乙型肝炎病毒诱导的肝细胞癌关键生物标志物及潜在分子机制的生物信息学分析
Bioinformatics analysis of key biomarkers and potential molecular mechanisms in hepatocellular carcinoma induced by hepatitis B virus.
作者信息
Li Zhe, Xu Jingyong, Cui Hongyuan, Song Jinghai, Chen Jian, Wei Junmin
出版信息
Medicine (Baltimore). 2020 May;99(20):e20302. doi: 10.1097/MD.0000000000020302.
BACKGROUND
Hepatocellular carcinoma (HCC) accounts for up to 90% of all primary hepatic malignancies; it is the sixth most common cancer and the second most common cause of cancer mortality worldwide. Numerous studies have shown that hepatitis B virus and its products, HBV integration, and mutation can induce HCC. However, the molecular mechanisms underpinning the regulation of HCC induced by HBV remain unclear.
METHODS
We downloaded 2 gene expression profiling datasets, of HBV and of HCC induced by HBV, from the gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) between HCC and HBV were identified to explore any predisposing changes in gene expression associated with HCC. DEGs between HCC and adjacent healthy tissues were investigated to identify genes that may play a key role in HCC. Any overlapping genes among these DEGs were included in our bioinformatics analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of overlapping genes were performed using the Metascape online database; the protein-protein interaction (PPI) network was analyzed using the STRING online database; and we obtained the hub genes of the PPI network using Cytoscape software. An overall survival (OS) analysis of hub genes was performed using km-plotter and the gene expression profiling interactive analysis (GEPIA) online database. The expression levels of hub genes were determined using the TCGA and GEPIA databases. Finally, the relationships between hub genes and tumors were analyzed using the comparative toxicogenomics database (CTD).
RESULTS
We identified 113 overlapping genes from the 2 datasets. Using functional and pathway analyses, we found that the overlapping genes were mainly related to the AMPK signaling pathway and cellular responses to cadmium ions. C8A, SPP2, KLKB1, PROZ, C6, FETUB, MBL2, HGFAC, C8B, and ANGPTL3 were identified as hub genes and C8A, SPP2, PROZ, C6, HGFAC, and C8B were found to be significant for survival.
CONCLUSION
The DEGs re-analyzed between HCC and hepatitis B enable a systematic understanding of the molecular mechanisms of HCC reliant on hepatitis B virus.
背景
肝细胞癌（HCC）占所有原发性肝脏恶性肿瘤的比例高达90%；它是全球第六大常见癌症，也是癌症死亡的第二大常见原因。众多研究表明，乙型肝炎病毒及其产物、乙肝病毒整合和突变均可诱发HCC。然而，乙肝病毒诱发HCC的调控分子机制仍不清楚。
方法
我们从基因表达综合数据库（GEO）下载了2个基因表达谱数据集，分别是乙肝病毒及乙肝病毒诱发的HCC的数据集。鉴定了HCC与乙肝病毒之间的差异表达基因（DEG），以探索与HCC相关的基因表达的任何易感性变化。研究了HCC与相邻健康组织之间的DEG，以鉴定可能在HCC中起关键作用的基因。这些DEG中的任何重叠基因都纳入我们的生物信息学分析。使用Metascape在线数据库对重叠基因进行基因本体（GO）和京都基因与基因组百科全书（KEGG）分析；使用STRING在线数据库分析蛋白质-蛋白质相互作用（PPI）网络；并使用Cytoscape软件获得PPI网络的核心基因。使用km-plotter和基因表达谱交互式分析（GEPIA）在线数据库对核心基因进行总生存期（OS）分析。使用TCGA和GEPIA数据库确定核心基因的表达水平。最后，使用比较毒理基因组学数据库（CTD）分析核心基因与肿瘤之间的关系。
结果
我们从这2个数据集中鉴定出113个重叠基因。通过功能和通路分析，我们发现重叠基因主要与AMPK信号通路以及细胞对镉离子的反应有关。C8A、SPP2、KLKB1、PROZ、C6、FETUB、MBL2、HGFAC、C8B和ANGPTL3被鉴定为核心基因，并且发现C8A、SPP2、PROZ、C6、HGFAC和C8B对生存具有显著性意义。
结论
对HCC和乙肝之间重新分析的DEG能够系统地了解依赖乙肝病毒的HCC的分子机制。
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