Modeling tumor cell migration: From microscopic to macroscopic models.
It has been shown experimentally that contact interactions may influence the migration of cancer cells. Previous works have modelized this thanks to stochastic, discrete models (cellular automata) at the cell level. However, for the study of the growth of real-size tumors with several million cells, it is best to use a macroscopic model having the form of a partial differential equation (PDE) for the density of cells. The difficulty is to predict the effect, at the macroscopic scale, of contact interactions that take place at the microscopic scale. To address this, we use a multiscale approach: starting from a very simple, yet experimentally validated, microscopic model of migration with contact interactions, we derive a macroscopic model. We show that a diffusion equation arises, as is often postulated in the field of glioma modeling, but it is nonlinear because of the interactions. We give the explicit dependence of diffusivity on the cell density and on a parameter governing cell-cell interactions. We discuss in detail the conditions of validity of the approximations used in the derivation, and we compare analytic results from our PDE to numerical simulations and to some in vitro experiments. We notice that the family of microscopic models we started from includes as special cases some kinetically constrained models that were introduced for the study of the physics of glasses, supercooled liquids, and jamming systems.
Deroulers
Christophe
C
IMNC, Universités Paris VII-Paris XI-CNRS, UMR 8165, Bâtiment 104, 91406 Orsay Cedex, France. deroulers@imnc.in2p3.fr
Aubert
Marine
M
Badoual
Mathilde
M
Grammaticos
Basil
B
D002450:Cell Communication; D002452:Cell Count; D002465:Cell Movement; D004058:Diffusion; D007700:Kinetics; D008954:Models, Biological; D009369:Neoplasms / Q000473:pathology*; D017711:Nonlinear Dynamics; D015203:Reproducibility of Results; D013269:Stochastic Processes