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

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