Adaptive Therapy: Using Evolutionary Game Theory to Combat Cancer Treatment Resistance
DOI:
https://doi.org/10.47611/jsrhs.v13i1.6104Keywords:
Adaptive Therapy, Oncology, Cancer Treatment, Evolutionary Game Theory, Maximum Tolerated Dose, Quality of Life, Treatment ResistanceAbstract
Adaptive therapy is a cancer treatment based upon the principles of evolutionary game theory (EGT) utilized to minimize treatment resistance as a cause of tumor evolution. This treatment strategy incorporates a foundation of Darwinian evolutionary principles with mathematical modeling and clinical data. As a result, adaptive therapy ameliorates the negative effects of traditional cancer treatments such as therapy resistance and a debilitated quality of life. By eliminating the use of maximum tolerated dose (MTD), the hallmark of traditional therapies, the evolutionary properties of tumors to develop drug resistance are circumvented and the probability of a prolonged life for patients is significantly increased. This paper explores the effectiveness of an expanded usage of adaptive therapy through an evaluation of current oncological research.
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Anderson, S. (2021, February 15). Moffitt researchers identify key factors impacting adaptive therapy [Press release]. https://moffitt.org/newsroom/press-release-archive/moffitt-researchers-identify-key-factors-impacting-adaptive-therapy
Baker, A. M. (2017). Adapting for survival [Press release]. https://moffitt.org/publications/moffitt-momentum/volume-4-issue-2-moffitt-momentum/adapting-for-survival/
Banks, M. A. (2021, July 12). Moving away from the maximum tolerated dose. Cancer Today Magazine. https://www.cancertodaymag.org/cancer-talk/moving-away-from-the-maximum-tolerated-dose/
Bayer, P., Brown, J. S., Dubbeldam, J., & Broom, M. (2022). A Markovian decision model of adaptive cancer treatment and quality of life. Journal of Theoretical Biology, 551-552, 111237. https://doi.org/10.1016/j.jtbi.2022.111237
Belkhir, S., Thomas, F., & Roche, B. (2021). Darwinian approaches for cancer treatment: Benefits of mathematical modeling. Cancers, 13(17), 4448. https://doi.org/10.3390/cancers13174448
Brady-Nicholls, R., Zhang, J., Zhang, T., Wang, A. Z., Butler, R., Gatenby, R. A., & Enderling, H. (2021). Predicting patient-specific response to adaptive therapy in metastatic castration-resistant prostate cancer using prostate-specific antigen dynamics. Neoplasia, 23(9), 851-858. https://doi.org/10.1016/j.neo.2021.06.013
Chasnov, J. R. (2016). The Lotka-Volterra predator-prey model. Libre Texts Mathematics. Retrieved February 22, 2023, from https://math.libretexts.org/Bookshelves/Applied_Mathematics/Mathematical_Biology_(Chasnov)/01%3A_Population_Dynamics/1.04%3A_The_Lotka-Volterra_Predator-Prey_Model
Eldridge, L. (2023, February 28). Will cancer ever be cured? Verywell Health. Retrieved April 22, 2023, from https://www.verywellhealth.com/will-cancer-ever-be-cured-4686392
Gatenby, R. A., Silva, A. S., Gillies, R. J., & Frieden, B. R. (2009). Adaptive therapy. Cancer Research, 69(11), 4894-4903. https://doi.org/10.1158/0008-5472.CAN-08-3658
How adaptive therapy works [Infographic]. (n.d.). National Cancer Institute. https://www.cancer.gov/research/annual-plan/scientific-topics/how-adaptive-cancer-therapy-works-infographic
Jitender, Solanki et al. "Quality of life of cancer patients." Journal of Experimental Therapeutics & Oncology vol. 12,3 (2018): 217-221. https://pubmed.ncbi.nlm.nih.gov/29790313/
Thomas, F., Donnadieu, E., Charriere, G. M., Jacqueline, C., Tasiemski, A., Pujol, P., Renaud, F., Roche, B., Hamede, R., Brown, J., Gatenby, R., & Ujvari, B. (2018). Is adaptive therapy natural? PLOS Biology, 16(10), e2007066. https://doi.org/10.1371/journal.pbio.2007066
West, J., You, L., Zhang, J., Gatenby, R. A., Brown, J. S., Newton, P. K., & Anderson, A. R.a. (2020). Towards multidrug adaptive therapy. Cancer Research, 80(7), 1578-1589. https://doi.org/10.1158/0008-5472.CAN-19-2669
Wölfl, B., te Rietmole, H., Salvioli, M., Kaznatcheev, A., Thuijsman, F., Brown, J. S., Burgering, B., & Staňková, K. (2021). The contribution of evolutionary game theory to understanding and treating cancer. Dynamic Games and Applications, 12(2), 313-342. https://doi.org/10.1007/s13235-021-00397-w
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