Yang Yao, Sun Xu, Liu Bin, Zhang Yunshu, Xie Tong, Li Junchen, Liu Jifeng, Zhang Qingkai
Department of General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Institute of Integrative Medicine, Dalian Medical University, Dalian, Liaoning, China.
BMC Pharmacol Toxicol. 2025 May 13;26(1):103. doi: 10.1186/s40360-025-00939-7.
Ulcerative colitis (UC), a chronic relapsing-remitting inflammatory bowel disease. Recent studies have shown that lactylation modifications may be involved in metabolic-immune interactions in intestinal inflammation through epigenetic regulation, but their specific mechanisms in UC still require in-depth validation.
We conducted comparative analyses of transcriptomic profiles, immune landscapes, and functional pathways between UC and normal cohorts. Lactylation-related differentially expressed genes were subjected to enrichment analysis to delineate their mechanistic roles in UC. Through machine learning algorithms, the diagnostic model was established. Further elucidating the mechanisms and regulatory network of the model gene in UC were GSVA, immunological correlation analysis, transcription factor prediction, immunofluorescence, and single-cell analysis. Lastly, the CMap database and molecular docking technology were used to investigate possible treatment drugs for UC.
Twenty-two lactylation-related differentially expressed genes were identified, predominantly enriched in actin cytoskeleton organization and JAK-STAT signaling. By utilizing machine learning methods, 3 model genes (S100A11, IFI16, and HSDL2) were identified. ROC curves from the train and test cohorts illustrate the superior diagnostic value of our model. Further comprehensive bioinformatics analyses revealed that these three core genes may be involved in the development of UC by regulating the metabolic and immune microenvironment. Finally, regorafenib and R-428 were considered as possible agents for the treatment of UC.
This study offers a novel strategy to early UC diagnosis and treatment by thoroughly characterizing lactylation modifications in UC.
溃疡性结肠炎（UC）是一种慢性复发缓解型炎症性肠病。最近的研究表明，乳酰化修饰可能通过表观遗传调控参与肠道炎症中的代谢-免疫相互作用，但其在UC中的具体机制仍需深入验证。
我们对UC队列和正常队列之间的转录组图谱、免疫格局和功能通路进行了比较分析。对与乳酰化相关的差异表达基因进行富集分析，以阐明它们在UC中的作用机制。通过机器学习算法建立诊断模型。通过基因集变异分析（GSVA）、免疫相关性分析、转录因子预测、免疫荧光和单细胞分析进一步阐明模型基因在UC中的机制和调控网络。最后，利用连接图谱（CMap）数据库和分子对接技术研究UC的可能治疗药物。
鉴定出22个与乳酰化相关的差异表达基因，主要富集于肌动蛋白细胞骨架组织和JAK-STAT信号通路。利用机器学习方法，确定了3个模型基因（S100A11、IFI16和HSDL2）。训练队列和测试队列的受试者工作特征（ROC）曲线说明了我们模型具有优越的诊断价值。进一步的综合生物信息学分析表明，这三个核心基因可能通过调节代谢和免疫微环境参与UC的发生发展。最后，瑞戈非尼和R-428被认为是治疗UC的可能药物。
本研究通过全面表征UC中的乳酰化修饰，为UC的早期诊断和治疗提供了一种新策略。
