Establish immune-related gene prognostic index for esophageal cancer - Guo, Caiyu; Zeng, Fanye; Liu, Hui; Wang, Jianlin; Huang, Xue; Luo, Judong (Frontiers in Genetics, 2022)
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 genes prognostic index of esophageal cancer(EC), We screened 363 upregulated and 83 downregulated immune-related genes that were differentially expressed EC compared to normal tissue. By multivariate Cox regression and weighted gene coexpression network analysis (WGCNA), we built a prognostic model based on 8 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 and 83 downregulated IRGs. Next, we found a prognostic model, that was constructed with 8 IRGs (OSM, CEACAM8, HSPA6, HSP90AB1, PCSK2, PLXNA1, TRIB2, HMGB3), by multivariate Cox regression analysis and WGCNA. According to the K-M curve, the model established by us could be used as a predictive patient. The result can be verified by using the Gene Expression Omnibus (GEO). The patients were classified into two groups with different outcomes. IRGPI-low patients had a better overall survival than IRGPI-high patients. Conclusions: Our findings indicated the potential value of the IRGPI risk model for predicting the prognosis of EC patients. Keyword Esophageal cancer, RNA-seq data, Immune-related genes, Prognostic model; Overall survival, Immune-related function.