Dataset Information

A systematic multi-omics investigation of breast cancer metabolism mapping its tiered regulation

ABSTRACT: Altered metabolism is a hallmark of cancer, but little is still known about its regulation. Here we measure transcriptomic, proteomic, phospho-proteomic and fluxomics data in a breast cancer cell-line across three different 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, predicting which enzymes and pathways are regulated at which level. We distinguish between two types of reactions, directly or 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. Indirectly regulated reactions are those that currently lack evidence for direct regulation in our measurements or predictions (~930). Remarkably, we find that the flux of indirectly regulated reactions is strongly coupled to the flux of the directly regulated ones, uncovering a hierarchical organization of breast cancer metabolism. Furthermore, the predicted indirectly regulated reactions are predominantly bi-directional. Taken together, this architecture may facilitate the formation of stochiometrically consistent flux distributions in response to the varying environmental conditions incurred by the tumor cells. The approach presented lays a conceptual and computational basis for a more complete mapping of metabolic regulation in different cancers with incoming additional data.

OTHER RELATED OMICS DATASETS IN: MTBLS183

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Breast Epithelium, Cell Culture

DISEASE(S): Breast Cancer

SUBMITTER: Tamar Geiger

LAB HEAD: Tamar Geiger

PROVIDER: PXD006449 | Pride | 2020-05-26

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	20130426_SK_SA_marta_24.raw	Raw
	20130426_SK_SA_marta_24_gln.raw	Raw
	20130426_SK_SA_marta_24_gln_oligo.raw	Raw
	20130426_SK_SA_marta_8.raw	Raw
	20130426_SK_SA_marta_8_gln.raw	Raw

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Publications

The landscape of tiered regulation of breast cancer cell metabolism.

Katzir Rotem R Polat Ibrahim H IH Harel Michal M Katz Shir S Foguet Carles C Selivanov Vitaly A VA Sabatier Philippe P Cascante Marta M Geiger Tamar T Ruppin Eytan E

Scientific reports 20191128 1

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 pa ...[more]

PMID: 31780802

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