Microglia-Based Gene Expression Signature Highly Associated with Prognosis in Low-Grade Glioma

Abstract

Simple SummaryGliomas make up ~80% of malignant brain tumors in adults and are responsible for the majority of deaths from primary brain tumors. Consequently, a better understanding of the malignant features of the TME in glioma is pertinent. The aim of our study was to evaluate the expression of immune-related genes (IRGs) in glioma and their association with patient prognosis. We utilized several approaches to interrogate the glioma immune microenvironment. We found that immune genes are generally negatively associated with survival and that overall survival was significantly lower in those with a high level of microglia infiltration. The microglia abundance was significantly associated with common genomic aberrations. Lastly, we generated a 23-gene expression signature that is highly associated with patient prognosis, independent of clinical variables. These findings are relevant to investigators in the glioma field, those working in biomarker development, but also to individuals working on glioma therapeutics.Gliomas make up ~80% of malignant brain tumors in adults and are responsible for the majority of deaths from primary brain tumors. The glioma tumor microenvironment (TME) is a dynamic, heterogeneous mixture of extracellular matrix and malignant and non-malignant cells. Several ongoing clinical trials are evaluating the efficacy of therapies that target non-malignant cells, particularly immune cells. Consequently, a better understanding of the TME in glioma is pertinent. We utilized several gene expression datasets to evaluate the relationship between immune-related genes (IRGs) and patient prognosis. We generated microglia signatures using single-cell RNAseq data from human and mouse glioma cells to infer microglia abundance. Lastly, we built a LASSO Cox regression model that predicts patient survival. We found that 428 IRGs were negatively associated with survival in glioma patients. Overall survival was significantly lower in those with a high level of microglia infiltration. In addition, we also found that microglia abundance was significantly associated with several common genomic aberrations, including IDH2 and TP53 mutations. Furthermore, we found that patients with high risk scores had significantly worse overall survival than those with low risk scores in several independent datasets. Altogether, we characterized immune features predictive of overall survival in glioma and found that microglia abundance is negatively associated with survival. We developed a 23-gene risk score that can significantly stratify patients into low- and high-risk categories.