Identification of cancer-related gene network in hepatocellular carcinoma by combined bioinformatic approach and experimental validation
Identification of cancer-related gene network in hepatocellular carcinoma by combined bioinformatic approach and experimental validation
复制标题
结合生物信息学方法和实验验证鉴定肝细胞癌中的癌症相关基因网络
DOI：
10.1016/j.prp.2019.04.020
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发表时间：
2019-01-01
影响因子：
2.8
通讯作者：
Zhou, Pinghong
中科院分区：
文献类型：
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作者：
Ni, Wenkai;Zhang, Shiqing;Zhou, Pinghong
HCC（肝细胞癌）是一种高度侵袭性的恶性肿瘤，在世界范围内导致大量死亡。我们选择GEO数据库中GSE27635和GSE28248的基因表达数据集来找出HCC进展和转移过程中的关键基因及其相互作用网络。 GEO2R在线工具用于根据这两个数据集筛选肿瘤和pert-tumor组织之间的差异表达基因（DEG）。鉴定出的差异表达基因可用于进一步分析，如 GO 功能、KEGG 通路、使用注释、可视化和集成发现数据库 (DAVID) 以及相互作用基因检索 (STRING) 的 PPI 网络分析。通过Cytoscape中的MOCDE插件构建了两个模块，并在本次分析中选择了21个基因作为中心基因。 hub基因的表达热图和GO功能分别使用R pheatmap包和Cytoscape中的BiNGO插件进行。重新收集 CDC25 A、CDK1、HMMR、MYBL2、TOP2A 等 6 个中心基因进行生存分析，并使用 Kaplan Meier-plotter 和 GEPIA 网站验证其表达。我们还研究了转移组织和非转移组织之间的 DEG，发现两个基因（NQO1 和 PTHLH）与 HCC 的转移高度相关。使用伤口愈合和跨孔实验进一步验证证实了它们介导细胞迁移和侵袭的能力。总之，我们通过生物信息分析和实验验证获得的结果揭示了与 HCC 进展和转移相关的显性基因及其相互作用网络，并可能作为 HCC 治疗和诊断的潜在靶点。
HCC (hepatocellular carcinoma) is a highly aggressive malignancy that cause a mass of deaths world widely. We chose gene expression datasets of GSE27635 and GSE28248 from GEO database to find out key genes and their interaction network during the progression and metastasis of HCC. GEO2R online tool was used to screen differentially expressed genes (DEGs) between tumor and pert-tumor tissues based on these two datasets. The identified differentially expressed genes were prepared for further analysis such as GO function, KEGG pathway, PPI network analysis using Database for Annotation, Visualization and Integrated Discovery (DAVID) and Retrieval of Interacting Genes (STRING). Two modules were constructed by MOCDE plugin in Cytoscape and 21 genes were selected as hub genes during this analysis. The expression heatmap and GO function of hub genes were performed using R pheatmap package and BiNGO plugin in Cytoscape respectively. Six hub genes including CDC25 A, CDK1, HMMR, MYBL2, TOP2A were recollected for survival analysis and their expression was validated using Kaplan Meier-plotter and GEPIA website. We also investigated the DEGs between metastasis and non-metastasis tissues and two genes (NQO1 and PTHLH) are highly associated with the metastasis in HCC. Further verification using woundhealing and transwell assay confirmed their ability to mediate cell migration and invasion. In summary, our results obtained by bioinformatic analysis and experimental validation revealed the dominant genes and their interaction networks that are associated with the progression and metastasis of HCC and might serve as potential targets for HCC therapy and diagnosis.