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Structured models of cell migration incorporating molecular binding processes.

Pia Domschke1, Dumitru Trucu2, Alf Gerisch3

  • 1Fachbereich Mathematik, Technische Universität Darmstadt, Dolivostr. 15, 64293, Darmstadt, Germany. domschke@mathematik.tu-darmstadt.de.

Journal of Mathematical Biology
|April 14, 2017
PubMed
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This study introduces a new framework to model how cells move and signal, crucial for understanding tissue development and diseases like cancer. It details molecular binding to cell membranes alongside cell population dynamics.

Area of Science:

  • Computational Biology
  • Biophysics
  • Systems Biology

Background:

  • Collective cell movement and cell signaling are vital in development and disease.
  • Understanding molecular interactions with cell surfaces is key to exploring these processes.
  • Existing models may not fully capture the spatio-temporal dynamics of cell populations and molecular binding.

Purpose of the Study:

  • To establish a general spatio-temporal-structural framework for modeling molecular binding to cell membranes.
  • To couple this framework with cell population dynamics.
  • To illustrate the framework's utility with examples from cancer invasion.

Main Methods:

  • Development of a general theoretical framework integrating structural, spatial, and temporal aspects.
Keywords:
Cancer invasionCell-surface receptorsSpatio-temporal modelStructured population model

Related Experiment Videos

  • Mathematical modeling of molecular binding to cell-surface receptors.
  • Integration of cell population dynamics within the framework.
  • Application and validation using three distinct cancer invasion scenarios.

    • Main Results:

    • A unified framework is established to describe molecular binding and cell population dynamics simultaneously.
    • The framework allows detailed exploration of molecular interactions within evolving cell populations.
    • Demonstrated applicability to complex biological processes, specifically cancer invasion.

    Conclusions:

    • The developed framework provides a powerful tool for studying collective cell behaviors and molecular signaling.
    • This approach enhances our understanding of biological processes like development and cancer.
    • The model offers insights into the mechanisms underlying pathological scenarios involving cell movement and signaling.