A Radiosensitivity Gene Signature and PD-L1 Status Predict Clinical Outcome of Patients with Glioblastoma Multiforme in The Cancer Genome Atlas Dataset
Authors:
Open Access
- 15 April 2020
- journal article
- research article
- Published by Korean Cancer Association in Cancer Research and Treatment
- Vol. 52 (2) , 530-542
Abstract
PurposeCombination 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. We aimed to identify a subset of patients that could potentially benefit from this strategy using The Cancer Genome Atlas (TCGA) dataset for glioblastoma (GBM).Materials and MethodsA total of 399 cases were clustered into radiosensitive versus radioresistant (RR) groups based on a radiosensitivity gene signature and were also stratified as PD-L1 high versus PD-L1 low groups by 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.ResultsWe identified a subset of GBM, PD-L1-high-RR group which showed worse survival compared to others. In PD-L1-high-RR, differentially expressed genes (DEG) were highly enriched for immune response and mapped into activation of phosphoinositide 3-kinase–AKT and mitogen-activated protein kinase (MAPK) signaling pathways. Integration of DEG and differentially methylated region identified that the kinase MAP3K8-involved in T-cell receptor signaling was upregulated and BAI1, a factor which inhibits angiogenesis, was silenced. CIBERSORT showed that a higher infiltration of the immune repertoire, which included M2 macrophages and regulatory T cells.ConclusionTaken together, PD-L1-high-RR group could potentially benefit from radiotherapy combined with PD-1/PD-L1 blockade and angiogenesis inhibition.Keywords
Funding Information
- Ministry of Science and Information and Communication Technology
- National Research Foundation of Korea (2017R1A2B4002710;2017M2A2A7A01018438)
- SNUBH Research Fund (18-2018-001)
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