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

Abstract

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.