Bioinformatic analysis and experimental validation of the potential gene in the airway inflammation of steroid-resistant asthma.

Steroid-resistant asthma is a troublesome clinical problem in public health. The pathogenesis of steroid-resistant asthma is complex and remains to be explored. In our work, the online Gene Expression Omnibus microarray dataset GSE7368 was used to explore differentially expressed genes (DEGs) between steroid-resistant asthma patients and steroid-sensitive asthma patients. Tissue-specific gene expression of DEGs was analyzed using BioGPS. The enrichment analyses were performed using GO, KEGG, and GSEA analysis. The protein-protein interaction network and key gene cluster were constructed using STRING, Cytoscape, MCODE, and Cytohubba. A steroid-resistant neutrophilic asthma mouse model was established using lipopolysaccharide (LPS) and ovalbumin (OVA). An LPS-stimulated J744A.1 macrophage model was prepared to validate the underlying mechanism of the interesting DEG gene using the quantitative reverse transcription-polymerase chain reaction (qRT-PCR). A total of 66 DEGs were identified, most of which were present in the hematologic/immune system. Enrichment analysis displayed that the enriched pathways were the IL-17 signaling pathway, MAPK signal pathway, Toll-like receptor signaling pathway, and so on. DUSP2, as one of the top upregulated DEGs, has not been clearly demonstrated in steroid-resistant asthma. In our study, we observed that the salubrinal administration (DUSP2 inhibitor) reversed neutrophilic airway inflammation and cytokine responses (IL-17A, TNF-α) in a steroid-resistant asthma mouse model. We also found that salubrinal treatment reduced inflammatory cytokines (CXCL10 and IL-1β) in LPS-stimulated J744A.1 macrophages. DUSP2 may be a candidate target for the therapy of steroid-resistant asthma.