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Tracking the evolution of cancer cell populations through the mathematical lens of phenotype-structured equations

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Date
23/08/2016
Author
Lorenzi, Tommaso
Chisholm, Rebecca H.
Clairambault, Jean
Keywords
Cancer cell populations
Phenotypic evolution
Natural selection
Phenotype plasticity
Epimutations
Cytotoxic-drug resistance
Phenotypic heterogeneity
Mathematical oncology
Phenotype-structured equations
QR Microbiology
QA Mathematics
T-NDAS
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Abstract
Background: A thorough understanding of the ecological and evolutionary mechanisms that drive the phenotypic evolution of neoplastic cells is a timely and key challenge for the cancer research community. In this respect, mathematical modelling can complement experimental cancer research by offering alternative means of understanding the results of in vitro and in vivo experiments, and by allowing for a quick and easy exploration of a variety of biological scenarios through in silico studies. Results: To elucidate the roles of phenotypic plasticity and selection pressures in tumour relapse, we present here a phenotype-structured model of evolutionary dynamics in a cancer cell population which is exposed to the action of a cytotoxic drug. The analytical tractability of our model allows us to investigate how the phenotype distribution, the level of phenotypic heterogeneity, and the size of the cell population are shaped by the strength of natural selection, the rate of random epimutations, the intensity of the competition for limited resources between cells, and the drug dose in use. Conclusions: Our analytical results clarify the conditions for the successful adaptation of cancer cells faced with environmental changes. Furthermore, the results of our analyses demonstrate that the same cell population exposed to different concentrations of the same cytotoxic drug can take different evolutionary trajectories, which culminate in the selection of phenotypic variants characterised by different levels of drug tolerance. This suggests that the response of cancer cells to cytotoxic agents is more complex than a simple binary outcome, i.e., extinction of sensitive cells and selection of highly resistant cells. Also, our mathematical results formalise the idea that the use of cytotoxic agents at high doses can act as a double-edged sword by promoting the outgrowth of drug resistant cellular clones. Overall, our theoretical work offers a formal basis for the development of anti-cancer therapeutic protocols that go beyond the ‘maximum-tolerated-dose paradigm’, as they may be more effective than traditional protocols at keeping the size of cancer cell populations under control while avoiding the expansion of drug tolerant clones.
Citation
Lorenzi , T , Chisholm , R H & Clairambault , J 2016 , ' Tracking the evolution of cancer cell populations through the mathematical lens of phenotype-structured equations ' , Biology Direct , vol. 11 , 43 . https://doi.org/10.1186/s13062-016-0143-4
Publication
Biology Direct
Status
Peer reviewed
DOI
https://doi.org/10.1186/s13062-016-0143-4
ISSN
1745-6150
Type
Journal article
Rights
© 2016 The Author(s). Open Access. This 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.
Description
This work was supported in part by the French National Research Agency through the “ANR blanche” project Kibord [ANR-13-BS01-0004].
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/9363

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