空军军医大学学报2025，Vol.46Issue(6)：739-745,754,8.DOI:10.13276/j.issn.2097-1656.2025.06.007
免疫原性细胞死亡在特发性肺纤维化中的分子机制和诊断应用
Molecular mechanisms and diagnostic applications of immunogenic cell death in idiopathic pulmonary fibrosis
摘要
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.关键词
特发性肺纤维化/免疫原性细胞死亡/诊断模型/机器学习/关键基因/生信分析Key words
idiopathic pulmonary fibrosis/immunogenic cell death/diagnostic model/machine learning/key genes/bioinformatics analysis分类
临床医学引用本文复制引用
魏丁,金发光,高永恒..免疫原性细胞死亡在特发性肺纤维化中的分子机制和诊断应用[J].空军军医大学学报,2025,46(6):739-745,754,8.基金项目
国家自然科学基金面上项目(82270084) （82270084）
陕西省重点产业链项目(2022ZDLSF01-10) （2022ZDLSF01-10）
