Molecular Biology Reports

, Volume 39, Issue 1, pp 269–275

A genetic variant in microRNA-196a2 is associated with increased cancer risk: a meta-analysis

  • Feng Wang
  • Yan-Lei Ma
  • Peng Zhang
  • Jian-Jun Yang
  • Hong-Qi Chen
  • Zhi-Hua Liu
  • Jia-Yuan Peng
  • Yu-Kun Zhou
  • Huan-Long Qin
Article

DOI: 10.1007/s11033-011-0735-0

Cite this article as:
Wang, F., Ma, YL., Zhang, P. et al. Mol Biol Rep (2012) 39: 269. doi:10.1007/s11033-011-0735-0

Abstract

MicroRNAs (miRNAs) are small non-coding RNA molecules that function as negative regulators of gene expression. Common genetic variants (single nucleotide polymorphisms, SNPs) in miRNA genes may alter their expression or maturation resulting in varied functional consequences. Until now, several studies had evaluated the association between the polymorphisms in the hsa-miR-196a2 rs11614913 and cancer risk in diverse populations and in multiple types of cancer, with contradictory outcomes. Therefore, here we performed a meta-analysis to address the association between this polymorphism and cancer risk. A total of nine studies involving 6,540 cases and 7,562 controls were retrieved based on PubMed. Our analysis demonstrated that hsa-miR-196a2 rs11614913 CC genotype significantly increased the cancer risk in homozygote comparison model compared to TT genotype (OR = 1.18; 95% CI, 1.01–1.68). Moreover, significant association of this polymorphism with breast cancer was found based on homozygote comparison model (OR = 1.30; 95% CI, 1.01–1.26) and dominant model (OR = 1.11; 95% CI, 1.01–1.23). In addition, hsa-miR-196a2 rs11614913 CC genotype was significantly associated with cancer risk in Chinese and Indian (OR = 1.21; 95% CI, 1.05–1.40), but not in Caucasians (OR = 1.03; 95% CI, 0.89–1.19). Taken together, our results indicate that the polymorphism of hsa-miR-196a2 rs11614913 is associated with cancer susceptibility, especially with breast cancer and in Chinese and Indian populations.

Keywords

Hsa-miR-196a2 rs11614913CancerSingle nucleotide polymorphismMeta-analysis

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Feng Wang
    • 1
  • Yan-Lei Ma
    • 1
  • Peng Zhang
    • 1
  • Jian-Jun Yang
    • 1
  • Hong-Qi Chen
    • 1
  • Zhi-Hua Liu
    • 1
  • Jia-Yuan Peng
    • 1
  • Yu-Kun Zhou
    • 1
  • Huan-Long Qin
    • 1
  1. 1.Department of SurgeryThe Sixth People’s Hospital Affiliated to Shanghai Jiao Tong UniversityShanghaiPeople’s Republic of China