The landscape of tiered regulation of breast cancer cell metabolism
Autor: | Carles Foguet, Vitaly A. Selivanov, Rotem Katzir, Marta Cascante, Philippe Sabatier, Eytan Ruppin, Shir Katz, Ibrahim H. Polat, Michal Harel, Tamar Geiger |
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Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
Proteomics
lcsh:Medicine Breast Neoplasms Computational biology Biology Article Càncer de mama Transcriptome Machine Learning 03 medical and health sciences Breast cancer 0302 clinical medicine medicine Cancer genomics Humans Computational models Phosphorylation lcsh:Science Fluxomics 030304 developmental biology Cell Proliferation chemistry.chemical_classification 0303 health sciences Multidisciplinary lcsh:R Cancer Metabolism medicine.disease Regulatory networks Metabolisme Metabolic pathway Enzyme chemistry 030220 oncology & carcinogenesis MCF-7 Cells Female lcsh:Q Flux (metabolism) Metabolic Networks and Pathways |
Zdroj: | Scientific Reports, Vol 9, Iss 1, Pp 1-12 (2019) Scientific Reports Dipòsit Digital de la UB Universidad de Barcelona |
ISSN: | 2045-2322 |
Popis: | 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. |
Databáze: | OpenAIRE |
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