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

Abstract

BackgroundRecent 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.MethodsPatients 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.ResultsA 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.ConclusionWe 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.

Glioblastoma-derived Macrophage Colony-stimulating Factor (MCSF) Induces Microglial Release of Insulin-like Growth Factor-binding Protein 1 (IGFBP1) to Promote Angiogenesis

“…C, annotated MS/MS spectra of five different IGFBP1 peptides. (49). Correspondingly, we also found that MCSF mRNA level was a poor prognostic indicator in GBM and that a subgroup with high MCSF mRNA is enriched with mesenchymal GBM patients significantly.…”

TP53 gain-of-function mutation promotes inflammation in glioblastoma

“…Inflammation accelerates cancer progression in GBM and enables resistance to treatment. Analysis of tissue samples from patients, used for selecting prognostic gene signatures, indicated that predictive gene signatures were mostly associated with inflammatory response [40]. Similarly, increase in the number of neutrophils and inflammatory serum protein levels is associated with poor prognosis [41,42].…”

Molecular sub-group-specific immunophenotypic changes are associated with outcome in recurrent posterior fossa ependymoma

“…This immunosuppressed phenotype is proposed to dampen the anti-tumor effect conferred by innate host immunity and has been associated with worse clinical outcome [38]. However, there is recent evidence by two groups, both who utilized transcriptome microarray, that immunophenotypic variation exists amongst previously described molecular sub-types of glioblastoma [10, 2]. Immunobiologic characteristics of pediatric brain tumors are less well known.…”