Identification of biomarkers associated with histological grade and prognosis of gastric cancer by co-expression network analysis.

ABSTRACT: The biological characteristics and clinical outcomes of gastric cancer (GC) are largely dependent on the histopathological type and degree of differentiation. The identification of the molecular mechanisms underlying the histological grade of GC may provide information about tumorigenesis and tumor progression, and may subsequently be used to develop novel therapeutic agents. The present study obtained the RNA sequencing data and clinical characteristics of patients with GC from The Cancer Genome Atlas. A total of 1,400 differentially expressed genes (DEGs) were screened between two histological grades. Weighted gene co-expression network analysis (WGCNA) was subsequently used to identify nine co-expressed gene modules, and the black module was found to be the most significant for prognosi

SUBMITTER: Chen W 

PROVIDER: S-EPMC6781762 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature