Open AccessA coupled 3D-1D multiscale Keller-Segel model of chemotaxis and its application to cancer invasion
Author(s) -
Federica Bubba,
Benôıt Perthame,
Daniele Cerroni,
Pasquale Ciarletta,
Paolo Zunino
Publication year - 2022
Publication title -
discrete and continuous dynamical systems. series s
Language(s) - English
Resource type - Journals
eISSN - 1937-1632
pISSN - 1937-1179
DOI - 10.3934/dcdss.2022044
Subject(s) - multiscale modeling , reduction (mathematics) , computer science , population , matrix (chemical analysis) , space (punctuation) , statistical physics , biological system , algorithm , theoretical computer science , physics , mathematics , materials science , geometry , bioinformatics , biology , demography , sociology , composite material , operating system
Many problems arising in biology display a complex system dynamics at different scales of space and time. For this reason, multiscale mathematical models have attracted a great attention as they enable to take into account phenomena evolving at several characteristic lengths. However, they require advanced model reduction techniques to reduce the computational cost of solving all the scales. In this work, we present a novel version of the Keller-Segel model of chemotaxis on embedded multiscale geometries, i.e. , one-dimensional networks embedded in three-dimensional bulk domains. Applying a model reduction technique based on spatial averaging for geometrical order reduction, we reduce a fully three-dimensional Keller-Segel system to a coupled 3D-1D multiscale model. In the reduced model, the dynamics of the cellular population evolves on a one-dimensional network and its migration is influenced by a three-dimensional chemical signal evolving in the bulk domain. We propose the multiscale version of the Keller-Segel model as a realistic approach to describe the invasion of malignant cancer cells along the collagen fibers that constitute the extracellular matrix. Performing several numerical simulations, we investigate how the invasive abilities of the cells are affected by the topology of the network ( i.e. , matrix fibers orientation and alignment) as well as by three-dimensional spatial effects. We discuss these results in light of biological evidences.