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Liver metastases are a signiﬁcant cause of death in cancer, but the role of liver tissue mechanics on early metastatic seeding and growth is unclear. We used an agent-based model (ABM) to study how the mechanical interactions between tumor cells and the liver parenchyma (normal liver tissue) aﬀect cancer metastatic seeding and growth in large, centimeter-scale liver tissues. By exploring the space of biomechanical parameters for the stress-based apoptosis in the parenchyma and pressure-regulated cycling in tumor cells, we ﬁnd that the biomechanical interactions (adhesive, repulsive, and elastic forces on short time scales, and plastic reorganization on longer time scales) play a very important role in the tumor cell’s seeding and growth within the liver tissue.
There are two types of cell in our model: parenchyma cell and tumor cell. We didn't model proliferation in the parenchyma, instead assuming that it begins in a state of homeostasis. However, we simulated cells' apoptosis based on the following rule, where the cell experiences the elastic and plastic force with ECM.
Parenchyma cells' stress-based apoptosis rule;
For tumor cells, we modeled its apoptosis rate as constant, but the cycling rate was simulated with below rule, where its proliferation rate is controlled by the interaction between tumor cells and parenchyma cells
Tumor cells' pressure-based proliferation rule:
This app was developed to simulate the liver tissue mechanobiology, and it successfully models the interaction between tumor cells and parenchyma cells in different biomechanical parameters. In the demo, we used a small domain (2mm × 2mm) in order to reduce the computational time.
This software is powered by PhysiCell, a powerful simulation tool that combines multi-substrate diffusive transport and off-lattice cell models. PhysiCell is BSD-licensed, and available at:
- GitHub releases: https://github.com/MathCancer/PhysiCell/releases
- SourceForge downloads: https://sourceforge.net/projects/physicell/
It is a C++, cross-platform code with minimal software dependencies. It has been tested and deployed in Linux, BSD, OSX, Windows, and other environments, using the standard g++ compiler.
Randy Heiland, Research Associate, Intelligent Systems Engineering, Indiana University.
Paul Macklin, Ph.D. , Associate Professor, Intelligent Systems Engineering, Indiana University
We appreciate both Randy and Paul's support in debug source code and test the GUI
• National Science Foundation (Fox, 1720625)
• Breast Cancer Research Foundation / Jayne Koskinas Ted Giovanis Foundation for Health and Policy (Ewald, Gilkes, Macklin)
• National Cancer Institute (Agus, Atala, Soker, 1R01CA180149)
• National Cancer Institute (Finley, Macklin, Mumenthaler 1U01CA232137)
 Ghaffarizadeh A, Heiland R, Friedman SH, Mumenthaler SM, Macklin P (2018) PhysiCell: An open source physics-based cell simulator for 3-D multicellular systems. PLoS Comput Biol 14(2): e1005991. https://doi.org/10.1371/journal.pcbi.1005991
 Ghaffarizadeh A, Friedman SH, Macklin P (2016) BioFVM: an efficient, parallelized diffusive transport solver for 3-D biological simulations. Bioinformatics 32(8):1256-8. https://doi.org/10.1093/bioinformatics/btv730
 Randy Heiland, Daniel Mishler, Tyler Zhang, Eric Bower, Paul Macklin (2019) xml2jupyter: Mapping parameters between XML and Jupyter widgets. DOI: https://doi.org/10.1101/601211
We are preparing the manuscript: "Yafei Wang et al, A multi-model investigation on the impact of liver tissue mechanobiology on cancer metastatic seeding" for submission soon.
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