A four-gene signature-derived risk score for glioblastoma: prospects for prognostic and response predictive analyses

Objective: Glioblastoma (GBM) is the most common primary malignant brain tumor regulated by numerous genes, with poorsurvival outcomes and unsatisfactory response to therapy. Therefore, a robust, multi-gene signature-derived model is required topredict the prognosis and treatment response in GBM. Methods: Gene expression data of GBM from TCGA and GEO datasets were used to identify differentially expressed genes (DEGs)through DESeq2 or LIMMA methods. The DEGs were then overlapped and used for survival analysis by univariate andmultivariate COX regression. Based on the gene signature of multiple survival-associated DEGs, a risk score model was established,and its prognostic and predictive role was estimated through Kaplan–Meier analysis and log-rank test. Gene set enrichmentanalysis (GSEA) was conducted to explore high-risk score-associated pathways. Western blot was used for protein detection. Results: Four survival-associated DEGs of GBM were identified: OSMR, HOXC10, SCARA3, and SLC39A10. The four-genesignature-derived risk score was higher in GBM than in normal brain tissues. GBM patients with a high-risk score had poorsurvival outcomes. The high-risk group treated with temozolomide chemotherapy or radiotherapy survived for a shorter durationthan the low-risk group. GSEA showed that the high-risk score was enriched with pathways such as vasculature development andcell adhesion. Western blot confirmed that the proteins of these four genes were differentially expressed in GBM cells. Conclusions: The four-gene signature-derived risk score functions well in predicting the prognosis and treatment response inGBM and will be useful for guiding therapeutic strategies for GBM patients. Cite this article as: Cao M, Cai J, Yuan Y, Shi Y, Wu H, Liu Q, et al. A fourgenesignature-derived risk score for glioblastoma: prospects for prognosticand response predictive analyses. Cancer Biol Med. 2019; 16: 595-605. doi:10.20892/j.issn.2095-3941.2018.0277