EMT-induced metabolite signature identifies poor clinical outcome
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Salil Kumar Bhowmik1,2,3,*, Esmeralda Ramirez-Peña4,*, James Michael Arnold1,2,3,*, Vasanta Putluri1,2,3, Nathalie Sphyris4, George Michailidis5, Nagireddy Putluri1,2,3, Stefan Ambs6, Arun Sreekumar1,2,3, Sendurai A. Mani4
1Department of Molecular and Cell Biology, Baylor College of Medicine, Houston, TX, USA
2Verna and Marrs McLean Department of Biochemistry, Baylor College of Medicine, TX, USA
3Alkek Center for Molecular Discovery, Baylor College of Medicine, Houston, TX, USA
4Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
5Department of Statistics, University of Michigan, Ann Arbor, MI, USA
6Laboratory of Human Carcinogenesis, Center for Cancer Research (CCR), National Cancer Institute (NCI), NIH, Bethesda, Maryland, USA
*These authors have contributed equally to this work
Sendurai A. Mani, e-mail: [email protected]
Arun Sreekumar, e-mail: [email protected]
Keywords: EMT, breast cancer, metabolism, metabolic reprogramming, LC-MS metabolomics
Received: April 21, 2015 Accepted: July 20, 2015 Published: August 01, 2015
Metabolic reprogramming is a hallmark of cancer. Epithelial-mesenchymal transition (EMT) induces cancer stem cell (CSC) characteristics and promotes tumor invasiveness; however relatively little is known about the metabolic reprogramming in EMT. Here we show that breast epithelial cells undergo metabolic reprogramming following EMT. Relative to control, cell lines expressing EMT transcription factors show ≥1.5-fold accumulation of glutamine, glutamate, beta-alanine and glycylleucine as well as ≥1.5-fold reduction of phosphoenolpyruvate, urate, and deoxycarnitine. Moreover, these metabolic alterations were found to be predictive of overall survival (hazard ratio = 2.3 (95% confidence interval: 1.31–4.2), logrank p-value = 0.03) and define breast cancer molecular subtypes. EMT-associated metabolites are primarily composed of anapleurotic precursors, suggesting that cells undergoing EMT have a shift in energy production. In summary, we describe a unique panel of metabolites associated with EMT and demonstrate that these metabolites have the potential for predicting clinical and biological characteristics associated with patient survival.
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