A glycolysis-related gene signature predicts prognosis of patients with esophageal adenocarcinoma

Abstract

The Cancer Genome Atlas database was investigated for the gene expression profile of EAC patients. Glycolytic gene sets difference between EAC and normal tissues were identified via Gene set enrichment analysis (GSEA). Univariate and multivariate Cox analysis were utilized to construct a prognostic gene signature. The signature was evaluated by receiver operating characteristic curves and Kaplan-Meier curves. A prognosis model integrating clinical parameters with the gene signature was established with nomogram.