Kong Xinru, Qi Jixia, Yan Yao, Chen Liwei, Zhao Yali, Fang Zhongju, Fan Junda, Liu Mingbo, Liu Yehai
Clinical Medical College, Weifang Medical University, Weifang, P.R. China.
Hainan Hospital of Chinese PLA General Hospital, Sanya, P.R. China.
J Cell Biochem. 2019 Oct;120(10):17963-17974. doi: 10.1002/jcb.29063. Epub 2019 May 24.
This study aimed to uncover a regulatory network comprised of long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) in laryngeal squamous cell carcinoma (LSCC), to explore its underlying mechanisms and development, and to identify key genetic biomarkers for the prognosis of LSCC.
Here, we compared mRNA, lncRNA, and miRNA expression profiles between 111 LSCC and 12 adjacent normal tissues using RNA sequencing (RNA-Seq) data from the Cancer Genome Atlas (TCGA) database. Based on the interaction information obtained from miRcode, TargetScan, miRTarBase, and miRDB, a lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network was constructed using differentially expressed lncRNAs (DElncRNA), miRNAs (DEmiRNA), and mRNAs (DEmRNA). By assessing the functional enrichment of DEmRNAs in this network, the potential underlying mechanisms were explored. In addition, Kaplan-Meier survival analysis was used to assess genetic biomarkers related to the prognosis of LSCC patients.
Upon comparing LSCC and control tissues, 1640 DElncRNAs, 75 DEmiRNAs, and 3217 DEmRNAs were identified. Based on the prediction between lncRNA-miRNA and miRNA-mRNA relationships, we constructed a ceRNA network comprised of 93 lncRNAs, nine miRNAs, and nine mRNAs. This network predicted that two lncRNAs (AC016773.1 and C00299), two mRNAs (DIO1 and STC2), and two miRNAs (hsa-mir-137 and hsa-mir-210) were significant biomarkers of LSCC prognosis according to thorough topological and survival analyses (P < .05).
Through a ceRNA network analysis, our study identifies new lncRNAs, miRNAs, and mRNAs, which can be used as potential biomarkers of LSCC and as therapeutic targets for treating LSCC, thus laying a foundation for future clinical studies.
本研究旨在揭示喉鳞状细胞癌(LSCC)中由长链非编码RNA(lncRNA)、微小RNA(miRNA)和信使RNA(mRNA)组成的调控网络,探索其潜在机制和发展过程,并确定LSCC预后的关键遗传生物标志物。
在此,我们使用来自癌症基因组图谱(TCGA)数据库的RNA测序(RNA-Seq)数据,比较了111例LSCC组织和12例相邻正常组织之间的mRNA、lncRNA和miRNA表达谱。基于从miRcode、TargetScan、miRTarBase和miRDB获得的相互作用信息,利用差异表达的lncRNA(DElncRNA)、miRNA(DEmiRNA)和mRNA(DEmRNA)构建了lncRNA-miRNA-mRNA竞争性内源RNA(ceRNA)网络。通过评估该网络中DEmRNA的功能富集情况,探索潜在的机制。此外,采用Kaplan-Meier生存分析来评估与LSCC患者预后相关的遗传生物标志物。
比较LSCC组织和对照组织后,鉴定出1640个DElncRNA、75个DEmiRNA和3217个DEmRNA。基于lncRNA-miRNA和miRNA-mRNA关系的预测,我们构建了一个由93个lncRNA、9个miRNA和9个mRNA组成的ceRNA网络。根据全面的拓扑和生存分析(P < 0.05),该网络预测两个lncRNA(AC016773.1和C00299)、两个mRNA(DIO1和STC2)以及两个miRNA(hsa-mir-137和hsa-mir-210)是LSCC预后的重要生物标志物。
通过ceRNA网络分析,我们的研究鉴定出了新的lncRNA、miRNA和mRNA,它们可作为LSCC的潜在生物标志物以及治疗LSCC的靶点,从而为未来的临床研究奠定基础。