CBMT-18. INTEGRATIVE CROSS PLATFORM ANALYSES IDENTIFY ENHANCED HETEROTROPHY AS A METABOLIC HALLMARK IN GLIOBLASTOMA. (5th November 2018)

• Record Type: Journal Article
• Authors: Prabhu, Antony; Kant, Shiva; Kesarwani, Pravin; Ahmed, Kamran; Forsyth, Peter; Nakano, Ichiro; Chinnaiyan, Prakash
• Is Part Of: Neuro-oncology. Volume 20(2018)Supplement 6
• Page Start: vi36
• Page End: vi36
• Publication Date: 2018-11-05
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noy148.137
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: Although considerable progress has been made in understanding molecular alterations driving gliomagenesis, diverse metabolic programs contributing towards is aggressive phenotype remains unclear. We performed integrative cross platform analyses coupling global metabolomic profiling with genomics in patient-derived glioma (low-grade astrocytoma [LGA; n=28] and glioblastoma [GBM; n=80]) to define and provide molecular context to metabolic reprogramming driving gliomagenesis. Clear metabolic programs were identified differentiating LGA from GBM, with aberrant lipid, peptide and amino acid metabolism representing the most dominant metabolic nodes associated with malignant transformation. Although the metabolomic profiles of GBM and LGA appeared mutually exclusive, considerable metabolic heterogeneity was still observed in GBM. Surprisingly, these integrative analyses demonstrated that MGMT methylation and IDH mutation status, which represent two of the strongest prognostic factors in GBM, were equally distributed among GBM metabolic subtypes. Transcriptional subtypes, on the other hand, tightly clustered by their metabolomic signature, with proneural and mesenchymal tumors' profiles being mutually exclusive. Extending genomic signatures of individual metabolic phenotypes to Ivy GAP, we demonstrated the observed metabolic subtypes were a function of intra - rather than inter -tumoral heterogeneity. Integrating these metabolic phenotypes with gene expression analyses uncovered tightly orchestrated and highly redundant transcriptional programs designed to support the observed metabolic programs by actively importing these biochemical substrates from the microenvironment. These findings were metabolomically, genomically, and functionally recapitulated in preclinical models by demonstrating the potential of subtype-specific GBM lines to actively important fatty acids and protein/amino acids from the environment. This contributed to a state of enhanced metabolic heterotrophy supporting survival in diverse microenvironments that are implicit in this malignancy. Collectively, we demonstrate that despite disparate molecular pathways driving the progression of GBM, metabolic programs designed to maintain its aggressive phenotype remain conserved and are a function of its diverse tumor ecology.