膀胱癌转录组数据中长链非编码RNA的挖掘和预后分析模型的构建

发布时间：2018-05-23 19:20

  本文选题：长链非编码RNA + 预后分析模型　； 参考：《华东师范大学》2017年硕士论文

【摘要】：膀胱癌是全球第九大常见的恶性肿瘤。膀胱尿路上皮癌(Bladder Urothelial Carcinoma,BLCA)是膀胱癌中最常见的病理类型。大多数膀胱癌病人都是在晚期才被诊断出来,并且5年生存率只有50～60%。因此,挖掘新型膀胱癌生物标记对于膀胱癌病人的早期诊断、治疗以及预后具有十分重要的意义。近年来,大量研究表明长链非编码RNA(long non-coding RNA,lncRNA)在癌症的发生、发展过程中起着十分关键的作用。但现如今基于lncRNA表达水平的,用于预测膀胱癌病人预后生存的分析模型尚未被研究。在本研究中,我们从癌症基因组图谱计划(The Cancer Genome Atlas,TCGA)的数据库中收集了 234个膀胱癌病人的lncRNA的表达数据和临床信息数据,对其进行了综合分析研究。首先把整个数据集随机分为训练集和测试集。然后在训练集中,利用单因素Cox回归分析,挖掘出4个与膀胱癌病人生存显著相关的预后lncRNA。随后利用这4个lncRNA构建了一个可以有效预测膀胱癌病人预后生存的分析模型。利用这个模型可以把训练集中膀胱癌病人显著的分为高风险组和低风险组,并且此预后分析模型的预测能力在测试集和整个数据集中得到了进一步验证。然后利用多因素Cox回归分析和分层生存分析证明了由这4个lncRNA构建的膀胱癌预后分析模型是独立于其它临床变量的,包括病人年龄,病人性别,癌症时期和癌症亚型。最后对这4个预后lncRNA进行了 GO功能富集分析和KEGG通路分析,揭示了它们可能参与了已知与膀胱癌发生相关的生物学过程和通路。综上所述,我们的研究结果表明,由这4个lncRNA构建的膀胱癌预后分析模型可以作为预测膀胱癌病人预后生存的新型生物标记。
[Abstract]:Bladder cancer is the ninth most common malignant tumor in the world. Bladder Urothelial carcinoma (BLCA) is the most common pathological type of bladder cancer. Most bladder cancer patients are diagnosed at an advanced stage, and the 5-year survival rate is only 50 to 60. Therefore, it is very important to excavate new biomarkers for early diagnosis, treatment and prognosis of bladder cancer patients. In recent years, a large number of studies have shown that long chain noncoding RNA(long non-coding RNAs (LNRNAs) play a key role in the carcinogenesis and development of cancer. However, analysis models based on lncRNA expression level to predict survival of bladder cancer patients have not been studied. In this study, we collected 234 bladder cancer patients' lncRNA expression data and clinical information data from the Cancer Genome Atlas TCGA database of the Cancer Genome Map Project. First, the whole data set is randomly divided into training set and test set. Then, in the training concentration, the single factor Cox regression analysis was used to find out four prognostic factors, lncRNA, which were significantly related to the survival of bladder cancer patients. Then, using these four lncRNA, an analytical model was constructed to predict the survival of bladder cancer patients. Using this model, patients with bladder cancer can be significantly divided into high risk group and low risk group, and the predictive ability of this prognostic analysis model has been further verified in the test set and the whole data set. Then multivariate Cox regression analysis and stratified survival analysis showed that the prognostic analysis models of bladder cancer constructed by these four lncRNA were independent of other clinical variables, including patient age, patient sex, cancer stage and cancer subtype. Finally, go functional enrichment analysis and KEGG pathway analysis of the four prognostic lncRNA showed that they may be involved in the known biological processes and pathways related to the development of bladder cancer. In conclusion, our results suggest that the prognostic analysis models constructed by the four lncRNA can be used as a new biomarker to predict the survival of bladder cancer patients.
【学位授予单位】：华东师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R737.14
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本文编号：1926018