线粒体相关基因的综合分析揭示了急性胰腺炎的诊断生物标志物和治疗靶点。

IF 1.9 4区 生物学 Q4 CELL BIOLOGY
Yun Lin, Xing Wan, Xuetao Zhang, Jifeng Liu, Xinyu Lu, Qingping Wen
{"title":"线粒体相关基因的综合分析揭示了急性胰腺炎的诊断生物标志物和治疗靶点。","authors":"Yun Lin,&nbsp;Xing Wan,&nbsp;Xuetao Zhang,&nbsp;Jifeng Liu,&nbsp;Xinyu Lu,&nbsp;Qingping Wen","doi":"10.1049/syb2.70040","DOIUrl":null,"url":null,"abstract":"<p>Mitochondrial dysfunction is increasingly recognised as a critical contributor to acinar cell injury and systemic inflammation in acute pancreatitis (AP). However, comprehensive screening of mitochondrial-related genes (MRGs) and their mechanistic roles in AP progression remains limited. We integrated transcriptomic data with MRGs from the MitoCarta database. A total of 34 differentially expressed MRGs were identified, enabling classification of AP samples into three molecular subtypes with distinct immune cell infiltration patterns and clinical severity. Three hub genes were consistently identified by three machine learning algorithms: LASSO, SVM-RFE, and RF. qRT-PCR validation in cellular models confirmed consistent expression trends. Multi-level functional annotation was conducted through GSVA, CIBERSORT, transcription factor prediction, subcellular localisation and single-cell analyses. Talniflumate and ABT-737 were predicted as potential therapeutic agents using the CMap and validated through molecular docking and 100-ns molecular dynamics simulations. This study establishes a mitochondria-related diagnostic model for AP and identifies candidate therapeutic agents, offering novel insights into the molecular pathogenesis and targeted intervention of AP.</p>","PeriodicalId":50379,"journal":{"name":"IET Systems Biology","volume":"19 1","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12527819/pdf/","citationCount":"0","resultStr":"{\"title\":\"Integrative Analysis of Mitochondrial-Related Genes Reveals Diagnostic Biomarkers and Therapeutic Targets in Acute Pancreatitis\",\"authors\":\"Yun Lin,&nbsp;Xing Wan,&nbsp;Xuetao Zhang,&nbsp;Jifeng Liu,&nbsp;Xinyu Lu,&nbsp;Qingping Wen\",\"doi\":\"10.1049/syb2.70040\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Mitochondrial dysfunction is increasingly recognised as a critical contributor to acinar cell injury and systemic inflammation in acute pancreatitis (AP). However, comprehensive screening of mitochondrial-related genes (MRGs) and their mechanistic roles in AP progression remains limited. We integrated transcriptomic data with MRGs from the MitoCarta database. A total of 34 differentially expressed MRGs were identified, enabling classification of AP samples into three molecular subtypes with distinct immune cell infiltration patterns and clinical severity. Three hub genes were consistently identified by three machine learning algorithms: LASSO, SVM-RFE, and RF. qRT-PCR validation in cellular models confirmed consistent expression trends. Multi-level functional annotation was conducted through GSVA, CIBERSORT, transcription factor prediction, subcellular localisation and single-cell analyses. Talniflumate and ABT-737 were predicted as potential therapeutic agents using the CMap and validated through molecular docking and 100-ns molecular dynamics simulations. This study establishes a mitochondria-related diagnostic model for AP and identifies candidate therapeutic agents, offering novel insights into the molecular pathogenesis and targeted intervention of AP.</p>\",\"PeriodicalId\":50379,\"journal\":{\"name\":\"IET Systems Biology\",\"volume\":\"19 1\",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2025-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12527819/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Systems Biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/syb2.70040\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Systems Biology","FirstCategoryId":"99","ListUrlMain":"https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/syb2.70040","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

线粒体功能障碍越来越被认为是急性胰腺炎(AP)中腺泡细胞损伤和全身性炎症的关键因素。然而,线粒体相关基因(MRGs)及其在AP进展中的机制作用的综合筛选仍然有限。我们将转录组学数据与MitoCarta数据库中的mrg结合起来。共鉴定出34个差异表达的MRGs,从而将AP样本分为具有不同免疫细胞浸润模式和临床严重程度的三种分子亚型。通过LASSO、SVM-RFE和RF三种机器学习算法一致地识别出三个中心基因。细胞模型的qRT-PCR验证证实了一致的表达趋势。通过GSVA、CIBERSORT、转录因子预测、亚细胞定位和单细胞分析进行多级功能注释。利用CMap预测了他尼氟酸酯和ABT-737是潜在的治疗药物,并通过分子对接和100-ns分子动力学模拟进行了验证。本研究建立了线粒体相关的AP诊断模型,并确定了候选治疗药物,为AP的分子发病机制和靶向干预提供了新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Integrative Analysis of Mitochondrial-Related Genes Reveals Diagnostic Biomarkers and Therapeutic Targets in Acute Pancreatitis

Integrative Analysis of Mitochondrial-Related Genes Reveals Diagnostic Biomarkers and Therapeutic Targets in Acute Pancreatitis

Mitochondrial dysfunction is increasingly recognised as a critical contributor to acinar cell injury and systemic inflammation in acute pancreatitis (AP). However, comprehensive screening of mitochondrial-related genes (MRGs) and their mechanistic roles in AP progression remains limited. We integrated transcriptomic data with MRGs from the MitoCarta database. A total of 34 differentially expressed MRGs were identified, enabling classification of AP samples into three molecular subtypes with distinct immune cell infiltration patterns and clinical severity. Three hub genes were consistently identified by three machine learning algorithms: LASSO, SVM-RFE, and RF. qRT-PCR validation in cellular models confirmed consistent expression trends. Multi-level functional annotation was conducted through GSVA, CIBERSORT, transcription factor prediction, subcellular localisation and single-cell analyses. Talniflumate and ABT-737 were predicted as potential therapeutic agents using the CMap and validated through molecular docking and 100-ns molecular dynamics simulations. This study establishes a mitochondria-related diagnostic model for AP and identifies candidate therapeutic agents, offering novel insights into the molecular pathogenesis and targeted intervention of AP.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
IET Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
期刊介绍: IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells. The scope includes the following topics: Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信