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This research aims to identify key genes and shared pathways linked to acute pancreatitis-associated lung injury using bioinformatics techniques.

May 24, 2026Open Access

Identification of key genes and signaling pathways associated with acute pancreatitis and acute lung injury by bioinformatics analysis

Key Points

This research aims to identify key genes and shared pathways linked to acute pancreatitis-associated lung injury using bioinformatics techniques.
Utilized datasets from mouse models of acute pancreatitis and lung injury and human datasets for analysis.
Screened differentially expressed genes and conducted bioinformatic analyses including GO, KEGG, and PPI.
Validated cross-species consistency of key pathways between mouse and human datasets.
Identified 469 DEGs in acute pancreatitis and 153 in acute lung injury, with 94 common DEGs.
GO/KEGG analyses revealed enrichment in immune-inflammatory responses and NF-κB signaling pathways.
Highlighted 10 key hub genes (like IL-1β and CXCL2) that may contribute to AP-ALI mechanisms.

Abstract

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. PPI network analysis identified the top 10 hub genes in mice (IL-1β, CCL3, CXCL2, CXCL10, CCL2, CXCL9, CXCL1, CXCR2, TLR2, TNF). Ten hub genes (S100A9, ARG1, RETN, etc.) were screened from the human AP dataset (GSE194331). Cross-species comparison of mouse lung tissue and human peripheral blood revealed 6 common GO-BP terms related to systemic inflammatory responses, suggesting shared mechanisms between local lung injury and systemic inflammation in AP. Conclusions The identified hub genes (e.g., IL-1β, CXCL2) and the IL-17/NF-κB signaling pathway represent candidate molecular signatures implicated in AP-ALI. These computational findings generate testable hypotheses regarding inflammatory mechanisms, potentially highlighting shared systemic inflammatory processes between mouse lung injury and human peripheral blood. Direct validation in human pulmonary tissue or bronchoalveolar lavage fluid is warranted to confirm their local pathogenic relevance.

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