Modeling Cancer Cell Growth Dynamics In vitro in Response to Antimitotic Drug Treatment

Type: Article

Publication Date: 2017-08-30

Citations: 12

DOI: https://doi.org/10.3389/fonc.2017.00189

Abstract

Investigating the role of intrinsic cell heterogeneity emerging from variations in cell-cycle parameters and apoptosis is a crucial step toward better informing drug administration. Antimitotic agents, widely used in chemotherapy, target exclusively proliferative cells and commonly induce a prolonged mitotic arrest followed by cell death via apoptosis. In this paper, we developed a physiologically motivated mathematical framework for describing cancer cell growth dynamics that incorporates the intrinsic heterogeneity in the time individual cells spend in the cell-cycle and apoptosis process. More precisely, our model comprises two age-structured partial differential equations for the proliferative and apoptotic cell compartments and one ordinary differential equation for the quiescent compartment. To reflect the intrinsic cell heterogeneity that governs the growth dynamics, proliferative and apoptotic cells are structured in "age," i.e., the amount of time remaining to be spent in each respective compartment. In our model, we considered an antimitotic drug whose effect on the cellular dynamics is to induce mitotic arrest, extending the average cell-cycle length. The prolonged mitotic arrest induced by the drug can trigger apoptosis if the time a cell will spend in the cell cycle is greater than the mitotic arrest threshold. We studied the drug's effect on the long-term cancer cell growth dynamics using different durations of prolonged mitotic arrest induced by the drug. Our numerical simulations suggest that at confluence and in the absence of the drug, quiescence is the long-term asymptotic behavior emerging from the cancer cell growth dynamics. This pattern is maintained in the presence of small increases in the average cell-cycle length. However, intermediate increases in cell-cycle length markedly decrease the total number of cells and can drive the cancer population to extinction. Intriguingly, a large "switch-on/switch-off" increase in the average cell-cycle length maintains an active cell population in the long term, with oscillating numbers of proliferative cells and a relatively constant quiescent cell number.

Locations

  • Frontiers in Oncology - View - PDF
  • PubMed Central - View
  • Europe PMC (PubMed Central) - View - PDF
  • DOAJ (DOAJ: Directory of Open Access Journals) - View
  • King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology) - View - PDF
  • PubMed - View

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Works Cited by This (15)

Action Title Year Authors
+ Investigating the development of chemotherapeutic drug resistance in cancer: A multiscale computational study 2014 Gibin Powathil
Mark A. J. Chaplain
Maciej Swat
+ Asymptotic Analysis of a Cell Cycle Model Based on Unequal Division 1987 Ovide Arino
Marek Kimmel
+ PDF Chat Dynamics between Cancer Cell Subpopulations Reveals a Model Coordinating with Both Hierarchical and Stochastic Concepts 2014 Weikang Wang
Yi Quan
Qibin Fu
Yu Liu
Ying Liang
Jingwen Wu
Gen Yang
Chunxiong Luo
Qi Ouyang
Yugang Wang
+ Emergence of Drug Tolerance in Cancer Cell Populations: An Evolutionary Outcome of Selection, Nongenetic Instability, and Stress-Induced Adaptation 2015 Rebecca H. Chisholm
Tommaso Lorenzi
Alexander Lorz
Annette K. Larsen
Luís Almeida
Alexandre E. Escargueil
Jean Clairambault
+ Stability analysis of models of cell production systems 1986 Ovide Arino
Marek Kimmel
+ PDF Chat Modeling intrinsic heterogeneity and growth of cancer cells 2014 James M. Greene
Doron Levy
King Leung Fung
Paloma Silva de Souza
Michael M. Gottesman
Orit Lavi
+ A nonlinear structured population model of tumor growth with quiescence 1990 Mats Gyllenberg
Glenn F. Webb
+ Modelling the balance between quiescence and cell death in normal and tumour cell populations 2006 Lorenzo Spinelli
Alessandro Torricelli
Paolo Ubezio
Britta Basse
+ A mathematical model for analysis of the cell cycle in cell lines derived from human tumors 2003 Britta Basse
Bruce C. Baguley
Elaine S. Marshall
Wayne R. Joseph
Bruce van Brunt
G.C. Wake
David J. N. Wall
+ Determining the initial age distribution for an age structured population 1991 Michael Pilant
William Rundell