Characterising the Behaviour of a Structured PDE Model of the Cell Cycle in Contrast to a Corresponding ODE System

Experimental results have shown that anti-cancer therapies, such as radiotherapy and chemotherapy, can modulate the cell cycle and generate cell cycle phase-dependent responses. As a result, obtaining a detailed understanding of the cell cycle is one possible path towards improving the efficacy of many of these therapies. Here, we consider a basic structured partial differential equation (PDE) model for cell progression through the cell cycle, and derive expressions for key quantities, such as the population growth rate and cell phase proportions. These quantities are shown to be periodic and, as such, we compare the PDE model to a corresponding ordinary differential equation (ODE) model in which the parameters are linked by ensuring that the long-term ODE behaviour agrees with the average PDE behaviour. By design, we find that the ODE model does an excellent job of representing the mean dynamics of the PDE model within just a few cell cycles. However, by probing the parameter space we find cases in which this mean behaviour is not a good measure of the PDE population growth. Our analytical comparison of two caricature models (one PDE and one ODE system) provides insight into cases in which the simple ODE model is an appropriate approximation to the PDE model.

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Publication Details

Journal
Bulletin of Mathematical Biology
Published
2025-06-08
DOI
https://doi.org/10.1007/s11538-025-01472-8
Citations
2
Primary Topic
Mathematical Biology Tumor Growth
Type
article
Field-Weighted Citation Impact
2.74

Funders

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article

Characterising the Behaviour of a Structured PDE Model of the Cell Cycle in Contrast to a Corresponding ODE System

Philip K. Maini, Joe Pitt‐Francis, Helen M. Byrne, Ruby Nixson
2 citations
Bulletin of Mathematical Biology
Mathematical Biology Tumor Growth
2.74
article

Characterising the Behaviour of a Structured PDE Model of the Cell Cycle in Contrast to a Corresponding ODE System

Philip K. Maini, Joe Pitt‐Francis, Helen M. Byrne, Ruby Nixson
article en
2 citations

Abstract

Experimental results have shown that anti-cancer therapies, such as radiotherapy and chemotherapy, can modulate the cell cycle and generate cell cycle phase-dependent responses. As a result, obtaining a detailed understanding of the cell cycle is one possible path towards improving the efficacy of many of these therapies. Here, we consider a basic structured partial differential equation (PDE) model for cell progression through the cell cycle, and derive expressions for key quantities, such as the population growth rate and cell phase proportions. These quantities are shown to be periodic and, as such, we compare the PDE model to a corresponding ordinary differential equation (ODE) model in which the parameters are linked by ensuring that the long-term ODE behaviour agrees with the average PDE behaviour. By design, we find that the ODE model does an excellent job of representing the mean dynamics of the PDE model within just a few cell cycles. However, by probing the parameter space we find cases in which this mean behaviour is not a good measure of the PDE population growth. Our analytical comparison of two caricature models (one PDE and one ODE system) provides insight into cases in which the simple ODE model is an appropriate approximation to the PDE model.

Bulletin of Mathematical BiologyVol. 87(7)
University of Oxford (GB), Ludwig Cancer Research (GB)
Engineering and Physical Sciences Research Council
Good health and well-being
Openalex Percentile: Top 11%
Mathematical Biology Tumor Growth
2.74
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