A genuinely hybrid, multiscale 3D cancer invasion and metastasis modelling framework

bioRxiv
MathOnco
Preprint
MathBio
Authors
Affiliations

Dimitrios Katsaounis

School of Mathematics and Statistics, University St Andrews, North Haugh, St Andrews, UK

Nicholas Harbour

Center for Mathematical Medicine and Biology, University of Nottingham, UK

Thomas Williams

School of Mathematics and Statistics, The University of Melbourne, Australia

Mark Chaplain

School of Mathematics and Statistics, University St Andrews, North Haugh, St Andrews, UK

Nikolaos Sfakianakis

School of Mathematics and Statistics, University St Andrews, North Haugh, St Andrews, UK

Published

January 15, 2024

Doi

Abstract

We introduce in this paper substantial enhancements to a previously proposed hybrid multiscale cancer invasion modelling framework to better reflect the biological reality and dynamics of cancer. These model updates contribute to a more accurate representation of cancer dynamics, they provide deeper insights and enhance our predictive capabilities.

Key updates include the integration of porous medium-like diffusion for the evolution of Epithelial-like Cancer Cells and other essential cellular constituents of the system, more realistic modelling of Epithelial-Mesenchymal Transition and Mesenchymal-Epithelial Transition models with the inclusion of Transforming Growth Factor beta within the tumour microenvironment, and the introduction of Compound Poisson Process in the Stochastic Differential Equations that describe the migration behaviour of the Mesenchymal-like Cancer Cells. Another innovative feature of the model is its extension into a multi-organ metastatic framework. This framework connects various organs through a circulatory network, enabling the study of how cancer cells spread to secondary sites.

Citation

BibTeX citation:
@article{katsaounis2024,
  author = {Katsaounis, Dimitrios and Harbour, Nicholas and Williams,
    Thomas and Chaplain, Mark and Sfakianakis, Nikolaos},
  title = {A Genuinely Hybrid, Multiscale {3D} Cancer Invasion and
    Metastasis Modelling Framework},
  journal = {bioRxiv},
  date = {2024-01-15},
  doi = {10.1101/2024.01.12.575361},
  langid = {en}
}
For attribution, please cite this work as:
Katsaounis, Dimitrios, Nicholas Harbour, Thomas Williams, Mark Chaplain, and Nikolaos Sfakianakis. 2024. “A Genuinely Hybrid, Multiscale 3D Cancer Invasion and Metastasis Modelling Framework.” bioRxiv, January. https://doi.org/10.1101/2024.01.12.575361.