Construction and Evaluation of a Prognostic Model Based on Efferocytosis-related Genes for Idiopathic Pulmonary Fibrosis

Introduction: Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and often fatal interstitial lung disease with limited treatment options. Impaired efferocytosis, the clearance of apoptotic cells, is implicated in IPF pathogenesis. This study aimed to identify prognostic efferocytosis-related genes (ECRGs) and construct a predictive gene signature for IPF. Methods: Differentially expressed ECRGs (DEECRGs) were identified by intersecting DEGs between IPF and healthy samples with known ECRGs. A risk model was built using univariate Cox and LASSO regression analyses, and its performance was evaluated via Kaplan-Meier and ROC curves. Multivariate Cox analysis, nomogram construction, GSVA, and immune infiltration analysis were conducted. Validation was performed using datasets GSE70866 (training) and GSE10667. Results: A five-gene prognostic signature (CXCR4, ODC1, AXL, DOCK5, MERTK) was established. High-risk patients had significantly poorer survival. The model showed strong predictive accuracy with AUCs >0.78 for 1-3-year survival. GSVA revealed enrichment of pathways like TNFSF11 signaling and ECM-receptor interaction in high- -risk patients. Immune infiltration analysis showed distinct profiles, notably in mast cells and macrophages. Results were consistent in validation cohorts. Discussion: The efferocytosis-related gene signature robustly predicts IPF prognosis and provides insights into underlying immunological and fibrotic mechanisms. Conclusion: This novel gene signature offers a potential tool for risk stratification and personalized treatment planning in IPF patients.