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本研究探究表皮生长因子受体抑制剂(epidermal growth factor receptor inhibitor, EGFRI)所致皮肤毒性的发生和治疗机制,筛选其特征基因生物标志物,并从分子水平阐明中药复方消疹方的干预机制。首先,从美国国家生物技术信息中心(national center for biotechnology information, NCBI)的基因表达整库(gene expression omnibus, GEO)中纳入9个与EGFRI皮肤毒性相关的转录组数据集,进行Meta分析以筛选差异表达基因(differentially expressed genes, DEGs)。联合最小绝对收缩与选择算子(least absolute shrinkage and selection operator, LASSO)、支持向量机-递归特征消除(support vector machine-recursive feature elimination, SVM-RFE)及随机森林(random forest, RF)三种机器学习(machine learning, ML)算法,从DEGs中鉴定出核心特征基因。随后,通过给小鼠灌胃厄洛替尼建立皮肤毒性模型,设立消疹方预防组和治疗组进行干预。最后,利用转录组测序(RNA sequencing, RNA-seq)、实时定量聚合酶链式反应(real-time quantitative polymerase chain reaction, RT-qPCR)及蛋白质免疫印迹法(western blotting, WB)等技术,验证消疹方的疗效并探索相关治疗机制。Meta分析初步筛选出127个与EGFRI皮肤毒性显著相关的DEGs。通过3种机器学习算法的交集分析,并结合转录组学结果,最终确定VCAN、 VSNL1、CDC20、 NUF2和BIRC5为潜在生物标志物。动物实验表明,消疹方能有效改善厄洛替尼诱导的皮肤损伤。转录组学及后续分子生物学验证表明,消疹方可通过调节炎症反应、细胞周期等相关通路,缓解EGFRI所致皮肤毒性,并且在这一过程中,上述5个生物标志物的表达变化趋势具有较好一致性。本研究成功鉴定出一组可作为EGFRI皮肤毒性潜在生物标志物的特征基因,并揭示了消疹方是通过调控“细胞周期-干细胞轴”和“神经微环境”来发挥预防和治疗作用。该发现为消疹方的临床应用提供了坚实的理论依据,也为利用中医药防治靶向药物副作用提供了新的研究策略。
Abstract：This study investigated the mechanisms underlying the development and treatment of epidermal growth factor receptor inhibitor( EGFRI)-induced skin toxicity, identified characteristic gene biomarkers, and elucidated the molecular mechanisms of intervention by the traditional Chinese medicine Xiaozhen Fang. First, nine transcriptomic datasets related to EGFRI-induced skin toxicity were included from the gene expression omnibus( GEO) database of the national center for biotechnology information( NCBI), and a metaanalysis was performed to screen differentially expressed genes( DEGs). Least absolute shrinkage and selection operator( LASSO), support vector machine-recursive feature elimination( SVM-RFE), and random forest( RF), three machine learning( ML) algorithms, were then applied in combination to identify key characteristic genes from the DEGs. Subsequently, a mouse model of skin toxicity was established by intragastric administration of erlotinib, and Xiaozhen Fang was administered to prevention and treatment groups for intervention. Finally, RNA sequencing( RNA-seq), real-time quantitative polymerase chain reaction( RT-qPCR), and western blotting( WB) were used to verify the efficacy of Xiaozhen Fang and to explore its related therapeutic mechanisms. Meta-analysis initially screened 127 DEGs significantly associated with EGFRI-induced skin toxicity. Through intersection analysis of the three machine learning algorithms, combined with transcriptomic results, VCAN, VSNL1, CDC20, NUF2, and BIRC5 were ultimately identified as potential biomarkers. Animal experiments showed that Xiaozhen Fang effectively improved erlotinib-induced skin injury. Transcriptomic analysis and subsequent molecular biological validation indicated that Xiaozhen Fang could alleviate EGFRI-induced skin toxicity by regulating pathways related to inflammatory responses and the cell cycle, and that, during this process, the expression trends of the above five biomarkers showed good consistency. This study successfully identified a set of characteristic genes that may serve as potential biomarkers for EGFRI-induced skin toxicity. It also revealed that Xiaozhen Fang exerts preventive and therapeutic effects by regulating the “cell cycle-stem cell axis” and the “neural microenvironment”. These findings provide a solid theoretical basis for the clinical application of Xiaozhen Fang and offer a new research strategy for the prevention and treatment of targeted therapy-related adverse effects with traditional Chinese medicine.
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基本信息:
DOI：10.13417/j.gab.045.000841
中图分类号:R285.5
引用信息:
[1]程呈,韩紫彤,罗玲,等.基于机器学习的EGFRI皮肤毒性特征基因及消疹方干预机制研究[J].基因组学与应用生物学,2026,45(04):841-855.DOI:10.13417/j.gab.045.000841.
基金信息:
江苏省重点研发计划社会发展项目(BE2022816); 江苏省中医药科技发展计划重点项目(ZD202321); 江苏省临床诊疗关键技术攻关项目(BF2025621); 南京市医疗机构中药传统制剂备案研究项目(NJCC-ZJ-202345)共同资助
2026-04-27
2026-04-27
2026-04-27