TBIO-19. MASS SPECTROMETRY OF COMMON CEREBELLAR TUMOURS IDENTIFIES DIFFERENCES IN METABOLISM. Issue 2 (22nd June 2018) - Bennett, Christopher; Kohe, Sarah; Gill, Simrandip; Davies, Nigel; Storer, Lisa; Ritzmann, Timothy; Dunn, Warwick; Tennant, Daniel; Grundy, Richard; Peet, Andrew
Abstract: Metabolic profiling by Magnetic Resonance Spectroscopy has shown the three most common paediatric cerebellar tumours are metabolically distinct; however, these techniques are limited by their sensitivity. Mass spectrometry is more sensitive and able to detect many more metabolites. In this study, metabolic phenotyping was performed to investigate the water-soluble metabolome and the lipidome of the three most common paediatric cerebellar tumours with the aim of informing a detailed metabolic pathway analysis. A discovery based experiment was performed on 60 surgically resected snap frozen pilocytic astrocytomas, ependymomas and medulloblastomas using UPLC-MS assays to detect water soluble and lipid metabolites. Principal component analysis demonstrates separation of the tumours based on the relative concentration of thousands of detected metabolites. The relative concentrations of glucose and glycolytic intermediates varied between the tumour types, as did metabolites involved in purine and pyrimidine metabolism. Key metabolites within the taurine metabolism pathway were found to be higher in medulloblastoma. Alterations were observed in lipid metabolism, with a wide range of relative concentration differences in di- and triacylglycerides, sphingolipids, ceramides, cardiolipins and glycerophospholipids. This study has shown that these tumours are metabolically distinct and offer the opportunities for stratified diagnosis and treatment. Some of the observed changes in relative concentration between the tumours reflect findings from spectroscopic studies, particularly with regards to taurine which is known to be higher in medulloblastoma. The ability of mass spectrometry to identify and measure lipid species and low concentration metabolites from tissue could allow targetable metabolic differences to be characterised and exploited.