Can the AGE/RAGE/ERK signalling pathway and the epithelial-to-mesenchymal transition interact in the pathogenesis of chronic rhinosinusitis with nasal polyps?
Chronic rhinosinusitis with nasal polyps (CRSwNP) is a persistent sinonasal mucosa inflammatory disease with still unclear pathophysiologic mechanisms that imply events of tissue repair and structural remodelling. Several cascades seem to have a considerable role in the onset and progression of mucosa hyperproliferation in nasal polyps including transforming growth factor β/Small mother against decapentaplegic (TGFβ/Smads), mitogenactivated protein kinases (MAPKs), advanced glycosylation end-products (AGEs) together with epithelial-tomesenchymal transition (EMT). Since many inflammatory mediators are reported to play important roles in the development of nasal polyps (NP) disease, this study aimed to analyse the correlation between the AGEs/receptor of advanced glycosylation end-products (RAGE)/extracellular signal-regulated kinase (ERK) signalling pathway and the main markers of EMT to better understand the influence that they exert on the remodelling of nasal mucous membranes in patients affected by CRSwNP vs normal controls. A total of 30 patients were enrolled in this study. Immunohistochemical analysis, using AGE, RAGE, p-ERK, MMP-3, TGF-β1, Smad2/3, Collagen I-III, α-SMA, E-cadherin, IL-6 and Vimentin antibodies, was performed. AGE, RAGE, ERK, p-ERK and MMP3 were also evaluated using western blot analysis. We observed an overexpression of the AGE/RAGE/p-ERK and the main mesenchymal markers of EMT (Vimentin and IL-6) in CRSwNP vs controls whereas the TGF-β/Smad3 pathway did not show any significant differences between the two groups of patients. These observations suggest a complex network of processes in the pathogenesis of NP, and the AGE/RAGE/ERK pathway and EMT might work together in promoting tissue remodelling in the formation of CRSwNP.
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
Copyright (c) 2020 The Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.