Identification of the Prognostic Value of Immune-Related Genes in Esophageal Cancer

Esophageal cancer (EC) is a serious malignant tumor, both in terms of mortality and prognosis, and immune-related genes (IRGs) are key contributors to its development. In recent years, immunotherapy for tumors has been widely studied, but a practical prognostic model based on immune-related genes (IRGs) in EC has not been established and reported. This study aimed to develop an immunogenomic risk score for predicting survival outcomes among EC patients. In this study, we downloaded the transcriptome profiling data and matched clinical data of EC patients from The Cancer Genome Atlas (TCGA) database and found 4,094 differentially expressed genes (DEGs) between EC and normal esophageal tissue (p < 0.05 and fold change >2). Then, the intersection of DEGs and the immune genes in the “ImmPort” database resulted in 303 differentially expressed immune-related genes (DEIRGs). Next, through univariate Cox regression analysis of DEIRGs, we obtained 17 immune genes related to prognosis. We detected nine optimal survival-associated IRGs (HSPA6, CACYBP, DKK1, EGF, FGF19, GAST, OSM, ANGPTL3, NR2F2) by using Lasso regression and multivariate Cox regression analyses. Finally, we used those survival-associated IRGs to construct a risk model to predict the prognosis of EC patients. This model could accurately predict overall survival in EC and could be used as a classifier for the evaluation of low-risk and high-risk groups. In conclusion, we identified a practical and robust nine-gene prognostic model based on immune gene dataset. These genes may provide valuable biomarkers and prognostic predictors for EC patients and could be further studied to help understand the mechanism of EC occurrence and development.