Background: Programmed cell death protein-1 (PD-1) blockade therapy is one of the most remarkable immunotherapy strategies in many solid tumors, excluding glioma. The PD-1 expression, immune characteristics, and prognosis relevance in glioma remain poorly understood.
Patients and methods: RNA sequencing (RNA-seq) and mRNA microarray data were obtained for 325 and 301 glioma patients, respectively, from the Chinese Glioma Genome Atlas (CGGA) database. We analyzed the expression profile of PDCD1 (encoding PD-1) according to the different grade, isocitrate dehydrogenase (IDH) mutation status, and molecular subtype of glioblastoma. Gene ontology (GO) analyses were performed to explore biological processes of PD-1-related genes. Survival analysis was conducted using the Kaplan-Meier method. The findings were validated using The Cancer Genome Atlas (TCGA) RNA-seq data from 697 glioma samples. We also confirmed the PDCD1 gene expression feature and survival relevance in our own cohort of 73 glioma patients. R language was used for statistical analysis and generating figures.
Results: PDCD1 was enriched in glioblastoma (WHO, grade IV), IDH wild-type glioma and mesenchymal glioblastoma in CGGA and TCGA datasets; similar results were validated in our own patient cohort. GO analysis revealed that PDCD1-related genes were involved in inflammation immune responses and T cell-mediated immune responses in glioma. Circos plots indicated that PDCD1 was positively associated with CD28, ICOS, and the inhibitory checkpoint molecules CTLA4, HAVCR2, TIGIT, and LAG3. Patients with PDCD1 upregulation had much shorter overall survival.
Conclusion: PDCD1 upregulation was found in more malignant phenotypes of glioma and indicated a worse prognosis. Immunotherapy of targeting PD-1 or combined with other checkpoint molecules (eg, TIM-3, LAG-3, or TIGIT) blockade may represent a promising treatment strategy for glioma.
Keywords: The Cancer Genome Atlas; costimulatory; glioma; immunotherapy; inhibitory T-cell receptors; programmed cell death 1; survival analysis.
© 2020 Liu et al.