Identification of Novel Susceptible Genes of Gastric Cancer Based on Integrated Omics Data - Yaoxing, Huang; Danchun, Yu; Xiaojuan, Sun; Shuman, Jiang; Qingqing, Yan; Lin, Jia (Frontiers in Cell and Developmental Biology, 2021)
Gastric Cancer (GC) is one of the most common cause of cancer-related deaths in the world. The cancer have been regarded as a biological and genetically heterogeneous disease with a poorly understood carcinogenesis at the molecular level. A large amount of biomarkers and susceptible loci have been explored via experimental and computational methods, but their effects on GC outcome are still unknown. Genome-wide association studies (GWAS) have also identified multiple susceptible loci for GC, but due to the linkage disequilibrium (LD), SNPs may fall within the non-coding region and exert their biological function by modulating the gene expression level. In this study, we collected 1,091 cases and 410,350 controls from GWAS catalog database. Integrating with gene expression level data obtained from stomach tissue, we conducted a machine learning based method to predict gastric cancer susceptible genes. As a result, we identified 787 novel susceptible genes related to GC, which will provide new insight into the genetic and biological basis for the mechanism and pathology of GC development.