The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
The Warburg effect as an adaptation of cancer cells to rapid fluctuations in energy demand
Open accessAbstract
To maintain optimal fitness, a cell must balance the risk of inadequate energy reserve for response to a potentially fatal perturbation against the long-term cost of maintaining high concentrations of ATP to meet occasional spikes in demand. Here we apply a game theoretic approach to address the dynamics of energy production and expenditure in eukaryotic cells. Conventionally, glucose metabolism is viewed as a function of oxygen concentrations in which the more efficient oxidation of glucose to CO2 and H2O produces all or nearly all ATP except under hypoxic conditions when less efficient (2 ATP/ glucose vs. about 36ATP/glucose) anaerobic metabolism of glucose to lactic acid provides an emergency backup. We propose an alternative in which energy production is governed by the complex temporal and spatial dynamics of intracellular ATP demand. In the short term, a cell must provide energy for constant baseline needs but also maintain capacity to rapidly respond to fluxes in demand particularly due to external perturbations on the cell membrane. Similarly, longer-term dynamics require a trade-off between the cost of maintaining high metabolic capacity to meet uncommon spikes in demand versus the risk of unsuccessfully responding to threats or opportunities. Here we develop a model and computationally explore the cell's optimal mix of glycolytic and oxidative capacity. We find the Warburg effect, high glycolytic metabolism even under normoxic conditions, is represents a metabolic strategy that allow cancer cells to optimally meet energy demands posed by stochastic or fluctuating tumor environments.
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Cites
The Ecology of Fear: Optimal Foraging, Game Theory, and Trophic Interactions
Brown, J. S., Laundre, J. W., & Gurung, M. (1999) · Journal of Mammalogy · doi:10.2307/1383287 · Cited by 1,347
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Cited by
The hallmarks of cancer metabolism: still emerging
Pavlova, N. N., Zhu, J., & Thompson, C. B. (2022) · Cell Metabolism · doi:10.1016/j.cmet.2022.01.007 · Cited by 1,418
Vaupel, P., Schmidberger, H., & Mayer, A. (2019) · International Journal of Radiation Biology · doi:10.1080/09553002.2019.1589653 · Cited by 893
Energy metabolism in health and diseases
Liu, H., Wang, S., Wang, J., Guo, X., Song, Y., Fu, K., Gao, Z., Liu, D., He, W., & Yang, L.-L. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-025-02141-x · Cited by 399
Ganapathy-Kanniappan, S. (2018) · Critical Reviews in Biochemistry and Molecular Biology · doi:10.1080/10409238.2018.1556578 · Cited by 216
Zanotelli, M. R., Rahman-Zaman, A., VanderBurgh, J. A., Taufalele, P. V., Jain, A., Erickson, D., Bordeleau, F., & Reinhart-King, C. A. (2019) · Nature Communications · doi:10.1038/s41467-019-12155-z · Cited by 165
Metadata
- Authors
- Epstein, T., Gatenby, R. A., & Brown, J. S.
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2017-09-18
- Volume
- 12
- Issue
- 9
- Pages
- e0185085
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2754515846
- Cited by
- 170
- References
- 1
- FWCI
- 4.83
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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