Metabolic associations of reduced proliferation and oxidative stress in advanced breast cancer

Livnat Jerby, Lior Wolf, Carsten Denkert, Gideon Y. Stein, Mika Hilvo, Matej Orešič, Tamar Geiger, Eytan Ruppin

Research output: Contribution to journalArticleScientificpeer-review

73 Citations (Scopus)

Abstract

Aberrant metabolism is a hallmark of cancer, but whole metabolomic flux measurements remain scarce. To bridge this gap, we developed a novel metabolic phenotypic analysis (MPA) method that infers metabolic phenotypes based on the integration of transcriptomics or proteomics data within a human genome-scale metabolic model. MPA was applied to conduct the first genome-scale study of breast cancer metabolism based on the gene expression of a large cohort of clinical samples. The modeling correctly predicted cell lines' growth rates, tumor lipid levels, and amino acid biomarkers, outperforming extant metabolic modeling methods. Experimental validation was obtained in vitro. The analysis revealed a subtype-independent “go or grow” dichotomy in breast cancer, where proliferation rates decrease as tumors evolve metastatic capability. MPA also identified a stoichiometric tradeoff that links the observed reduction in proliferation rates to the growing need to detoxify reactive oxygen species. Finally, a fundamental stoichiometric tradeoff between serine and glutamine metabolism was found, presenting a novel hallmark of estrogen receptor (ER)+ versus ER− tumor metabolism. Together, our findings greatly extend insights into core metabolic aberrations and their impact in breast cancer.
Original languageEnglish
Pages (from-to)5712-5720
JournalCancer Research
Volume72
Issue number22
DOIs
Publication statusPublished - 2012
MoE publication typeA1 Journal article-refereed

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Oxidative Stress
Breast Neoplasms
Estrogen Receptors
Neoplasms
Metabolomics
Human Genome
Glutamine
Proteomics
Serine
Reactive Oxygen Species
Biomarkers
Genome
Phenotype
Lipids
Gene Expression
Amino Acids
Cell Line
Growth

Cite this

Jerby, L., Wolf, L., Denkert, C., Stein, G. Y., Hilvo, M., Orešič, M., ... Ruppin, E. (2012). Metabolic associations of reduced proliferation and oxidative stress in advanced breast cancer. Cancer Research, 72(22), 5712-5720. https://doi.org/10.1158/0008-5472.CAN-12-2215
Jerby, Livnat ; Wolf, Lior ; Denkert, Carsten ; Stein, Gideon Y. ; Hilvo, Mika ; Orešič, Matej ; Geiger, Tamar ; Ruppin, Eytan. / Metabolic associations of reduced proliferation and oxidative stress in advanced breast cancer. In: Cancer Research. 2012 ; Vol. 72, No. 22. pp. 5712-5720.
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abstract = "Aberrant metabolism is a hallmark of cancer, but whole metabolomic flux measurements remain scarce. To bridge this gap, we developed a novel metabolic phenotypic analysis (MPA) method that infers metabolic phenotypes based on the integration of transcriptomics or proteomics data within a human genome-scale metabolic model. MPA was applied to conduct the first genome-scale study of breast cancer metabolism based on the gene expression of a large cohort of clinical samples. The modeling correctly predicted cell lines' growth rates, tumor lipid levels, and amino acid biomarkers, outperforming extant metabolic modeling methods. Experimental validation was obtained in vitro. The analysis revealed a subtype-independent “go or grow” dichotomy in breast cancer, where proliferation rates decrease as tumors evolve metastatic capability. MPA also identified a stoichiometric tradeoff that links the observed reduction in proliferation rates to the growing need to detoxify reactive oxygen species. Finally, a fundamental stoichiometric tradeoff between serine and glutamine metabolism was found, presenting a novel hallmark of estrogen receptor (ER)+ versus ER− tumor metabolism. Together, our findings greatly extend insights into core metabolic aberrations and their impact in breast cancer.",
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Jerby, L, Wolf, L, Denkert, C, Stein, GY, Hilvo, M, Orešič, M, Geiger, T & Ruppin, E 2012, 'Metabolic associations of reduced proliferation and oxidative stress in advanced breast cancer', Cancer Research, vol. 72, no. 22, pp. 5712-5720. https://doi.org/10.1158/0008-5472.CAN-12-2215

Metabolic associations of reduced proliferation and oxidative stress in advanced breast cancer. / Jerby, Livnat; Wolf, Lior; Denkert, Carsten; Stein, Gideon Y.; Hilvo, Mika; Orešič, Matej; Geiger, Tamar; Ruppin, Eytan.

In: Cancer Research, Vol. 72, No. 22, 2012, p. 5712-5720.

Research output: Contribution to journalArticleScientificpeer-review

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AU - Jerby, Livnat

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AB - Aberrant metabolism is a hallmark of cancer, but whole metabolomic flux measurements remain scarce. To bridge this gap, we developed a novel metabolic phenotypic analysis (MPA) method that infers metabolic phenotypes based on the integration of transcriptomics or proteomics data within a human genome-scale metabolic model. MPA was applied to conduct the first genome-scale study of breast cancer metabolism based on the gene expression of a large cohort of clinical samples. The modeling correctly predicted cell lines' growth rates, tumor lipid levels, and amino acid biomarkers, outperforming extant metabolic modeling methods. Experimental validation was obtained in vitro. The analysis revealed a subtype-independent “go or grow” dichotomy in breast cancer, where proliferation rates decrease as tumors evolve metastatic capability. MPA also identified a stoichiometric tradeoff that links the observed reduction in proliferation rates to the growing need to detoxify reactive oxygen species. Finally, a fundamental stoichiometric tradeoff between serine and glutamine metabolism was found, presenting a novel hallmark of estrogen receptor (ER)+ versus ER− tumor metabolism. Together, our findings greatly extend insights into core metabolic aberrations and their impact in breast cancer.

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