Computational and Mathematical Methods in Medicine

Computational and Mathematical Methods in Medicine / 2003 / Article

Open Access

Volume 5 |Article ID 383045 | https://doi.org/10.1080/10273660310001630443

L. A. Bach, D. J. T. Sumpter, J. Alsner, V. Loeschcke, "Spatial Evolutionary Games of Interaction among Generic Cancer Cells", Computational and Mathematical Methods in Medicine, vol. 5, Article ID 383045, 12 pages, 2003. https://doi.org/10.1080/10273660310001630443

Spatial Evolutionary Games of Interaction among Generic Cancer Cells

Received01 Nov 2002
Revised31 Jul 2003
Accepted14 Aug 2003

Abstract

Evolutionary game models of cellular interactions have shown that heterogeneity in the cellular genotypic composition is maintained through evolution to stable coexistence of growth-promoting and non-promoting cell types. We generalise these mean-field models and relax the assumption of perfect mixing of cells by instead implementing an individual-based model that includes the stochastic and spatial effects likely to occur in tumours. The scope for coexistence of genotypic strategies changed with the inclusion of explicit space and stochasticity. The spatial models show some interesting deviations from their mean-field counterparts, for example the possibility of altruistic (paracrine) cell strategies to thrive. Such effects can however, be highly sensitive to model implementation and the more realistic models with semi-synchronous and stochastic updating do not show evolution of altruism. We do find some important and consistent differences between the spatial and mean-field models, in particular that the parameter regime for coexistence of growth-promoting and nonpromoting cell types is narrowed. For certain parameters in the model a selective collapse of a generic growth promoter occurs, hence the evolutionary dynamics mimics observable in vivo tumour phenomena such as (therapy induced) relapse behaviour. Our modelling approach differs from many of those previously applied in understanding growth of cancerous tumours in that it attempts to account for natural selection at a cellular level. This study thus points a new direction towards more plausible spatial tumour modelling and the understanding of cancerous growth.

Copyright © 2003 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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