Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/156377
Title: The landscape of tiered regulation of breast cancer cell metabolism
Author: Katzir, Rotem
Polat, Ibrahim H.
Harel, Michal
Katz, Shir
Foguet Coll, Carles
Selivanov, Vitaly A.
Sabatier, Philippe
Cascante i Serratosa, Marta
Geiger, Tamar
Ruppin, Eytan
Keywords: Càncer de mama
Metabolisme
Breast cancer
Metabolism
Issue Date: 28-Nov-2019
Publisher: Nature Publishing Group
Abstract: Altered metabolism is a hallmark of cancer, but little is still known about its regulation. In this study, we measure transcriptomic, proteomic, phospho-proteomic and fluxomics data in a breast cancer cell-line (MCF7) across three different growth conditions. Integrating these multiomics data within a genome scale human metabolic model in combination with machine learning, we systematically chart the different layers of metabolic regulation in breast cancer cells, predicting which enzymes and pathways are regulated at which level. We distinguish between two types of reactions, directly and indirectly regulated. Directly-regulated reactions include those whose flux is regulated by transcriptomic alterations (~890) or via proteomic or phospho-proteomics alterations (~140) in the enzymes catalyzing them. We term the reactions that currently lack evidence for direct regulation as (putative) indirectly regulated (~930). Many metabolic pathways are predicted to be regulated at different levels, and those may change at different media conditions. Remarkably, we find that the flux of predicted indirectly regulated reactions is strongly coupled to the flux of the predicted directly regulated ones, uncovering a tiered hierarchical organization of breast cancer cell metabolism. Furthermore, the predicted indirectly regulated reactions are predominantly reversible. Taken together, this architecture may facilitate rapid and efficient metabolic reprogramming in response to the varying environmental conditions incurred by the tumor cells. The approach presented lays a conceptual and computational basis for mapping metabolic regulation in additional cancers.
Note: Reproducció del document publicat a: https://doi.org/10.1038/s41598-019-54221-y
It is part of: Scientific Reports, 2019, vol. 9, num. 1, p. 17760
URI: http://hdl.handle.net/2445/156377
Related resource: https://doi.org/10.1038/s41598-019-54221-y
ISSN: 2045-2322
Appears in Collections:Articles publicats en revistes (Bioquímica i Biomedicina Molecular)

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