Genetic polymorphisms and lung cancer risk: Evidence from meta-analyses and genome-wide association studies. - PubMed - NCBI
Lung Cancer. 2017 Nov;113:18-29. doi: 10.1016/j.lungcan.2017.08.026. Epub 2017 Sep 1.
Genetic polymorphisms and lung cancer risk: Evidence from meta-analyses and genome-wide association studies.
Abstract
A growing number of studies investigating the association between Single Nucleotide Polymorphisms (SNPs) and lung cancer risk have been published since over a decade ago. An updated integrative assessment on the credibility and strength of the associations is required. We searched PubMed, Medline, and Web of Science on or before August 29th, 2016. A total of 198 articles were deemed eligible for inclusion, which addressed the associations between 108 variants and lung cancer. Among the 108 variants, 63 were reported to be significantly associated with lung cancer while the remaining 45 were reported non-significant. Further evaluation integrating the Venice Criteria and false-positive report probability (FPRP) was performed to determine the strength of cumulative epidemiological evidence for the 63 significant associations. As a result, 15 SNPs on or near 12 genes and one miRNA with strong evidence of association with lung cancer risk were identified, including TERT (rs2736098), CHRNA3 (rs1051730), AGPHD1 (rs8034191), CLPTM1L (rs401681 and rs402710), BAT3 (rs3117582), TRNAA (rs4324798), ERCC2 (Lys751Gln), miR-146a2 (rs2910164), CYP1B1 (Arg48Gly), GSTM1 (null/present), SOD2 (C47T), IL-10 (-592C/A and -819C/T), and TP53 (intron 6). 19 SNPs were given moderate rating and 17 SNPs were rated as having weak evidence. In addition, all of the 29 SNPs identified in 12 genome-wide association studies (GWAS) were proved to be noteworthy based on FPRP value. This review summarizes and evaluates the cumulative evidence of genetic polymorphisms and lung cancer risk, which can serve as a general and useful reference for further genetic studies. Copyright © 2017 Elsevier B.V. All rights reserved.
KEYWORDS:
Genome-wide association study; Lung cancer; Meta-analysis; Polymorphisms
No hay comentarios:
Publicar un comentario