Recombinant Human Prolidase (rhPEPD) Induces Wound Healing in Experimental Model of Inflammation through Activation of EGFR Signalling in Fibroblasts.
Weronika BaszanowskaMagdalena NiziolIlona OściłowskaJustyna Czyrko-HorczakWojciech MiltykJerzy A PalkaPublished in: Molecules (Basel, Switzerland) (2023)
The potential of recombinant human prolidase (rhPEPD) to induce wound healing in an experimental model of IL-1β-induced inflammation in human fibroblasts was studied. It was found that rhPEPD significantly increased cell proliferation and viability, as well as the expression of the epidermal growth factor receptor (EGFR) and downstream signaling proteins, such as phosphorylated PI3K, AKT, and mTOR, in the studied model. Moreover, rhPEPD upregulated the expression of the β1 integrin receptor and its downstream signaling proteins, such as p-FAK, Grb2 and p-ERK 1/2. The inhibition of EGFR signaling by gefitinib abolished rhPEPD-dependent functions in an experimental model of inflammation. Subsequent studies showed that rhPEPD augmented collagen biosynthesis in IL-1β-treated fibroblasts as well as in a wound healing model (wound closure/scratch test). Although IL-1β treatment of fibroblasts increased cell migration, rhPEPD significantly enhanced this process. This effect was accompanied by an increase in the activity of MMP-2 and MMP-9, suggesting extracellular matrix (ECM) remodeling during the inflammatory process. The data suggest that rhPEPD may play an important role in EGFR-dependent cell growth in an experimental model of inflammation in human fibroblasts, and this knowledge may be useful for further approaches to the treatment of abnormalities of wound healing and other skin diseases.
Keyphrases
- long non coding rna
- wound healing
- epidermal growth factor receptor
- extracellular matrix
- poor prognosis
- cell migration
- cell proliferation
- pi k akt
- recombinant human
- tyrosine kinase
- oxidative stress
- small cell lung cancer
- advanced non small cell lung cancer
- signaling pathway
- endothelial cells
- diabetic rats
- healthcare
- high glucose
- induced pluripotent stem cells
- binding protein
- cell cycle arrest
- risk assessment
- machine learning
- big data
- cell death
- case control
- virtual reality
- soft tissue