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Game Theory of Tumor–Stroma Interactions in Multiple Myeloma: Effect of Nonlinear Benefits

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  • Javad Salimi Sartakhti

    (Department of Electrical and Computer Engineering, University of Kashan, Kashan 8731753153, Iran)

  • Mohammad Hossein Manshaei

    (Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 8415683111, Iran)

  • Marco Archetti

    (School of Biological Sciences, University of East Anglia, Norwich NR4 7TJ, UK)

Abstract

Cancer cells and stromal cells often exchange growth factors with paracrine effects that promote cell growth: a form of cooperation that can be studied by evolutionary game theory. Previous models have assumed that interactions between cells are pairwise or that the benefit of a growth factor is a linear function of its concentration. Diffusible factors, however, affect multiple cells and generally have nonlinear effects, and these differences are known to have important consequences for evolutionary dynamics. Here, we study tumor–stroma paracrine signaling using a model with multiplayer collective interactions in which growth factors have nonlinear effects. We use multiple myeloma as an example, modelling interactions between malignant plasma cells, osteoblasts, and osteoclasts. Nonlinear benefits can lead to results not observed in linear models, including internal mixed stable equilibria and cyclical dynamics. Models with linear effects, therefore, do not lead to a meaningful characterization of the dynamics of tumor–stroma interactions. To understand the dynamics and the effect of therapies it is necessary to estimate the shape of the benefit functions experimentally and parametrize models based on these functions.

Suggested Citation

  • Javad Salimi Sartakhti & Mohammad Hossein Manshaei & Marco Archetti, 2018. "Game Theory of Tumor–Stroma Interactions in Multiple Myeloma: Effect of Nonlinear Benefits," Games, MDPI, vol. 9(2), pages 1-11, May.
    • Handle: RePEc:gam:jgames:v:9:y:2018:i:2:p:32-:d:149268
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    References listed on IDEAS

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    1. Marco Archetti, 2014. "Stable Heterogeneity for the Production of Diffusible Factors in Cell Populations," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-8, September.
    2. Moritz Gerstung & Hani Nakhoul & Niko Beerenwinkel, 2011. "Evolutionary Games with Affine Fitness Functions: Applications to Cancer," Dynamic Games and Applications, Springer, vol. 1(3), pages 370-385, September.
    3. Javad Salimi Sartakhti & Mohammad Hossein Manshaei & Soroosh Bateni & Marco Archetti, 2016. "Evolutionary Dynamics of Tumor-Stroma Interactions in Multiple Myeloma," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-17, December.
    4. D. Basanta & H. Hatzikirou & A. Deutsch, 2008. "Studying the emergence of invasiveness in tumours using game theory," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 63(3), pages 393-397, June.
    5. Marco Archetti, 2018. "How to Analyze Models of Nonlinear Public Goods," Games, MDPI, vol. 9(2), pages 1-15, April.
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    Cited by:

    1. 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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