recent paper points to the new laws enacted
by the United States to both encourage parents
of individuals or adult individuals to have their
genome sequenced in its entirety.92,93 By having
a trove of genetic information some sense
may be made of miR-polymorphisms and how
to effectively diagnose and treat individuals
possessing known SNPs showing incomplete
penetrance within a population or limited
expressivity within an individual.
Excitingly, a new study shows that miRSNPs
have been associated with prostate cancer
in men can be used to effectively predict
how effective of androgen-deprivation therapy
(ADT).94 15 total SNPs spread between three
prognoses (disease progression, prostate cancer-
specific mortality and all-cause mortality)
were found.94 These SNPs were found within
miRNAs and miRNA binding sites.
Combinatorial analysis between SNPs show
that during ADT, patients having a larger number
of adverse genotypes have a more rapid
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[page 36] [Journal of Nucleic Acids Investigation 2011; 2:e6]
time to progression and poorer prostate cancer-
specific survival rates.94 In effect miRSNPs
could act as prognostic markers in
patients.
Limitations of miR-SNP studies
MiR-SNP studies with regards to disease
relationship have at least two major caveats,
the population size used in the study and the
diversity of that population. There are also conflicting
reports about miR-SNPs and their ability
to affect cancer outcome.95,96 A recent report
on colorectal cancer (CRC) in Han Chinese
using 126 CRC patients and 407 healthy individuals
showed that a miR-196a2 polymorphism
(rs11614913 T>C) is not associated
with CRC. This is in direct conflict with nonepidemiological
studies demonstrating that
the polymorphism could be involved with CRC
onset.97-99 Therefore mir-196a2 would not be
indicative of a CRC condition. The gene bcl-2,
its overexpression regulated by miR-16 +7, has
been indicated as tumor suppressor with
regards to chronic lymphocytic leukemia
(CLL).100 A recent study using 39 CLL patient
demonstrated that miR-16 +7 would be a poor
diagnostic marker of CLL.26
It should be noted however that these case
control studies did not incorporate GWA studies.
GWAS is a more useful tool than traditional
methods involving linkage studies and candidate
gene analysis.101 Because many cancers
have polygenic origins it is important that many
loci are examined. GWAS has the statistical
power to perform this task in an unbiased
way.15,101 GWAS has its own limitations however
in that the data set produced by many studies is
large and complex, leading to confusion about
which SNPs may be relevant to disease.102,103
GWAS SNP analysis also requires validation in
unrelated populaces are necessary. To assist in
data analysis tools have been constructed that
will closely examine the amount of linkage disequilibrium
between SNPs. These tools are
useful in analyzing miR-SNP data as some
studies do not incorporate GWAS, but instead
concentrate solely on linkage data and candidate
gene analysis.102
Conclusions
Mir-SNPs have already been shown on a
molecular level to be associated with a plethora
of cancers. It is imperative not only to have
insight into which cancers in general have differentiating
levels of miR-SNPs, but also to
have an understanding of which miR-SNPs
would best predict cancer onset and outcome.
MiR-SNPs, used within GWA studies with a
large case-control group reflective of true population
heterogeneity may ultimately prove
successful in predicting cancer risks. 14,15,104
Interestingly, miR-146a has been shown to
be involved in a large range of cancers including
BC, OC, papillary thyroid carcinoma, renal
cell carcinoma and ESCC. Much work has been
done on BC. MiRNA mutation as well as mRNA
with modified miRNA binding sites are likely
to be useful in disease prognosis. A critical
point is that heterozygosity of miRNA-SNPs
can have an epistatic effect on gene expression.
Also crucial, not only do cancers originate
from SNPs located on miRNA binding sites of
genes directly associated with cancer and
SNPs within the miRNAs themselves, cancers
are also associated with SNPs within the
miRNA machinery genes themselves. Some
cancers show a relationship between miRNA
binding sites in genes such as GEMIN3 and
RNASEN in bladder cancer and early-stage
head and neck cancer respectively.
Genetic differentiation among cancers
across populations is only starting to be extensively
documented. As just one example, renal
cell carcinoma would greatly benefit from miRSNP
markers to trace patients likely to need
advanced forms of therapy to avoid remission
after initial treatment.79 One cautionary note
to building large databases with miR-SNP data
from many populations would be maintenance
of privacy to the donors. MiR-SNPs will prove a
notable trove of data and most likely be very
effective as a clinical outcome predictor.
References
1. Bartel DP, Chen CZ. Micromanagers of
gene expression: the potentially widespread
influence of metazoan microRNAs.
Nat Rev Genet 2004;5:396-400.
2. Kumar MS, Lu J, Mercer KL, et al. Impaired
microRNA processing enhances cellular
transformation and tumorigenesis. Nat
Genet 2007;39:673-7.
3. miRBase: the microRNA database. 2011
[updated September, 2010; cited 2011
January, 27 2011]; Available from:
http://www.mirbase.org/
4. Lim LP, Lau NC, Garrett-Engele P, et al.
Microarray analysis shows that some
microRNAs downregulate large numbers
of target mRNAs. Nature 2005;433:769-73.
5. Chiang HR, Schoenfeld LW, Ruby JG, et al.
Mammalian microRNAs: experimental
evaluation of novel and previously annotated
genes. Genes Dev 2010;24:992-1009.
6. Moretti F, Thermann R, Hentze MW.
Mechanism of translational regulation by
miR-2 from sites in the 5′ untranslated
region or the open reading frame. RNA
2010;16:2493-502.
7. Lee EK, Gorospe M. Coding region: The
neglected post-transcriptional code. RNA
Biol 2011;1. Epublished ahead of print.
8. Brennecke J, Stark A, Russell RB, Cohen
SM. Principles of MicroRNA–Target
Recognition. PLoS Biol 2005;3:e85.
9. Bartel DP. MicroRNAs: target recognition
and regulatory function. Cell 2009;136:
215-33.
10. Lewis BP, Burge CB, Bartel DP. Conserved
Seed Pairing, Often Flanked by
Adenosines, Indicates that Thousands of
Human Genes are MicroRNA Targets. Cell
2005;120:15-20.
11. Friedman RC, Farh KK-H, Burge CB, Bartel
DP. Most mammalian mRNAs are conserved
targets of microRNAs. Genom Res
2009;19:92-105.
12. Kruglyak L, Nickerson DA. Variation is the
spice of life. Nat Genet 2001;27:234-6.
13. Milne RL, Antoniou AC. Genetic modifiers
of cancer risk for BRCA1 and BRCA2 mutation
carriers. Ann Oncol 2011;22:i11-i7.
14. Easton DF, Eeles RA. Genome-wide association
studies in cancer. Hum Mol Genet
2008;17:R109-R15.
15. Varghese JS, Easton DF. Genome-wide
association studies in common cancers--
what have we learnt? Curr Opin Genet Dev
2010;20:201-9.
16. Nelson HH, Christensen BC, Plaza SL, et
al. KRAS mutation, KRAS-LCS6 polymorphism,
and non-small cell lung cancer.
Lung Cancer 2010;69:51-3.
17. Takamizawa J, Konishi H, Yanagisawa K,
et al. Reduced expression of the let-7
microRNAs in human lung cancers in
association with shortened postoperative
survival. Cancer Res 2004;64:3753-6.
18. Wynendaele J, Böhnke A, Leucci E, et al.
An Illegitimate microRNA Target Site within
the 3′ UTR of MDM4 Affects Ovarian
Cancer Progression and Chemosensitivity.
Cancer Res 2010;70:9641-9.
19. Tsang WP, Kwok TT. The miR-18a*
microRNA functions as a potential tumor
suppressor by targeting on K-Ras.
Carcinogenesis 2009;30:953-9.
20. Nicoloso MS, Spizzo R, Shimizu M, et al.
MicroRNAs [mdash] the micro steering
wheel of tumour metastases. Nat Rev
Cancer 2009;9:293-302.
21. Spizzo R, Nicoloso MS, Croce CM, Calin
GA. SnapShot: MicroRNAs in Cancer. Cell
2009;137:586-.e1.
22. Xiang J, Wu J. Feud or Friend? The Role of
the miR-17-92 Cluster in Tumorigenesis.
Curr Genomics 2010;11:129-35.
23. Calin GA, Sevignani C, Dumitru CD, et al.
Human microRNA genes are frequently
located at fragile sites and genomic
regions involved in cancers. Proc Natl Acad
Sci USA 2004;101:2999-3004.
24. Wu M, Jolicoeur N, Li Z, et al. Genetic variations
of microRNAs in human cancer and
their effects on the expression of miRNAs.
Review
Non-commercial use only
[Journal of Nucleic Acids Investigation 2011; 2:e6] [page 37]
Carcinogenesis 2008;29:1710-6.
25. Landi D, Gemignani F, Barale R, Landi S. A
catalog of polymorphisms falling in
microRNA-binding regions of cancer
genes. DNA Cell Biol 2008;27:35-43.
26. Yazici H, Zipprich J, Peng T, et al.
Investigation of the miR16-1 (C > T) + 7
Substitution in seven different types of
cancer from three ethnic groups. J Oncol
2009;2009:827532.
27. Chen K, Song F, Calin GA, et
al.Polymorphisms in microRNA targets: a
gold mine for molecular epidemiology.
Carcinogenesis 2008;29:1306-11.
28. Du T, Zamore PD. microPrimer: the biogenesis
and function of microRNA.
Development 2005;132:4645-52.
29. Davis-Dusenbery BN, Hata A. Mechanisms
of control of microRNA biogenesis. J
Biochem 2010;148:381-92.
30. Ryan BM, Robles AI, Harris CC. Genetic
variation in microRNA networks: the
implications for cancer research. Nat Rev
Cancer 2010;10:389-402.
31. Suzuki HI, Miyazono K. Emerging complexity
of microRNA generation cascades.
J Biochem 2011;149:15-25.
32. Lee Y, Ahn C, Han J, et al. The nuclear
RNase III Drosha initiates microRNA processing.
Nature 2003;425:415-9.
33. Han J. The Drosha-DGCR8 complex in primary
microRNA processing. Genes Dev
2004;18:3016-27.
34. Han J, Lee Y, Yeom K, et al. Molecular
Basis for the Recognition of Primary
microRNAs by the Drosha-DGCR8
Complex. Cell 2006;125:887-901.
35. Gregory RI, Yan K-p, Amuthan G, et al. The
Microprocessor complex mediates the
genesis of microRNAs. Nature 2004;432:
235-40.
36. Lund E, Guttinger S, Calado A, et al.
Nuclear export of microRNA precursors.
Science 2004;303:95-8.
37. Lin L, Vitale AV, Jin P. Small RNAs in
Neurological Disorders: John Wiley &
Sons, Ltd; 2010.
38. Bernstein E, Caudy AA, Hammond SM,
Hannon GJ. Role for a bidentate ribonuclease
in the initiation step of RNA interference.
Nature 2001;409:363-6.
39. Chendrimada TP, Gregory RI,
Kumaraswamy E, et al. TRBP recruits the
Dicer complex to Ago2 for microRNA processing
and gene silencing. Nature
2005;436:740-4.
40. Miyoshi K, Tsukumo H, Nagami T, et al.
Slicer function of Drosophila Argonautes
and its involvement in RISC formation.
Genes Dev 2005;19:2837-48.
41. Calin GA, Ferracin M, Cimmino A, et al. A
MicroRNA signature associated with prognosis
and progression in chronic lymphocytic
leukemia. N Engl J Med 2005;353:
1793-801.
42. He L, Thomson JM, Hemann MT, et al. A
microRNA polycistron as a potential
human oncogene. Nature 2005;435:828-33.
43. O'Donnell KA, Wentzel EA, Zeller KI, et al.
c-Myc-regulated microRNAs modulate
E2F1 expression. Nature 2005;435:839-43.
44. Garzon R, Pichiorri F, Palumbo T, et al.
MicroRNA fingerprints during human
megakaryocytopoiesis. Proceedings of the
National Academy of Sciences of the
United States of America 2006;103:5078-
83.
45. Volinia S, Calin GA, Liu C-G, et al. A
microRNA expression signature of human
solid tumors defines cancer gene targets.
Proceedings of the National Academy of
Sciences of the United States of America
2006;103:2257-61.
46. Meiri E, Levy A, Benjamin H, et al.
Discovery of microRNAs and other small
RNAs in solid tumors. Nucleic Acids Res
2010;38:6234-46.
47. Shen J, Ambrosone CB, DiCioccio RA, et
al. A functional polymorphism in the miR-
146a gene and age of familial breast/ovarian
cancer diagnosis. Carcinogenesis
2008;29:1963-6.
48. Hu Z, Liang J, Wang Z, et al. Common
genetic variants in pre-microRNAs were
associated with increased risk of breast
cancer in Chinese women. Hum Mutat
2009;30:79-84.
49. Ryan BM, Robles AI, Harris CC. Genetic
variation in microRNA networks: the
implications for cancer research. Nat Rev
Cancer 2010;10:389-402.
50. Saunders MA, Liang H, Li WH. Human
polymorphism at microRNAs and
microRNA target sites. Proceedings of the
National Academy of Sciences 2007;104:
3300-5.
51. Duan R, Pak C, Jin P. Single nucleotide
polymorphism associated with mature
miR-125a alters the processing of primiRNA.
Hum Mol Genet 2007;16:1124-31.
52. Chen K, Rajewsky N. Natural selection on
human microRNA binding sites inferred
from SNP data. Nat Genet 2006;38:1452-6.
53. Tchatchou S, Jung A, Hemminki K, et al. A
variant affecting a putative miRNA target
site in estrogen receptor (ESR) 1 is associated
with breast cancer risk in premenopausal
women. Carcinogenesis 2009;
30:59-64.
54. Wacholder S, Struewing JP, Hartge P, et al.
Breast cancer risks for BRCA1/2 carriers.
Science 2004;306:2187-91.
55. Robles-Diaz L, Goldfrank DJ, Kauff ND, et
al. Hereditary ovarian cancer in Ashkenazi
Jews. Fam Cancer 2004;3:259-64.
56. Narod SA. Modifiers of risk of hereditary
breast cancer. Oncogene 2006;25:5832-6.
57. Levy-Lahad E, Friedman E. Cancer risks
among BRCA1 and BRCA2 mutation carriers.
Br J Cancer 2007;96:11-5.
58. Kontorovich T, Levy A, Korostishevsky M,
et al. Single nucleotide polymorphisms in
miRNA binding sites and miRNA genes as
breast/ovarian cancer risk modifiers in
Jewish high-risk women. Int J Cancer
2010;127:589-97.
59. Sætrom P, Biesinger J, Li SM, et al. A Risk
Variant in an miR-125b Binding Site in
BMPR1B Is Associated with Breast Cancer
Pathogenesis. Cancer Res 2009;69:7459-
65.
60. Yang R, Schlehe B, Hemminki K, et al. A
genetic variant in the pre-miR-27a oncogene
is associated with a reduced familial
breast cancer risk. Breast Cancer Res
Treat 2010;121:693-702.
61. Prevention CfDCa. United States Cancer
Statistics. Department of Health and
Human Services; 2007 [updated 2007;
cited 2011 2/11/11]; Available from:
http://apps.nccd.cdc.gov/uscs/toptencancers.
aspx
62. Chin LJ, Ratner E, Leng S, et al. A SNP in
a let-7 microRNA Complementary Site in
the KRAS 3' Untranslated Region
Increases Non-Small Cell Lung Cancer
Risk. Cancer Res 2008;68:8535-40.
63. Kim JS, Choi YY, Jin G, et al. Association of
a common AGO1 variant with lung cancer
risk: a two-stage case-control study. Mol
Carcinog 2010;49:913-21.
64. Xu T, Zhu Y, Wei QK, et al. A functional
polymorphism in the miR-146a gene is
associated with the risk for hepatocellular
carcinoma. Carcinogenesis 2008;29:2126-
31.
65. Parkin DM. The global health burden of
infection-associated cancers in the year
2002. Int J Cancer 2006;118:3030-44.
66. El-Serag HB, Rudolph KL. Hepatocellular
Carcinoma: Epidemiology and Molecular
Carcinogenesis. Gastroenterology 2007;
132:2557-76.
67. Li XD, Li ZG, Song XX, Liu CF. A variant in
microRNA-196a2 is associated with susceptibility
to hepatocellular carcinoma in
Chinese patients with cirrhosis. Pathology
2010;42:669-73.
68. Qi P, Dou TH, Geng L, et al. Association of
a variant in MIR 196A2 with susceptibility
to hepatocellular carcinoma in male
Chinese patients with chronic hepatitis B
virus infection. Hum Immunol 2010;71:
621-6.
69. Parkin DM, Bray F, Ferlay J, Pisani P.
Global Cancer Statistics, 2002. CA Cancer J
Clin 2005;55:74-108.
70. Zhou X, Chen X, Hu L, et al. Polymor -
phisms involved in the miR-218-LAMB3
pathway and susceptibility of cervical cancer,
a case-control study in Chinese
women. Gynecol Oncol 2010;117:287-90.
Review
Non-commercial use only
[page 38] [Journal of Nucleic Acids Investigation 2011; 2:e6]
71. Yang H, Dinney CP, Ye Y, et al. Evaluation
of Genetic Variants in MicroRNA-Related
Genes and Risk of Bladder Cancer. Cancer
Res 2008;68:2530-7.
72. Shpargel KB, Matera AG. Gemin proteins
are required for efficient assembly of Smclass
ribonucleoproteins. Proc Natl Acad
Sci USA 2005;102:17372-7.
73. Mourelatos Z, Dostie J, Paushkin S, et al.
miRNPs: a novel class of ribonucleoproteins
containing numerous microRNAs.
Genes Dev 2002;16:720-8.
74. Zhang X, Yang H, Lee JJ, et al. MicroRNArelated
Genetic Variations as Predictors
for Risk of Second Primary Tumor and/or
Recurrence in Patients with Early-Stage
Head and Neck Cancer. Carcinogenesis
2010;31:2118-23.
75. Revenkova E, Eijpe M, Heyting C, et al.
Cohesin SMC1 beta is required for meiotic
chromosome dynamics, sister chromatid
cohesion and DNA recombination.
Nat Cell Biol 2004;6:555-62.
76. Bao L, Zhou M, Wu L, et al. PolymiRTS
Database: linking polymorphisms in
microRNA target sites with complex traits.
Nucleic Acids Res 35:D51-D4.
77. Jemal A, Siegel R, Ward E, et al. Cancer
statistics, 2009. CA Cancer J Clin 2009;
59:225-49.
78. Janzen NK, Kim HL, Figlin RA, Belldegrun
AS. Surveillance after radical or partial
nephrectomy for localized renal cell carcinoma
and management of recurrent disease.
Urol Clin North Am 2003;30:843-52.
79. Lin J, Horikawa Y, Tamboli P, et al. Genetic
variations in microRNA-related genes are
associated with survival and recurrence in
patients with renal cell carcinoma.
Carcinogenesis 2010;31:1805-12.
80. Horikawa Y, Wood CG, Yang H, et al. Single
nucleotide polymorphisms of microRNA
machinery genes modify the risk of renal
cell carcinoma. Clin Cancer Res 2008;14:
7956-62.
81. Jazdzewski K, Murray EL, Franssila K, et
al. Common SNP in pre-miR-146a decreases
mature miR expression and predisposes
to papillary thyroid carcinoma. Proc Natl
Acad Sci USA 2008;105:7269-74.
82. Jazdzewski K, Liyanarachchi S, Swierniak
M, et al. Polymorphic mature microRNAs
from passenger strand of pre-miR-146a
contribute to thyroid cancer. Proc Natl
Acad Sci USA 2009;106:1502-5.
83. Guo H, Wang K, Xiong G, et al. A functional
varient in microRNA-146a is associated
with risk of esophageal squamous cell carcinoma
in Chinese Han. Fam Cancer
2010;9:599-603.
84. George GP, Gangwar R, Mandal RK, et al.
Genetic variation in microRNA genes and
prostate cancer risk in North Indian population.
Mol Biol Rep 2011;38:1609-1
85. Fishman J, Osborne MP, Telang NT. The
role of estrogen in mammary carcinogenesis.
Ann NY Acad Sci 1995;768:91-100.
86. Martin G, Davio C, Rivera E, et al.
Hormone dependence of mammary tumors
induced in rats by intraperitoneal NMU
injection. Cancer Invest 1997;15:8-17.
87. Brendle A, Lei H, Brandt A, et al.
Polymorphisms in predicted microRNAbinding
sites in integrin genes and breast
cancer: ITGB4 as prognostic marker.
Carcinogenesis 2008;29:1394-9.
88. Boni V, Zarate R, Villa JC, et al. Role of primary
miRNA polymorphic variants in
metastatic colon cancer patients treated
with 5-fluorouracil and irinotecan.
Pharmacogenomics 2010 Jun 29.
89. Mishra PJ. MicroRNA polymorphisms: a
giant leap towards personalized medicine.
Per Med 2009;6:119-25.
90. Rossbach M. Small non-coding RNAs as
Novel Therapeutics. Current Molecular
Medicine. 2010;10:361-8.
91. Mishra PJ, Humeniuk R, Longo-Sorbello
GS, et al. A miR-24 microRNA binding-site
polymorphism in dihydrofolate reductase
gene leads to methotrexate resistance.
Proc Natl Acad Sci USA 2007;104:13513-8.
92. Genetic Information Nondiscrimination
Act of 2008. 2010; Available from:
http://thomas.loc.gov/cgi-bin/bdquery/
z?d110:h.r.00493:
93. National Human Genome Research
Institute. 2010; Available from:
http://www.genome.gov/10002077
94. Bao BY, Pao JB, Huang CN, et al.
Polymorphisms inside MicroRNAs and
MicroRNA Target Sites Predict Clinical
Outcomes in Prostate Cancer Patients
Receiving Androgen-Deprivation Therapy.
Clinical Cancer Research. Clin Cancer Res
2011;17:928-36.
95. Chen H, Sun LY, Chen Ll, et al. A variant
in microRNA-196a2 is not associated with
susceptibility to and progression of colorectal
cancer in Chinese. Intern Med J
2011. doi: 10.1111/j.1445-5994.2011.024
34.x[Epub ahead of print]
96. Yazici H, Zipprich J, Peng T. Investigation
of the miR16-1 (C>T) + 7 Substitution in
Seven Different Types of Cancer from
Three Ethnic Groups. J Oncol
2009;2009:827532. [Epub ahead of print]
97. Motoyama K, Inoue H, Takatsuno Y, et al.
Over- and under-expressed microRNAs in
human colorectal cancer. Int J Oncol 2009;
34:1069-75.
98. Schepeler T, Reinert JT, Ostenfeld MS, et
al. Diagnostic and prognostic microRNAs
in stage II colon cancer. Cancer Res 2008;
68:6416-24.
99. Bandres E, Agirre X, Bitarte N, et al.
Epigenetic regulation of microRNA
expression in colorectal cancer. Int J
Cancer 2009;125:2737-43.
100.Cimmino A, Calin GA, Fabbri M, et al. miR-
15 and miR-16 induce apoptosis by targeting
BCL2. Proc Natl Acad Sci USA 2005;
102:13944-9.
101.Sethupathy P, Collins FS. MicroRNA target
site polymorphisms and human disease.
Trends Genet 2008;24:489-97.
102.Xu Z, Taylor JA. SNPinfo: integrating
GWAS and candidate gene information
into functional SNP selection for genetic
association studies. Nucleic Acids Res
2009;37:W600-W5.
103.Yoshida T, Ono H, Kuchiba A, et al.
Genome-wide germline analyses on cancer
susceptibility and GeMDBJ database:
Gastric cancer as an example. Cancer Sci
2010;101:1582-9.
104.Genome-wide association study of 14,000
cases of seven common diseases and 3,000
shared controls. Nature 2007;447:661-78.
Review
Non-commercial use only
