Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0017636 (glioblastoma)
 18,345 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Altered metabolism of glucose, lipid and glutamine is a prominent hallmark of cancer cells. Currently, cell heterogeneity is believed to be the main cause of poor prognosis of glioblastoma (GBM) and is closely related to relapse caused by therapy resistance. However, the comprehensive model of genes related to glucose-, lipid- and glutamine-metabolism associated with the prognosis of GBM remains unclear, and the metabolic heterogeneity of GBM still needs to be further explored. Based on the expression profiles of 1,395 metabolism-related genes in three datasets of TCGA/CGGA/GSE, consistent cluster analysis revealed that GBM had three different metabolic status and prognostic clusters. Combining univariate Cox regression analysis and LASSO-penalized Cox regression machine learning methods, we identified a 17-metabolism-related genes risk signature associated with GBM prognosis. Kaplan-Meier analysis found that obtained signature could differentiate the prognosis of high- and low-risk patients in three datasets. Moreover, the multivariate Cox regression analysis and receiver operating characteristic curves indicated that the signature was an independent prognostic factor for GBM and had a strong predictive power. The above results were further validated in the CGGA and GSE13041 datasets, and consistent results were obtained. Gene set enrichment analysis (GSEA) suggested glycolysis gluconeogenesis and oxidative phosphorylation were significantly enriched in high- and low-risk GBM. Lastly Connectivity Map screened 54 potential compounds specific to different subgroups of GBM patients. Our study identified a novel metabolism-related gene signature, in addition the existence of three different metabolic status and two opposite biological processes in GBM were recognized, which revealed the metabolic heterogeneity of GBM. Robust metabolic subtypes and powerful risk prognostic models contributed a new perspective to the metabolic exploration of GBM.
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PMID:Identification of a Metabolism-Related Risk Signature Associated With Clinical Prognosis in Glioblastoma Using Integrated Bioinformatic Analysis. 3304 7

Cancer cells can metabolize glutamine to replenish TCA cycle intermediates, leading to a dependence on glutaminolysis for cell survival. However, a mechanistic understanding of the role that glutamine metabolism has on the survival of glioblastoma (GBM) brain tumor stem cells (BTSC) has not yet been elucidated. Here we report that, across a panel of 19 glioblastoma BTSC lines, inhibition of glutaminase (GLS) showed a variable response from complete blockade of cell growth to absolute resistance. Surprisingly, BTSC sensitivity to GLS inhibition was a result of reduced intracellular glutamate triggering the amino acid deprivation response (AADR) and not due to the contribution of glutaminolysis to the TCA cycle. Moreover, BTSC sensitivity to GLS inhibition negatively correlated with expression of the astrocytic glutamate transporters EAAT1 and EAAT2. Blocking glutamate transport in BTSCs with high EAAT1/EAAT2 expression rendered cells susceptible to GLS inhibition, triggering the AADR and limiting cell growth. These findings uncover a unique metabolic vulnerability in BTSCs and support the therapeutic targeting of upstream activators and downstream effectors of the AADR pathway in GBM. Moreover, they demonstrate that gene expression patterns reflecting the cellular hierarchy of the tissue of origin can alter the metabolic requirements of the cancer stem cell population.
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PMID:Brain tumor stem cell dependence on glutaminase reveals a metabolic vulnerability through the amino acid deprivation response pathway. 3310 33


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