Identification of Immunogenic Cell Death-Related Signature for Glioma to Predict Survival and Response to Immunotherapy

SIMPLE SUMMARY: Glioma is a malignant primary brain tumor accounting for 75% of the total cases. Notably, several immunotherapeutic and chemotherapeutic agents in glioma have been demonstrated to induce immunogenic cell death (ICD). However, the studies on glioma have targeted individual ICD-related genes, and comprehensive analyses of all the ICD-related genes are still lacking. The aim of this study was to identify a novel molecular signature based on ICD-related genes in glioma, which might be beneficial for the diagnosis and treatment of glioma. We eventually identified a 14 ICD-related gene signature, which could effectively predict prognosis and immunotherapy response in glioma. These findings might be significantly helpful in selecting the best therapeutic strategy for glioma. ABSTRACT: Immunogenic cell death (ICD) is a type of regulated cell death (RCD) and is correlated with the progression, prognosis, and therapy of tumors, including glioma. Numerous studies have shown that the immunotherapeutic and chemotherapeutic agents of glioma might induce ICD. However, studies on the comprehensive analysis of the role of ICD-related genes and their correlations with overall survival (OS) in glioma are lacking. The genetic, transcriptional, and clinical data of 1896 glioma samples were acquired from five distinct databases and analyzed in terms of genes and transcription levels. The method of consensus unsupervised clustering divided the patients into two disparate molecular clusters: A and B. All of the patients were randomly divided into training and testing groups. Employing the training group data, 14 ICD-related genes were filtered out to develop a risk-score model. The correlations between our risk groups and prognosis, cells in the tumor microenvironment (TME) and immune cells infiltration, chemosensitivity and cancer stem cell (CSC) index were assessed. A highly precise nomogram model was constructed to enhance and optimize the clinical application of the risk score. The results demonstrated that the risk score could independently predict the OS rate and the immunotherapeutic response of glioma patients. This study analyzed the ICD-related genes in glioma and evaluated their role in the OS, clinicopathological characteristics, TME and immune cell infiltration of glioma. Our results may help in assessing the OS of glioma and developing better immunotherapeutic strategies.