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.