Department of General Surgery, Beijing Youan Hospital, Capital Medical University, 8 Xitoutiao, Youanmenwai, Feng-tai District, Beijing, 100069, China.
Beijing Institute of Hepatology, Beijing YouAn Hospital, Capital Medical University, 8 Xitoutiao, Youanmenwai, Feng-tai District, Beijing, 100069, China.
World J Surg Oncol. 2019 May 1;17(1):77. doi: 10.1186/s12957-019-1616-6.
Hepatocellular carcinoma (HCC) is the major pathological type of primary liver cancer, one of the leading causes of cancer death worldwide. In addition, the long-term survival rates of HCC still remain low. Therefore, we attempted to identify the potential key genes in the occurrence of HCC by comparing the expression profiles of very early HCC tissue samples with that of chronic cirrhotic tissue samples by integrating the bioinformatics analysis in this study.
Gene expression profiles of 19 very early HCC and 19 cirrhotic tissue samples were selected from GSE63898. Differentially expressed genes (DEGs) were also identified by using online tool GEO2R. Furthermore, the GO and KEGG enrichment analysis of the DGEs were conducted on DAVID datasets. Then a protein-protein interaction (PPI) network was constructed and the modules were analyzed based on STRING database and Cytoscape software. The hub genes were screened by applying the cytoHubba plugin and then analyzed with the Kaplan Meier plotter.
A total of 118 DEGs were identified between very early HCC and cirrhotic tissue samples. These DGEs were strongly associated with several biological processes, such as negative regulation of growth and p53 signaling pathway. A PPI network was constructed and top eight hub genes, including CDKN3, CDK1, CCNB1, TOP2A, CCNA2, CCNB2, PRC1, and RRM2, were determined. High expressions of CDK1, CCNB1, TOP2A, CCNA2, PRC1, RRM2, CDKN3, and CCNB2 were associated with poorer overall survivals (OS) in HCC patients.
We had compared the expression profiles between the very early HCC and cirrhotic tissue samples by using bioinformatics analysis tools, which might help us better to understand the molecular mechanism of the initiation of HCC and even to find novel targets for HCC therapy.
肝细胞癌（HCC）是原发性肝癌的主要病理类型，也是全球癌症死亡的主要原因之一。此外，HCC 的长期生存率仍然较低。因此，我们试图通过整合本研究中的生物信息学分析，比较非常早期 HCC 组织样本和慢性肝硬化组织样本的表达谱，来确定 HCC 发生的潜在关键基因。
从 GSE63898 中选择 19 个非常早期 HCC 和 19 个肝硬化组织样本的基因表达谱。使用在线工具 GEO2R 还鉴定了差异表达基因（DEGs）。然后，在 DAVID 数据集上对 DGEs 进行了 GO 和 KEGG 富集分析。然后，根据 STRING 数据库和 Cytoscape 软件构建了蛋白质-蛋白质相互作用（PPI）网络，并对其进行了分析。使用 cytoHubba 插件筛选出枢纽基因，然后通过 Kaplan Meier plotter 进行分析。
在非常早期 HCC 和肝硬化组织样本之间共鉴定出 118 个 DEGs。这些 DGEs 与多个生物学过程密切相关，如生长的负调控和 p53 信号通路。构建了一个 PPI 网络，并确定了前 8 个枢纽基因，包括 CDKN3、CDK1、CCNB1、TOP2A、CCNA2、CCNB2、PRC1 和 RRM2。CDK1、CCNB1、TOP2A、CCNA2、PRC1、RRM2、CDKN3 和 CCNB2 的高表达与 HCC 患者的总体生存率（OS）较差相关。
我们通过使用生物信息学分析工具比较了非常早期 HCC 和肝硬化组织样本之间的表达谱，这可能有助于我们更好地了解 HCC 发生的分子机制，甚至为 HCC 治疗找到新的靶点。
