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Review
. 2018 Mar 1:11:1121-1139.
doi: 10.2147/OTT.S154211. eCollection 2018.

rs11614913 polymorphism in miRNA-196a2 and cancer risk: an updated meta-analysis

Yuhan Liu #  1 , Anbang He #  1   2 , Baoer Liu  1 , Yucheng Zhong  1 , Xinhui Liao  1 , Jiangeng Yang  1 , Jieqing Chen  1 , Jianting Wu  1 , Hongbing Mei  1
Affiliations
Review

rs11614913 polymorphism in miRNA-196a2 and cancer risk: an updated meta-analysis

Yuhan Liu et al. Onco Targets Ther. .

Abstract

Several epidemiological studies have reported that polymorphisms in microRNA-196a2 (miR-196a2) were associated with various cancers. However, the results remained unverified and were inconsistent in different cancers. Therefore, we carried out an updated meta-analysis to elaborate the effects of rs11614913 polymorphism on cancer susceptibility. A total of 84 articles with 35,802 cases and 41,541 controls were included to evaluate the association between the miR-196a2 rs11614913 and cancer risk by pooled odds ratios (ORs) and 95% confidence intervals (CIs). The results showed that miR-196a2 rs11614913 polymorphism is associated with cancer susceptibility, especially in lung cancer (homozygote comparison, OR =0.840, 95% CI =0.734-0.961; recessive model, OR =0.858, 95% CI =0.771-0.955), hepatocellular carcinoma (allelic contrast, OR =0.894, 95% CI =0.800-0.998; homozygote comparison, OR =0.900, 95% CI =0.813-0.997; recessive model, OR =0.800, 95% CI =0.678-0.944), and head and neck cancer (allelic contrast, OR =1.076, 95% CI =1.006-1.152; homozygote comparison, OR =1.214, 95% CI =1.043-1.413). In addition, significant association was found among Asian populations (allele model, OR =0.847, 95% CI =0.899-0.997, P=0.038; homozygote model, OR =0.878, 95% CI =0.788-0.977, P=0.017; recessive model, OR =0.895, 95% CI =0.824-0.972, P=0.008) but not in Caucasians. The updated meta-analysis confirmed the previous results that miR-196a2 rs11614913 polymorphism may serve as a risk factor for patients with cancers.

Keywords: cancer risk; meta-analysis; miR-196a2; polymorphisms.

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Conflict of interest statement

Disclosure The authors report no conflicts of interest in this work.

Figures

Figure 1
Figure 1
The flow diagram of the included and excluded studies.
Figure 2
Figure 2
Forest plots of the association between miR-196a2 rs11614913 polymorphism and cancer risk in different cancer types for homozygote comparison (TT vs CC). Note: Weights are from random effects analysis. Abbreviations: BRC, breast cancer; CRC, colorectal cancer; ESCC, esophageal squamous cell carcinoma; GC, gastric cancer; HCC, hepatocellular carcinoma; HNC, head and neck cancer; LC, lung cancer; miR-196a2, microRNA-196a2; OR, odds ratio.
Figure 3
Figure 3
Forest plots of the association between miR-196a2 rs11614913 polymorphism and cancer risk in different cancer types for recessive model (TT vs TC+CC). Note: Weights are from random effects analysis. Abbreviations: BRC, breast cancer; CRC, colorectal cancer; ESCC, esophageal squamous cell carcinoma; GC, gastric cancer; HCC, hepatocellular carcinoma; HNC, head and neck cancer; LC, lung cancer; miR-196a2, microRNA-196a2; OR, odds ratio.
Figure 4
Figure 4
Begg’s funnel plot for publication bias of miR-196a2 rs11614913 polymorphism and cancer risk by homozygote comparison and recessive model. Notes: Each point represents a separate study for the indicated association. LogES represents natural logarithm of OR. Horizontal line means magnitude of the effect. Funnel plot with pseudo 95% confidence limits was used. Abbreviations: miR-196a2, microRNA-196a2; OR, odds ratio.
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