ArticleNPJ systems biology and applications2017
An individual-based model for collective cancer cell migration explains speed dynamics and phenotype variability in response to growth factors.
Article in NPJ systems biology and applications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 55 citations in OpenAlex.
- Simulation-based inference of cell migration dynamics in complex spatial environments.NPJ systems biology and applications · 2026Article
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- Aquaporin 5 expression regulates MDA-MB-231 spheroid multicellular invasion.American journal of physiology. Cell physiology · 2025Article
- The salt-and-pepper pattern in mouse blastocysts is compatible with signaling beyond the nearest neighbors.iScience · 2023Article
- Spatial cumulant models enable spatially informed treatment strategies and analysis of local interactions in cancer systems.Journal of mathematical biology · 2023Article
- A computational framework for testing hypotheses of the minimal mechanical requirements for cell aggregation using early annual killifish embryogenesis as a model.Frontiers in cell and developmental biology · 2023Article
- QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis.BMC bioinformatics · 2021Article
- Long-term live imaging and multiscale analysis identify heterogeneity and core principles of epithelial organoid morphogenesis.BMC biology · 2021Article
- Cell fate clusters in ICM organoids arise from cell fate heredity and division: a modelling approach.Scientific reports · 2020Article
- Modelling collective cell motion: are on- and off-lattice models equivalent?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020Review
- Multiscale modelling of motility wave propagation in cell migration.Scientific reports · 2020Article
- Computational models of melanoma.Theoretical biology & medical modelling · 2020Review
- Identifying density-dependent interactions in collective cell behaviour.Journal of the Royal Society, Interface · 2020Article
- A Camera Sensors-Based System to Study Drug Effects On In Vitro Motility: The Case of PC-3 Prostate Cancer Cells.Sensors (Basel, Switzerland) · 2020Article
- Modeling heterogeneous tumor growth dynamics and cell-cell interactions at single-cell and cell-population resolution.Current opinion in systems biology · 2019Article
- Mechanistic description of spatial processes using integrative modelling of noise-corrupted imaging data.Journal of the Royal Society, Interface · 2018Article
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Collective cell migration is a common phenotype in epithelial cancers, which is associated with tumor cell metastasis and poor patient survival. However, the interplay between physiologically relevant pro-migratory stimuli and the underlying mechanical cell-cell interactions are poorly understood. We investigated the migratory behavior of different collectively migrating non-small cell lung cancer cell lines in response to motogenic growth factors (e.g. epidermal growth factor) or clinically relevant small compound inhibitors. Depending on the treatment, we observed distinct behaviors in a classical lateral migration assay involving traveling fronts, finger-shapes or the development of cellular bridges. Particle image velocimetry analysis revealed characteristic speed dynamics (evolution of the average speed of all cells in a frame) in all experiments exhibiting initial acceleration and subsequent deceleration of the cell populations. To better understand the mechanical properties of individual cells leading to the observed speed dynamics and the phenotypic differences we developed a mathematical model based on a Langevin approach. This model describes intercellular forces, random motility, and stimulation of active migration by mechanical interaction between cells. Simulations show that the model is able to reproduce the characteristic spatio-temporal speed distributions as well as most migratory phenotypes of the studied cell lines. A specific strength of the proposed model is that it identifies a small set of mechanical features necessary to explain all phenotypic and dynamical features of the migratory response of non-small cell lung cancer cells to chemical stimulation/inhibition. Furthermore, all processes included in the model can be associated with potential molecular components, and are therefore amenable to experimental validation. Thus, the presented mathematical model may help to predict which mechanical aspects involved in non-small cell lung cancer cell migration are affected by the respective therapeutic treatment.
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