lunes, 4 de diciembre de 2017

A glycolysis-based ten-gene signature correlates with the clinical outcome, molecular subtype and IDH1 mutation in glioblastoma. - PubMed - NCBI

A glycolysis-based ten-gene signature correlates with the clinical outcome, molecular subtype and IDH1 mutation in glioblastoma. - PubMed - NCBI



 2017 Sep 21. pii: S1673-8527(17)30149-2. doi: 10.1016/j.jgg.2017.05.007. [Epub ahead of print]

A glycolysis-based ten-gene signature correlates with the clinical outcome, molecular subtype and IDH1 mutation in glioblastoma.

Abstract

Reprogrammed metabolism is a hallmark of cancer. Glioblastoma (GBM) tumor cells predominantly utilize aerobic glycolysis for the biogenesis of energy and intermediate nutrients. However, in GBM, the clinical significance of glycolysis and its underlying relations with the molecular features such as IDH1 mutation and subtype have not been elucidated yet. Herein, based on glioma datasets including TCGA (The Cancer Genome Atlas), REMBRANDT (Repository for Molecular Brain Neoplasia Data) and GSE16011, we established a glycolytic gene expression signature score (GGESS) by incorporating ten glycolytic genes. Then we performed survival analyses and investigated the correlations between GGESS and IDH1 mutation as well as the molecular subtypes in GBMs. The results showed that GGESS independently predicted unfavorable prognosis and poor response to chemotherapy of GBM patients. Notably, GGESS was high in GBMs of mesenchymal subtype but low in IDH1-mutant GBMs. Furthermore, we found that the promoter regions of tumor-promoting glycolytic genes were hypermethylated in IDH1-mutant GBMs. Finally, we found that high GGESS also predicted poor prognosis and poor response to chemotherapy when investigating IDH1-wildtype GBM patients only. Collectively, glycolysis represented by GGESS predicts unfavorable clinical outcome of GBM patients and is closely associated with mesenchymal subtype and IDH1 mutation in GBMs.

KEYWORDS:

Glioblastoma; Glycolysis; IDH1; Molecular subtype; Prognosis

PMID:
 
29169920
 
DOI:
 
10.1016/j.jgg.2017.05.007

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