Molecular mechanisms and diagnostic applications of immunogenic cell death in idiopathic pulmonary fibrosis

WEI Ding; JIN Faguang; GAO Yongheng

doi:10.13276/j.issn.2097-1656.2025.06.007

Abstract：Objective To identify differentially expressed genes(DEGs)associated with immunogenic cell death(ICD)in patients with idiopathic pulmonary fibrosis(IPF)and explore their potential as diagnostic biomarkers.Methods The GSE150910 dataset was used as the training cohort and 1 885 DEGs were identified from the comparison of 103 IPF patients with 103 normal lung samples using the DESeq2 algorithm.A Venn diagram analysis combined with the GeneCards database(containing 2 149 ICD-related genes)revealed 244 ICD-related DEGs.Subsequently,key differential genes were screened through further machine learning,and a diagnostic model was established and validated.Results Machine learning techniques,including random forest and LASSO regression,identified key genes(NOS2,CDH3,COL17A1,CHRM3,ALPP,COL3A1,and NCR1),which were used to construct the diagnostic model.The model showed high diagnostic sensitivity and specificity,with the highest area under the curve values for CDH3 and CHRM3,and the validation in an independent dataset confirmed the robustness of the model.Additionally,immune infiltration analysis revealed significant differences in immune cell types between IPF patients and the control group(P＜0.05),and correlations between key genes and immune cell infiltration levels were observed.Gene set enrichment analysis further identified significant differences in gene sets associated with IPF diagnosis between the high-risk and low-risk groups.Conclusion Our findings enhance the understanding of the underlying molecular mechanisms of IPF and identify key genes as potential therapeutic targets for this disease.Future studies should focus on translational research to explore the therapeutic applications of these markers and their role in the immunology of the disease.