Mining genes related to microenvironment of esophageal squamous cell carcinoma based on TCGA database

Abstract

Background：Esophageal squamous cell carcinoma (ESCC) is one of the most common malignant tumors in the world, and its mechanism is related to tumor microenvironment. Immune / stromal score can be used to identify differential expressed genes (DEGs) of cancer, but it has not been reported in ESCC.Methods: The expression profile and clinicopathological information of patients with ESCC were downloaded from The Cancer Genome Atlas (TCGA) database. The immune score and stromal score of patients with ESCC were calculated by ESTIMATE algorithm. The relationship between immune / stromal score and clinicopathological characteristics and survival prognosis of patients with ESCC was analyzed. DEGs were identified according to the score, followed by gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) analysis. The DEGs with prognostic value were revealed by overall survival analysis. Protein-protein interaction (PPI) network analysis was performed on these DEGs. Finally, the DEGs were verified by Chinese Cancer Genomic Database-Esophageal Squamous-Cell Carcinoma (CCGD-ESCC) database. Results: Immune and stromal scores were related to the prognosis of patients with ESCC. 223 DEGs were screened according to immune / stromal scores. GO and KEGG analysis showed that the selected DEGs was mainly related to plasma membrne, immune response and inflammatory response. Overall survival analysis showed that 68 genes were associated with prognosis. PPI network analysis showed that the core genes were CD86, LCP2, TLR7, CSF1R, C1QA, IRF8, CTLA4 and so on. A total of 17 genes with prognostic value were verified by CCGD-ESCC database. Conclusions: we screened and verified tumor microenvironment-related genes that have prognostic value and are expected to be used as therapeutic targets for patients with ESCC.