Genetic expression and mutational profile analysis in different pathologic stages of hepatocellular carcinoma patients.
Genetic expression and mutational profile analysis in different pathologic stages of hepatocellular carcinoma patients.
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肝细胞癌患者不同病理阶段的基因表达及突变谱分析
DOI：
10.1186/s12885-021-08442-y
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发表时间：
2021-07-08
期刊：
影响因子：
3.8
通讯作者：
Yang J
中科院分区：
文献类型：
--
作者：
Gao X;Zhao C;Zhang N;Cui X;Ren Y;Su C;Wu S;Yao Z;Yang J
肝细胞癌（HCC）的临床病理分期（I、II、III-IV期）与患者的临床预后密切相关。本研究的目的是调查基因表达和突变谱在不同的临床病理阶段HCC。方法基于TCGA-LIHC队列，我们利用一系列的分析方法，如统计分析，随机森林，决策树，主成分分析（PCA），以确定差异基因表达和突变谱。几个靶向基因的表达模式也通过分析中国HLivH 060 PG 02肝癌队列，几个GEO数据集，HPA数据库，和二乙基亚硝胺诱导的肝癌小鼠model.ResultsWe确定了一系列的靶向基因的拷贝数变异，这是统计学相关的基因表达。非同义突变主要存在于某些基因中（例如，TTN、TP53、CTNNB1）。然而，没有检测到基因突变频率和病理分期分布之间的关联。随机森林和决策树模型分析数据显示了一组与肝癌不同病理阶段相关的基因，包括GAS 2L 3和SEMA 3F。此外，我们的PCA数据显示了几个与不同病理阶段相关的基因，包括SNRPA和SNRPD 2。与癌旁正常组织相比，我们观察到HLivH 060 PG 02队列HCC组织中GAS 2L 3、SNRPA和SNRPD 2基因的高表达水平（P= 0.002）。我们还在GSE 102079、GSE 76427、GSE 64041、GSE 121248、GSE 84005的数据集中检测到GAS 2L 3、SEMA 3F、SNRPA和SNRPD 2的高表达模式，并使用二乙基亚硝胺诱导的HCC小鼠模型进行qPCR分析。此外，SEMA 3F和SNRPD 2蛋白在HPA数据库的HCC组织中高度染色。这四个基因的高表达水平与HCC cases.ConclusionsOur研究提供的证据，在不同的临床病理阶段的TCGA HCC病例的基因表达和突变谱的生存预后不良。GAS 2L 3、SNRPA、SNRPD 2和SEMA 3F等4个靶基因的鉴定，为深入了解肝癌不同发病机制提供了新的思路。
BackgroundThe clinical pathologic stages (stage I, II, III-IV) of hepatocellular carcinoma (HCC) are closely linked to the clinical prognosis of patients. This study aims at investigating the gene expression and mutational profile in different clinical pathologic stages of HCC.MethodsBased on the TCGA-LIHC cohort, we utilized a series of analytical approaches, such as statistical analysis, random forest, decision tree, principal component analysis (PCA), to identify the differential gene expression and mutational profiles. The expression patterns of several targeting genes were also verified by analyzing the Chinese HLivH060PG02 HCC cohort, several GEO datasets, HPA database, and diethylnitrosamine-induced HCC mouse model.ResultsWe identified a series of targeting genes with copy number variation, which is statistically associated with gene expression. Non-synonymous mutations mainly existed in some genes (e.g.,TTN,TP53,CTNNB1). Nevertheless, no association between gene mutation frequency and pathologic stage distribution was detected. The random forest and decision tree modeling analysis data showed a group of genes related to different HCC pathologic stages, includingGAS2L3andSEMA3F. Additionally, our PCA data indicated several genes associated with different pathologic stages, includingSNRPAandSNRPD2. Compared with adjacent normal tissues, we observed a highly expressed level ofGAS2L3,SNRPA, andSNRPD2(P= 0.002) genes in HCC tissues of our HLivH060PG02 cohort. We also detected the high expression pattern ofGAS2L3,SEMA3F,SNRPA, andSNRPD2in the datasets of GSE102079, GSE76427, GSE64041, GSE121248, GSE84005, and the qPCR assay using diethylnitrosamine-induced HCC mouse model. Moreover, SEMA3F and SNRPD2 protein were highly stained in the HCC tissues of the HPA database. The high expression level of these four genes was associated with the poor survival prognosis of HCC cases.ConclusionsOur study provides evidence regarding the gene expression and mutational profile in different clinical pathologic stages of TCGA HCC cases. Identifying four targeting genes, includingGAS2L3,SNRPA,SNRPD2,andSEMA3F, offers insight into the molecular mechanisms associated with different prognoses of HCC.
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