基于数据挖掘的肝细胞癌肿瘤突变负荷相关性分析  

Correlations analysis between HCC mutation burden and patients,prognosis based on data mining

作　　者：李喋祺 曹亚文 沈粤春[1] 李君[1] Li Rongqi;Cao Yawen;Shen Yuechun;Li Jun(Department of Hepatobiliary Surgery,the First Affiliated Hospital of Guangzhou Medical University,Guangzhou 510120,China)

机构地区：[1]广州医科大学附属第一医院肝胆外科,广州,510120

出　　处：《中华肝胆外科杂志》2020年第1期32-37,共6页Chinese Journal of Hepatobiliary Surgery

基　　金：广州市科技计划(201804010021)。

摘　　要：目的研究肿瘤突变负荷(TMB)与肝细胞癌患者预后的相关性,以及TMB对肝细胞癌基因差异表达和肿瘤组织内浸润性免疫细胞占比的影响。方法从癌症基因组图谱(TCGA)数据库中获取肝细胞癌患者的体细胞变异数据、基因转录表达数据和临床信息。采用R程序语言(3.6.1版本)maftools函数包分析样本的基因突变数据特征。利用VarScan2平台的肝细胞癌患者全外显子测序数据计算每个样本的TMB值,按TMB值大小排序,取中位值将全部样本分为高TMB组和低TMB组。采用Kaplan-Meier法绘制两组患者生存曲线并进行log-rank检验判断肿瘤突变负荷与预后的相关性。采用R语言Limma函数包筛选两组之间的差异表达基因(FDR=0.05并logFC=1),并采用R语言clusterProfiler函数包对差异基因进行基因本体论(GO)富集分析及京都基因与基因组百科全书(KEGG)富集分析(筛选标准均为P<0.05)。然后采用CIBERSORT I具对比分析两组之间浸润性免疫细胞的占比差异。结果从TCGA数据库中共获取了364例肝细胞癌患者的体细胞变异数据、基因转录表达数据和临床信息。其中327例(84%)样本存在突变.OBSCN与FLG的突变有协同相关性(P<0.05),而CTNNB1与AXIN1的突变相斥(P<0.05)o共363例患者纳入到TMB单因素生存分析中,按TMB值大小排序,按中位值2.9474将全部样本分为高TMB组(182例)和低TMB组(181例),TMB对肝细胞癌患者的预后没有明显影响(P>0.05)。高TMB组和低TMB组之间共筛选出差异表达基因198个(上调基因28个,下调基因170个)。GO富集分析中发现差异基因主要富集在细胞外基质组织、细胞外结构组织、细胞外基质、含胶原细胞外基质、细胞外基质结构成分等功能。KEGG富集分析中,差异基因在细胞外基质受体相互作用通路和黏着斑通路上高度富集。两组之间浸润性免疫细胞的占比差异分析,CD4^+记忆性T细胞在低TMB组中浸润程度更高(P<0.05);单核细胞�Objective To study the correlations between tumor mutation burden(TMB)and the prognosis of hepatocellular carcinoma(HCC)patients,and to investigate the effect of TMB on differential expression genes of HCC and the proportion of invasive immune cells in tumor tissues.Methods The somatic variation data,gene transcriptional expression data and clinical information of HCC patients were obtained from the cancer genome adas(TCGA)database.The R program language(version 3.6.1)maftools function package was used to analyze the gene mutation data characteristics of the samples.The TMB value of each sample was calculated using the full-exon sequencing data of patients with hepatocellular carcinoma on the VarScan2 platform,sorted by TMB value,and the median value was used to divide all samples into high TMB and low TMB groups.Kaplan-Meier method was used to draw the survival curves of two groups of patients and log-rank test was performed to determine the correlation between tumor mutation load and prognosis.The Limma function package of R language was used to screen the differentially expressed genes between the two groups(FDR=0.05 and logFC=1),and the clusterProfiler function package of R language was used to perform gene ontology(GO)enrichment analysis of the differential genes and kyoto encyclopedia of genes and genomes(KEGG)enrichment analysis(screening criteria were all P<0.05).Then the CIBERSORT tool was used to compare and analyze the difference in the proportion of invasive immune cells between the two groups.Results A total of 364 patients with HCC from TCGA database were included in the study.Mutations were found in 327(84%)samples,and there was a synergistic correlation between OBSCN and FLG mutations(P<0.05),while mutations in CTNNB1 and AXIN1 are mutually exclusive(P<0.05).A total of 363 patients were included in the TMB survival analysis,sorted by the size of TMB value.All samples were divided into high TMB group(182 cases)and low TMB group(181 cases)with the median value.We found that TMB had no significant ef

关 键 词：癌 肝细胞 肿瘤突变负荷 预后 

分 类 号：R735.7[医药卫生—肿瘤]