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Aberrant cell migration contributes to defective airway epithelial repair in childhood wheeze
Thomas Iosifidis, … , Western Australian Epithelial Research Program (WAERP), Australian Respiratory Epithelium Consortium (AusREC)
Thomas Iosifidis, … , Western Australian Epithelial Research Program (WAERP), Australian Respiratory Epithelium Consortium (AusREC)
Published March 24, 2020
Citation Information: JCI Insight. 2020;5(7):e133125. https://doi.org/10.1172/jci.insight.133125.
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Research Article Cell biology Pulmonology

Aberrant cell migration contributes to defective airway epithelial repair in childhood wheeze

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Abstract

Abnormal wound repair has been observed in the airway epithelium of patients with chronic respiratory diseases, including asthma. Therapies focusing on repairing vulnerable airways, particularly in early life, present a potentially novel treatment strategy. We report defective lower airway epithelial cell repair to strongly associate with common pre–school-aged and school-aged wheezing phenotypes, characterized by aberrant migration patterns and reduced integrin α5β1 expression. Next generation sequencing identified the PI3K/Akt pathway as the top upstream transcriptional regulator of integrin α5β1, where Akt activation enhanced repair and integrin α5β1 expression in primary cultures from children with wheeze. Conversely, inhibition of PI3K/Akt signaling in primary cultures from children without wheeze reduced α5β1 expression and attenuated repair. Importantly, the FDA-approved drug celecoxib — and its non–COX2-inhibiting analogue, dimethyl-celecoxib — stimulated the PI3K/Akt–integrin α5β1 axis and restored airway epithelial repair in cells from children with wheeze. When compared with published clinical data sets, the identified transcriptomic signature was also associated with viral-induced wheeze exacerbations highlighting the clinical potential of such therapy. Collectively, these results identify airway epithelial restitution via targeting the PI3K–integrin α5β1 axis as a potentially novel therapeutic avenue for childhood wheeze and asthma. We propose that the next step in the therapeutic development process should be a proof-of-concept clinical trial, since relevant animal models to test the crucial underlying premise are unavailable.

Authors

Thomas Iosifidis, Erika N. Sutanto, Alysia G. Buckley, Laura Coleman, Erin E. Gill, Amy H. Lee, Kak-Ming Ling, Jessica Hillas, Kevin Looi, Luke W. Garratt, Kelly M. Martinovich, Nicole C. Shaw, Samuel T. Montgomery, Elizabeth Kicic-Starcevich, Yuliya V. Karpievitch, Peter Le Souëf, Ingrid A. Laing, Shyan Vijayasekaran, Francis J. Lannigan, Paul J. Rigby, Robert E.W. Hancock, Darryl A. Knight, Stephen M. Stick, Anthony Kicic, Western Australian Epithelial Research Program (WAERP), Australian Respiratory Epithelium Consortium (AusREC)

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Figure 7

Evaluation of the defective pAEC repair gene signature in published transcriptomic data sets.

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Evaluation of the defective pAEC repair gene signature in published tran...
(A) Weighted gene coexpression network analysis (WGCNA) cluster dendrogram. Hierarchical cluster analysis was conducted to detect gene coexpression clusters with corresponding color assignments using data from 64 children with or without recurrent wheeze. Each color represents a module in the constructed gene coexpression network by WGCNA. (B) WGCNA modules and sample trait heatmap. Using the default parameter settings and genes filtered based on probeset concordance (n = 1737), 5 gene modules were identified to correlate with recurrence of respiratory wheeze. Data are presented with the correlation coefficient (P value), where positive correlations are red, and negative correlations are blue. (C) Weighted gene coexpression network analysis calculation of gene significance (GS) to sample trait of interest, recurrence of wheeze, in each gene module. The blue module had an overrepresented number of genes associating with wheeze recurrence. (D) Minimum network map of blue module genes that strongly associate with wheeze recurrence in the pediatric acute wheeze data set. Genes are highlighted as highly interconnected (pink) or weakly interconnected (purple) according to known protein/protein interactions from published studies (prior knowledge). Size of nodes indicate a larger number of connections.

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