目的：通过构建肝细胞癌（hepatocellular carcinoma，HCC）的竞争性内源RNA(competing endogenous RNAs，ceRNA）调控网络，寻找与HCC发生发展及预后相关的分子。方法：从TCGA数据库下载HCC转录组数据，通过“Perl”语言处理转化得到mRNA、lncRNA和miRNA的表达谱矩阵。通过“Edge R”包提取3种RNA的差异表达基因（differential expression genes，DGEs），其阈值为|log FC|>2.0 且P<0.01。通过数据库比对得到差异lncRNA-差异miRNA、差异miRNA-差异mRNA关系对，导入至Cytoscape 软件构建ceRNA调控网络图。整理3 种DGEs相关的生存数据，通过“Survival”包及Kaplan-Meier Plotter 分析软件进行生存分析，绘制DGEs的生存曲线，分析获取预后相关基因。结果：成功构建HCC的lncRNA相关ceRNA调控网络，通过该网络分析DGEs 间的相互作用和调控关系，获取3 条lncRNA-miRNA-mRNA 调控关系对，其中1 条调控通路（CCDC26-hsa-mir-141-EPHA2）符合ceRNA 理论。预后分析显示，14 个mRNA高表达组患者生存率低于低表达组，可作为HCC不良预后的生物标志物；1 个lncRNA（TSPEAR-AS1）和2 个mRNA（CPEB3 和PROK2）低表达组患者生存率低于高表达组（P<0.05 或P<0.01），可能是HCC的保护性基因。结论：通过HCC lncRNA 相关的ceRNA调控网络筛查到高表达的14 个mRNA可能为HCC不良预后相关分子，低表达的1 个lncRNA和2 个mRNA可能为HCC良好预后相关分子，研究结果为HCC治疗和预后测评提供了参考依据。

Objective: To identify the molecules related to the occurrence, development and prognosis of hepatocellular carcinoma (HCC) by constructing ceRNA regulatory network of HCC. Methods: Data of HCC transcription group were downloaded from TCGA database. We processed the original data into expression matrix of mRNA, lncRNA and miRNA via Perl language. DGEs of RNA and microRNA were extracted and analyzed from the“Edge”package of R language with the threshold of (|log FC|>2.0 and P<0.01).Through the database comparison, the relationship pairs of different lncRNAs-different miRNAs, different miRNAs-different mRNAs were obtained, and then imported them into the Cytoscape software to construct the ceRNA regulatory network diagram. The survival data of three DGEs were collected and analyzed by“survival”package and Kaplan Meier plotter analysis software. The survival curves were drawn and the genes were obtained by survival analysis. Results: The lncRNA related ceRNA regulatory network of HCC was successfully constructed. Three regulatory pairs of lncRNA-miRNA-mRNA were obtained by analyzing the interaction and regulatory relationship between DGEs via ceRNA network. Among them, one regulatory pathway (CCDC26-hsa-mir-141-EPHA2)was in accordance with ceRNA theory. The prognostic analyses showed that the survival rate of patients with high expression of 14 mRNAs was lower than those with low expression, which could be used as biomarkers of adverse prognosis of HCC. The survival rate of patients with low expression of 1 lncRNA (TSPEAR-AS1) and 2 mRNA (CPEB3 and PROK2) was lower than those with high expression, which may be the protective gene of HCC. Conclusions: Through screening of HCC lncRNA related ceRNA regulatory network, 14 mRNAs with high expression may be the relevant molecules related to poor prognosis of HCC, while 1 lncRNAand 2 mRNAs with low expression may be the molecules related to good prognosis of HCC, providing reference for HCC treatment and prognosis evaluation.

国家自然科学基金资助项目（No.81670594）