Zhang Huo, Zhu Mingxia, Du Yiping, Zhang Hui, Zhang Qing, Liu Qingxie, Huang Zebo, Zhang Lan, Li Hai, Xu Lei, Zhou Xin, Zhu Wei, Shu Yongqian, Liu Ping
Department of Oncology, First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
Department of Radiation Oncology, The First Affiliated Hospital of Soochow University, Suzhou 215006, China.
J Cancer. 2019 Feb 26;10(6):1550-1559. doi: 10.7150/jca.27823. eCollection 2019.
Recent studies have highlighted the important roles of long non-coding RNAs (lncRNAs) in pancreatic adenocarcinoma (PCa) prognosis. However, most studies explored a limited number of lncRNAs based on small sample size. Systematic and comprehensive analysis of the data from The Cancer Genome Atlas (TCGA) was performed to identify a panel of lncRNA signature for predicting prognosis in PCa. A total of 160 PCa patients with complete clinical data were included in our study. Twelve lncRNAs were identified to be significantly associated with overall survival (OS) in PCa patients using Cox regression analysis. A risk score formula was constructed to assess the prognostic value of the lncRNA signature in PCa. Patients with high risk score had worse OS than those with low risk score. The multivariate Cox regression analyses revealed that the lncRNA signature was an independent prognostic factor. Additionally, the signature might act as an indicator to predict treatment outcome. Functional enrichment analyses showed that the lncRNAs might involve in several molecular pathways closely related with PCa such as DNA replication, pancreatic cancer and regulation of tor signaling. Our study demonstrated a lncRNA signature including 12 lncRNAs with the potential to be served as an independent prognostic biomarker of PCa.
近期研究突显了长链非编码RNA（lncRNAs）在胰腺腺癌（PCa）预后中的重要作用。然而，大多数研究基于小样本量探索了有限数量的lncRNAs。我们对来自癌症基因组图谱（TCGA）的数据进行了系统全面的分析，以确定一组用于预测PCa预后的lncRNA特征。我们的研究纳入了160例具有完整临床数据的PCa患者。使用Cox回归分析确定了12种lncRNAs与PCa患者的总生存期（OS）显著相关。构建了一个风险评分公式来评估lncRNA特征在PCa中的预后价值。高风险评分的患者OS比低风险评分的患者更差。多变量Cox回归分析显示lncRNA特征是一个独立的预后因素。此外，该特征可能作为预测治疗结果的指标。功能富集分析表明，这些lncRNAs可能参与了与PCa密切相关的多种分子途径，如DNA复制、胰腺癌和雷帕霉素靶蛋白信号通路的调控。我们的研究证明了一个包含12种lncRNAs的lncRNA特征，其有可能作为PCa的独立预后生物标志物。
