Computational Modeling for Predicting 3D Cancer Cell Invasion into the Extracellular Fiber Network

Massachusetts Institute Of Technology, Cambridge MA

Investigators

Abstract

Physical interaction of a cell with the surrounding tissue is very important in cancer metastasis, wound healing, development, angiogenesis and many other normal and disease conditions. We still have only a small quantitative understanding of this for real tissues. One type of interaction that is not understood quantitatively is where a cell extends thin structures called a 'filopodia' that sense chemicals and "feel" the stiffness of the surrounding parts of the tissue. This research will create a three dimensional (3D) model of filipodia from the finest scale, to model the molecules in the 3D network of collagen fibers around the cell through the intermediate scale, where the molecules for viscoelastic mesh structures that undergo large deformations caused by the filopodia pushing and pulling on the network, and at the largest scale, model the migration of the cell as a coordinated activity of multiple filopodia, secretions of molecules that change the surrounding mesh and the pulling forces of the cell. This research will help to bring computational cell mechanics into the mainstream by building a 3D cell migration simulation software for researchers, educators, and students. The tools will be available as web tutorial modules and open software for educators, students, and researchers around the world. The project will also form a Forum of software users and research collaborators. This research project will further the goal of the United States to understand the activities of cells that contribute to health and disease of its citizens. This project's computational model will significantly advance the quantitative understanding of 3D cell invasion into the ECM fiber network. It will include cell-ECM interactions at the binding kinetics level and integrate the numerous key mechanisms into the modeling of whole cell-level migration. In vitro microfluidic experiments will be conducted to determine unknown parameters and verify the computational model. The resultant model will be used to predict how cell migration in 3D ECM is influenced by the stiffness and, also, ECM porosity, single fiber diameter, and cross-linker properties. It will be used to predict whether there is an optimal MMP secretion level for 3D cell invasion into ECM; too much secretion of MMP rapidly degrades the ECM fiber network and makes it too soft, while too little secretion of MMP impedes the cell to invade into ECM. A group of cells can communicate with one another through stress and strain propagation in the ECM and create migratory behaviors as a collective event. The emergent behavior of collective cell migration will be predicted using the multi-scale computational model. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.