A Decade of GWAS Results in Lung Cancer

Cancer Epidemiol Biomarkers Prev. 2018 Apr;27(4):363-379. doi: 10.1158/1055-9965.EPI-16-0794. Epub 2017 Jun 14.

Abstract

Genome-wide association studies (GWAS) were successful to identify genetic factors robustly associated with lung cancer. This review aims to synthesize the literature in this field and accelerate the translation of GWAS discoveries into results that are closer to clinical applications. A chronologic presentation of published GWAS on lung cancer susceptibility, survival, and response to treatment is presented. The most important results are tabulated to provide a concise overview in one read. GWAS have reported 45 lung cancer susceptibility loci with varying strength of evidence and highlighted suspected causal genes at each locus. Some genetic risk loci have been refined to more homogeneous subgroups of lung cancer patients in terms of histologic subtypes, smoking status, gender, and ethnicity. Overall, these discoveries are an important step for future development of new therapeutic targets and biomarkers to personalize and improve the quality of care for patients. GWAS results are on the edge of offering new tools for targeted screening in high-risk individuals, but more research is needed if GWAS are to pay off the investment. Complementary genomic datasets and functional studies are needed to refine the underlying molecular mechanisms of lung cancer preliminarily revealed by GWAS and reach results that are medically actionable. Cancer Epidemiol Biomarkers Prev; 27(4); 363-79. ©2018 AACRSee all articles in this CEBP Focus section, "Genome-Wide Association Studies in Cancer."

Publication types

  • Historical Article
  • Review

MeSH terms

  • Datasets as Topic
  • Genetic Loci
  • Genetic Predisposition to Disease*
  • Genome-Wide Association Study / history*
  • Genomics / history
  • Genomics / methods*
  • History, 21st Century
  • Humans
  • Lung Neoplasms / genetics*
  • Lung Neoplasms / mortality
  • Lung Neoplasms / therapy
  • Polymorphism, Single Nucleotide
  • Precision Medicine / methods
  • Smoking