Metabolic/Proteomic Signature Defines Two Glioblastoma Subtypes With Different Clinical Outcome

Maurizio Martini, Luigi Maria Larocca, Ruggero De Maria Marchiano, Roberto Pallini, Alessandro Palma, G. Marziali, M. Signore, M. Buccarelli, S. Grande, A. Palma, M. Biffoni, A. Rosi, L. Ricci-Vitiani

Research output: Contribution to journalArticle

47 Citations (Scopus)

Abstract

Glioblastoma (GBM) is one of the deadliest human cancers. Because of the extremely unfavorable prognosis of GBM, it is important to develop more effective diagnostic and therapeutic strategies based on biologically and clinically relevant subclassification systems. Analyzing a collection of seventeen patient-derived glioblastoma stem-like cells (GSCs) by gene expression profiling, NMR spectroscopy and signal transduction pathway activation, we identified two GSC clusters, one characterized by a pro-neural-like phenotype and the other showing a mesenchymal-like phenotype. Evaluating the levels of proteins differentially expressed by the two GSC clusters in the TCGA GBM sample collection, we found that SRC activation is associated with a GBM subgroup showing better prognosis whereas activation of RPS6, an effector of mTOR pathway, identifies a subgroup with a worse prognosis. The two clusters are also differentiated by NMR spectroscopy profiles suggesting a potential prognostic stratification based on metabolic evaluation. Our data show that the metabolic/proteomic profile of GSCs is informative of the genomic/proteomic GBM landscape, which differs among tumor subtypes and is associated with clinical outcome.
Original languageEnglish
Pages (from-to)21557-N/A
JournalScientific Reports
Volume2016
DOIs
Publication statusPublished - 2016

Keywords

  • glioblastoma stem cells

Fingerprint

Dive into the research topics of 'Metabolic/Proteomic Signature Defines Two Glioblastoma Subtypes With Different Clinical Outcome'. Together they form a unique fingerprint.

Cite this