Association between Polymorphisms in MicroRNAs and Risk of Urological Cancer: A Meta-Analysis Based on 17,019 Subjects

Abstract

Accumulating evidence has demonstrated that some single nucleotide polymorphisms (SNPs) existing in miRNAs correlate with the susceptibility to urological cancers. However, a clear consensus still not reached due to the limited statistical power in individual study. Thus, we concluded a meta-analysis to systematically evaluate the association between microRNA SNPs and urological cancer risk. Eligible studies were collected from PubMed, Embase, Web of Science, and CNKI databases. Pooled odds ratio (OR) and corresponding 95% confidence interval (95% CI) were calculated to assess the strength of the relationships between three SNPs (miR-196a2, C>T rs11614913; miR-146a, G>C rs2910164; and miR-499, A>G rs3746444) and the risk of urological cancers. In addition, the stability of our analysis was evaluated by publication bias, sensitivity and heterogeneity analysis. Overall, a total of 17,019 subjects from 14 studies were included in this meta-analysis. We found that CT (miR-196a2, C>T rs11614913) was a risk factor for renal cell carcinoma (CT vs. CC: OR = 1.72, 95%CI = 1.05-2.80, P = 0.03, I² = 66%), especially in Asian population (CT vs. CC: OR = 1.17, 95%CI = 1.04-1.32, P < 0.01, I² = 0%). miR-146a G>C rs2910164 was a protective factor of urological cancers (C vs. G: OR = 0.87, 95%CI = 0.81-0.93, P < 0.01, I² = 0%), especially for bladder cancer. miR-499 A>G rs3746444 was correlated with an increased risk of urological cancers, specifically in Asian population. In conclusion, our meta-analysis suggests that polymorphisms in microRNAs, miR-196a2, C>T rs11614913, miR-146a G>C rs2910164 and miR-499 A>G rs3746444, may be associated with the development of urological cancers and the risks mainly exist in Asian populations.

Keywords: meta-analysis; microRNA-146a; microRNA-196a2; microRNA-499; polymorphism; urological cancers.

Figure 1

Flow diagram of the study selection process.

Figure 2

OR and 95% CIs for the associations between microRNA-146a rs2910164 G>C polymorphism and urological cancer risk in dominant genetic model for overall populations.

Figure 3

OR and 95% CIs for the associations between microRNA-146a rs2910164 G>C polymorphism and urological cancer risk in dominant genetic model stratified by cancer type.

Figure 4

OR and 95% CIs for the associations between microRNA-146a rs2910164 G>C polymorphism and urological cancer risk in dominant genetic model stratified by ethnicity.

Figure 5

OR and 95% CIs for the associations between microRNA-146a rs2910164 G>C polymorphism and urological cancer risk in dominant genetic model stratified by source of control.

Figure 6

Sensitivity analysis through the deletion of each study to reflect the individual influence on the calculated ORs in dominant genetic model of microRNA-146a rs2910164 G>C polymorphism.

Figure 7

Funnel plot analysis to detect publication bias for dominant genetic model of microRNA-146a rs2910164 G>C polymorphism. The weight of studies is presented by the size of circles.