Association of miR-608 rs4919510 polymorphism and cancer risk: a meta-analysis based on 13,664 subjects
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Huiquan Liu1, Yaqun Zhou2, Qingquan Liu3, Guangqin Xiao4, Bangyan Wang1, Weijuan Li1, Dawei Ye1 and Shiying Yu1
1Cancer Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
2Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
3Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
4Department of Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
Dawei Ye, email: [email protected]
Shiying Yu, email: [email protected]
Keywords: miR-608, rs4919510, polymorphism, cancer risk, meta-analysis
Received: February 03, 2016 Accepted: April 16, 2016 Published: May 20, 2016
Single nucleotide polymorphisms (SNPs) in MicroRNAs (miRNAs) are involved in the mechanism of carcinogenesis. Several studies have evaluated the association of rs4919510 SNP in miR-608 with cancer susceptibility in different types of cancer, with inconclusive outcomes. To obtain a more precise estimation, we carried out this meta-analysis through systematic retrieval from the PubMed and Embase database. A total of 10 case-control studies were analyzed with 6,000 cases and 7,664 controls. The results showed that 4919510 SNP in miR-608 was significantly associated with decreased cancer risk only in recessive model (CC vs. GG+GC: OR=0.89, 95% CI: 0.82-0.97, P=0.009). By further stratified analysis, we found that rs4919510 SNP had some relationship with decreased cancer risk in both homozygote model (CC vs. GG: OR=0.59, 95% CI: 0.36-0.96, P=0.034) and dominant model (CG+ CC vs. GG: OR=0.60, 95% CI: 0.37-0.98, P=0.042) in Caucasians but no relationship in any genetic model in Asians. These results indicated that miR-608 rs4919510 polymorphism may contribute to the decreased cancer susceptibility and could be a promising target to forecast cancer risk for clinical practice. However, to further confirm these results, well-designed large scale case–control studies are needed in the future.
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