Volume 52, Issue 4
An Evolutionary Perspective on Cancer, with Applications to Anticancer Drug Resistance Modelling and Perspectives in Therapeutic Control

Jean Clairambault

J. Math. Study, 52 (2019), pp. 470-496.

Published online: 2019-12

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  • Abstract

The question of a mathematical representation and theoretical overcoming by optimised therapeutic strategies of drug-induced drug resistance in cancer cell populations is tackled here from the point of view of adaptive dynamics and optimal population growth control, using integro-differential equations. Combined impacts of external continuous-time functions, standing for drug actions, on targets in a plastic (i.e., able to quickly change its phenotype in deadly environmental conditions) cell population model, represent a therapeutical control to be optimised. A justification for the introduction of the adaptive dynamics setting, retaining such plasticity for cancer cell populations, is firstly presented in light of the evolution of multicellular species and disruptions in multicellularity coherence that are characteristics of cancer and of its progression. Finally, open general questions on cancer and evolution in the Darwinian sense are listed, that may open innovative tracks in modelling and treating cancer by circumventing drug resistance. This study sums up results that were presented at the international NUMACH workshop, Mulhouse, France, in July 2018.

  • Keywords

Integro-differential equations, asymptotic analysis, optimal control, mathematical oncology.

  • AMS Subject Headings

35B40, 35Q92, 35R09, 45J05, 49J20, 92C50, 92D15, 92D25, 93D20

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address

jean.clairambault@inria.fr (Jean Clairambault)

  • BibTex
  • RIS
  • TXT
@Article{JMS-52-470, author = {Clairambault , Jean }, title = {An Evolutionary Perspective on Cancer, with Applications to Anticancer Drug Resistance Modelling and Perspectives in Therapeutic Control}, journal = {Journal of Mathematical Study}, year = {2019}, volume = {52}, number = {4}, pages = {470--496}, abstract = {

The question of a mathematical representation and theoretical overcoming by optimised therapeutic strategies of drug-induced drug resistance in cancer cell populations is tackled here from the point of view of adaptive dynamics and optimal population growth control, using integro-differential equations. Combined impacts of external continuous-time functions, standing for drug actions, on targets in a plastic (i.e., able to quickly change its phenotype in deadly environmental conditions) cell population model, represent a therapeutical control to be optimised. A justification for the introduction of the adaptive dynamics setting, retaining such plasticity for cancer cell populations, is firstly presented in light of the evolution of multicellular species and disruptions in multicellularity coherence that are characteristics of cancer and of its progression. Finally, open general questions on cancer and evolution in the Darwinian sense are listed, that may open innovative tracks in modelling and treating cancer by circumventing drug resistance. This study sums up results that were presented at the international NUMACH workshop, Mulhouse, France, in July 2018.

}, issn = {2617-8702}, doi = {https://doi.org/10.4208/jms.v52n4.19.06}, url = {http://global-sci.org/intro/article_detail/jms/13467.html} }
TY - JOUR T1 - An Evolutionary Perspective on Cancer, with Applications to Anticancer Drug Resistance Modelling and Perspectives in Therapeutic Control AU - Clairambault , Jean JO - Journal of Mathematical Study VL - 4 SP - 470 EP - 496 PY - 2019 DA - 2019/12 SN - 52 DO - http://dor.org/10.4208/jms.v52n4.19.06 UR - https://global-sci.org/intro/article_detail/jms/13467.html KW - Integro-differential equations, asymptotic analysis, optimal control, mathematical oncology. AB -

The question of a mathematical representation and theoretical overcoming by optimised therapeutic strategies of drug-induced drug resistance in cancer cell populations is tackled here from the point of view of adaptive dynamics and optimal population growth control, using integro-differential equations. Combined impacts of external continuous-time functions, standing for drug actions, on targets in a plastic (i.e., able to quickly change its phenotype in deadly environmental conditions) cell population model, represent a therapeutical control to be optimised. A justification for the introduction of the adaptive dynamics setting, retaining such plasticity for cancer cell populations, is firstly presented in light of the evolution of multicellular species and disruptions in multicellularity coherence that are characteristics of cancer and of its progression. Finally, open general questions on cancer and evolution in the Darwinian sense are listed, that may open innovative tracks in modelling and treating cancer by circumventing drug resistance. This study sums up results that were presented at the international NUMACH workshop, Mulhouse, France, in July 2018.

Jean Clairambault. (2019). An Evolutionary Perspective on Cancer, with Applications to Anticancer Drug Resistance Modelling and Perspectives in Therapeutic Control. Journal of Mathematical Study. 52 (4). 470-496. doi:10.4208/jms.v52n4.19.06
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