by Lingfeng Chen, Fengzhu Guo, Chunlin Hong Objective To identify key genes and shared pathogenic pathways associated with acute pancreatitis-associated acute lung injury (AP-ALI), through bioinformatics analysis, and to provide potential molecular targets for the diagnosis and treatment of AP-ALI. Methods The cerulein-induced severe acute pancreatitis (SAP) mouse lung tissue dataset (GSE244335), lipopolysaccharide (LPS)-induced acute lung injury (ALI) mouse lung tissue dataset (GSE216943), and human AP patient peripheral blood dataset (GSE194331) were retrieved from the Gene Expression Omnibus (GEO) database.
Differentially expressed genes (DEGs) were screened. Subsequently, we conducted a series of bioinformatic analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction (PPI) network construction.
The PPI network was constructed and hub genes were screened. Cross-species consistency of key pathways was verified using the human dataset.
Results A total of 469 and 153 DEGs were screened from GSE244335 and GSE216943, respectively, with 94 overlapping common DEGs. GO/KEGG enrichment analyses showed that these common DEGs were mainly enriched in immune-inflammatory responses, chemokine receptor binding, and NF-κB signaling pathways.
PLOS ONE (Medicine) published a clinical update in Research Highlights on 22 May 2026.
The item focuses on Identification of key genes and signaling pathways associated with acute pancreatitis and acute lung injury by bioinformatics analysis.
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