Modeling of Extracellular Matrix Degradation in a Metastatic Tumor Microenvironment Using CompuCell3D

Introduction: Every year, there are 8.2 million cancer-related deaths worldwide. The spreading of tumor cells in a human body, called metastasis, is known to be the primary cause of death. In the early stages of metastatic invasion, tumor cells and cancer associated fibroblasts (CAFs) produce two primary types of chemicals: matrix metalloproteinases (MMPs) and lysyl oxidase (LOX). MMPs degrade the extracellular matrix (ECM) fibers, perforate the basement membrane, and allow tumor cells to escape. LOX crosslinks and aligns the ECM fibers, which generates a pathway for cancer cells to migrate more easily through the ECM and eventually invade into a blood vessel and spread to other locations of the body. The mechanism of such ECM remodeling in the local tumor microenvironment remains ambiguous. Multi-scale computational models can provide a fundamental understanding of how ECM remodeling impacts the physical properties of metastatic cancer cells and the dynamics of migration from the tumor microenvironment and this understanding is of keen interest in cancer research.

Materials and Methods: A computational simulation predicting the changes in the ECM during metastasis is developed using the open-source modeling software package CompuCell3D (CC3D). The biological aspects of the CC3D simulation are implemented based on the Glazier-Graner-Hogeweg (GGH) model. In the GGH framework, the effective energy or Hamiltonian is utilized to define the thermodynamics of behaviors and interactions among cellular and non-cellular elements in the simulation, while the Metropolis algorithm is applied to model the stochastic changes in the cell dynamics. The evolution of one of the chemical signals, MMP, with respect to time is described and implemented in the simulation via a reaction-diffusion partial differential equation (PDE). The PDE accounts for the secretion of MMP due to tumor cells and CAFs and the diffusion and decay of MMP. The PDE was solved simultaneously with the agent-based model by the CC3D program.

Conclusions: We expect our model could be applicable to potential therapeutics that can prevent or detect such modification in the ECM during cancer metastasis. Unlike experimental approaches, computational models, especially ones built in CC3D, are not difficult to modify. Hence, that allows our CC3D simulation to be easily updated and further developed by adding more complex interactions to the current model implementation considering various cell types, as well as other unaccounted for biological elements and chemical signals and analyzing their effects on the local tumor microenvironment.