4.4 Article

Identifying Mechanisms of Homeostatic Signaling in Fibroblast Differentiation

期刊

BULLETIN OF MATHEMATICAL BIOLOGY
卷 77, 期 8, 页码 1556-1582

出版社

SPRINGER
DOI: 10.1007/s11538-015-0096-2

关键词

TGF-beta 1; PGE(2); Mathematical model

资金

  1. [R01 EB012579]
  2. [R01 HL 110811]
  3. [R01 HL 115618]

向作者/读者索取更多资源

Fibroblasts play an important role in the wound-healing process by generating extracellular matrix (ECM) and undergoing differentiation into myofibroblasts, but these cells can also be involved in pathologic remodeling of tissue. Nascent ECM provides a substrate for re-epithelialization to occur, restoring damaged tissue to a functional state. Dysregulation of this process can result in fibrosis-stiffening and scarring of the tissue. Current treatments cannot halt or reverse this process. The molecular mechanisms underlying fibrotic dysregulation are poorly understood, providing an untapped pool of potential therapeutic targets. Transforming growth factor- ( and adhesion signaling are involved in inducing fibroblast differentiation into -smooth muscle actin () expressing myofibroblasts, while prostaglandin ( has been shown to antagonize signaling; however, the temporal and mechanistic details of this relationship have not yet been fully characterized. We measured , a marker of fibroblast to myofibroblast differentiation, as a function of: receptor-ligand complex internalization, binding, and adhesion signaling and developed a mathematical model capturing the molecular mechanisms of fibroblast differentiation. Using our model, we predict the following: Periodic dosing with temporarily renders fibroblasts incapable of differentiation and refractory to additional stimulation; conversely, periodic dosing with in the presence of induces a reduced signal response that can be further inhibited by the addition of more . Controlled fibroblast differentiation is necessary for effective wound healing; however, excessive accumulation of -expressing myofibroblasts can result in fibrosis. Homeostasis of in our model requires a balance of positive and negative regulatory signals. Sensitivity analysis predicts that availability, availability, and the rate of receptor recycling each highly influence the rates of production. With this model, we are able to demonstrate that regulation of both and signaling levels is essential for preventing fibroblast dysregulation.

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