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微阵列数据分析与丙型肝炎病毒相关性肝细胞癌的初步生物信息学分析。

Microarray Data Mining and Preliminary Bioinformatics Analysis of Hepatitis D Virus-Associated Hepatocellular Carcinoma.

机构信息

Peking University 302 Clinical Medical School, Beijing 100039, China.

Department of Liver Disease of Chinese PLA General Hospital, The Fifth Medical Center of Chinese PLA General Hospital, Beijing 100039, China.

出版信息

Biomed Res Int. 2021 Jan 30;2021:1093702. doi: 10.1155/2021/1093702. eCollection 2021.

Abstract

Several studies have demonstrated that chronic hepatitis delta virus (HDV) infection is associated with a worsening of hepatitis B virus (HBV) infection and increased risk of hepatocellular carcinoma (HCC). However, there is limited data on the role of HDV in the oncogenesis of HCC. This study is aimed at assessing the potential mechanisms of HDV-associated hepatocarcinogenesis, especially to screen and identify key genes and pathways possibly involved in the pathogenesis of HCC. We selected three microarray datasets: GSE55092 contains 39 cancer specimens and 81 paracancer specimens from 11 HBV-associated HCC patients, GSE98383 contains 11 cancer specimens and 24 paracancer specimens from 5 HDV-associated HCC patients, and 371 HCC patients with the RNA-sequencing data combined with their clinical data from the Cancer Genome Atlas (TCGA). Afterwards, 948 differentially expressed genes (DEGs) closely related to HDV-associated HCC were obtained using the R package and filtering with a Venn diagram. We then performed gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to determine the biological processes (BP), cellular component (CC), molecular function (MF), and KEGG signaling pathways most enriched for DEGs. Additionally, we performed Weighted Gene Coexpression Network Analysis (WGCNA) and protein-to-protein interaction (PPI) network construction with 948 DEGs, from which one module was identified by WGCNA and three modules were identified by the PPI network. Subsequently, we validated the expression of 52 hub genes from the PPI network with an independent set of HCC dataset stored in the Gene Expression Profiling Interactive Analysis (GEPIA) database. Finally, seven potential key genes were identified by intersecting with key modules from WGCNA, including 3 reported genes, namely, , , and , and 4 novel genes, namely, , , , and , which are associated with nucleoplasm, cell cycle, DNA replication, and mitotic cell cycle. The and stage of HCC were the independent factors associated with overall survival of HDV-associated HCC. All the related findings of these genes can help gain a better understanding of the role of HDV in the underlying mechanism of HCC carcinogenesis.

摘要

已有多项研究表明,慢性丁型肝炎病毒(HDV)感染与乙型肝炎病毒(HBV)感染的恶化和肝细胞癌(HCC)风险增加有关。然而,关于 HDV 在 HCC 发生中的作用的数据有限。本研究旨在评估 HDV 相关肝癌发生的潜在机制,特别是筛选和鉴定可能参与 HCC 发病机制的关键基因和途径。我们选择了三个微阵列数据集:GSE55092 包含 11 例 HBV 相关 HCC 患者的 39 例癌症标本和 81 例癌旁标本,GSE98383 包含 5 例 HDV 相关 HCC 患者的 11 例癌症标本和 24 例癌旁标本,以及来自癌症基因组图谱(TCGA)的 371 例 HCC 患者的 RNA 测序数据及其临床数据。之后,使用 R 包并通过 Venn 图进行过滤,获得了 948 个与 HDV 相关 HCC 密切相关的差异表达基因(DEG)。然后,我们进行基因本体(GO)注释和京都基因与基因组百科全书(KEGG)途径富集分析,以确定 DEG 最富集的生物过程(BP)、细胞成分(CC)、分子功能(MF)和 KEGG 信号通路。此外,我们使用 948 个 DEG 进行加权基因共表达网络分析(WGCNA)和蛋白质-蛋白质相互作用(PPI)网络构建,通过 WGCNA 确定了一个模块,通过 PPI 网络确定了三个模块。随后,我们使用存储在基因表达谱交互式分析(GEPIA)数据库中的 HCC 数据集的独立数据集验证了 PPI 网络中 52 个枢纽基因的表达。最后,通过与 WGCNA 的关键模块相交,确定了 7 个潜在的关键基因,包括 3 个报道基因,即 、 、 和 ,以及 4 个新基因,即 、 、 、 和 ,它们与核质、细胞周期、DNA 复制和有丝分裂细胞周期有关。HCC 的 和分期是与 HDV 相关 HCC 总生存期相关的独立因素。这些基因的所有相关发现都有助于更好地理解 HDV 在 HCC 癌变潜在机制中的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e6a/7867452/50247867d16e/BMRI2021-1093702.001.jpg

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