基于单细胞转录组学测序的巨噬细胞在肝硬化-肝癌疾病进展中的功能研究  

Functional Analysis of Macrophages in the Progression of Liver Cirrhosis and Liver Cancer

作　　者：任凌萱 卢子琪 齐威[1] 冯志杰[1] REN Lingxuan;LU Ziqi;QI Wei;FENG Zhijie(Department of Gastroenterology,the Second Hospital of Hebei Medical University/Hebei Key Laboratory of Gastroenterology/Hebei Institute of Gastroenterology/Hebei Clinical Research Center for Digestive Diseases,Shijiazhuang 050000,China)

机构地区：[1]河北医科大学第二医院消化内科、河北省消化病重点实验室、河北省消化病研究所河北省消化系统疾病临床医学研究中心,河北省石家庄市050000

出　　处：《中国全科医学》2024年第29期3654-3663,共10页Chinese General Practice

基　　金：河北省自然科学基金资助项目(H2021206314);河北省省级科技计划资助项目(22377703D)。

摘　　要：背景肝脏巨噬细胞在构建宿主防御机制及维持机体内环境稳定中发挥重要作用,也是参与肝脏损伤和修复的重要细胞成分。单核细胞来源的巨噬细胞在基因调控以及具体功能方面与肝脏固有巨噬细胞不尽相同。90%以上的原发性肝癌发生在肝硬化的基础上,巨噬细胞在肝硬化及肝癌疾病进展中的动态变化规律值得探讨。目的解析不同来源肝脏巨噬细胞的转录组学差异,分析巨噬细胞在肝硬化-肝癌疾病进展中的动态变化规律,探索预防肝硬化进展为肝癌的潜在策略。方法本研究通过从GEO数据库获取健康、肝硬化及肝癌组织的单细胞转录组学数据。健康及肝硬化数据来自GEO数据库GSE136103数据集,取自5例健康肝脏以及5例肝硬化肝脏的数据。肝癌数据来自GEO数据库GSE149614数据集,取自10例肝癌患者的数据。通过Seurat软件包分别对肝硬化及肝癌样本的数据进行聚类,鉴定各个细胞类型。将肝硬化样本中的3簇巨噬细胞亚群提取后,分析各个亚群前200个特异性表达基因,应用Metascape在线分析软件对各亚簇特异性表达基因进行功能分析。提取巨噬细胞亚群肝硬化特异性表达基因,通过KEGG功能分析探究巨噬细胞在肝硬化中的功能。将肝硬化以及肝癌单细胞转录组数据通过CellChat软件包进行细胞间相互作用分析,对比肝硬化与肝癌样本巨噬细胞的细胞通讯的差异。将健康对照、肝硬化以及肝癌三者不同来源的巨噬细胞通过Harmony软件包去批次效应,之后导入Monocle软件包进行伪时序分析,构建健康肝脏-肝硬化肝脏-肝癌巨噬细胞的演变轨迹。利用limma软件包找寻在健康肝脏-肝硬化肝脏-肝癌巨噬细胞的演变过程中连续上调以及下调的基因,并进行功能富集分析。结果对所有细胞进行无监督聚类,根据标记基因表达情况,共提取出3个巨噬细胞亚簇(分别为Mac1,Mac2和Mac3)。其中Mac1Background Hepatic macrophages play a vital role in the defense mechanisms and maintaining the internal environment stability of body,and are also major cellular components involved in liver injury and repair.Macrophages derived from hematopoietic stem cells exhibit distinct gene regulation patterns compared to resident macrophages in the liver.More than 90%of primary liver cancer occurs on the basis of cirrhosis,and the dynamic changes of macrophages in the progression of cirrhosis to hepatocellular carcinoma are worth exploring.Objective To analyze the transcriptomic differences of hepatic macrophages originating from diverse sources,analyze the dynamic pattern of macrophage changes in liver cirrhosis and liver cancer progression,and explore potential strategies for preventing the progression of liver cancer.Methods In this study,single-cell transcriptomics data of healthy,cirrhotic and hepatocellular carcinoma(HCC)tissues were obtained from the Gene Expression Omnibus(GEO)database.The healthy and liver fibrosis data were obtained from the GSE136103 dataset of the GEO database,which included samples from five healthy liver tissues and five liver cirrhosis tissues.The HCC data were obtained from the GSE149614 dataset of the GEO database,which consisted of 21 samples from ten HCC patients.Utilizing the Seurat package,a clustering analysis was conducted on the transcriptomic data derived from liver fibrosis and HCC samples to identify distinct cell types.Notably,three distinctive clusters of macrophage subtypes were identified within the fibrosis samples,from which the top 200 marker genes were extracted.Metascape online analysis software was applied to functionally analyze each subcluster-specific expressed gene.Subgroup-specific expressed genes in liver fibrosis were extracted,and the function of macrophages in cirrhosis was explored by KEGG functional analysis.The CellChat software package was utilized to analyze intercellular interactions within liver fibrosis and HCC single-cell transcriptome data,differences

关 键 词：巨噬细胞 肝硬化 肝纤维化 肝肿瘤 单细胞转录组学测序 细胞间相互作用 

分 类 号：R329.24[医药卫生—人体解剖和组织胚胎学]