Xu Baojin, Lv Wu, Li Xiaoyan, Zhang Lina, Lin Jie
Department of General Surgery, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, China.
Department of Pathology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, China.
J Cell Biochem. 2019 Jul;120(7):11616-11623. doi: 10.1002/jcb.28441. Epub 2019 Feb 18.
Hepatocellular carcinoma (HCC) is the most common subtype in liver cancer whose prognosis is affected by malignant progression associated with complex gene interactions. However, there is currently no available biomarkers associated with HCC progression in clinical application. In our study, RNA sequencing expression data of 50 normal samples and 374 tumor samples was analyzed and 9225 differentially expressed genes were screened. Weighted gene coexpression network analysis was then conducted and the blue module we were interested was identified by calculating the correlations between 17 gene modules and clinical features. In the blue module, the calculation of topological overlap was applied to select the top 30 genes and these 30 genes were divided into the green group (11 genes) and the yellow group (19 genes) through searching whether these genes were validated by in vitro or in vivo experiments. The genes in the green group which had never been validated by any experiments were recognized as hub genes. These hub genes were subsequently validated by a new data set GSE76427 and KM Plotter Online Tool, and the results indicated that 10 genes (FBXO43, ARHGEF39, MXD3, VIPR1, DNASE1L3, PHLDA1, CSRNP1, ADR2B, C1RL, and CDC37L1) could act as prognosis and progression biomarkers of HCC. In summary, 10 genes who have never been mentioned in HCC were identified to be associated with malignant progression and prognosis of patients. These findings may contribute to the improvement of the therapeutic decision, risk stratification, and prognosis prediction for HCC patients.
肝细胞癌（HCC）是肝癌中最常见的亚型，其预后受与复杂基因相互作用相关的恶性进展影响。然而，目前在临床应用中尚无与HCC进展相关的生物标志物。在我们的研究中，分析了50个正常样本和374个肿瘤样本的RNA测序表达数据，筛选出9225个差异表达基因。随后进行加权基因共表达网络分析，并通过计算17个基因模块与临床特征之间的相关性，确定了我们感兴趣的蓝色模块。在蓝色模块中，应用拓扑重叠计算来选择前30个基因，并通过搜索这些基因是否在体外或体内实验中得到验证，将这30个基因分为绿色组（11个基因）和黄色组（19个基因）。绿色组中从未在任何实验中得到验证的基因被认定为枢纽基因。这些枢纽基因随后通过新数据集GSE76427和在线工具KM Plotter进行验证，结果表明10个基因（FBXO43、ARHGEF39、MXD3、VIPR1、DNASE1L3、PHLDA1、CSRNP1、ADR2B、C1RL和CDC37L1）可作为HCC的预后和进展生物标志物。总之，鉴定出10个在HCC中从未被提及的基因与患者的恶性进展和预后相关。这些发现可能有助于改善HCC患者的治疗决策、风险分层和预后预测。
