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Integrating evolutionary dynamics into treatment of metastatic castrate-resistant prostate cancer

Author

Listed:
  • Jingsong Zhang

    (Moffitt Cancer Center & Research Institute)

  • Jessica J. Cunningham

    (Moffitt Cancer Center & Research Institute)

  • Joel S. Brown

    (Moffitt Cancer Center & Research Institute
    University of Illinois at Chicago)

  • Robert A. Gatenby

    (Moffitt Cancer Center & Research Institute
    Moffitt Cancer Center & Research Institute)

Abstract

Abiraterone treats metastatic castrate-resistant prostate cancer by inhibiting CYP17A, an enzyme for testosterone auto-production. With standard dosing, evolution of resistance with treatment failure (radiographic progression) occurs at a median of ~16.5 months. We hypothesize time to progression (TTP) could be increased by integrating evolutionary dynamics into therapy. We developed an evolutionary game theory model using Lotka–Volterra equations with three competing cancer “species”: androgen dependent, androgen producing, and androgen independent. Simulations with standard abiraterone dosing demonstrate strong selection for androgen-independent cells and rapid treatment failure. Adaptive therapy, using patient-specific tumor dynamics to inform on/off treatment cycles, suppresses proliferation of androgen-independent cells and lowers cumulative drug dose. In a pilot clinical trial, 10 of 11 patients maintained stable oscillations of tumor burdens; median TTP is at least 27 months with reduced cumulative drug use of 47% of standard dosing. The outcomes show significant improvement over published studies and a contemporaneous population.

Suggested Citation

  • Jingsong Zhang & Jessica J. Cunningham & Joel S. Brown & Robert A. Gatenby, 2017. "Integrating evolutionary dynamics into treatment of metastatic castrate-resistant prostate cancer," Nature Communications, Nature, vol. 8(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_s41467-017-01968-5
    DOI: 10.1038/s41467-017-01968-5
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    Cited by:

    1. Guillaume Harmange & Raúl A. Reyes Hueros & Dylan L. Schaff & Benjamin Emert & Michael Saint-Antoine & Laura C. Kim & Zijian Niu & Shivani Nellore & Mitchell E. Fane & Gretchen M. Alicea & Ashani T. W, 2023. "Disrupting cellular memory to overcome drug resistance," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    2. Serhii Aif & Nico Appold & Lucas Kampman & Oskar Hallatschek & Jona Kayser, 2022. "Evolutionary rescue of resistant mutants is governed by a balance between radial expansion and selection in compact populations," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    3. Elsa Hansen & Jason Karslake & Robert J Woods & Andrew F Read & Kevin B Wood, 2020. "Antibiotics can be used to contain drug-resistant bacteria by maintaining sufficiently large sensitive populations," PLOS Biology, Public Library of Science, vol. 18(5), pages 1-20, May.
    4. Li You & Maximilian von Knobloch & Teresa Lopez & Vanessa Peschen & Sidney Radcliffe & Praveen Koshy Sam & Frank Thuijsman & Kateřina Staňková & Joel S. Brown, 2019. "Including Blood Vasculature into a Game-Theoretic Model of Cancer Dynamics," Games, MDPI, vol. 10(1), pages 1-22, March.
    5. Francesca Menghi & Edison T. Liu, 2022. "Functional genomics of complex cancer genomes," Nature Communications, Nature, vol. 13(1), pages 1-4, December.
    6. Gregory J Kimmel & Philip Gerlee & Philipp M Altrock, 2019. "Time scales and wave formation in non-linear spatial public goods games," PLOS Computational Biology, Public Library of Science, vol. 15(9), pages 1-22, September.
    7. Benjamin Wölfl & Hedy te Rietmole & Monica Salvioli & Artem Kaznatcheev & Frank Thuijsman & Joel S. Brown & Boudewijn Burgering & Kateřina Staňková, 2022. "The Contribution of Evolutionary Game Theory to Understanding and Treating Cancer," Dynamic Games and Applications, Springer, vol. 12(2), pages 313-342, June.
    8. Teemu Kuosmanen & Johannes Cairns & Robert Noble & Niko Beerenwinkel & Tommi Mononen & Ville Mustonen, 2021. "Drug-induced resistance evolution necessitates less aggressive treatment," PLOS Computational Biology, Public Library of Science, vol. 17(9), pages 1-22, September.
    9. Maria Kleshnina & Sabrina Streipert & Joel S. Brown & Kateřina Staňková, 2023. "Game Theory for Managing Evolving Systems: Challenges and Opportunities of Including Vector-Valued Strategies and Life-History Traits," Dynamic Games and Applications, Springer, vol. 13(4), pages 1130-1155, December.
    10. Marco Archetti, 2018. "How to Analyze Models of Nonlinear Public Goods," Games, MDPI, vol. 9(2), pages 1-15, April.
    11. Péter Bayer & Jeffrey West, 2023. "Games and the Treatment Convexity of Cancer," Dynamic Games and Applications, Springer, vol. 13(4), pages 1088-1105, December.
    12. Christian Hilbe & Maria Kleshnina & Kateřina Staňková, 2023. "Evolutionary Games and Applications: Fifty Years of ‘The Logic of Animal Conflict’," Dynamic Games and Applications, Springer, vol. 13(4), pages 1035-1048, December.
    13. Pranav I. Warman & Artem Kaznatcheev & Arturo Araujo & Conor C. Lynch & David Basanta, 2018. "Fractionated Follow-Up Chemotherapy Delays the Onset of Resistance in Bone Metastatic Prostate Cancer," Games, MDPI, vol. 9(2), pages 1-10, April.
    14. Nassim Nicholas Taleb & Jeffrey West, 2022. "Working With Convex Responses: Antifragility From Finance to Oncology," Papers 2209.14631, arXiv.org, revised Jan 2023.
    15. Nicolosi, Gabriel & Friesz, Terry & Griffin, Christopher, 2022. "Approximation of optimal control surfaces for 2 × 2 skew-symmetric evolutionary game dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).

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