Metabolomic Profiles of Human Glioma Inform Patient Survival.

Daniel Orringer, Daniel R Wahl, Costas A Lyssiotis, Arvind Rao, Jason Heth, Prakash Chinnaiyan, Wajd N Al-Holou, Joseph E Ippolito, Theodore S Lawrence, Sandra Camelo-Piragua, Sriram Venneti, Denise Leung, Yoshie Umemura, Larry Junck, Michelle M Kim, Andrew J Scott, Shawn Hervey-Jumper, Shannon A Carty, Oren Sagher, Karin Muraszko, Kait Verbal, Neil Jairath, Sudharsan Srinivasan, Li Zhang, Anthony C Andren, Visweswaran Ravikumar, Yilun Sun, Donna M Edwards, Luis O Correa

Journal: Antioxidants & redox signaling 2023;39(13-15):942-956

PMID: 36852494

Abstract

Targeting tumor metabolism may improve the outcomes for patients with glioblastoma (GBM). To further preclinical efforts targeting metabolism in GBM, we tested the hypothesis that brain tumors can be stratified into distinct metabolic groups with different patient outcomes. Therefore, to determine if tumor metabolites relate to patient survival, we profiled the metabolomes of human gliomas and correlated metabolic information with clinical data. We found that isocitrate dehydrogenase-wildtype (IDHwt) GBMs are metabolically distinguishable from IDH mutated (IDHmut) astrocytomas and oligodendrogliomas. Survival of patients with IDHmut gliomas was expectedly more favorable than those with IDHwt GBM, and metabolic signatures can stratify IDHwt GBMs subtypes with varying prognoses. Patients whose GBMs were enriched in amino acids had improved survival, while those whose tumors were enriched for nucleotides, redox molecules, and lipid metabolites fared more poorly. These findings were recapitulated in validation cohorts using both metabolomic and transcriptomic data. Our results suggest the existence of metabolic subtypes of GBM with differing prognoses, and further support the concept that metabolism may drive the aggressiveness of human gliomas. Our data show that metabolic signatures of human gliomas can inform patient survival. These findings may be used clinically to tailor novel metabolically targeted agents for GBM patients with different metabolic phenotypes. . 39, 942-956.

Address: Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.; Department of Rogel Cancer Center, University of Michigan, Ann Arbor, Michigan, USA.; Department of Immunology Graduate Program, University of Michigan, Ann Arbor, Michigan, USA.; Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA.; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.; Department of Molecular & Integrative Physiology, University of Michigan, Ann Arbor, Michigan, USA.; Department of Neurosurgery, University of Michigan, Ann Arbor, Michigan, USA.; Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.; Department of Neurological Surgery, University of California, San Francisco, San Francisco, California, USA.; Department of Neurosurgery, New York University Langone Health, New York, New York, USA.; Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA.; Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.; Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, USA.; Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA.; Department of Radiation Oncology, Beaumont Health, Royal Oak, Michigan, USA.; Oakland University William Beaumont School of Medicine, Rochester, Michigan, USA.; Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.; Division of Gastroenterology and Hepatology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.
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