Genome-wide analysis to identify a novel distant metastasis-related gene signature predicting survival in patients with gastric cancer

Biomed Pharmacother. 2019 Sep:117:109159. doi: 10.1016/j.biopha.2019.109159. Epub 2019 Jun 24.

Abstract

This study designed to identify a potential novel distant metastasis-related gene (DMGs) signature that predicting prognosis in patients with gastric cancer. DMGs was screened by overlapping the differentially expressed genes between M0 and M1 stage, and between tumor and adjacent normal tissue of gastric cancer by analyzing The Cancer Genome Atlas (TCGA) dataset. There were 83 DMGs were identified, the integrative analysis revealed these DMGs were involved in several biological process and pathway. A six-DMGs prognostic signature was developed based on the risk score obtained from Cox analysis. Patients with low risk score presented significantly shorter survival time. This prognostic signature has a moderate predictive value for the overall survival in gastric cancer patients, with an area under curve of 0.604. The DMGs prognostic signature also significantly associated with the overall survival of gastric cancer patients, and showed a better performance for predicting prognosis than traditional clinical indicators. The joint effect of risk score with clinical features could remarkably increased the predictive value as compared with single variable. The results from 60 gastric cancer tissues verified the prognostic value of the six-DMGs prognostic signature. In conclusions, the present study identified a novel six-DMGs prognostic signature that could serve as a biomarker for the prognosis prediction of patients with gastric cancer.

Keywords: Gastric cancer; Metastasis-Related gene; Prognostic signature; TCGA.

MeSH terms

  • Aged
  • Cohort Studies
  • Female
  • Gene Expression Profiling*
  • Gene Expression Regulation, Neoplastic*
  • Genome-Wide Association Study*
  • Humans
  • Male
  • Neoplasm Metastasis
  • Predictive Value of Tests
  • Prognosis
  • Proportional Hazards Models
  • Regression Analysis
  • Risk Factors
  • Stomach Neoplasms / genetics*
  • Stomach Neoplasms / pathology*