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Association of GEMIN4 gene polymorphism and the risk of cancer: a meta-analysis

Authors Wu N, Zhang X, Tian J, Yu S, Qiao Y

Received 25 July 2017

Accepted for publication 29 September 2017

Published 2 November 2017 Volume 2017:10 Pages 5263—5271


Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Amy Norman

Peer reviewer comments 2

Editor who approved publication: Dr Yao Dai

Nan Wu, Xiaowei Zhang, Jinlong Tian, Shuang Yu, Ying Qiao

The Core Laboratory for Public Health Science and Practice, The First Affiliated Hospital of China Medical University, Shenyang, People’s Republic of China

Abstract: Gem-associated protein 4 (GEMIN4) gene is a key regulator for the miRNA biogenesis processes. Recent studies have demonstrated that some single-nucleotide polymorphisms (SNPs) in GEMIN4 gene are associated with the risk of cancer, but the results are still controversial. Therefore, we conducted a meta-analysis to analyze the association between three major SNPs (rs2740348, rs7813, and rs3744741) in the GEMIN4 gene and the risk of cancer. Relevant articles were searched in Web of Science, PubMed, Cochrane Library, Chinese Wan Fang, and Chinese National Knowledge Infrastructure databases. Pooled odds ratio (OR) with 95% confidence interval (CI) was calculated to quantitatively estimate the association. Publication bias and sensitivity analyses were undertaken to evaluate the stability of the results. Overall, the pooled results showed that rs2740348 involving 3,604 cases and 3,770 controls was significantly associated with increased cancer risk (GG vs GC/CC: OR =1.16, 95% CI =1.05–1.29, P=0.004) and rs7813 involving 4,729 cases and 4,562 controls was also related to increased cancer risk (TT vs TC/CC: OR =1.12, 95% CI =1.03–1.22, P=0.009). However, there was no significant association between rs3744741 and cancer risk under overall genetic models. In conclusion, our study has demonstrated that rs2740348 and rs7813 are associated with increased risk of cancer, and they may be new biomarkers for predicting cancer risk.

Keywords: gem-associated protein 4, single-nucleotide polymorphism, cancer, meta-analysis

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