title: A joint analysis of transcriptomic and metabolomic data uncovers enhanced enzyme-metabolite coupling in breast cancer.
abstract: 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.
authors.affiliation: Center for Bioinformatics and Computational Biology and the Department of Computer Science, University of Maryland, College Park 20742, Maryland, USA.
authors.forename: Noam
authors.initials: N
authors.lastname: Auslander
authors.affiliation: The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel.
authors.forename: Keren
authors.initials: K
authors.lastname: Yizhak
authors.affiliation: The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel.
authors.forename: Adam
authors.initials: A
authors.lastname: Weinstock
authors.affiliation: Liver Carcinogenesis Section, Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA.
authors.forename: Anuradha
authors.initials: A
authors.lastname: Budhu
authors.affiliation: Molecular Epidemiology Section, Laboratory of Human Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
authors.forename: Wei
authors.initials: W
authors.lastname: Tang
authors.affiliation: Liver Carcinogenesis Section, Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA.
authors.forename: Xin Wei
authors.initials: XW
authors.lastname: Wang
authors.affiliation: Molecular Epidemiology Section, Laboratory of Human Carcinogenesis, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
authors.forename: Stefan
authors.initials: S
authors.lastname: Ambs
authors.affiliation: Center for Bioinformatics and Computational Biology and the Department of Computer Science, University of Maryland, College Park 20742, Maryland, USA.|The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel.|The Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel.
authors.forename: Eytan
authors.initials: E
authors.lastname: Ruppin
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics*; D006528:Carcinoma, Hepatocellular / Q000235:genetics; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics; D006801:Humans; D008113:Liver Neoplasms / Q000235:genetics; D055432:Metabolomics / Q000379:methods; D059467:Transcriptome / Q000235:genetics*