Bioinformatics analysis of microenvironment-related genes associated with radioresistance in glioblastoma

Immune and stromal cells are the two major non-tumor cell types in the glioblastoma (GBM) microenvironment, which play critical roles in the prognostic assessment of tumors. Previous findings have identified genes with prognostic value in the GBM microenvironment; however, correlations between microenvironment-related genes and GBM radioresistance remain unclear. Therefore, in this study, we screened for vital microenvironment-related genes associated with radioresistance in GBM.

We analyzed the data from 348 patients with primary GBM that had undergone radiotherapy (patients with GBM-RT), in The Cancer Genome Atlas database. The Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm was used to calculate stromal and immune scores to identify the differentially expressed genes (DEGs). Functional enrichment analyses and a protein-protein interaction (PPI) network construction were performed. Survival analysis was conducted to determine genes with prognostic value. The Chinese Glioma Genome Atlas (CGGA) cohort was utilized for validation.

The stromal score was significantly correlated with the prognoses of patients with GBM-RT. Based on the stromal and immune scores, 139 common DEGs involved in inflammation or immune-related activities were identified. We also identified 86 DEGs associated with poor prognosis, which further intersected with the top nodes in the PPI network. Finally, we identified the shared DEGs using the CGGA database and found 10 genes with prognostic value that contributed to GBM radioresistance. These genes included TLR2, C3AR1, CD163, ALOX5AP, NCF2, CYBB, FCGR1A, FCGR2A, FCGR2B, and RNASE6.

We identified several genes related to the immune microenvironment that may mediate GBM radioresistance. Our findings provide a theoretical basis for predicting the radioresponse and survival of patients with GBM.