7th Annual Symposium
Physics of Cancer
Leipzig, Germany
October 4-6, 2016
Invited Talk
Novel Methods to Study Cancer Cell Migration and Invasion
Ben Fabry
University of Erlangen-Nuremburg, Department of Physics, Henkestrasse 91, 91052 Erlangen, Germany
Contact:  | Website
To migrate and metastasize in complex environments, tumor cells display a set of elementary activities, such as protrusion and retraction of cellular extensions, adhesion and de-adhesion, generation of tractions, or the chemical degradation of the surrounding matrix. However, an efficient and persistent cell migration on longer time scales requires coordination of these activities in close response to the local environmental conditions. As tumor cells can metastasize to different organs, an adaptation process must occur initially in the primary tumor. Despite numerous recent studies that have attempted to relate the metastatic potential of cancer cells to bio-mechanical measurements, no single cell parameter has emerged that can reliably predict how cancer cells invade or otherwise behave in a 3D matrix.

We therefore utilize a combined approach to evaluate multiple biophysical and functional properties that the cell can “tune” to adapt its migration strategies to the local environment. These properties include adhesion strength, contractility, visco-elastic cell properties, protrusion morphodynamics, and the activity and persistence of migration. We measure these properties in cells grown on 2D matrices with different adhesive ligand functionalization and stiffness, and in 3D matrices where we can modify the pore size, adhesive ligand composition and concentration, and stiffness. Our results demonstrate that not just a single biophysical attribute but rather a complex biophysical signature correlates with the ability of tumor cells to migrate in a complex 3D environment. In my presentation, I will focus on novel methods that we have recently developed to measure these biophysical properties with high accuracy, sensitivity and throughput, including 3-D traction force microscopy in highly non-linear biopolymer networks, Bayesian inference of migration parameter, and histogram-matching for bias-free microfluidic cell mechanical analysis.
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