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Stochastic competitive release and adaptive chemotherapy.
Park, J; Newton, P K.
Afiliación
  • Park J; Department of Mathematics, University of Southern California, Los Angeles, California 90089-1191, USA.
  • Newton PK; Department of Aerospace & Mechanical Engineering, Department of Mathematics, and Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, California 90089-1191, USA.
Phys Rev E ; 108(3-1): 034407, 2023 Sep.
Article en En | MEDLINE | ID: mdl-37849192
ABSTRACT
We develop a finite-cell model of tumor natural selection dynamics to investigate the stochastic fluctuations associated with multiple rounds of adaptive chemotherapy. The adaptive cycles are designed to avoid chemoresistance in the tumor by managing the ecological mechanism of competitive release of a resistant subpopulation. Our model is based on a three-component evolutionary game played among healthy (H), sensitive (S), and resistant (R) populations of N cells, with a chemotherapy control parameter, C(t), which we use to dynamically impose selection pressure on the sensitive subpopulation to slow tumor growth and manage competitive release of the resistant population. The adaptive chemoschedule is designed based on the deterministic (N→∞) adjusted replicator dynamical system, then implemented using the finite-cell stochastic frequency dependent Moran process model (N=10K-50K) to ascertain the cumulative effect of the stochastic fluctuations on the efficacy of the adaptive schedules over multiple rounds. We quantify the stochastic fixation probability regions of the R and S populations in the HSR trilinear phase plane as a function of the control parameter C∈[0,1], showing that the size of the R region increases with increasing C. We then implement an adaptive time-dependent schedule C(t) for the stochastic model and quantify the variances (using principal component coordinates) associated with the evolutionary cycles over multiple rounds of adaptive therapy. The variances increase subquadratically through several rounds before the evolutionary cycle begins to break down. Despite this, we show the stochastic adaptive schedules are more effective at delaying resistance than standard maximum tolerated dose and low-dose metronomic schedules. The simplified low-dimensional model provides some insights on how well multiple rounds of adaptive therapies are likely to perform over a range of tumor sizes (i.e., different values of N) if the goal is to maintain a sustained balance among competing subpopulations of cells to avoid chemoresistance via competitive release in a stochastic environment.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Evolución Biológica / Neoplasias Idioma: En Revista: Phys Rev E Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Evolución Biológica / Neoplasias Idioma: En Revista: Phys Rev E Año: 2023 Tipo del documento: Article