Abstract
Recent mechanistic studies have indicated that combinations of radiotherapy (RT) plus immunotherapy (via CSF-1R inhibition) can serve as a strategy to overcome RT resistance and improve the survival of glioma mice. Given the high mortality rate for glioma, including low-grade glioma (LGG) patients, it is of critical importance to investigate the mechanism of the combination of RT and immunotherapy and further translate the mechanism from mouse studies to improve survival of RT-treated human glioma patients. Using the RNA-seq data from a glioma mouse study, 874 differentially expressed genes (DEGs) between the group of RT-treated mice at glioma recurrence and the group of mice with combination treatment (RT plus CSF-1R inhibition) were translated to the human genome to identify significant molecular pathways using the KEGG enrichment analysis. The enrichment analysis yields statistically significant signaling pathways, including the phosphoinositide 3-kinase (PI3K)/AKT pathway, Hippo pathway, and Notch pathway. Within each pathway, a candidate gene set was selected by Cox regression models as genetic biomarkers for resistance to RT and response to the combination of RT plus immunotherapies. Each Cox model is trained using a cohort of 295 RT-treated LGG patients from The Cancer Genome Atlas (TCGA) database and validated using a cohort of 127 RT-treated LGG patients from the Chinese Glioma Genome Atlas (CGGA) database. A four-DEG signature (ITGB8, COL9A3, TGFB2, JAG1) was identified from the significant genes within the three pathways and yielded the area under time-dependent ROC curve AUC = 0.86 for 5-year survival in the validation set, which indicates that the selected DEGs have strong prognostic value and are potential intervention targets for combination therapies. These findings may facilitate future trial designs for developing combination therapies for glioma patients.