Liberti, M. V., Dai, Z., Wardell, S. E., Baccile, J. A., Liu, X., Gao, X., Baldi, R., Mehrmohamadi, M., Johnson, M. O., Madhukar, N. S., Shestov, A. A., Chio, I. I. C., Elemento, O., Rathmell, J. C., Schroeder, F. C., McDonnell, D. P., Locasale, J. W. (October 2017) A Predictive Model for Selective Targeting of the Warburg Effect through GAPDH Inhibition with a Natural Product. Cell Metab, 26 (4). pp. 648-659. ISSN 1550-4131
Abstract
Targeted cancer therapies that use genetics are successful, but principles for selectively targeting tumor metabolism that is also dependent on the environment remain unknown. We now show that differences in rate-controlling enzymes during the Warburg effect (WE), the most prominent hallmark of cancer cell metabolism, can be used to predict a response to targeting glucose metabolism. We establish a natural product, koningic acid (KA), to be a selective inhibitor of GAPDH, an enzyme we characterize to have differential control properties over metabolism during the WE. With machine learning and integrated pharmacogenomics and metabolomics, we demonstrate that KA efficacy is not determined by the status of individual genes, but by the quantitative extent of the WE, leading to a therapeutic window in vivo. Thus, the basis of targeting the WE can be encoded by molecular principles that extend beyond the status of individual genes.
| Item Type: | Paper |
|---|---|
| Uncontrolled Keywords: | Warburg effect cancer metabolism glucose metabolism metabolic control analysis metabolic flux analysis metabolomics natural product pharmacogenomics precision medicine systems biology |
| Subjects: | diseases & disorders > cancer organs, tissues, organelles, cell types and functions > organs types and functions > metabolism |
| CSHL Authors: | |
| Communities: | CSHL labs > Tuveson lab |
| Depositing User: | Matt Covey |
| Date: | 3 October 2017 |
| Date Deposited: | 21 Sep 2017 20:19 |
| Last Modified: | 25 Oct 2017 16:39 |
| PMCID: | PMC5629112 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/35286 |
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