Abstract B168: A Radiosensitivity gene signature and PD-L1 status predict clinical outcome of patients with glioblastoma multiforme in The Cancer Genome Atlas Dataset

Background: A combination of radiotherapy and immune checkpoint blockade, such as programmed death-1 (PD-1) or programmed death-ligand 1 (PD-L1) blockade, is being actively tested in clinical trial settings. Here, we tried to identify a subset of patients that could potentially benefit from this strategy using The Cancer Genome Atlas (TCGA) dataset for glioblastoma (GBM). Methods: A total of 399 cases were clustered into radiosensitive (RS) versus radioresistant (RR) groups based on radiosensitivity gene signature and were further stratified into PD-L1 high versus PD-L1 low groups according to the median expression of CD274 mRNA. Differential and integrated analyses with expression and methylation data were performed. CIBERSORT was used to enumerate the immune repertoire that resulted from transcriptome profiles. Results: We identified a subset of GBM patients, the “PD-L1 high-RR group” that had a worse clinical outcome compared to the other groups. In this group, differentially expressed genes (DEG) were highly enriched for an immune response and mapped into activation of PI3K-AKT and MAPK signaling pathways. Through integration of DEG and differentially methylated regions, kinase MAP3K8, which is involved in T-cell receptor signaling, was found to be upregulated, while BAI1, a factor that inhibits angiogenesis, was silenced. CIBERSORT showed that a higher infiltration of the immune repertoire, which included M2 macrophages and regulatory T-cells, contributed to an immunosuppressive tumor microenvironment. Conclusion: Looking at the results collectively, the “PD-L1-high-RR group” could potentially benefit from radiotherapy combined with PD-1/PD-L1 blockade and angiogenesis inhibition. Citation Format: Inah Kim, Bum Sup Jang. A Radiosensitivity gene signature and PD-L1 status predict clinical outcome of patients with glioblastoma multiforme in The Cancer Genome Atlas Dataset [abstract]. In: Proceedings of the Fourth CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; Sept 30-Oct 3, 2018; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2019;7(2 Suppl):Abstract nr B168.