BIOM-43. GLUTAMATE RECEPTOR AND GLUTAMINE METABOLISM PROFILING BY GENE EXPRESSION ANALYSIS AMONG PATIENTS WITH HIGH GRADE GLIOMA (HGG). (9th November 2020)

• Record Type: Journal Article
• Authors: Castro, Michael; Badra-Azar, Nilofar; Kessler, Thomas; Schütte, Moritz; Lange, Bodo; Yaspo, Marie-Laure
• Is Part Of: Neuro-oncology. Volume 22(2020)Supplement 2
• Page Start: ii11
• Page End: ii11
• Publication Date: 2020-11-09
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noaa215.042
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: BACKGROUND: Glutaminolysis and excessive glutamate production are among the metabolic hallmarks of HGG. In addition to a probable role in causing seizures, autocrine stimulation of metabotropic and ionotropic (NMDA, AMPA, and kainate) receptors are capable of activating intracellular signaling pathways that are tumorigenic and contribute to drug and radiation resistance. While hints of a survival benefit from glutamate receptor targeting have occasionally emerged from the clinic, no single strategy has consistently demonstrated efficacy. Hence, we sought to characterize the magnitude of glutamate receptor overexpression and its diversity across a population of HGG patients. METHODS: A set of 41 genes related to glutamate metabolism was selected from the literature. RNA gene counts for TCGA glioblastoma multiforme (N=163) and Grade 3 glioma samples (Astrocytoma=82, Oligodendroglioma=47, Oligoastrocytoma=39) were downloaded from https://portal.gdc.cancer.gov/ . Annotation on subtypes and PFS values were obtained from PMID: 24120142 and 26061751. Gene expression normalization as FPKM and hierarchical clustering were performed using R-3.6.0 genes. RESULTS: A heatmap with hierarchical clustering for glutamate and glutamine-related genes for the TCGA GBM and grade III glioma samples cohort was generated including colored annotation for the subtype and progression free survival. The graph shows a rough separation into two groups, with grade III gliomas and proneural samples tentatively clustering together and showing higher expression for most of the glutamate related genes. The magnitude of glutaminolysis-related gene over-expression varied significantly across the cohort suggesting a wide variety in the extent of glutamine addiction. CONCLUSION: Specific glutamate receptors are commonly upregulated in HGG patients, however the heterogeneity underlying this phenomenon suggests that uniform drug strategies are unlikely to succeed in a diverse population. However, gene expression analysis has utility to identify specific glutamate receptor and glutamine profiles and to inform the treatment strategies for discrete subsets of patients using drugs that are already in the armamentarium.