PRLHR Immune Genes Associated with Tumor Mutation Burden Can Be Used As Prognostic Markers in Patients with Gliomas

Tumor mutation burden (TMB) is a useful biomarker for predicting the prognosis and efficacy of immune checkpoint inhibitor (ICIs). In this study, we aimed to explore the prognostic value of TMB and TMB-related PRLHR immune genes as prognostic markers in patients with gliomas. We downloaded MAF files, RNA-seq data, and clinical information from the Cancer Genome Atlas (TCGA) database. The TMB of glioma was calculated and its correlation with clinical features and prognosis was analyzed. We found that TMB was statistically correlated with the grade and age of patients with gliomas. Kaplan-Meier curve analysis showed that low TMB was associated with better clinical outcome in patients with gliomas. Additionally, a predictive model based on five HUB genes (FABP5, VEGFA, SAA1, ADM, and PRLHR) was constructed to predict OS in patients with gliomas. Receiver operating characteristic curve analysis shows that the model is reliable in predicting the risk of survival and prognosis. Immune microenvironment analysis revealed a correlation between TMB and infiltrating immune cells. The clinical-related immune gene, PRLHR, can be used as an independent prognostic factor for patients with brain glioma, and it is negatively correlated with the grade of glioma and age of patients with glioma. We found that the higher the tumor grade and the older the age, the lower the PRLHR expression, which was verified by CGGA database and independent experimental data. These results suggest that PRLHR may be a tumor suppressor for the progression of glioma and might provide a new therapeutic target for the treatment and improvement of survival rate in patients with glioma.