Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Department of Rheumatology, The First Affiliated Hospital of Nanchang University, Nanchang, China.
Gastroenterol Hepatol. 2020 Dec;43(10):598-606. doi: 10.1016/j.gastrohep.2020.01.016. Epub 2020 Jul 14.
Accumulating evidence has demonstrated that long non-coding RNAs (lncRNAs) play important regulatory roles in the tumorigenesis and progression of gastric cancer (GC). The aim of this study was to construct the prognostic predictive model of lncRNAs signature and improve the survival prediction of GC.
The expression profiling of lncRNAs in large GC cohorts was performed from The Cancer Genome Atlas (TCGA) databases using the lncRNAs-mining approach, including training data set (N=160) and testing data set (N=159). A 13-lncRNAs signature significantly associated with overall survival (OS) in the training data set was selected. The prognostic value of this 13-lncRNAs signature was then confirmed in the test validation set and the entire validation set, respectively.
Based on lncRNA expression profiling of 319 patients with stomach adenocarcinoma (STAD), prognostic 13-lncRNAs signature was found to be significantly associated with the prognosis of GC. Compared to patients with low-risk scores, patients with high-risk scores had a significantly shorter survival time. Moreover, functional enrichment analysis indicated that this 13-lncRNAs signature was potentially involved in multiple biological processes, such as DNA replication and cell cycle signaling pathway.
The prognostic model of the 13-lncRNAs signature established by our study could improve the survival prediction of GC to a greater extent.
越来越多的证据表明,长链非编码 RNA(lncRNA)在胃癌(GC)的发生和发展中发挥着重要的调控作用。本研究旨在构建 lncRNA 特征的预后预测模型,以提高 GC 的生存预测。
采用 lncRNAs-mining 方法从癌症基因组图谱(TCGA)数据库中对大量 GC 队列的 lncRNA 表达谱进行分析,包括训练数据集(N=160)和测试数据集(N=159)。选择与训练数据集中总生存期(OS)显著相关的 13 个 lncRNA 特征。然后分别在测试验证集和整个验证集中验证该 13 个 lncRNA 特征的预后价值。
基于 319 例胃腺癌(STAD)患者的 lncRNA 表达谱,发现预后 13-lncRNA 特征与 GC 的预后显著相关。与低风险评分的患者相比,高风险评分的患者生存时间明显缩短。此外,功能富集分析表明,该 13-lncRNA 特征可能参与多种生物学过程,如 DNA 复制和细胞周期信号通路。
本研究建立的 13-lncRNA 特征预后模型能在更大程度上提高 GC 的生存预测。