(176af) Understanding the Metabolism of Cancer Persisters | AIChE

(176af) Understanding the Metabolism of Cancer Persisters


Karki, P. - Presenter, University of Houston
Orman, M., University of Houston
Many conventional cancer therapies target mechanisms that allow rapid growth of tumor cells. However, the benefits of these approaches can be limited as studies suggest the existence of small subpopulations of persister cells that are transiently dormant, tolerant to lethal concentration of cancer drugs, and present across a broad range of cancer types 1-3. The existence of persister population is an important health concern as they can facilitate cancer recurrence as well as the emergence of drug resistant mutants1-3. Considering the similarities in defense mechanisms observed in persister subpopulations from different cancer types 1-3, pre-existing or drug-induced stress signaling pathways potentially play vital role in persistence. Given that repair mechanisms are plausible targets for therapeutic applications3, herein we describe a methodology to map the active repair mechanisms in persister cells from three different cancer cell lines (breast, lung and skin cancer) by integrating mathematical modeling of metabolic network analysis4 with high-throughput metabolomics and transcriptomics technologies. Overall, our study aims to fill a fundamental knowledge gap within our understanding of persister physiology by reporting repair mechanisms that are conserved in all three cancer types or those that are specific to a cancer type or a drug treatment.


  1. Sharma, S.V., et al. 2010. A chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations. Cell, 141(1), 69-80.
  2. Hata, A.N.,et al. 2016. Tumor cells can follow distinct evolutionary paths to become resistant to epidermal growth factor receptor inhibition. Nature medicine, 22(3), 262.
  3. Hangauer, M.J., et al. 2017. Drug-tolerant persister cancer cells are vulnerable to GPX4 inhibition. Nature, 551(7679), 247.
  4. Mardinoglu A., et al. 2014. Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease. Nat Commun, 5:3083.