Prognostic Features of the Tumor Immune Microenvironment in Glioma and Their Clinical Applications: Analysis of Multiple Cohorts - Zhang, Chunlong; Zhang, Yuxi; Tan, Guiyuan; Mi, Wanqi; Zhong, Xiaoling; Zhang, Yu; Zhao, Ziyan; Li, Feng; Xu, Yanjun; Zhang, Yunpeng (Frontiers in Immunology, 2022)
Glioma is the most common malignant tumor of the central nervous system. Tumor purity is a source of important prognostic factor for glioma patients, showing the key roles of microenvironment in glioma prognosis. In this study, we systematically screened functional characterization related with tumor immune microenvironment, and constructed a risk model named Glioma MicroEnvironment Functional Signature (GMEFS) based on eight cohorts. The prognostic value of GMEFS model was also verified in another two glioma cohorts from GBM and LGG cohorts from The Cancer Genome Atlas (TCGA). Nomograms were established in the training and testing cohorts to validate the clinical use of this model. Furthermore, relationships between the risk score, intrinsic molecular subtypes, tumor purity, and tumor-infiltrating immune cell abundances were also evaluated. In the meanwhile, the performance of the GMEFS model in glioma formation and glioma recurrence were systematical analyzed, based on 16 glioma cohorts from Gene Expression Omnibus (GEO) database. Based on multiple cohorts integrated analysis, risk subpathway signatures were identified, and a drug-subpathway association network was further constructed for exploring candidate therapy target regions. Three subpathways derived from Focal adhesion (path: 04510) were identified and contained known target including PDGFRA, EGFR and ERBB2. In conclusion, the novel functional signatures identified in this study could serve as a robust prognostic biomarker and this study provided a framework for identifying candidate therapeutic target regions, which further guidance glioma patients clinical decision.