MEDB-67. Subgroup specific analysis of cellular metabolism in medulloblastoma. (3rd June 2022)

• Record Type: Journal Article
• Authors: Funke, Viktoria; Walter, Carolin; Melcher, Viktoria; Wei, Lanying; Sandmann, Sarah; Varghese, Julian; Jäger, Natalie; Albert, Thomas K; Schüller, Ulrich; Kerl, Kornelius
• Is Part Of: Neuro-oncology. Volume 24(2022)Supplement 1
• Page Start: i122
• Page End: i122
• Publication Date: 2022-06-03
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noac079.441
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: INTRODUCTION : Molecular subgrouping of Medulloblastoma (MB) has expanded our understanding of its biology and the impact on clinical parameters. However, detailed analysis of inter- and intratumoral heterogeneity on a metabolic level is currently lacking. Within this study, we aimed at improving our understanding of metabolic heterogeneity between the MB subgroups, between samples within these subgroups and how these differences affect prognosis. METHODS : We analyzed metabolic characteristics of four MB cohorts covering 1, 804 samples in total. In 911 samples (ICGC and MAGIC cohort), we explored metabolic programs on RNA level. In two cohorts (ICGC and G3/G4 samples from the HIT cohort; n=1, 035) we examined genetic alterations on DNA level. Furthermore, single-cell RNA-sequencing data of six samples were used to explore intratumoral metabolic heterogeneity. Inter- and intratumoral heterogeneity were correlated to clinical data. RESULTS : Using publicly available gene signatures, we discovered significant differences in metabolic gene expression comparing established MB subgroups. Three metabolically distinct clusters of G3/G4 samples could be defined by unsupervised analyses in two independent cohorts. We were able to confirm our finding of intertumoral metabolic differences on single-cell RNA level. Additionally, our analysis revealed the possibility of sample-specific metabolic features. On DNA level, we identified regulatory genes with known role in MB development to be predominantly associated with lipid metabolic processes. After all, lipid metabolism and metabolism of nucleotides in MB have prognostic value and correlate with the outcome of patients. CONCLUSION : Our data highlight the importance of metabolic properties in MB. We show the distinct metabolic signatures are clinically relevant and, thus, might provide opportunities for novel target-directed therapeutic options in the future.