| 肖金荣,王可,刘颖,李泽武,周玉静,王唤卓,卢静雅,程珊珊,魏晟.基于公共数据库挖掘肝细胞癌预后相关的长链非编码RNA分子标签[J].Chinese journal of Epidemiology,2019,40(7):805-809 |
| 基于公共数据库挖掘肝细胞癌预后相关的长链非编码RNA分子标签 |
| Exploring of a prognostic long non-coding RNA signature of hepatocellular carcinoma by using public database |
| Received:November 08, 2018 |
| DOI：10.3760/cma.j.issn.0254-6450.2019.07.014 |
| KeyWord: 肝细胞肿瘤 分子标签 |
| English Key Word: Hepatocellular carcinoma Molecular signature |
| FundProject:国家自然科学基金（81773520）；湖北省自然科学基金（2017CFB648） |
| Author Name | Affiliation | E-mail | | Xiao Jinrong | Department of Epidemiology and Biostatistics, Key Laboratory of Ministry of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China | | | Wang Ke | Department of Epidemiology and Biostatistics, Key Laboratory of Ministry of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China | | | Liu Ying | Department of Epidemiology and Biostatistics, Key Laboratory of Ministry of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China | | | Li Zewu | Department of Epidemiology and Biostatistics, Key Laboratory of Ministry of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China | | | Zhou Yujing | Department of Epidemiology and Biostatistics, Key Laboratory of Ministry of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China | | | Wang Huanzhuo | Department of Epidemiology and Biostatistics, Key Laboratory of Ministry of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China | | | Lu Jingya | Department of Epidemiology and Biostatistics, Key Laboratory of Ministry of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China | | | Cheng Shanshan | Department of Epidemiology and Biostatistics, Key Laboratory of Ministry of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China | | | Wei Sheng | Department of Epidemiology and Biostatistics, Key Laboratory of Ministry of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China | weisheng@mails.tjmu.edu.cn |
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| Abstract: |
| 目的 通过对癌症和肿瘤基因图谱（TCGA）公共数据库中肝细胞癌病例癌和癌旁组织RNA测序数据的分析，挖掘与肝细胞癌预后相关的长链非编码RNA（lncRNA）分子标签。方法 截至2018年2月，从TCGA数据库中获得377例肝细胞癌病例的癌及癌旁组织RNAseq数据及临床预后信息，将50对癌和癌旁组织的lncRNA表达水平进行差异t检验分析，进而采用LASSO Cox回归分析筛选肝细胞癌预后相关的lncRNA，并构建lncRNA分子标签。将所有病例按分子标签表达水平分为4组（<P25、P25～、P50～、≥P75），采用Cox回归计算P25～、P50～、≥P75组相对于<P25组的预后风险比，进而评估分子标签表达水平对肝细胞癌病例总体生存率的影响。结果 筛选出951个癌和癌旁组织中表达水平有统计学意义差异的lncRNA，通过LASSO Cox回归分析进一步筛选出3个lncRNA（LNCSRLR、MKLN1-AS及ZFPM2-AS1），并构建分子标签。分子标签表达水平≥P75组的死亡风险是<P25组的1.57倍（95% CI：1.06～2.31，P<0.05）。结论 通过对TCGA数据库的挖掘，由LNCSRLR、MKLN1-AS及ZFPM2-AS1构建的lncRNA分子标签表达水平与肝细胞癌病例的预后有关。 |
| English Abstract: |
| Objective To explore an effective long non-coding RNA (lncRNA) signature in predicting the prognosis of hepatocellular carcinoma through the analysis on RNA sequencing data of hepatocellular carcinoma patients and peritumoral tissues in the Cancer Genome Atlas (TCGA) database. Methods The clinical characteristics and RNA sequencing data of 377 hepatocellular carcinoma patients were obtained from TCGA database by the end of February 2018. Then, differentially expressed lncRNAs between 50 pairs of tumor and peritumoral tissues were explored using student's t-test. Next, a lncRNA signature was established through LASSO Cox regression analysis. All the patients were divided into four groups (<P25, P25-, P50-, ≥ P75) based on the cut-off quartiles signature. Finally, compared with the control group (<P25), the hazard ratios (HRs) of three groups (P25-, P50-, ≥ P75) were calculated by using Cox regression. The survival outcomes of patients in the four groups were compared to evaluate the capacity of the lncRNA signature model. Results A total of 951 differentially expressed lncRNAs were identified between tumor and peritumoral tissues. A three-lncRNA signature, including LNCSRLR, MKLN1-AS and ZFPM2-AS1, was established to predict the prognosis of hepatocellular carcinoma patients. The outcome suggested that the death risk of the ≥ P75 group was 1.57 times larger than that of the <P25 group (95%CI:1.06-2.31, P<0.05). Conclusion The three-lncRNA signature, which established by LNCSRLR, MKLN1-AS and ZFPM2-AS1, was significantly associated with the prognosis of hepatocellular carcinoma patients based on TCGA database data. |
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