Li Yan, Jiang-Han Li, Ai-Li Zhang, He Li, Bo Pang, De-Yang Meng, Qian Fu, Li-Juan Du, Yan Su
{"title":"生物标志物CD28和PF4在特发性肺纤维化发病机制中的潜在作用及其对预后的影响:免疫微环境分析","authors":"Li Yan, Jiang-Han Li, Ai-Li Zhang, He Li, Bo Pang, De-Yang Meng, Qian Fu, Li-Juan Du, Yan Su","doi":"10.1186/s41065-025-00464-x","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>This study aims to identify and investigate biomarkers associated with mitochondrial-related genes (MRGs) and programmed cell death-related genes (PCDRGs) that concurrently influence the progression of idiopathic pulmonary fibrosis (IPF) and to explore the underlying biological mechanisms involved.</p><p><strong>Methods: </strong>The GSE28042 and GSE27957 datasets, comprising 1,136 MRGs and 1,548 PCDRGs, were utilized in this study. Differentially expressed genes (DEGs) between the IPF and control groups were initially identified through differential expression analysis. Subsequently, key module genes closely associated with IPF samples were selected using Weighted Gene Co-expression Network Analysis (WGCNA). Intersection genes 1 and 2 were then identified by overlapping DEGs with key module genes, MRGs, and PCDRGs. Candidate genes were further selected through Spearman correlation analysis involving intersection genes 1 and 2. Additionally, biomarkers were identified, and a risk model was developed using Cox regression analysis, proportional hazards (PH) assumption testing, and machine learning methods. Patients with IPF were stratified into high- and low-risk cohorts. Finally, functional enrichment analysis, immune infiltration analysis, regulatory network construction, and reverse transcription quantitative PCR (RT-qPCR) were conducted separately to validate the findings.</p><p><strong>Results: </strong>CD28 and PF4 were identified as biomarkers, and a risk model was established. The distinct risk cohorts exhibited differences in pathways related to hemostasis, prion diseases, and other biological processes. A significant positive correlation with was observed between CD28 and native CD4 T cells, while PF4 showed a negative correlation with activated NK cells. Based on these two biomarkers, 30 miRNAs and 532 lncRNAs were predicted, resulting in the construction of a lncRNA-miRNA-biomarker network. Additionally, 11 chemicals associated with these biomarkers were identified. RT-qPCR analysis further confirmed that expression levels of CD28 and PF4 were significantly reduced in IPF samples (P < 0.05).</p><p><strong>Conclusion: </strong>The results of this study suggested that the biomarkers CD28 and PF4 might play a potential role in the pathogenesis of IPF and might have an impact on the prognosis of the disease. These findings might offer valuable insights for future treatment strategies and prognostic evaluation for patients with IPF.</p>","PeriodicalId":12862,"journal":{"name":"Hereditas","volume":"162 1","pages":"98"},"PeriodicalIF":2.5000,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12144798/pdf/","citationCount":"0","resultStr":"{\"title\":\"The potential role of biomarkers CD28 and PF4 in the pathogenesis of idiopathic pulmonary fibrosis and their impact on the prognosis: an immune microenvironment analysis.\",\"authors\":\"Li Yan, Jiang-Han Li, Ai-Li Zhang, He Li, Bo Pang, De-Yang Meng, Qian Fu, Li-Juan Du, Yan Su\",\"doi\":\"10.1186/s41065-025-00464-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>This study aims to identify and investigate biomarkers associated with mitochondrial-related genes (MRGs) and programmed cell death-related genes (PCDRGs) that concurrently influence the progression of idiopathic pulmonary fibrosis (IPF) and to explore the underlying biological mechanisms involved.</p><p><strong>Methods: </strong>The GSE28042 and GSE27957 datasets, comprising 1,136 MRGs and 1,548 PCDRGs, were utilized in this study. Differentially expressed genes (DEGs) between the IPF and control groups were initially identified through differential expression analysis. Subsequently, key module genes closely associated with IPF samples were selected using Weighted Gene Co-expression Network Analysis (WGCNA). Intersection genes 1 and 2 were then identified by overlapping DEGs with key module genes, MRGs, and PCDRGs. Candidate genes were further selected through Spearman correlation analysis involving intersection genes 1 and 2. Additionally, biomarkers were identified, and a risk model was developed using Cox regression analysis, proportional hazards (PH) assumption testing, and machine learning methods. Patients with IPF were stratified into high- and low-risk cohorts. Finally, functional enrichment analysis, immune infiltration analysis, regulatory network construction, and reverse transcription quantitative PCR (RT-qPCR) were conducted separately to validate the findings.</p><p><strong>Results: </strong>CD28 and PF4 were identified as biomarkers, and a risk model was established. The distinct risk cohorts exhibited differences in pathways related to hemostasis, prion diseases, and other biological processes. A significant positive correlation with was observed between CD28 and native CD4 T cells, while PF4 showed a negative correlation with activated NK cells. Based on these two biomarkers, 30 miRNAs and 532 lncRNAs were predicted, resulting in the construction of a lncRNA-miRNA-biomarker network. Additionally, 11 chemicals associated with these biomarkers were identified. RT-qPCR analysis further confirmed that expression levels of CD28 and PF4 were significantly reduced in IPF samples (P < 0.05).</p><p><strong>Conclusion: </strong>The results of this study suggested that the biomarkers CD28 and PF4 might play a potential role in the pathogenesis of IPF and might have an impact on the prognosis of the disease. These findings might offer valuable insights for future treatment strategies and prognostic evaluation for patients with IPF.</p>\",\"PeriodicalId\":12862,\"journal\":{\"name\":\"Hereditas\",\"volume\":\"162 1\",\"pages\":\"98\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2025-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12144798/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Hereditas\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1186/s41065-025-00464-x\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hereditas","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s41065-025-00464-x","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The potential role of biomarkers CD28 and PF4 in the pathogenesis of idiopathic pulmonary fibrosis and their impact on the prognosis: an immune microenvironment analysis.
Background: This study aims to identify and investigate biomarkers associated with mitochondrial-related genes (MRGs) and programmed cell death-related genes (PCDRGs) that concurrently influence the progression of idiopathic pulmonary fibrosis (IPF) and to explore the underlying biological mechanisms involved.
Methods: The GSE28042 and GSE27957 datasets, comprising 1,136 MRGs and 1,548 PCDRGs, were utilized in this study. Differentially expressed genes (DEGs) between the IPF and control groups were initially identified through differential expression analysis. Subsequently, key module genes closely associated with IPF samples were selected using Weighted Gene Co-expression Network Analysis (WGCNA). Intersection genes 1 and 2 were then identified by overlapping DEGs with key module genes, MRGs, and PCDRGs. Candidate genes were further selected through Spearman correlation analysis involving intersection genes 1 and 2. Additionally, biomarkers were identified, and a risk model was developed using Cox regression analysis, proportional hazards (PH) assumption testing, and machine learning methods. Patients with IPF were stratified into high- and low-risk cohorts. Finally, functional enrichment analysis, immune infiltration analysis, regulatory network construction, and reverse transcription quantitative PCR (RT-qPCR) were conducted separately to validate the findings.
Results: CD28 and PF4 were identified as biomarkers, and a risk model was established. The distinct risk cohorts exhibited differences in pathways related to hemostasis, prion diseases, and other biological processes. A significant positive correlation with was observed between CD28 and native CD4 T cells, while PF4 showed a negative correlation with activated NK cells. Based on these two biomarkers, 30 miRNAs and 532 lncRNAs were predicted, resulting in the construction of a lncRNA-miRNA-biomarker network. Additionally, 11 chemicals associated with these biomarkers were identified. RT-qPCR analysis further confirmed that expression levels of CD28 and PF4 were significantly reduced in IPF samples (P < 0.05).
Conclusion: The results of this study suggested that the biomarkers CD28 and PF4 might play a potential role in the pathogenesis of IPF and might have an impact on the prognosis of the disease. These findings might offer valuable insights for future treatment strategies and prognostic evaluation for patients with IPF.
HereditasBiochemistry, Genetics and Molecular Biology-Genetics
CiteScore
3.80
自引率
3.70%
发文量
0
期刊介绍:
For almost a century, Hereditas has published original cutting-edge research and reviews. As the Official journal of the Mendelian Society of Lund, the journal welcomes research from across all areas of genetics and genomics. Topics of interest include human and medical genetics, animal and plant genetics, microbial genetics, agriculture and bioinformatics.