Development and validation of a combined glycolysis and immune prognostic signature for lung squamous cell carcinoma - Huang, Qiang; Yang, Shan; Yan, Hao; Chen, Hong; Wang, Yuzhu; Wang, Yang (Frontiers in Genetics, 2022)
Background: The involvement of glycolysis in the regulation of the tumor immune microenvironment has become a novel research field. In this study, the specific functions and clinical significance of glycolysis-related genes (GRGs) and immune-related genes (IRGs) were systematically characterized in lung squamous cell carcinoma (LUSC). Methods: We evaluated the prognostic value, interactions, somatic mutations, and copy-number variations of GRGs and IRGs in LUSC from a dataset of The Cancer Genome Atlas (TCGA). An integrated glycolysis–immune score (GIS) model was generated by random forest algorithm and stepwise Cox regression analysis. The predictive power of the GIS was examined by survival analysis, receiver operating characteristics, univariate and multivariate analyses, and subgroup analysis. The correlations between GIS and biological functions, glycolysis, immune activity, immune cell infiltration, and genomic changes were analyzed, and the potential of GIS to guide clinical treatment decisions was evaluated. Results: A total of 54 prognostic GRGs and IRGs were identified, and a strong correlation was noted among them. However, most of them had somatic mutations and a high incidence of CNV. The GIS model that contains two GRGs (PYGB and MDH1) and three IRGs (TSLP, SERPIND1, and GDF2) was generated. A high GIS indicated poor survival, and GIS was proved to be an independent and sensitive predictor by system verification. Thus, we presumed that low GIS indicated “hot” tumors with immune-activated phenotypes, whereas high GIS indicated “cold” tumors with active tumor proliferation and immunosuppression. Finally, patients with low GIS were more sensitive to chemotherapy and immunotherapy. Conclusion: An integrated model based on glycolysis and immune genes can distinguish the “cold and hot” patterns of individual tumors from biological functions and immune infiltrating systems, quantitatively estimate the prognosis of patients with LUSC, and guide chemotherapy and immunotherapy decisions.