Multi-Parameter Optimization of the ECM: A Novel Approach to Controlling Cancer

Overview

Cancer originates from genetic and non-genetic alterations, which induce abnormal cell proliferation and migration. Cancer formation consists of 4 main stages: initiation, progression, epithelial mesenchymal transition (EMT), and metastasis, which is the focus of this research. Metastasis refers to the spread of cancer to secondary tumor locations and contributes to over 90% of cancer mortalities. The first stage of metastasis is intravasation, which involves motile cancer cells advancing through the extracellular matrix (ECM) by secreting Matrix Metalloproteinase (MMP). ECM microenvironments differ in matrix arrangement, cell-matrix adhesions, and fiber plasticity, which strongly affect cancer migration. To understand the interactions between cancer cells and the ECM, I used the Cellular Potts Model (CPM), otherwise known as the Graner- Glazier- Hogeweg (GGH) Model to simulate cancer cell migration through varying ECM arrangements. I found randomly curved arrangements produce minimal matrix metalloproteinase (MMP) secretion and fiber degradation, resulting in decreased metastasis. In contrast, wave-like and parallel linear arrangements provide contact guidance, which adheres the cells to the ECM fibers and guides them through the arrangement. Parallel linear fiber configuration was used to investigate the effect of cell matrix adhesion energy and fiber elasticity on cancer cell migration. ECM fibers with strong cell-matrix attractions generate cell pseudopodia, which aid in increasing metastatic rate, while weaker adhesions prevent the cells from attaching to the fibers and forming protrusive regions, limiting metastasis. ECM arrays with rigid fibers elongate the cell body, allowing the cells to form cell protrusions and reinforce focal adhesions. Conversely, soft fibers stimulate cell rounding, which is associated with limited migration. Optimizing cell-matrix adhesions and fiber elasticity results in below 10% metastasis. Despite the limitations of computational modeling, the results I have obtained have powerful implications. Understanding the interactions between the ECM and cancer cells may provide insight into novel therapeutic approaches to prevent cancer metastasis and improve survival.

Competition history

• AJAS 2020 Category not listed

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