A model of cell migration within the extracellular matrix based on a phenotypic switching mechanism.
Cell migration involves different mechanisms in different cell types and tissue environments. Changes in migratory behaviour have been observed experimentally and associated with phenotypic switching in various situations, such as the migration-proliferation dichotomy of glioma cells, the epithelial-mesenchymal transition or the mesenchymal-amoeboid transition of fibrosarcoma cells in the extracellular matrix (ECM). In the present study, we develop a modelling framework to account for changes in migratory behaviour associated with phenotypic switching. We take into account the influence of the ECM on cell motion and more particularly the alignment process along the fibers. We use a mesoscopic description to model two cell populations with different migratory properties. We derive the corresponding continuum (macroscopic) model by appropriate rescaling, which leads to a generic reaction-diffusion system for the two cell phenotypes. We investigate phenotypic adaptation to dense and sparse environments and propose two complementary transition mechanisms. We study these mechanisms by using a combination of linear stability analysis and numerical simulations. Our investigations reveal that when the cell migratory ability is reduced by a crowded environment, a diffusive instability may appear and lead to the formation of aggregates of cells of the same phenotype. Finally, we discuss the importance of the results from a biological perspective.
Chauviere
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A
Center for Information Services and High Performance Computing, Technische Universität Dresden, D-01062 Dresden, Germany. arnaud.chauviere@tu-dresden.de
Preziosi
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L
Byrne
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H
D000818:Animals; D001932:Brain Neoplasms / Q000503:physiopathology; D002450:Cell Communication; D002465:Cell Movement; D003198:Computer Simulation; D058750:Epithelial-Mesenchymal Transition; D005109:Extracellular Matrix / Q000473:pathology / Q000502:physiology*; D005910:Glioma / Q000473:pathology; D008954:Models, Biological; D009716:Numerical Analysis, Computer-Assisted; D010641:Phenotype