Molecular mechanisms of efferocytosis imbalance in the idiopathic pulmonary fibrosis microenvironment: from gene screening to dynamic regulation analysis.

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive pulmonary disease characterized by alveolar structural destruction and fibrosis. In recent years, efferocytosis has been recognized as playing a crucial role in the occurrence and progression of IPF. This study aimed to identify and regulate key efferocytosis-related genes to elucidate their potential roles and clinical significance in IPF.

METHODS

IPF-related datasets (GSE32537) were obtained from the Gene Expression Omnibus (GEO) database. Differential gene expression analysis and weighted gene coexpression network analysis (WGCNA) were applied to identify key genes associated with IPF, intersecting them with efferocytosis-related genes (ERGs) to obtain IPF-ERGs. Protein‒protein interaction (PPI) network construction and enrichment analysis were performed to elucidate the potential functions of these genes in IPF. Seven machine learning algorithms were employed to screen for hub genes with high diagnostic value. The GSE70866 dataset was used for validation, and a nomogram was constructed. Additionally, the CIBERSORT algorithm was used to analyze immune infiltration levels, and transcriptomic validation of the hub genes was conducted in animal experiments.

RESULTS

A total of 21 IPF-ERGs were identified, and machine learning further identified TLR2, ATG7, SPHK1, and ICAM1 as hub genes, which were significantly upregulated in the IPF group. Immune infiltration analysis revealed a significant increase in the infiltration levels of immune cell subsets, including memory B cells, CD8 + T cells, and resting dendritic cells, in the IPF group. Further clinical correlation analysis revealed a strong association between the expression levels of the hub genes and pulmonary function. A nomogram was constructed on the basis of the hub genes and validated for its potential clinical application. Consensus clustering classified IPF patients into two subtypes: C1, which was primarily by metabolic pathway activation, and C2, which was enriched in inflammatory and immune pathways. Transcriptomic analysis of animal experiments also confirmed the upregulation of hub gene expression in IPF.

CONCLUSION

This study identified TLR2, ATG7, SPHK1, and ICAM1 as four key hub genes, revealing their potential diagnostic value and biological functions in IPF. These genes may serve as potential diagnostic biomarkers and therapeutic targets, providing new insights for precision treatment.

CLINICAL TRIAL NUMBER

Not applicable.