Abstract
Three-dimensional (3D) in vitro tumour spheroid experiments are an important tool for studying cancer progression and potential cancer drug therapies. Standard experiments involve growing and imaging spheroids to explore how different conditions lead to different rates of spheroid growth. These kinds of experiments, however, do not reveal any information about the spatial distribution of the cell cycle within the expanding spheroid. Since 2008, a new experimental technology called fluorescent ubiquitination-based cell cycle indicator (FUCCI) has enabled real-time in situ visualisation of the cell cycle progression. Observations of 3D tumour spheroids with FUCCI labelling reveal significant intratumoural structure, as the cell cycle status can vary with location. Although many mathematical models of tumour spheroid growth have been developed, none of the existing mathematical models are designed to interpret experimental observations with FUCCI labelling. In this work, we adapt the mathematical framework originally proposed by Ward and King (Math Med Biol 14:39–69, 1997. https://doi.org/10.1093/imammb/14.1.39) to produce a new mathematical model of FUCCI-labelled tumour spheroid growth. The mathematical model treats the spheroid as being composed of three subpopulations: (i) living cells in G1 phase that fluoresce red; (ii) living cells in S/G2/M phase that fluoresce green; and (iii) dead cells that are not fluorescent. We assume that the rates at which cells pass through different phases of the cell cycle, and the rate of cell death, depend upon the local oxygen concentration. Parameterising the new mathematical model using experimental measurements of cell cycle transition times, we show that the model can qualitatively capture important experimental observations that cannot be addressed using previous mathematical models. Further, we show that the mathematical model can be used to qualitatively mimic the action of anti-mitotic drugs applied to the spheroid. All software programs required to solve the nonlinear moving boundary problem associated with the new mathematical model are available on GitHub. at https://github.com/wang-jin-mathbio/Jin2021
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Acknowledgements
MJS and NKH are supported by the Australian Research Council (DP200100177). NKH is supported by the National Health and Medical Research Council (APP1084893). WJ is supported by a QUT Vice-Chancellor’s Research Fellowship. We thank two referees and Emeritus Professor Sean McElwain for their helpful suggestions.
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Jin, W., Spoerri, L., Haass, N.K. et al. Mathematical Model of Tumour Spheroid Experiments with Real-Time Cell Cycle Imaging. Bull Math Biol 83, 44 (2021). https://doi.org/10.1007/s11538-021-00878-4
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DOI: https://doi.org/10.1007/s11538-021-00878-4