Transcriptomic landscape of airway epithelial repair: Contrasting acute and chronic injury in mustard lung and COPD.

BACKGROUND: Airway epithelial cells play a central role in response to environmental injury and may contribute to progression from acute to chronic respiratory disease. This study investigates transcriptomic changes in airway epithelial cells following exposure to cigarette smoke and mustard gas, and compares acute injury models with chronic disease states, including COPD and mustard lung. METHODS: Five airway epithelial microarray datasets were analyzed, including GSE5372 (mechanical injury; 22 samples, days 0, 7, 14), GSE20257 (COPD; 135 samples: COPD-smokers n = 23, healthy-smokers n = 53, healthy non-smokers n = 59), GSE77942 (smoke exposure; 36 samples), and two mustard-related datasets obtained from the original authors. Differential expression analysis was performed in R (limma) after normalization and filtering, using |FC| ≥ 2 and raw p ≤ 0.05. Dataset similarity was assessed by binary scoring and Pearson clustering with pvclust (100 bootstraps, AU ≥ 0.95). Functional enrichment (GO/KEGG) was performed in FunRich with Bonferroni correction, and interaction networks were analyzed using STRING (score ≥ 0.4) and visualized in Gephi. RESULTS: Comparative transcriptomic analysis of five airway epithelial datasets revealed no differentially expressed genes shared across all conditions (|FC| ≥ 2, raw p ≤ 0.05), indicating substantial molecular divergence between acute injury models, epithelial repair processes, and chronic lung disease states. Representative examples included strong upregulation of CYP1B1 in COPD (logFC = 6.10, p = 1.31 × 10-27) and LRRC63 in mechanical injury (logFC = 4.65, p = 1.28 × 10-4), alongside marked downregulation of TIMM17A (logFC = -4.62, p = 1.46 × 10-4) and AURKB (logFC = -2.62, p = 1.83 × 10-16). Similarity scoring and Pearson-based clustering segregated datasets into distinct injury-response groups with strong bootstrap support (pvclust AU ≥ 0.95). Functional enrichment and network analyses identified coordinated regulation of pathways related to extracellular matrix organization, inflammatory signaling, cell adhesion, and epithelial plasticity (EMT/MET), involving mediators such as FN1, SERPINE1, CAV1, and SNAI2. Temporal analysis of mechanical injury further suggested stage-specific remodeling programs, with extracellular matrix-associated genes enriched at day 14, while chronic smoke exposure and COPD displayed distinct extracellular matrix remodeling patterns. Together, these analyses highlight context-specific transcriptional programs underlying airway epithelial remodeling across diverse respiratory injury conditions. CONCLUSION: Airway epithelial injury does not converge on a single transcriptomic signature but instead follows distinct condition-specific programs. Across datasets, EMT/MET-associated gene expression and extracellular matrix remodeling emerged as central processes linking acute injury, epithelial repair, and chronic airway disease. These findings suggest that dysregulated epithelial repair mechanisms may drive persistent airway remodeling in COPD and mustard lung, highlighting EMT-associated pathways as potential targets for future investigation.