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A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer

Disrupted regulation of cellular processes is considered one of the hallmarks of cancer. We analyze metabolomic and transcriptomic profiles jointly collected from breast cancer and hepatocellular carcinoma patients to explore the associations between the expression of metabolic enzymes and the level...

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Autores principales: Auslander, Noam, Yizhak, Keren, Weinstock, Adam, Budhu, Anuradha, Tang, Wei, Wang, Xin Wei, Ambs, Stefan, Ruppin, Eytan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4942812/
https://www.ncbi.nlm.nih.gov/pubmed/27406679
http://dx.doi.org/10.1038/srep29662
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author Auslander, Noam
Yizhak, Keren
Weinstock, Adam
Budhu, Anuradha
Tang, Wei
Wang, Xin Wei
Ambs, Stefan
Ruppin, Eytan
author_facet Auslander, Noam
Yizhak, Keren
Weinstock, Adam
Budhu, Anuradha
Tang, Wei
Wang, Xin Wei
Ambs, Stefan
Ruppin, Eytan
author_sort Auslander, Noam
collection PubMed
description Disrupted regulation of cellular processes is considered one of the hallmarks of cancer. We analyze metabolomic and transcriptomic profiles jointly collected from breast cancer and hepatocellular carcinoma patients to explore the associations between the expression of metabolic enzymes and the levels of the metabolites participating in the reactions they catalyze. Surprisingly, both breast cancer and hepatocellular tumors exhibit an increase in their gene-metabolites associations compared to noncancerous adjacent tissues. Following, we build predictors of metabolite levels from the expression of the enzyme genes catalyzing them. Applying these predictors to a large cohort of breast cancer samples we find that depleted levels of key cancer-related metabolites including glucose, glycine, serine and acetate are significantly associated with improved patient survival. Thus, we show that the levels of a wide range of metabolites in breast cancer can be successfully predicted from the transcriptome, going beyond the limited set of those measured.
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spelling pubmed-49428122016-07-20 A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer Auslander, Noam Yizhak, Keren Weinstock, Adam Budhu, Anuradha Tang, Wei Wang, Xin Wei Ambs, Stefan Ruppin, Eytan Sci Rep Article Disrupted regulation of cellular processes is considered one of the hallmarks of cancer. We analyze metabolomic and transcriptomic profiles jointly collected from breast cancer and hepatocellular carcinoma patients to explore the associations between the expression of metabolic enzymes and the levels of the metabolites participating in the reactions they catalyze. Surprisingly, both breast cancer and hepatocellular tumors exhibit an increase in their gene-metabolites associations compared to noncancerous adjacent tissues. Following, we build predictors of metabolite levels from the expression of the enzyme genes catalyzing them. Applying these predictors to a large cohort of breast cancer samples we find that depleted levels of key cancer-related metabolites including glucose, glycine, serine and acetate are significantly associated with improved patient survival. Thus, we show that the levels of a wide range of metabolites in breast cancer can be successfully predicted from the transcriptome, going beyond the limited set of those measured. Nature Publishing Group 2016-07-13 /pmc/articles/PMC4942812/ /pubmed/27406679 http://dx.doi.org/10.1038/srep29662 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Auslander, Noam
Yizhak, Keren
Weinstock, Adam
Budhu, Anuradha
Tang, Wei
Wang, Xin Wei
Ambs, Stefan
Ruppin, Eytan
A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer
title A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer
title_full A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer
title_fullStr A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer
title_full_unstemmed A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer
title_short A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer
title_sort joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4942812/
https://www.ncbi.nlm.nih.gov/pubmed/27406679
http://dx.doi.org/10.1038/srep29662
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