Abstract P5-05-05: Computational modeling of breast cancer growth and spread: the role of matrix degrading enzymes

Abstract

Abstract Background: A “hallmark” of cancer growth and metastatic spread is the process of local invasion of the surrounding tissue. Cancer cells achieve this by the secretion of enzymes involved in proteolysis (tissue degradation) including matrix metalloproteinases (MMPs). These over-expressed proteolytic enzymes then proceed to degrade the host tissue allowing the cancer cells to disseminate throughout the microenvironment by active migration and interaction with components of the extracellular matrix such as collagen. The implications of MMP-2 activation by MMP-14 and the tissue inhibitor of metalloproteinases-2 (TIMP2) can be considered alongside the suitability of the matrix to be invaded. The suitability of the matrix incorporates pore size, since in some highly dense collagen structures such as breast tissue, the cancer cells are unable to physically fit through a porous region and rely on membrane-bound MMPs to forge a path through which degradation by other MMPs and movement of cancer cells can occur. Method: We have developed a multi-scale mathematical model of breast cancer cell invasion of host tissue by combining both micro- (cell) and macro- (tissue) scale dynamics. The model considers cancer cells and two matrix-degrading enzymes from the MMP family of differing mechanistic actions, namely MMP-2 and the membrane bound MMP-14 (also called MT1-MMP), and their interaction with, and effect on, the extracellular matrix (ECM) in a 2-D spatial domain. For the macro-scale we use a system of reaction-diffusion-taxis partial differential equations to capture the qualitative dynamics of the migratory response of the cancer cells. The micro-scale operates over a smaller spatial and temporal scale, and as such allows us to explicitly examine the stochastic role which is inherent within the region of enzyme operation. Computational simulations of the equations predict the spatio-temporal evolution of the cancer cell density, the concentration levels of the various enzymes and the density of the extracellular matrix. Results: The model exhibits a rich range of dynamic and heterogeneous spatio-temporal solutions, which qualitatively match experimental and clinically observed results for aggressive breast carcinoma invasion and can be used to determine the speed of invasion through a variety of structured mediums such as the highly dense collagen constitution of some peritumoral stroma. Using the “worst case” scenario, an estimate for the maximum region of invasion over time from the initial data can be obtained suggesting the likely extent of breast cancer cell invasion into the surrounding tissue. Conclusion: This modeling is most relevant to and informs the biological processes occurring in early stage breast cancer, in which local invasion is a crucial aspect of tumor behavior. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P5-05-05.