Construction of prognostic risk model for patients with esophageal carcinoma based on immunogenomic analysis

Objective To construct a prognostic risk model of esophageal carcinoma (ESCA) based on immune-associated genes (IAGs) with the assistance of bioinformatics technology. Methods The gene expression data and clinical data of ESCA were downloaded from public databases to screen out prognosis-related IAGs, which were then adopted to construct a prognostic risk model of ESCA and evaluate its predictive efficiency. Results A total of nine prognosis-related IAGs were identified to construct the prognostic risk model of ESCA. The prognosis of patients in the high risk group was significantly worse than those in the low risk group. The ROC curve suggested that the model had good predictive efficiency (AUC=0.833), which can be considered as an independent prognostic risk factor for ESCA. Conclusions The prognostic risk model of ESCA based on IAGs can provide accurate prognosis assessment for ESCA patients with different clinical characteristics.