PT - JOURNAL ARTICLE AU - Nikolaus Berndt AU - Antje Egners AU - Guido Mastrobuoni AU - Olga Vvedenskaya AU - Athanassios Fragoulis AU - Aurélien Dugourd AU - Sascha Bulik AU - Matthias Pietzke AU - Chris Bielow AU - Rob van Gassel AU - Steven Olde Damink AU - Merve Erdem AU - Julio Saez-Rodriguez AU - Hermann-Georg Holzhütter AU - Stefan Kempa AU - Thorsten Cramer TI - Kinetic modelling of quantitative proteome data predicts metabolic reprogramming of liver cancer AID - 10.1101/275040 DP - 2018 Jan 01 TA - bioRxiv PG - 275040 4099 - http://biorxiv.org/content/early/2018/03/05/275040.short 4100 - http://biorxiv.org/content/early/2018/03/05/275040.full AB - 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.