Integrative cross-platform analyses identify enhanced heterotrophy as a metabolic hallmark in glioblastoma. Issue 3 (10th November 2018)

• Record Type: Journal Article
• Authors: Prabhu, Antony H; Kant, Shiva; Kesarwani, Pravin; Ahmed, Kamran; Forsyth, Peter; Nakano, Ichiro; Chinnaiyan, Prakash
• Is Part Of: Neuro-oncology. Volume 21:Issue 3(2019)
• Page Start: 337
• Page End: 347
• Publication Date: 2018-11-10
• Subjects: genomics -- glioblastoma -- integrative analyses -- intratumoral heterogeneity -- metabolomics; Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noy185
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: Background: Although considerable progress has been made in understanding molecular alterations driving gliomagenesis, the diverse metabolic programs contributing to the aggressive phenotype of glioblastoma remain unclear. The aim of this study was to define and provide molecular context to metabolic reprogramming driving gliomagenesis. Methods: Integrative cross-platform analyses coupling global metabolomic profiling with genomics in patient-derived glioma (low-grade astrocytoma [LGA; n = 28] and glioblastoma [ n = 80]) were performed. Identified programs were then metabolomically, genomically, and functionally evaluated in preclinical models. Results: Clear metabolic programs were identified differentiating LGA from glioblastoma, with aberrant lipid, peptide, and amino acid metabolism representing dominant metabolic nodes associated with malignant transformation. Although the metabolomic profiles of glioblastoma and LGA appeared mutually exclusive, considerable metabolic heterogeneity was observed in glioblastoma. Surprisingly, integrative analyses demonstrated that O 6 -methylguanine-DNA methyltransferase methylation and isocitrate dehydrogenase mutation status were equally distributed among glioblastoma metabolic profiles. Transcriptional subtypes, on the other hand, tightly clustered by their metabolomic signature, with proneural and mesenchymal tumor profiles being mutually exclusive. 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, contributing to a state of enhanced metabolic heterotrophy. These findings were metabolomically, genomically, and functionally recapitulated in preclinical models. Conclusion: Despite disparate molecular pathways driving the progression of glioblastoma, metabolic programs designed to maintain its aggressive phenotype remain conserved. This contributes to a state of enhanced metabolic heterotrophy supporting survival in diverse microenvironments implicit in this malignancy.