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Kinetic modelling of quantitative proteome data predicts metabolic reprogramming of liver cancer

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Item Type:Article
Title:Kinetic modelling of quantitative proteome data predicts metabolic reprogramming of liver cancer
Creators Name:Berndt, N. and Egners, A. and Mastrobuoni, G. and Vvedenskaya, O. and Fragoulis, A. and Dugourd, A. and Bulik, S. and Pietzke, M. and Bielow, C. and van Gassel, R. and Olde Damink, S.W. and Erdem, M. and Saez-Rodriguez, J. and Holzhütter, H.G. and Kempa, S. and Cramer, T.
Abstract:BACKGROUND: Metabolic alterations can serve as targets for diagnosis and cancer therapy. Due to the highly complex regulation of cellular metabolism, definite identification of metabolic pathway alterations remains challenging and requires sophisticated experimentation. METHODS: We applied a comprehensive kinetic model of the central carbon metabolism (CCM) to characterise metabolic reprogramming in murine liver cancer. RESULTS: We show that relative differences of protein abundances of metabolic enzymes obtained by mass spectrometry can be used to assess their maximal velocity values. Model simulations predicted tumour-specific alterations of various components of the CCM, a selected number of which were subsequently verified by in vitro and in vivo experiments. Furthermore, we demonstrate the ability of the kinetic model to identify metabolic pathways whose inhibition results in selective tumour cell killing. CONCLUSIONS: Our systems biology approach establishes that combining cellular experimentation with computer simulations of physiology-based metabolic models enables a comprehensive understanding of deregulated energetics in cancer. We propose that modelling proteomics data from human HCC with our approach will enable an individualised metabolic profiling of tumours and predictions of the efficacy of drug therapies targeting specific metabolic pathways.
Keywords:Animal Disease Models, Cellular Reprogramming, Computer Simulation, Hepatocytes, Liver Neoplasms, Mass Spectrometry, Metabolic Networks and Pathways, Proteome, Transgenic Mice, Animals, Mice
Source:British Journal of Cancer
Publisher:Nature Publishing Group
Page Range:233-244
Date:21 January 2020
Official Publication:https://doi.org/10.1038/s41416-019-0659-3
PubMed:View item in PubMed
Related to:
https://edoc.mdc-berlin.de/17568/Preprint version

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