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Metabolites 2016, 6(4), 30; doi:10.3390/metabo6040030

Optimized Method for Untargeted Metabolomics Analysis of MDA-MB-231 Breast Cancer Cells

1
Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
2
Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
3
Division of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, Victoria 3000, Australia
4
Cousins Center for PNI, University of California Los Angeles, Los Angeles, CA 90095, USA
5
UCLA Semel Institute, University of California Los Angeles, Los Angeles, CA 90095, USA
6
Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, CA 90095, USA
7
UCLA AIDS Institute, University of California Los Angeles, Los Angeles, CA 90095, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Devin Benheim, Farhana R. Pinu, Konstantinos A. Kouremenos, Damien L. Callahan and David P. De Souza
Received: 31 August 2016 / Revised: 15 September 2016 / Accepted: 19 September 2016 / Published: 22 September 2016
View Full-Text   |   Download PDF [3028 KB, uploaded 22 September 2016]   |  

Abstract

Cancer cells often have dysregulated metabolism, which is largely characterized by the Warburg effect—an increase in glycolytic activity at the expense of oxidative phosphorylation—and increased glutamine utilization. Modern metabolomics tools offer an efficient means to investigate metabolism in cancer cells. Currently, a number of protocols have been described for harvesting adherent cells for metabolomics analysis, but the techniques vary greatly and they lack specificity to particular cancer cell lines with diverse metabolic and structural features. Here we present an optimized method for untargeted metabolomics characterization of MDA-MB-231 triple negative breast cancer cells, which are commonly used to study metastatic breast cancer. We found that an approach that extracted all metabolites in a single step within the culture dish optimally detected both polar and non-polar metabolite classes with higher relative abundance than methods that involved removal of cells from the dish. We show that this method is highly suited to diverse applications, including the characterization of central metabolic flux by stable isotope labelling and differential analysis of cells subjected to specific pharmacological interventions. View Full-Text
Keywords: cell metabolomics; breast cancer; glucose; glutamine; isotope labelling cell metabolomics; breast cancer; glucose; glutamine; isotope labelling
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Peterson, A.L.; Walker, A.K.; Sloan, E.K.; Creek, D.J. Optimized Method for Untargeted Metabolomics Analysis of MDA-MB-231 Breast Cancer Cells. Metabolites 2016, 6, 30.

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