IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0132306.html
   My bibliography  Save this article

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

Author

Listed:
  • Ángel Monteagudo
  • José Santos

Abstract

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.

Suggested Citation

  • Ángel Monteagudo & José Santos, 2015. "Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-16, July.
  • Handle: RePEc:plo:pone00:0132306
    DOI: 10.1371/journal.pone.0132306
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0132306
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0132306&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0132306?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0132306. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.