Yang Biao, Dai Jun-Xi, Pan Yuan-Bo, Ma Yan-Bin, Chu Sheng-Hua
Department of Neurosurgery, Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 201999, P.R. China.
Oncol Lett. 2019 Dec;18(6):6079-6089. doi: 10.3892/ol.2019.10941. Epub 2019 Sep 30.
Ependymomas (EPNs) are one of the most common types of malignant neuroepithelial tumors. In an effort to identify potential biomarkers involved in the pathogenesis of EPN, the mRNA expression profiles of the GSE25604, GSE50161, GSE66354, GSE74195 and GSE86574 datasets, in addition to the microRNA (miRNA/miR) expression profiles of GSE42657 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) between EPN and normal brain tissue samples were identified using the Limma package in R and GEO2R, respectively. Functional and pathway enrichment analyses were conducted using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction network was constructed using the Search Tool for Retrieval of Interacting Genes database, which was visualized using Cytoscape. The targeted genes of DEMs were predicted using miRWalk2.0 and a miRNA-mRNA regulatory network was constructed. Following analysis, a total of 948 DEGs and 129 DEMs were identified. Functional enrichment analysis revealed that 609 upregulated DEGs were significantly enriched in 'PI3K-Akt signaling pathway', while 339 downregulated DEGs were primarily involved in 'cell junction' and 'retrograde endocannabinoid signaling'. In addition, 6 hub genes [cyclin dependent kinase 1, CD44 molecule (Indian blood group) (), proliferating cell nuclear antigen (), , synaptotagmin 1 () and kinesin family member 4A] and 6 crucial miRNAs [ and ] were identified as biomarkers and potential therapeutic targets for EPN. Furthermore, a microRNA-mRNA regulatory network was constructed to highlight the interactions between DEMs and their target DEGs; this included the and pairs, whose expression levels were confirmed using reverse transcription-quantitative polymerase chain reaction. In conclusion, the present study may provide important data for the investigation of the molecular mechanisms of EPN pathogenesis.
室管膜瘤(EPNs)是最常见的恶性神经上皮肿瘤类型之一。为了确定参与EPN发病机制的潜在生物标志物,从基因表达综合数据库(GEO)下载了GSE25604、GSE50161、GSE66354、GSE74195和GSE86574数据集的mRNA表达谱,以及GSE42657的微小RNA(miRNA/miR)表达谱。分别使用R语言中的Limma软件包和GEO2R软件,鉴定EPN与正常脑组织样本之间的差异表达基因(DEGs)和差异表达miRNA(DEMs)。使用注释、可视化和综合发现数据库进行功能和通路富集分析。使用检索相互作用基因数据库的搜索工具构建蛋白质-蛋白质相互作用网络,并使用Cytoscape进行可视化。使用miRWalk2.0预测DEMs的靶基因,并构建miRNA-mRNA调控网络。经过分析,共鉴定出948个DEGs和129个DEMs。功能富集分析显示,609个上调的DEGs在“PI3K-Akt信号通路”中显著富集,而339个下调的DEGs主要参与“细胞连接”和“逆行内源性大麻素信号传导”。此外,鉴定出6个枢纽基因[细胞周期蛋白依赖性激酶1、CD44分子(印度血型)、增殖细胞核抗原、、突触结合蛋白1和驱动蛋白家族成员4A]和6个关键miRNA[和]作为EPN的生物标志物和潜在治疗靶点。此外,构建了miRNA-mRNA调控网络以突出DEMs与其靶标DEGs之间的相互作用;其中包括和对,其表达水平通过逆转录-定量聚合酶链反应得到证实。总之,本研究可能为EPN发病机制的分子机制研究提供重要数据。