Identification of immune subtypes associated with CD8+ T cell-related genes providing new treatment strategies of esophageal carcinoma - Wu, Youyi; Lin, Chen; Qian, Yuchen; Huang, Xiaowei; Xu, Yajing; Li, Jiayi; He, Youdi; Xie, Congying; Su, Huafang (Frontiers in Immunology, 2025)
BackgroundCD8+ T lymphocytes greatly affect the efficacy of immunotherapy, displaying promising potential in various tumors. Here, we aimed to identify immune subtypes associated with CD8+ T cell-related genes to predict the efficacy of treatment in esophageal cancer (ESCA).MethodsWe obtained 13 immune cell-related datasets from the Gene Expression Omnibus (GEO) database and removed batch effects. Weighted correlation network analysis (WGCNA) and co-expression analysis were performed to identify highly correlated CD8+ T cell genes. Cox analysis was used to process ESCA clinical information, and the immune clusters (ICs) were constructed through consensus cluster analysis. Furthermore, we constructed an immune risk score model to predict the prognosis of ESCA based on these CD8+ T cell genes. This model was verified using the IMvigor210 dataset, and we functionally validated the immune risk score model in vitro.ResultsThe results revealed significant correlations between CD8+ T cell-related genes and immune-related pathways. Three ICs were identified in ESCA, with IC3 demonstrating the most favorable prognosis. The final 6-gene prognostic risk model exhibited stable predictive performance in datasets across different platforms. Compared with that in normal esophageal epithelial (HEEC cells), CHMP7 in the 6-gene prognostic risk model was upregulated in KYSE150 and TE-1 cells. Si-CHMP7 transfection led to a decrease in tumor cell migration, invasion, and proliferation, accompanied by an accelerated apoptotic process.ConclusionsCollectively, we identified the immune subtypes of CD8+ T cell-related genes with different prognostic significance. We designated CHMP7 in the 6-gene prognostic risk model as a potential target to improve tumor cell prognosis. These insights provide a strong basis for improving prognosis and facilitating more personalized and accurate treatment decisions for the immunotherapy of ESCA.