Reference : Importance of the biomass formulation for cancer metabolic modeling and drug prediction.
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
http://hdl.handle.net/10993/48470
Importance of the biomass formulation for cancer metabolic modeling and drug prediction.
English
Moscardo Garcia, Maria mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)]
Pires Pacheco, Maria Irene mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM) >]
Bintener, Tamara Jean Rita []
Presta, Luana mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)]
Sauter, Thomas mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)]
2021
iScience
24
10
103110
Yes (verified by ORBilu)
International
2589-0042
2589-0042
[en] In silico biology ; Mathematical biosciences ; Metabolic flux analysis
[en] Genome-scale metabolic reconstructions include all known biochemical reactions occurring in a cell. A typical application is the prediction of potential drug targets for cancer treatment. The precision of these predictions relies on the definition of the objective function. Generally, the biomass reaction is used to illustrate the growth capacity of a cancer cell. Today, seven human biomass reactions can be identified in published metabolic models. The impact of these differences on the metabolic model predictions has not been explored in detail. We explored this impact on cancer metabolic model predictions and showed that the metabolite composition and the associated coefficients had a large impact on the growth rate prediction accuracy, whereas gene essentiality predictions were mainly affected by the metabolite composition. Our results demonstrate the importance of defining a consensus biomass reaction compatible with most human models, which would contribute to ensuring the reproducibility and consistency of the results.
http://hdl.handle.net/10993/48470
© 2021 The Author(s).

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