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

Item Type:Preprint
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. and Erdem, M. and Saez-Rodriguez, J. and Holzhütter, H.G. and Kempa, S. and Cramer, T.
Abstract:Metabolic alterations can serve as targets for diagnosis and therapy of cancer. Due to the highly complex regulation of cellular metabolism, definite identification of metabolic pathway alterations remains challenging and requires sophisticated experimentation. Here, we applied a comprehensive kinetic model of the central carbon metabolism (CCM) to characterize metabolic reprogramming in murine liver cancer. We show that relative differences of protein abundances of metabolic enzymes obtained by mass spectrometry can be used to scale maximal enzyme capacities. Model simulations predicted tumor-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 tumor cell killing. 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.
Keywords:Cancer Metabolism, Hepatocellular Carcinoma, Kinetic Modelling, Quantitative Mass Spectrometry
Source:bioRxiv
Publisher:Cold Spring Harbor Laboratory (U.S.A.)
Article Number:275040
Date:5 March 2018
Official Publication:https://doi.org/10.1101/275040

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