A novel immunogenic cell death-related gene risk signature can identify biomarkers of gliomas and predict the immunotherapeutic response

Immunogenic cell death (ICD) is a type of cell death that plays a pivotal role in immunity. Recent studies have identified the critical role of ICD in glioma treatment. This study aimed to use ICD-associated differentially expressed genes (ICD-DEGs) to predict survival of glioma patients. We investigated the relationship between clinical prognosis and the date-to-clinical prognosis of 1,721 glioma patients by examining the expression, methylation, and mutation status of ICD-related genes (IRGs) in these patients. Our prediction of survival in glioma patients was based on three risk genes, and we explored the association between these genes and clinical outcomes. Additionally, IRG expression was used to stratify glioma patients. We further examined the relationship among the three subgroups in terms of immune microenvironment heterogeneity and immunotherapy response. In addition, this study also included analyses of histograms and sensitivity to antitumor drugs. The expression of these genes was externally validated by RT-qPCR, Western blot (WB), and immunohistochemistry (IHC) in glioma and normal brain tissue. Our findings reveal that most IRGs are overexpressed in glioma tumor tissues, and this high expression was confirmed through histological validation. We successfully developed predictive models for three prognostic genes associated with ICD. These models not only predict survival in glioma but also correlate with the tumor's immune microenvironment. Finally, using consensus clustering, we identified three ICD-associated subtypes. Notably, patients with the C3 subtype showed high levels of immune cell infiltration, whereas those with the C1 subtype exhibited lower levels of immune cell infiltration. We successfully developed an innovative IRG-based systematic approach for evaluating glioma patients. This stratification in experimental studies opens new avenues for prognosis and assessing immunotherapy responses in glioma patients. Our study demonstrates the effectiveness of this approach in treating glioma, potentially paving the way for more promising and effective therapeutic strategies in the future.