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Background  Recent research on glioblastoma (GBM) has focused on deducing gene signatures predicting prognosis. The present study evaluated the mRNA expression of selected genes and correlated with outcome to arrive at a prognostic gene signature.    Methods  Patients with GBM (n = 123) were prospectively recruited, treated with a uniform protocol and followed up. Expression of 175 genes in GBM tissue was determined using qRT-PCR. A supervised principal component analysis followed by derivation of gene signature was performed. Independent validation of the signature was done using TCGA data. Gene Ontology and KEGG pathway analysis was carried out among patients from TCGA cohort.    Results  A 14 gene signature was identified that predicted outcome in GBM. A weighted gene (WG) score was found to be an independent predictor of survival in multivariate analysis in the present cohort (HR = 2 . 507; B = 0 . 919; p<0 . 001) and in TCGA cohort. Risk stratification by standardized WG score classified patients into low and high risk predicting survival both in our cohort (p = <0 . 001) and TCGA cohort (p = 0 . 001). Pathway analysis using the most differentially regulated genes (n = 76) between the low and high risk groups revealed association of activated inflammatory/immune response pathways and mesenchymal subtype in the high risk group.    Conclusion  We have identified a 14 gene expression signature that can predict survival in GBM patients. A network analysis revealed activation of inflammatory response pathway specifically in high risk group. These findings may have implications in understanding of gliomagenesis, development of targeted therapies and selection of high risk cancer patients for alternate adjuvant therapies.

A Fourteen Gene GBM Prognostic Signature Identifies Association of Immune Response Pathway and Mesenchymal Subtype with High Risk Group