Zhu Xin, Tan Jianyu, Liang Zongjian, Zhou Mi
Department of Urology.
Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Medicine (Baltimore). 2019 Jul;98(30):e16672. doi: 10.1097/MD.0000000000016672.
Long non-coding RNAs (lncRNAs) can act as competing endogenous RNAs (ceRNAs) to exert significant roles in regulating the expression of mRNAs by sequestering and binding miRNAs. To elucidate the functional roles and regulatory mechanism of lncRNAs in papillary renal cell cancer (pRCC), we conducted a comprehensive analysis of ceRNA network and constructed a mRNA signature to predict prognosis of pRCC.We collected mRNAs and lncRNAs expression profiles of 289 pRCC samples and 32 normal renal tissues, and miRNA expression profiles of 292 pRCC samples and 34 normal samples from The Cancer Genome Atlas (TCGA) database. Differential expressions of RNAs were evaluated by the "edgeR" package in R. Functional enrichment analysis of DEmRNA was performed by DAVID 6.8 and KEGG, while PPI network of top 200 DEmRNAs was conducted using the STRING database. The univariate and multivariate Cox regression were conducted to figure out the candidate DEmRNAs with predictive values in prognosis. Receiver operator characteristic (ROC) curve estimation was performed to achieve the area under the curve (AUC) of the ROC curve to judge mRNA-associated prognosic model. A ceRNA network was established relying on the basis of combination of lncRNA-miRNA interactions and miRNA-mRNA interactions.A total of 1928 DEmRNAs, 981 DElncRNAs, and 52 DEmiRNAs were identified at significance level of |log2Fold Change |>2 and adjusted P-value < .01. A 3-mRNA signatures consisting of ERG, RRM2, and EGF was constructed to predict survival in pRCC. Moreover, a pRCC-associated ceRNA network was constructed, with 57 lncRNAs, 11 miRNAs, and 28 mRNAs.Our study illustrated the regulatory mechanism of ceRNA network in papillary renal cancer. The identified mRNA signatures could be used to predict survival of pRCC.
长链非编码RNA（lncRNAs）可作为竞争性内源性RNA（ceRNAs），通过螯合和结合微小RNA（miRNAs）在调节信使RNA（mRNAs）表达中发挥重要作用。为阐明lncRNAs在乳头状肾细胞癌（pRCC）中的功能作用和调控机制，我们对ceRNA网络进行了全面分析，并构建了一个mRNA特征以预测pRCC的预后。我们从癌症基因组图谱（TCGA）数据库收集了289个pRCC样本和32个正常肾组织的mRNAs和lncRNAs表达谱，以及292个pRCC样本和34个正常样本的miRNA表达谱。通过R语言中的“edgeR”软件包评估RNA的差异表达。通过DAVID 6.8和KEGG对差异表达mRNA（DEmRNA）进行功能富集分析，同时使用STRING数据库构建前200个DEmRNA的蛋白质-蛋白质相互作用（PPI）网络。进行单变量和多变量Cox回归以找出在预后具有预测价值的候选DEmRNA。进行受试者工作特征（ROC）曲线估计以获得ROC曲线下面积（AUC），从而判断与mRNA相关的预后模型。基于lncRNA-miRNA相互作用和miRNA-mRNA相互作用的组合建立了一个ceRNA网络。在|log2倍数变化|>2且校正P值<0.01的显著性水平下，共鉴定出1928个DEmRNA、981个差异表达lncRNA（DElncRNAs）和52个差异表达miRNA（DEmiRNAs）。构建了一个由ERG、RRM2和EGF组成的3-mRNA特征以预测pRCC的生存情况。此外，构建了一个与pRCC相关的ceRNA网络, 包含57个lncRNAs、11个miRNAs和28个mRNAs。我们的研究阐明了ceRNA网络在乳头状肾癌中的调控机制。所鉴定的mRNA特征可用于预测pRCC的生存情况。
