ePoster
Tumor tissue metabolomics informs metabolic reprogramming in IDH wild-type gliomas
Fernanda Monedeiroand 9 co-authors
FENS Forum 2024 (2024)
Messe Wien Exhibition & Congress Center, Vienna, Austria
Presentation
Date TBA
Event Information
Poster
View posterAbstract
IDH (isocitrate dehydrogenase) wild-type gliomas are associated with rapid progression and poorer prognosis compared to IDH mutant counterparts, justifying the search for novel treatment approaches based on the concept of personalized medicine. Here, we aimed to investigate how the metabolic state of gliomas may reflect in their clinical features and to gain insights into metabolic processes that may represent therapeutic vulnerabilities. For this purpose, tumor tissue samples from human glioblastoma (IDH wild-type, n=24), astrocytoma, and oligodendroglioma (both IDH mutant, n=11 and 4, respectively) were comprehensively analyzed for metabolites using liquid chromatography coupled with high-resolution mass spectrometry. Then, univariate and multivariate methods along with pathway enrichment analysis were used to assess metabolic differences between glioma types. As expected, IDH mutant tumor was characterized by significantly increased levels of 2-hydroxyglutarate. IDH wild-type tumor tissue displayed significantly increased levels of tricarboxylic acid (TCA) cycle intermediates, amino acids, lipids and nucleotide derivatives. As a demonstration of metabolome relevance for glioma characterization, a partial least squares-discriminant analysis (PLS-DA) model enabled the classification of tumors per IDH status with 100% accuracy. Overall, the results indicated that nucleotide metabolism, central carbon metabolism, fatty acid beta-oxidation, and redox mechanisms were among the main pathways upregulated in IDH wild-type tumors. The observed metabolic alterations could be assigned to molecular mechanisms that support cell proliferation and tumor plasticity. Such data may be useful to track novel therapeutic possibilities directed towards IDH wild-type gliomas based on metabolic targets.