Yuan Zhang, Zhi-Chang Yang, Qian-Hua Zhou, Zhen-Yang Geng, Kai-Jun Huang, Yang Yang, Hao-Xiang Yuan, Pu Shen
{"title":"Lipid metabolism-related genes regulate the immune microenvironment during ex vivo lung perfusion for lung transplants.","authors":"Yuan Zhang, Zhi-Chang Yang, Qian-Hua Zhou, Zhen-Yang Geng, Kai-Jun Huang, Yang Yang, Hao-Xiang Yuan, Pu Shen","doi":"10.21037/jtd-2025-358","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Ex vivo lung perfusion (EVLP) serves as a vital platform for donor lung assessment and repair in transplantation. Although lipid metabolism plays a crucial role in pulmonary homeostasis and undergoes alterations during EVLP, the precise regulatory mechanisms linking metabolic changes to immune modulation remain poorly understood. This study aimed to identify key lipid metabolism-related genes governing immune microenvironment remodeling during EVLP and to validate their diagnostic and therapeutic potential.</p><p><strong>Methods: </strong>We analyzed transcriptomic profiles from human donor lungs before and after EVLP using datasets GSE127057 (discovery cohort) and GSE127055 (validation cohort). A comprehensive analytical framework was implemented, incorporating weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) networks, and three machine learning algorithms including least absolute shrinkage and selection operator (LASSO) regression, Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) to identify key lipid metabolism-related genes. Immune cell infiltration patterns were characterized using established computational methods, with subsequent validation in an EVLP model of C57BL/6J wild-type mice.</p><p><strong>Results: </strong>Analysis of GSE127057 revealed 656 differentially expressed genes (DEGs) post-EVLP. Through integrative bioinformatics approaches, three lipid metabolism-related hub genes (<i>UGCG</i>, <i>SAMD8</i>, <i>MED26</i>) were identified as consistently upregulated. These genes demonstrated significant positive correlations with resting natural killer (NK) cell populations and negative associations with activated NK cells. The diagnostic potential of these biomarkers was confirmed through receiver operating characteristic (ROC) analysis, achieving an area under curve (AUC) of 0.986 in the discovery cohort (GSE127057) and 0.922 in the independent validation cohort (GSE127055). Experimental validation in murine EVLP models recapitulated the significant upregulation of all three hub genes.</p><p><strong>Conclusions: </strong>This study establishes UGCG, SAMD8, and MED26 as central regulators of lipid metabolism during EVLP, with their expression patterns correlating with NK cell functional states. These findings provide mechanistic insights into metabolic-immune interactions during donor lung preservation and identify potential biomarkers for clinical monitoring and therapeutic targeting.</p>","PeriodicalId":17542,"journal":{"name":"Journal of thoracic disease","volume":"17 8","pages":"6045-6065"},"PeriodicalIF":1.9000,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12433055/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of thoracic disease","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/jtd-2025-358","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/8/27 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"RESPIRATORY SYSTEM","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Ex vivo lung perfusion (EVLP) serves as a vital platform for donor lung assessment and repair in transplantation. Although lipid metabolism plays a crucial role in pulmonary homeostasis and undergoes alterations during EVLP, the precise regulatory mechanisms linking metabolic changes to immune modulation remain poorly understood. This study aimed to identify key lipid metabolism-related genes governing immune microenvironment remodeling during EVLP and to validate their diagnostic and therapeutic potential.
Methods: We analyzed transcriptomic profiles from human donor lungs before and after EVLP using datasets GSE127057 (discovery cohort) and GSE127055 (validation cohort). A comprehensive analytical framework was implemented, incorporating weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) networks, and three machine learning algorithms including least absolute shrinkage and selection operator (LASSO) regression, Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) to identify key lipid metabolism-related genes. Immune cell infiltration patterns were characterized using established computational methods, with subsequent validation in an EVLP model of C57BL/6J wild-type mice.
Results: Analysis of GSE127057 revealed 656 differentially expressed genes (DEGs) post-EVLP. Through integrative bioinformatics approaches, three lipid metabolism-related hub genes (UGCG, SAMD8, MED26) were identified as consistently upregulated. These genes demonstrated significant positive correlations with resting natural killer (NK) cell populations and negative associations with activated NK cells. The diagnostic potential of these biomarkers was confirmed through receiver operating characteristic (ROC) analysis, achieving an area under curve (AUC) of 0.986 in the discovery cohort (GSE127057) and 0.922 in the independent validation cohort (GSE127055). Experimental validation in murine EVLP models recapitulated the significant upregulation of all three hub genes.
Conclusions: This study establishes UGCG, SAMD8, and MED26 as central regulators of lipid metabolism during EVLP, with their expression patterns correlating with NK cell functional states. These findings provide mechanistic insights into metabolic-immune interactions during donor lung preservation and identify potential biomarkers for clinical monitoring and therapeutic targeting.
期刊介绍:
The Journal of Thoracic Disease (JTD, J Thorac Dis, pISSN: 2072-1439; eISSN: 2077-6624) was founded in Dec 2009, and indexed in PubMed in Dec 2011 and Science Citation Index SCI in Feb 2013. It is published quarterly (Dec 2009- Dec 2011), bimonthly (Jan 2012 - Dec 2013), monthly (Jan. 2014-) and openly distributed worldwide. JTD received its impact factor of 2.365 for the year 2016. JTD publishes manuscripts that describe new findings and provide current, practical information on the diagnosis and treatment of conditions related to thoracic disease. All the submission and reviewing are conducted electronically so that rapid review is assured.