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Related Concept Videos

Introduction to Fibroblasts01:09

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Rudolph Virchow discovered spindle-shaped cells called fibroblasts in 1858. Inactive fibroblasts, called fibrocytes, become activated by various stimuli, such as growth factors and inflammatory cytokines. Activated fibroblasts play a crucial role in wound healing, inflammation, formation of new blood vessels, and cancer progression. Uncontrolled activation of fibroblasts results in fibrosis, the excess deposition of fibrous tissue, which can lead to scarring and affect normal organs. This...
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A 3D Spheroid Model as a More Physiological System for Cancer-Associated Fibroblasts Differentiation and Invasion In Vitro Studies
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Network Modeling Approach to Predict Myofibroblast Differentiation.

Alison K Schroer1, Larisa M Ryzhova1, W David Merryman1

  • 1Department of Biomedical Engineering, Vanderbilt University, Room 9445D, MRB4 2213 Garland Ave, Nashville, TN 37232, USA.

Cellular and Molecular Bioengineering
|October 19, 2020
PubMed
Summary
This summary is machine-generated.

Fibrotic diseases involve fibroblast to myofibroblast transition. This study reveals that p38 and Src signaling promote alpha smooth muscle actin (αSMA) production, while ERK signaling opposes it, offering insights into fibrotic disease regulation.

Keywords:
Alpha-smooth muscle actin (αSMA)Extracellular signaling-related kinase (ERK)Fibroblast growth factor (FGF)Focal adhesion kinase (FAK)IntegrinSrcTransforming growth factor beta (TGF-β1)p38

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Area of Science:

  • Cellular biology
  • Biochemistry
  • Systems biology

Background:

  • Fibrotic diseases are a significant cause of mortality.
  • Fibroblast differentiation into myofibroblasts, marked by alpha smooth muscle actin (αSMA) expression, is key to fibrosis.
  • Existing knowledge on signaling pathways regulating myofibroblast differentiation is incomplete regarding pathway interactions.

Purpose of the Study:

  • To investigate the crosstalk and regulatory mechanisms of αSMA production during fibroblast differentiation.
  • To develop a computational model of the cell signaling network involved in myofibroblast differentiation.

Main Methods:

  • Developed an Ordinary Differential Equation (ODE)-based computational model of the cell signaling network.
  • Conducted parallel in vitro experiments to validate model predictions.
  • Analyzed the roles of Src, FAK, ERK, and p38 signaling pathways in regulating αSMA expression.

Main Results:

  • Cells lacking Src or FAK showed significantly altered αSMA production compared to wild type.
  • Transforming growth factor beta 1 and fibroblast growth factor signaling differentially modulated ERK and MAPK p38 activity.
  • The model accurately reproduced αSMA expression across 22 experimental conditions and captured transient phosphorylation dynamics of ERK and p38.

Conclusions:

  • αSMA production, a marker of fibroblast differentiation, is promoted by active p38 and Src signaling.
  • ERK signaling acts antagonistically to p38 and Src, opposing αSMA production.
  • This study elucidates a potential regulatory mechanism for fibroblast differentiation in fibrotic diseases.