Lack of association of two common polymorphisms rs2910164 and rs11614913 with susceptibility to gastric cancer: A meta-analysis

• Published in: The Turkish journal of gastroenterology Vol. 26; no. 5; pp. 378 - 385
• Main Authors: Zhang, Liwei, Gao, Jiayan, Zhou, Dan, Bao, Feng
• Format: Journal Article
• Language: English
• Published: Turkey 01.09.2015
• Subjects: DNA, Neoplasm - genetics; Genes, Neoplasm - genetics; Genetic Predisposition to Disease; Genotype; Humans; Polymorphism, Genetic; Stomach Neoplasms - genetics
• ISSN: 1300-4948; 2148-5607
• DOI: 10.5152/tjg.2015.6603

MicroRNAs post-transcriptionally regulate the expression of their target genes and their function in a wide range of physiological pathways. Aberrant expression of microRNAs has been implicated in the development of human malignant tumors. Recent reports showed that two single nucleotide polymorphisms (SNPs), miR-146a rs2910164 and miR-196a2 rs11614913, are associated with increased risk of human gastric cancer. Nevertheless, results from the published reports are still inconsistent and inconclusive. Thus, we conducted this meta-analysis study to further evaluate the effects of these two SNPs on susceptibility to human gastric cancer. Using specific inclusion and exclusion criteria, we extracted data from selected studies that were identified from electronic databases, such as PubMed, Embase, and Wanfang. Odds ratio (ORs) and 95% CIs were then obtained to determine the impact of the two SNPs on susceptibility to human gastric cancer using the statistical software Stata. We identified six studies on rs2910164 and five reports regarding rs11614913 for our meta-analysis. Our data demonstrated that the two SNPs rs2910164 and rs11614913 do not produce any effects on the risk of human gastric cancer under all genetic models. There is no significant association between rs2910164 and rs11614913 and the risk of human gastric cancer. However, future studies with large and homogeneous population of patients with gastric cancer and well-matched controls are needed to validate these findings.