基于转录组和单细胞测序数据分析CALU与肝细胞癌患者预后的关系及其作用机制  

Analysis on relationship between CALU and prognosis of hepatocellular carcinoma patients and its mechanism based on transcriptome and single cell sequencing data

作　　者：王小燕 李雪莲 梁斌[1,2] 田文斐 马海林 莫之婧[2,3] WANG Xiaoyan;LI Xuelian;LIANG Bin;TIAN Wenfei;MA Hailin;MO Zhijing(Department of Experimental Teaching Center,School of Intelligent Medicine and Biotechnology,Guilin Medical University,Guilin 541199,China;Key Laboratory of Molecular Medical Engineering,Education Department of Guangxi Zhuang Autonomous Region,Guilin Medical University,Guilin 541199,China;Department of Biochemistry,School of Intelligent Medicine and Biotechnology,Guilin Medical University,Guilin 541199,China)

机构地区：[1]桂林医学院智能医学与生物技术学院实验教学中心,广西桂林541199 [2]桂林医学院广西高校分子医学工程重点实验室,广西桂林541199 [3]桂林医学院智能医学与生物技术学院生物化学教研室,广西桂林541199

出　　处：《吉林大学学报(医学版)》2025年第2期447-459,共13页Journal of Jilin University:Medicine Edition

基　　金：国家自然科学基金项目(32360171);广西壮族自治区科技厅自然科学基金项目联合专项项目(桂林医学院专项)(2025GXNSFHA069010);广西壮族自治区科技厅自然科学基金项目(2024GXNSFAA010362)。

摘　　要：目的:通过生物信息学方法分析人钙腔蛋白(CALU)的表达水平与肝细胞癌(HCC)预后之间的关系,构建HCC预后列线图,并阐明其可能的作用机制。方法:从癌症基因组数据库(TCGA)下载374例HCC组织样本数据,从基因型组织表达数据库(GTEx)下载160例正常组织样本数据。采用配对样本t检验分析在HCC组织样本和配对癌旁正常组织样本中CALU的表达差异,并采用人类蛋白图谱数据库(HPA)进行验证。采用DESeq2包对CALU低和高表达组HCC组织样本进行差异表达基因(DEGs)鉴定,采用pROC包进行受试者工作特征(ROC)曲线分析,采用单因素和多因素Cox回归分析确定CALU在不同临床病理特征HCC患者中的预后价值,采用ggplot2包绘制森林图,采用rms包和survival包构建列线图及校准图,分析CALU用于区分HCC组织与正常组织的诊断价值。采用Kaplan-Meier Plotter数据库数据对CALU与HCC患者预后的关系进行验证。采用GSE14520数据集中216例HCC样本基因转录表达数据对列线图预测准确性进行验证。采用基因本体(GO)功能注释和京都基因与基因组百科全书(KEGG)对DEGs进行功能及通路富集分析,采用基因集富集分析(GSEA)获得DEGs显著富集的基因集。采用GSE149614中10例HCC组织样本和8例癌旁正常组织样本单细胞测序数据对CALU与HCC患者预后关系及其作用机制进行验证。结果:与正常组织比较,HCC组织中CALU mRNA表达水平明显升高(P<0.001),HCC组织中CALU蛋白表达量升高。在HCC样本的CALU低表达组和CALU高表达组共发现928个DEGs,包括784个上调DEGs和144个下调DEGs。ROC分析,CALU用于区分癌和癌旁组织具有较高的诊断价值,ROC曲线下面积(AUC)为0.839。生存分析,CALU高表达组HCC患者生存率明显低于CALU低表达组(P<0.001)。单因素和多因素Cox回归分析确定CALU高表达是HCC患者预后的独立危险因素,并构建预后预测列线图。GSE14520数据集数据证实CALU可用于预测HObjective:To analyze the relationship between the expression level of calumenin(CALU)and the prognosis of hepatocellular carcinoma(HCC)patients by bioinformatics tools and establish the prognostic prediction nomogram,and to clarify its possible mechanism.Methods:The data of 374 HCC tissue samples were downloaded from The Cancer Genome Atlas(TCGA)database and the data of 160 normal tissue samples were down loaded from Genotype-Tissue Expression(GTEx)database.Paired sample t-test was used to analyze the difference in CALU expression between the HCC tissue samples and the paired adjacent normal tissue samples.Human Protein Atlas(HPA)database was used to verify the results.DESeq2 package was used to screen the differentially expressed genes(DEGs)between CALU low expression group and CALU high expression group in the HCC tissue samples.R package pROC was used to analyze the receiver operating characteristic(ROC)curve.Univariate and multivariate Cox regression analyses were used to confirm the prognosis value of CALU in the HCC patients with different clinicopathological characteristics,and ggplot2 package was used to construct the forest plot.R packages rms and survival were used to construct the nomogram and its calibration curve,and the diagnostic value of CALU in distinguishing HCC tissue from normal tissue was analyzed.The data from Kaplan-Meier Plotter database were used to further verify the relationship between CALU and the prognosis of HCC patients.The gene transcriptional expression data of 216 HCC samples obtained from GSE14520 dataset were used to verify the prediction accuracy of the nomogram.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses were used to determine the function and enrichment pathways of the DEGs,and Gene Set Enrichment Analysis(GSEA)was used to obtain the significantly enriched gene sets of the DEGs.Single-cell sequencing data of 10 HCC tissue samples and 8 adjacent normal tissue samples obtained from GSE149614 dataset were used to verify the relationshi

关 键 词：人钙腔蛋白 肝细胞癌 生物信息学 单细胞测序分析 癌症预后 

分 类 号：R735.7[医药卫生—肿瘤]