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Article Abstract
Aim: To identify the molecular signature of differentially expressed genes (DEGs) associated with PANoptosis in idiopathic pulmonary fibrosis (IPF) and to interpret their immune landscape and cellular distribution characteristics.
Methods And Results: We acquired two IPF datasets from the Gene Expression Omnibus (GEO) database to identify PANoptosis-related DGEs (PAN-DEGs), initially identifying thirty PAN-DEGs. Utilizing machine learning algorithms, we established a five-gene PANoptosis-related signature comprising IGF1, GPX3, GADD45β, SMAD7, and TIMP3, each demonstrating robust diagnostic performance. The expression of these hub genes was subsequently validated using a third GEO dataset and a bleomycin-induced pulmonary fibrosis model. Immune infiltration analysis revealed a close association of these genes with various immune cells, and single-cell RNA sequencing indicated significant expression changes in diverse pulmonary cell types, particularly endothelial cells and fibroblasts.
Conclusion: We identified and validated a PANoptosis-related gene signature in IPF, providing insights into their immune infiltration and potential cellular distribution. Further research is necessary to elucidate the biological functions and mechanisms of these genes in the pathogenesis of IPF.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12034268 | PMC |
| http://dx.doi.org/10.2147/JIR.S505229 | DOI Listing |
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