Institute for Computational Engineering and Sciences (ICES) | University of Texas at Austin/ USA
Biomechanical properties of the extracellular (ECM) matrix play a crucial role in cell function regulation. In disease conditions, an increase of ECM stiffness promotes tumor cell invasion and progression and limits nutrient diffusion through tissue. The goal of this project is to investigate how ECM stiffness affects the evolution of a tumor by integrating mathematical modelling and in vitro experiments through Bayesian inversion methods. Mathematical modelling of biological processes has been acknowledged to provide new insights in understanding the mechanisms. Modeling coupled to Bayesian inversion methods allows for quantitative predictions of tumor growth which take into account measurement and model uncertainties.
We will first investigate effects of the ECM stiffness in the avascular case and test the influence of different levels of spatially homogeneous stiffness on tumor evolution and production of angiogenetic factors. Then we will study effects of spatial inhomogeneities introducing gradients in the ECM and solving an infinite-dimensional Bayesian inverse problem to infer the space-dependent stiffness. We will use an artificial vessel to investigate effects of the ECM stiffness on vascular growth. In both the avascular and vascular settings, influence of ECM stiffness under drug supply will be addressed. In the second case, chemotherapeutics will be injected through the artificial vessel, creating a setting which may provide insight for real life scenarios of intravenous administration of treatment to patients.