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Modelling the Impact of Phenotypic Heterogeneity on Cell Migration: A Continuum Framework Derived from
Rebecca M Crossley1, Philip K Maini2, Ruth E Baker2
1Mathematical Institute, University of Oxford, Woodstock Road, Oxford, OX2 6GG, United Kingdom. crossley@maths.ox.ac.uk.
Bulletin of Mathematical Biology
|August 8, 2025
Summary
This study introduces a mathematical framework to model collective cell migration, considering diverse cell phenotypes. The model simplifies complex cellular dynamics for better analysis of invasion and therapeutic strategies.
Area of Science:
- Mathematical Biology
- Cell Biology
- Biophysics
Background:
- Collective cell migration is vital in tumor growth, wound healing, and immune responses.
- Migrating cell populations often exhibit diverse phenotypes, complicating modeling.
- Understanding phenotypic heterogeneity is key to addressing diseases involving cell migration.
Purpose of the Study:
- To develop a general mathematical framework for modeling collective cell migration with phenotypic heterogeneity.
- To provide a computationally efficient alternative to individual-based models for large numbers of phenotypes.
- To analyze the impact of phenotypic variation on cell invasion dynamics in various biological contexts.
Main Methods:
- Coarse-graining an individual-based model into a continuum, macroscopic model.
- Representing cell phenotype as a continuous variable.
- Applying the framework to model range expansion, extracellular matrix invasion, and T cell exhaustion.
Main Results:
- The generalized framework effectively captures the influence of cell phenotype on migration dynamics.
- Phenotypic structuring significantly impacts the spatial and temporal dynamics of cell populations.
- Environmental pressures and phenotypic transitions were shown to critically influence migration patterns.
Conclusions:
- The developed framework is a versatile tool for studying phenotypic heterogeneity in collective cell migration.
- This approach offers computational advantages for exploring complex biological scenarios.
- The findings have potential applications in optimizing therapeutic strategies for diseases characterized by cell migration.
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