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Evolutionary triage governs fitness in driver and passenger mutations and suggests targeting never mutations

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  • R. A. Gatenby

    (Cancer Biology and Evolution Program, Moffitt Cancer Center)

  • J. J. Cunningham

    (Cancer Biology and Evolution Program, Moffitt Cancer Center)

  • J. S. Brown

    (University of Illinois at Chicago)

Abstract

Genetic and epigenetic changes in cancer cells are typically divided into ‘drivers’ and ‘passengers’. Drug development strategies target driver mutations, but inter- and intratumoral heterogeneity usually results in emergence of resistance. Here we model intratumoral evolution in the context of a fecundity/survivorship trade-off. Simulations demonstrate that the fitness value of any genetic change is not fixed but dependent on evolutionary triage governed by initial cell properties, current selection forces and prior genotypic/phenotypic trajectories. We demonstrate that spatial variations in molecular properties of tumour cells are the result of changes in environmental selection forces such as blood flow. Simulated therapies targeting fitness-increasing (driver) mutations usually decrease the tumour burden but almost inevitably fail due to population heterogeneity. An alternative strategy targets gene mutations that are never observed. Because up or downregulation of these genes unconditionally reduces cellular fitness, they are eliminated by evolutionary triage but can be exploited for targeted therapy.

Suggested Citation

  • R. A. Gatenby & J. J. Cunningham & J. S. Brown, 2014. "Evolutionary triage governs fitness in driver and passenger mutations and suggests targeting never mutations," Nature Communications, Nature, vol. 5(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms6499
    DOI: 10.1038/ncomms6499
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    Cited by:

    1. 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.
    2. 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.

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