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通过高通量数据的生物信息学分析鉴定肝细胞癌中的关键基因和信号通路。

The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput data.

作者信息

Zhang Chaoyang, Peng Li, Zhang Yaqin, Liu Zhaoyang, Li Wenling, Chen Shilian, Li Guancheng

机构信息

Key Laboratory of Carcinogenesis of the Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, People's Republic of China.

Key Laboratory of Carcinogenesis and Cancer Invasion of Chinese Ministry of Education, Xiangya Hospital, Central South University, Changsha, People's Republic of China.

出版信息

Med Oncol. 2017 Jun;34(6):101. doi: 10.1007/s12032-017-0963-9. Epub 2017 Apr 21.

Abstract

Liver cancer is a serious threat to public health and has fairly complicated pathogenesis. Therefore, the identification of key genes and pathways is of much importance for clarifying molecular mechanism of hepatocellular carcinoma (HCC) initiation and progression. HCC-associated gene expression dataset was downloaded from Gene Expression Omnibus database. Statistical software R was used for significance analysis of differentially expressed genes (DEGs) between liver cancer samples and normal samples. Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, based on R software, were applied for the identification of pathways in which DEGs significantly enriched. Cytoscape software was for the construction of protein-protein interaction (PPI) network and module analysis to find the hub genes and key pathways. Finally, weighted correlation network analysis (WGCNA) was conducted to further screen critical gene modules with similar expression pattern and explore their biological significance. Significance analysis identified 1230 DEGs with fold change >2, including 632 significantly down-regulated DEGs and 598 significantly up-regulated DEGs. GO term enrichment analysis suggested that up-regulated DEG significantly enriched in immune response, cell adhesion, cell migration, type I interferon signaling pathway, and cell proliferation, and the down-regulated DEG mainly enriched in response to endoplasmic reticulum stress and endoplasmic reticulum unfolded protein response. KEGG pathway analysis found DEGs significantly enriched in five pathways including complement and coagulation cascades, focal adhesion, ECM-receptor interaction, antigen processing and presentation, and protein processing in endoplasmic reticulum. The top 10 hub genes in HCC were separately GMPS, ACACA, ALB, TGFB1, KRAS, ERBB2, BCL2, EGFR, STAT3, and CD8A, which resulted from PPI network. The top 3 gene interaction modules in PPI network enriched in immune response, organ development, and response to other organism, respectively. WGCNA revealed that the confirmed eight gene modules significantly enriched in monooxygenase and oxidoreductase activity, response to endoplasmic reticulum stress, type I interferon signaling pathway, processing, presentation and binding of peptide antigen, cellular response to cadmium and zinc ion, cell locomotion and differentiation, ribonucleoprotein complex and RNA processing, and immune system process, respectively. In conclusion, we identified some key genes and pathways closely related with HCC initiation and progression by a series of bioinformatics analysis on DEGs. These screened genes and pathways provided for a more detailed molecular mechanism underlying HCC occurrence and progression, holding promise for acting as biomarkers and potential therapeutic targets.

摘要

肝癌对公众健康构成严重威胁,其发病机制相当复杂。因此,鉴定关键基因和通路对于阐明肝细胞癌(HCC)发生和发展的分子机制至关重要。从基因表达综合数据库下载HCC相关基因表达数据集。使用统计软件R对肝癌样本和正常样本之间的差异表达基因(DEG)进行显著性分析。基于R软件进行基因本体论(GO)术语富集分析和京都基因与基因组百科全书(KEGG)通路分析,以鉴定DEG显著富集的通路。使用Cytoscape软件构建蛋白质-蛋白质相互作用(PPI)网络并进行模块分析,以找到枢纽基因和关键通路。最后,进行加权基因共表达网络分析(WGCNA),以进一步筛选具有相似表达模式的关键基因模块并探索其生物学意义。显著性分析鉴定出1230个差异倍数>2的DEG,其中包括632个显著下调的DEG和598个显著上调的DEG。GO术语富集分析表明,上调的DEG显著富集于免疫应答、细胞黏附、细胞迁移、I型干扰素信号通路和细胞增殖,而下调的DEG主要富集于对内质网应激和内质网未折叠蛋白反应的应答。KEGG通路分析发现DEG显著富集于五个通路,包括补体和凝血级联、粘着斑、细胞外基质-受体相互作用、抗原加工和呈递以及内质网中的蛋白质加工。HCC中排名前十的枢纽基因分别为GMPS、ACACA、ALB、TGFB1、KRAS、ERBB2、BCL2、EGFR、STAT3和CD8A,这些基因来自PPI网络。PPI网络中排名前三的基因相互作用模块分别富集于免疫应答、器官发育和对其他生物体的应答。WGCNA显示,确认的八个基因模块分别显著富集于单加氧酶和氧化还原酶活性、对内质网应激的应答和I型干扰素信号通路、肽抗原的加工、呈递和结合、细胞对镉和锌离子的应答、细胞运动和分化以及核糖核蛋白复合体和RNA加工以及免疫系统过程。总之,我们通过对DEG的一系列生物信息学分析,鉴定出了一些与HCC发生和发展密切相关的关键基因和通路。这些筛选出的基因和通路为HCC发生和发展的更详细分子机制提供了依据,有望作为生物标志物和潜在治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f11/5400790/fcba4300af27/12032_2017_963_Fig1_HTML.jpg

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