Cargando…

Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata

Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract mod...

Descripción completa

Detalles Bibliográficos
Autores principales: Monteagudo, Ángel, Santos, José
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4503350/
https://www.ncbi.nlm.nih.gov/pubmed/26176702
http://dx.doi.org/10.1371/journal.pone.0132306
_version_ 1782381290424631296
author Monteagudo, Ángel
Santos, José
author_facet Monteagudo, Ángel
Santos, José
author_sort Monteagudo, Ángel
collection PubMed
description Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC) and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation.
format Online
Article
Text
id pubmed-4503350
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-45033502015-07-17 Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata Monteagudo, Ángel Santos, José PLoS One Research Article Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC) and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation. Public Library of Science 2015-07-15 /pmc/articles/PMC4503350/ /pubmed/26176702 http://dx.doi.org/10.1371/journal.pone.0132306 Text en © 2015 Monteagudo, Santos http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Monteagudo, Ángel
Santos, José
Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata
title Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata
title_full Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata
title_fullStr Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata
title_full_unstemmed Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata
title_short Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata
title_sort treatment analysis in a cancer stem cell context using a tumor growth model based on cellular automata
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4503350/
https://www.ncbi.nlm.nih.gov/pubmed/26176702
http://dx.doi.org/10.1371/journal.pone.0132306
work_keys_str_mv AT monteagudoangel treatmentanalysisinacancerstemcellcontextusingatumorgrowthmodelbasedoncellularautomata
AT santosjose treatmentanalysisinacancerstemcellcontextusingatumorgrowthmodelbasedoncellularautomata