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Common genetic variants in pre‐microRNAs were associated with increased risk of breast cancer in Chinese women
Author(s) -
Hu Zhibin,
Liang Jie,
Wang Zhanwei,
Tian Tian,
Zhou Xiaoyi,
Chen Jiaping,
Miao Ruifen,
Wang Yan,
Wang Xinru,
Shen Hongbing
Publication year - 2009
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.20837
Subject(s) - breast cancer , biology , single nucleotide polymorphism , microrna , odds ratio , genetics , cancer , case control study , genotype , bioinformatics , oncology , medicine , gene
Small, noncoding RNA molecules, called microRNAs (miRNAs), are thought to function as either tumor suppressors or oncogenes. Common single‐nucleotide polymorphisms (SNPs) in miRNAs may change their property through altering miRNA expression and/or maturation, and thus they may have an effect on thousands of target mRNAs, resulting in diverse functional consequences. However, it remains largely unknown whether miRNA SNPs may alter cancer susceptibility. We evaluated the associations of selected four SNPs (rs2910164, rs2292832, rs11614913, and rs3746444) in pre‐miRNAs ( hsa‐mir‐146a , hsa‐mir‐149 , hsa‐mir‐196a2 , and hsa‐mir‐499 ) with breast cancer risk in a case‐control study of 1,009 breast cancer cases and 1,093 cancer‐free controls in a population of Chinese women and we found that hsa‐mir‐196a2 rs11614913:T>C and hsa‐mir‐499 rs3746444:A>G variant genotypes were associated with significantly increased risks of breast cancer (odds ratio [OR], 1.23; 95% confidence interval [CI], 1.02–1.48 for rs11614913:T>C; and OR, 1.25; 95% CI, 1.02–1.51 for rs3746444:A>G in a dominant genetic model) in a dose‐effect manner (P for trend was 0.010 and 0.037, respectively). These findings suggest, for the first time, that common SNPs in miRNAs may contribute to breast cancer susceptibility. Further functional characterization of miRNA SNPs and their influences on target mRNAs may provide underlying mechanisms for the observed associations and disease etiology. Hum Mutat 0, 1–6, 2008. © 2008 Wiley‐Liss, Inc.