Frontiers in Genetics (Aug 2022)
Establish immune-related gene prognostic index for esophageal cancer
Abstract
Background: Esophageal cancer is a tumor type with high invasiveness and low prognosis. As immunotherapy has been shown to improve the prognosis of esophageal cancer patients, we were interested in the establishment of an immune-associated gene prognostic index to effectively predict the prognosis of patients. Methods: To establish the immune-related gene prognostic index of esophageal cancer (EC), we screened 363 upregulated and 83 downregulated immune-related genes that were differentially expressed in EC compared to normal tissues. By multivariate Cox regression and weighted gene coexpression network analysis (WGCNA), we built a prognostic model based on eight immune-related genes (IRGs). We confirmed the prognostic model in both TCGA and GEO cohorts and found that the low-risk group had better overall survival than the high-risk group. Results: In this study, we identified 363 upregulated IRGs and 83 downregulated IRGs. Next, we found a prognostic model that was constructed with eight IRGs (OSM, CEACAM8, HSPA6, HSP90AB1, PCSK2, PLXNA1, TRIB2, and HMGB3) by multivariate Cox regression analysis and WGCNA. According to the Kaplan–Meier survival analysis results, the model we constructed can predict the prognosis of patients with esophageal cancer. This result can be verified by the Gene Expression Omnibus (GEO). Patients were divided into two groups with different outcomes. IRGPI-low patients had better overall survival than IRGPI-high patients.Conclusion: Our findings indicated the potential value of the IRGPI risk model for predicting the prognosis of EC patients.
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