Suppr超能文献

溃疡性结肠炎中细胞铁死亡的分子机制:机器学习、加权基因共表达网络分析和免疫细胞浸润分析的见解

Molecular mechanisms of ferroptosis in ulcerative colitis: insights from machine learning, WGCNA, and immune cell infiltration analysis.

作者信息

Zhai Leilei, Pan Huiyue, Guo Ziyi, Zhou Wei, Ding Qi, Wang Haikun, Chen Qian, Yao Ping

机构信息

The First Department of Gastroenterology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, China.

Department of Nephrology, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China.

出版信息

Front Immunol. 2025 Aug 29;16:1615186. doi: 10.3389/fimmu.2025.1615186. eCollection 2025.

Abstract

BACKGROUND

This study aimed to investigate ferroptosis-related biomarkers and their potential molecular basis in UC.

METHODS

UC datasets (GSE87466 and GSE47908) from the Gene Expression Omnibus database were merged as the training set, and batch effects were removed. Ferroptosis-related differentially expressed genes (DE-FRGs) were selected to construct a diagnostic risk model in UC. Machine learning (lasso regression and SVM-RFE), Weighted Gene Co-expression Network Analysis (WGCNA) and PPI were then used to obtain candidate hub genes. After identifying common DE-FRGs, functional enrichment analysis, GSEA and GSVA functional enrichment analysis and immune cell infiltration were performed to explore the pathogenesis of UC. Besides, the correlation of hub gene expression and ferroptosis signature markers (GPX4 and ACSL4) was validated in external validation (GSE92415) and experiments. Finally, we employed the human intestinal epithelial Caco-2 cell to establish an inflammatory model by treatment with LPS (1 μg/ml) for 24 hours. This model was used to validate the correlation between the expression levels of ferroptosis-related essential genes (ACSL4 and GPX4) and pro-inflammatory cytokines (TNF-α, IL-6, and IL-1β). Furthermore, to confirm ferroptosis involvement, Caco-2 cells were co-treated with RSL3 (a ferroptosis inducer) or Ferrostatin-1 (Fer-1, an inhibitor), followed by measurement of GSH, MDA as an indicator of lipid peroxidation, and cellular iron load. Mitochondrial ultrastructure was assessed via transmission electron microscopy (TEM) to detect ferroptosis-associated morphological changes.

RESULTS

MFN2 and CBS were identified as hub genes after further validation. Functional estimation, gene set enrichment analysis, and immune infiltration signature identification showed notable associations of the hub genes with macrophages, mast cells resting, and follicular helper T cell levels. , we observed that treatment with LPS/RSL3 obviously activated ferroptosis in Caco-2 cells, as indicated by altered expression of key ferroptosis-related genes (down-regulation of GPX4, CBS, and MFN2; up-regulation of ACSL4) and the levels of surrogate ferroptosis markers (elevated MDA and iron levels, along with reduced GSH). In addition, LPS-induced ferroptosis in Caco-2 cells could be reversed by Fer-1.

CONCLUSIONS

MFN2 and CBS may represent potential therapeutic targets and could serve as biomarkers for immune regulation in UC, warranting further investigation.

摘要

背景

本研究旨在探讨溃疡性结肠炎(UC)中与铁死亡相关的生物标志物及其潜在分子基础。

方法

将来自基因表达综合数据库的UC数据集(GSE87466和GSE47908)合并作为训练集,并消除批次效应。选择与铁死亡相关的差异表达基因(DE-FRGs)以构建UC的诊断风险模型。然后使用机器学习(套索回归和支持向量机递归特征消除)、加权基因共表达网络分析(WGCNA)和蛋白质-蛋白质相互作用(PPI)来获得候选枢纽基因。在确定常见的DE-FRGs后,进行功能富集分析、基因集富集分析(GSEA)和基因集变异分析(GSVA)功能富集分析以及免疫细胞浸润分析,以探索UC的发病机制。此外,在外部验证集(GSE92415)和实验中验证了枢纽基因表达与铁死亡特征标志物(GPX4和ACSL4)的相关性。最后,我们用人肠上皮Caco-2细胞通过用1μg/ml脂多糖(LPS)处理24小时建立炎症模型。该模型用于验证铁死亡相关必需基因(ACSL4和GPX4)的表达水平与促炎细胞因子(TNF-α、IL-6和IL-1β)之间的相关性。此外,为了证实铁死亡的参与,将Caco-2细胞与RSL3(一种铁死亡诱导剂)或铁抑素-1(Fer-1,一种抑制剂)共同处理,随后测量谷胱甘肽(GSH)、丙二醛(MDA,作为脂质过氧化的指标)和细胞铁负荷。通过透射电子显微镜(TEM)评估线粒体超微结构,以检测与铁死亡相关的形态学变化。

结果

经过进一步验证,确认MFN2和CBS为枢纽基因。功能评估、基因集富集分析和免疫浸润特征鉴定显示,枢纽基因与巨噬细胞、静息肥大细胞和滤泡辅助性T细胞水平存在显著关联。我们观察到,用LPS/RSL3处理明显激活了Caco-2细胞中的铁死亡,这表现为关键铁死亡相关基因表达的改变(GPX4、CBS和MFN2下调;ACSL4上调)以及替代铁死亡标志物水平的变化(MDA和铁水平升高,同时GSH降低)。此外,Fer-1可逆转LPS诱导的Caco-2细胞铁死亡。

结论

MFN2和CBS可能代表潜在的治疗靶点,可作为UC免疫调节的生物标志物,值得进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8193/12425917/3cdc05eb6bef/fimmu-16-1615186-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验