Development of a prognostic nomogram based on an eight-gene signature for esophageal squamous cell carcinoma by weighted gene co-expression network analysis (WGCNA).

Background: Esophageal squamous cell carcinoma (ESCC) is a highly aggressive malignant tumor. This study aims to develop a robust prognostic model for ESCC. Methods: Expression profiles of ESCC were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Co-expressed modules were constructed by weighted gene co-expression network analysis (WGCNA). Differentially expressed genes (DEGs) between ESCC and normal samples were identified with the screening criteria of adjusted P value <0.05 and log |fold change (FC)| >1. After univariate and multivariate Cox regression analysis, an 8-gene module was constructed. A receiver operating characteristic (ROC) curve for overall survival (OS) was used to assess the prediction efficacy of the risk score. A nomogram was developed based on the risk score, age, gender, and stage for 1-, 2- and 3-year survival. The potential biological functions and pathways of the 8 genes were predicted using the Metascape database. Results: The 2 ESCC-related co-expression modules were built via WGCNA. Among all DEGs, 55 survival-related genes were identified for ESCC. Based on these genes, an 8-gene module was constructed, composed of Conclusions: Our nomogram based on the 8-gene risk score could be a reliable prognostic tool for ESCC.