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Cancer heterogeneity and multilayer spatial evolutionary games

BACKGROUND: Evolutionary game theory (EGT) has been widely used to simulate tumour processes. In almost all studies on EGT models analysis is limited to two or three phenotypes. Our model contains four main phenotypes. Moreover, in a standard approach only heterogeneity of populations is studied, wh...

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Autores principales: Świerniak, Andrzej, Krześlak, Michał
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5064968/
https://www.ncbi.nlm.nih.gov/pubmed/27737715
http://dx.doi.org/10.1186/s13062-016-0156-z
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author Świerniak, Andrzej
Krześlak, Michał
author_facet Świerniak, Andrzej
Krześlak, Michał
author_sort Świerniak, Andrzej
collection PubMed
description BACKGROUND: Evolutionary game theory (EGT) has been widely used to simulate tumour processes. In almost all studies on EGT models analysis is limited to two or three phenotypes. Our model contains four main phenotypes. Moreover, in a standard approach only heterogeneity of populations is studied, while cancer cells remain homogeneous. A multilayer approach proposed in this paper enables to study heterogeneity of single cells. METHOD: In the extended model presented in this paper we consider four strategies (phenotypes) that can arise by mutations. We propose multilayer spatial evolutionary games (MSEG) played on multiple 2D lattices corresponding to the possible phenotypes. It enables simulation and investigation of heterogeneity on the player-level in addition to the population-level. Moreover, it allows to model interactions between arbitrary many phenotypes resulting from the mixture of basic traits. RESULTS: Different equilibrium points and scenarios (monomorphic and polymorphic populations) have been achieved depending on model parameters and the type of played game. However, there is a possibility of stable quadromorphic population in MSEG games for the same set of parameters like for the mean-field game. CONCLUSION: The model assumes an existence of four possible phenotypes (strategies) in the population of cells that make up tumour. Various parameters and relations between cells lead to complex analysis of this model and give diverse results. One of them is a possibility of stable coexistence of different tumour cells within the population, representing almost arbitrary mixture of the basic phenotypes. REVIEWERS: This article was reviewed by Tomasz Lipniacki, Urszula Ledzewicz and Jacek Banasiak.
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spelling pubmed-50649682016-10-18 Cancer heterogeneity and multilayer spatial evolutionary games Świerniak, Andrzej Krześlak, Michał Biol Direct Research BACKGROUND: Evolutionary game theory (EGT) has been widely used to simulate tumour processes. In almost all studies on EGT models analysis is limited to two or three phenotypes. Our model contains four main phenotypes. Moreover, in a standard approach only heterogeneity of populations is studied, while cancer cells remain homogeneous. A multilayer approach proposed in this paper enables to study heterogeneity of single cells. METHOD: In the extended model presented in this paper we consider four strategies (phenotypes) that can arise by mutations. We propose multilayer spatial evolutionary games (MSEG) played on multiple 2D lattices corresponding to the possible phenotypes. It enables simulation and investigation of heterogeneity on the player-level in addition to the population-level. Moreover, it allows to model interactions between arbitrary many phenotypes resulting from the mixture of basic traits. RESULTS: Different equilibrium points and scenarios (monomorphic and polymorphic populations) have been achieved depending on model parameters and the type of played game. However, there is a possibility of stable quadromorphic population in MSEG games for the same set of parameters like for the mean-field game. CONCLUSION: The model assumes an existence of four possible phenotypes (strategies) in the population of cells that make up tumour. Various parameters and relations between cells lead to complex analysis of this model and give diverse results. One of them is a possibility of stable coexistence of different tumour cells within the population, representing almost arbitrary mixture of the basic phenotypes. REVIEWERS: This article was reviewed by Tomasz Lipniacki, Urszula Ledzewicz and Jacek Banasiak. BioMed Central 2016-10-13 /pmc/articles/PMC5064968/ /pubmed/27737715 http://dx.doi.org/10.1186/s13062-016-0156-z Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Świerniak, Andrzej
Krześlak, Michał
Cancer heterogeneity and multilayer spatial evolutionary games
title Cancer heterogeneity and multilayer spatial evolutionary games
title_full Cancer heterogeneity and multilayer spatial evolutionary games
title_fullStr Cancer heterogeneity and multilayer spatial evolutionary games
title_full_unstemmed Cancer heterogeneity and multilayer spatial evolutionary games
title_short Cancer heterogeneity and multilayer spatial evolutionary games
title_sort cancer heterogeneity and multilayer spatial evolutionary games
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5064968/
https://www.ncbi.nlm.nih.gov/pubmed/27737715
http://dx.doi.org/10.1186/s13062-016-0156-z
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