The genetic association between pri-miR-34b/c polymorphism (rs4938723 T > C) and susceptibility to cancers: evidence from published studies

Tumour Biol. 2014 Dec;35(12):12525-34. doi: 10.1007/s13277-014-2572-y. Epub 2014 Sep 6.

Abstract

Recently, several molecular epidemiological studies have focused on the association between pri-miR-34b/c rs4938723 SNP and the susceptibility to different cancers. Due to the controversial rather than conclusive results, we performed this meta-analysis to assess more precise and comprehensive conclusion about the association. Data published until July 2014 were collected from PubMed, Embase, Web of Science, Chinese National Knowledge Infrastructure, Wanfang Data, Chinese BioMedical Literature Database, and VIP database of Chinese Journal. Ultimately, 13 articles with a total of 7,753 cases and 8,014 controls were considered eligible for inclusion. The odds ratio (OR) and its 95 % confidence interval (95%CI) were used to assess the strength of association. In the overall analysis, a significant association between pri-miR-34b/c rs4938723 polymorphism and increased cancer susceptibility was found in heterozygous model (TC vs. TT: OR = 1.148, 95%CI 1.034-1.275, P = 0.010) and dominant model (CC + TC vs. TT: OR =1.166, 95%CI 1.028-1.322, P = 0.017). In subgroup analysis of ethnicity, pri-miR-34b/c rs4938723 polymorphism was significantly associated with an increased cancer susceptibility for Asian population in heterozygous model (TC vs. TT: OR = 1.169, 95%CI 1.031-1.326, P = 0.015) and dominant model (CC + TC vs. TT: OR = 1.185, 95%CI 1.017-1.382, P = 0.030), whereas no significant association for Caucasian population was observed in any genetic models. Intriguingly, stratified analysis revealed opposite results that pri-miR-34b/c polymorphism contributed to susceptibility to hepatocellular carcinoma while reduced susceptibility to colorectal cancer and esophageal squamous cell cancer in Asians. Considering some limitation of our meta-analysis, future well-designed case-control studies with larger sample sizes are required to confirm our findings.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alleles
  • Genetic Association Studies
  • Genetic Predisposition to Disease*
  • Genotype
  • Humans
  • MicroRNAs / genetics*
  • Neoplasms / diagnosis
  • Neoplasms / genetics*
  • Odds Ratio
  • Polymorphism, Single Nucleotide*
  • Publication Bias
  • Racial Groups / genetics

Substances

  • MIRN34 microRNA, human
  • MicroRNAs