Systematic analysis identifies three-lncRNA signature as a potentially prognostic biomarker for lung squamous cell carcinoma using bioinformatics strategy
Systematic analysis identifies three-lncRNA signature as a potentially prognostic biomarker for lung squamous cell carcinoma using bioinformatics strategy
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DOI：
10.21037/tlcr.2019.09.13
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发表时间：
2019-10-01
影响因子：
4
通讯作者：
Chen, Qiang
中科院分区：
文献类型：
--
作者：
Hu, Jing;Xu, Lutong;Chen, Qiang
背景：肺鳞状细胞癌（LUSC）是肺癌（LC）第二常见的组织学亚型，迄今为止大多数LUSC患者的预后仍然很差。本研究旨在整合lncRNA、miRNA和mRNA表达数据，以识别竞争性内源RNA（ceRNA）网络中的lncRNA特征，作为LUSC患者潜在的预后生物标志物。方法：从癌症基因组图谱（TCGA）数据库中检索LUSC患者的基因表达数据和临床特征，并使用差异表达基因分析（DEGA）、加权基因共表达网络分析（WGCNA）等生物信息学方法进行综合分析。蛋白质与蛋白质相互作用（PPI）网络分析和ceRNA网络构建。随后，对 ceRNA 网络中差异表达的 lncRNA (DElncRNA) 进行单变量和多变量 Cox 回归分析，以预测 LUSC 患者的总生存期 (OS)。使用受试者工作特征（ROC）分析来评估多元Cox回归模型的性能。采用基因表达谱交互分析（GEPIA）对关键基因进行验证。结果：WGCNA显示包含1,694个DElncRNA、2,654个DEmRNA以及113个DEmiRNA的turquoise模块被确定为最显着的模块（cor=0.99，P
Background: Lung squamous cell carcinoma (LUSC) is the second most common histological subtype of lung cancer (LC), and the prognoses of most LUSC patients are so far still very poor. The present study aimed at integrating lncRNA, miRNA and mRNA expression data to identify lncRNA signature in competitive endogenous RNA (ceRNA) network as a potentially prognostic biomarker for LUSC patients.Methods: Gene expression data and clinical characteristics of LUSC patients were retrieved from The Cancer Genome Atlas (TCGA) database, and were integratedly analyzed using bioinformatics methods including Differentially Expressed Gene Analysis (DEGA), Weighted Gene Co-expression Network Analysis (WGCNA), Protein and Protein Interaction (PPI) network analysis and ceRNA network construction. Subsequently, univariate and multivariate Cox regression analyses of differentially expressed lncRNAs (DElncRNAs) in ceRNA network were performed to predict the overall survival (OS) in LUSC patients. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of multivariate Cox regression model. Gene expression profiling interactive analysis (GEPIA) was used to validate key genes.Results: WGCNA showed that turquoise module including 1,694 DElncRNAs, 2,654 DEmRNAs as well as 113 DEmiRNAs was identified as the most significant modules (cor=0.99, P