[1]彭莉蓉,黎村艳,史 杨.肿瘤微环境免疫细胞中差异lncRNA对肝细胞癌预后的预测价值[J].医学信息,2022,35(20):18-23，36.[doi:10.3969/j.issn.1006-1959.2022.20.005]
　PENG Li-rong,LI Cun-yan,SHI Yang.The Predictive Value of Differential lncRNA in Tumor Microenvironment Immune Cells for the Prognosis of Hepatocellular Carcinoma[J].Journal of Medical Information,2022,35(20):18-23，36.[doi:10.3969/j.issn.1006-1959.2022.20.005]
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肿瘤微环境免疫细胞中差异lncRNA对肝细胞癌预后的预测价值()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
35卷
期数:
2022年20期
页码:
18-23，36
栏目:
论著
出版日期:
2022-10-15

文章信息/Info

Title:
The Predictive Value of Differential lncRNA in Tumor Microenvironment Immune Cells for the Prognosis of Hepatocellular Carcinoma
文章编号:
1006-1959（2022）20-0018-07
作者:
彭莉蓉; 黎村艳; 史 杨
（1.湖南师范大学附属第一医院检验科，湖南 长沙 410005；2.人类干细胞国家工程研究中心，湖南 长沙 410000）
Author(s):
PENG Li-rong; LI Cun-yan; SHI Yang
(1.Department of Laboratory Medicine,the First Affiliated Hospital of Hunan Normal University,Changsha 410005,Hunan,China;2.National Engineering and Research Center of Human Stem Cells,Changsha 410000,Hunan,China)
关键词:
肝细胞癌; lncRNA; 肿瘤免疫; 单细胞测序
Keywords:
Hepatocellular carcinoma; lncRNA; Tumor immunity; Single-cell sequencing
分类号:
R735.7
DOI:
10.3969/j.issn.1006-1959.2022.20.005
文献标志码:
A
摘要:
目的 通过生物信息学分析肝癌微环境免疫细胞亚群的组成情况，绘制差异表达lncRNA图谱，并构建风险模型预测肝癌预后。方法 下载并分析GEO数据库中肝细胞癌（HCC）单细胞转录组数据GSE140228，比较肝癌和癌旁免疫细胞亚群的组成及lncRNA表达差异，并绘制差异表达的lncRNA图谱，分析差异lncRNA在免疫细胞中的富集情况；分析TCGA数据库中差异lncRNA与肝癌患者生存预后的关系，单变量Cox回归分析lncRNA的风险比（HR），多变量Cox分析构建风险评分模型，并使用受试者工作特征曲线（ROC）检测风险评分模型预测患者预后的能力。结果 与癌旁组织比较，肝癌组织中C1QA+ Mφ细胞更为富集，而CD160+ NK细胞较少；肝癌组织及癌旁组织的不同免疫细胞中差异表达的lncRNA有51个，绘制不同免疫细胞中差异表达的lncRNA图谱，进一步分析得到肿瘤微环境免疫细胞中特异性表达的lncRNA有42个，其中共同变化的34个lncRNA中有5个与预后相关（P＜0.05），按照设置的条件筛选后构建了由4个lncRNA（LINC00861、LINC01138、THUMPD3-AS1和DANCR）组成的HCC预后模型；生存分析表明，高风险组预后较差；多因素分析及ROC分析表明，风险评分能够作为独立的预后因素（P＜0.05）。结论 HCC患者肿瘤组织的免疫细胞lncRNA表达谱具有特异性，根据特异性表达谱筛选的lncRNA构建的预后模型在评估HCC患者预后方面具有潜在价值。
Abstract:
Objective To analyze the composition of immune cell subsets in the microenvironment of liver cancer by bioinformatics, to map the differentially expressed lncRNAs, and to construct a risk model to predict the prognosis of liver cancer.Methods The single-cell transcriptome data GSE140228 of hepatocellular carcinoma (HCC) in GEO database were downloaded and analyzed. The composition of immune cell subsets and the expression of lncRNA in HCC and adjacent tissues were compared, and the differentially expressed lncRNA profiles were drawn to analyze the enrichment of differentially expressed lncRNA in immune cells. The relationship between differential lncRNA and survival prognosis of HCC patients in TCGA database was analyzed. Univariate Cox regression was used to analyze the hazard ratio (HR) of lncRNA. Multivariate Cox analysis was used to construct a risk scoring model, and the receiver operating characteristic curve (ROC) was used to detect the ability of the risk scoring model to predict the prognosis of patients.Results Compared with adjacent tissues, C1QA+Mφ cells were more abundant in HCC tissues, while CD160+NK cells were less. There were 51 differentially expressed lncRNAs in different immune cells of liver cancer tissues and adjacent tissues. The differentially expressed lncRNA profiles in different immune cells were drawn, and further analysis showed that there were 42 lncRNAs specifically expressed in immune cells of tumor microenvironment. Among them, 5 of the 34 lncRNAs with common changes were related to prognosis (P<0.05). After screening according to the set conditions, a HCC prognosis model consisting of 4 lncRNAs (LINC00861, LINC01138, THUMPD3-AS1 and DANCR) was constructed. Survival analysis showed that the high risk group had poor prognosis. Multivariate analysis and ROC analysis showed that the risk score could be used as an independent prognostic factor ( P<0.05).Conclusion The lncRNA expression profiles of immune cells from tumor tissues of HCC patients are specific. The prognostic model constituted by lncRNAs screened in terms of specific expression profiles is potentially meaningful in evaluating the prognosis of HCC patients.

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更新日期/Last Update: 1900-01-01