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Modeling positive regulatory feedbacks in cell-cell interactions.

Zeljko Bajzer1, Stanimir Vuk-Pavlović

  • 1Biomathematics Resource Core, Department of Biochemistry and Molecular Biology, Mayo Clinic Cancer Center, Mayo Clinic College of Medicine, Rochester, Minnesota, USA. bajzer@mayo.edu

Bio Systems
|March 3, 2005
PubMed
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Mathematical models quantify how cell-cell communication influences tissue growth kinetics. This study reveals the finite impact of positive feedback loops in autocrine and paracrine signaling on overall tissue expansion.

Area of Science:

  • Mathematical biology
  • Cellular and tissue kinetics
  • Systems biology

Background:

  • Quantitative prediction of normal and malignant tissue growth kinetics remains challenging due to incomplete understanding of molecular mechanisms.
  • Growth-factor mediated cell-cell communication plays a crucial role in tissue kinetics, but its precise contribution is difficult to ascertain.
  • Existing models often lack the granularity to fully capture the complexities of autocrine and paracrine signaling in tissue growth.

Purpose of the Study:

  • To design and utilize mathematical models for quantifying the contribution of autocrine and paracrine interactions to tissue growth kinetics.
  • To investigate the role of humorally mediated regulatory feedback among cells within phenomenological growth models.
  • To propose a novel perturbation approach for distinguishing between perturbing agent-dependent and independent cell-cell interactions.

Related Experiment Videos

Main Methods:

  • Development of phenomenological mathematical models incorporating humorally mediated regulatory feedback.
  • Application of these models to existing biological data to assess contributions of cell-cell interactions.
  • Introduction of a perturbation approach to segregate different types of cell-cell interactions.

Main Results:

  • The mathematical models successfully quantified the finite contribution of positive feedback in cell-cell interactions to overall tissue growth.
  • Analysis demonstrated the impact of autocrine and paracrine signaling on tissue kinetics.
  • The proposed perturbation approach showed potential for separating specific cell-cell interaction pathways.

Conclusions:

  • Mathematical modeling provides a powerful framework for understanding and quantifying the influence of cell-cell communication on tissue growth.
  • Humoral feedback mechanisms, including autocrine and paracrine signaling, have a quantifiable, albeit finite, impact on tissue kinetics.
  • The developed perturbation method offers a promising strategy for dissecting complex cell-cell interaction networks in various biological contexts, including hormone-dependent tissues.