Scientific Reports · 2019 · 73 citations · 32 references
Life SciencesBiochemistryOncologyMetabolismMetabolomicsNeuro-oncologyBrain TumorsCancer MetabolismMetabolite ProfilingMetabolite QuantificationNuclear Magnetic Resonance MetabolomicsPediatric Brain TumorsCox RegressionMetabolic Biomarker DiscoveryMetabolomic BiomarkersMetabolomic Tumor MarkersMolecular Prognostic MarkersNuclear Magnetic Resonance Spectroscopy-based Metabolite ProfilingPrognostic BiomarkersPrognostic Tumor Markers
Abstract Brain tumours are the most common cause of cancer death in children. Molecular studies have greatly improved our understanding of these tumours but tumour metabolism is underexplored. Metabolites measured in vivo have been reported as prognostic biomarkers of these tumours but analysis of surgically resected tumour tissue allows a more extensive set of metabolites to be measured aiding biomarker discovery and providing validation of in vivo findings. In this study, metabolites were quantified across a range of paediatric brain tumours using 1 H-High-Resolution Magic Angle Spinning nuclear magnetic resonance spectroscopy (HR-MAS) and their prognostic potential investigated. HR-MAS was performed on pre-treatment frozen tumour tissue from a single centre. Univariate and multivariate Cox regression was used to examine the ability of metabolites to predict survival. The models were cross validated using C-indices and further validated by splitting the cohort into two. Higher concentrations of glutamine were predictive of a longer overall survival, whilst higher concentrations of lipids were predictive of a shorter overall survival. These metabolites were predictive independent of diagnosis, as demonstrated in multivariate Cox regression models. Whilst accurate quantification of metabolites such as glutamine in vivo is challenging, metabolites show promise as prognostic markers due to development of optimised detection methods and increasing use of 3 T clinical scanners.
32
R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
Ralph J. DeBerardinis, Anthony Mancuso, Evgueni Daikhin et al. · Proceedings of the National Academy of Sciences · 2007 · 2.6K citations · Full text
Akt Stimulates Aerobic Glycolysis in Cancer Cells
Rebecca Elstrom, Daniel E. Bauer, Monica Buzzai et al. · Cancer Research · 2004 · 1.5K citations
Medicine, Cancer Biology, Oncology +17
An Inhibitor of Mutant IDH1 Delays Growth and Promotes Differentiation of Glioma Cells
Dan Rohle, Janeta Popovici-Müller, Nicolaos Palaskas et al. · Science · 2013 · 1.2K citations
Medicine, Cancer Biology, Oncology +17