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通过综合生物信息学分析鉴定与上皮性卵巢癌进展和预后相关的潜在生物标志物

Identification of Potential Biomarkers in Association With Progression and Prognosis in Epithelial Ovarian Cancer by Integrated Bioinformatics Analysis.

作者信息

Liu Jinhui, Meng Huangyang, Li Siyue, Shen Yujie, Wang Hui, Shan Wu, Qiu Jiangnan, Zhang Jie, Cheng Wenjun

机构信息

Department of Gynecology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.

Department of Otorhinolaryngology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.

出版信息

Front Genet. 2019 Oct 24;10:1031. doi: 10.3389/fgene.2019.01031. eCollection 2019.

Abstract

Epithelial ovarian cancer (EOC) is one of the malignancies in women, which has the highest mortality. However, the microlevel mechanism has not been discussed in detail. The expression profiles GSE27651, GSE38666, GSE40595, and GSE66957 including 188 tumor and 52 nontumor samples were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were filtered using R software, and we performed functional analysis using the clusterProfiler. Cytoscape software, the molecular complex detection plugin and database STRING analyzed DEGs to construct protein-protein interaction network. We identified 116 DEGs including 81 upregulated and 35 downregulated DEGs. Functional analysis revealed that they were significantly enriched in the extracellular region and biosynthesis of amino acids. We next identified four bioactive compounds (vorinostat, LY-294002,trichostatin A, and tanespimycin) based on ConnectivityMap. Then 114 nodes were obtained in protein-protein interaction. The three most relevant modules were detected. In addition, according to degree ≥ 10, 14 core genes including FOXM1, CXCR4, KPNA2, NANOG, UBE2C, KIF11, ZWINT, CDCA5, DLGAP5, KIF15, MCM2, MELK, SPP1, and TRIP13 were identified. Kaplan-Meier analysis, Oncomine, and Gene Expression Profiling Interactive Analysis showed that overexpression of FOXM1, SPP1, UBE2C, KIF11, ZWINT, CDCA5, UBE2C, and KIF15 was related to bad prognosis of EOC patients. CDCA5, FOXM1, KIF15, MCM2, and ZWINT were associated with stage. Receiver operating characteristic (ROC) curve showed that messenger RNA levels of these five genes exhibited better diagnostic efficiency for normal and tumor tissues. The Human Protein Atlas database was performed. The protein levels of these five genes were significantly higher in tumor tissues compared with normal tissues. Functional enrichment analysis suggested that all the hub genes played crucial roles in citrate cycle tricarboxylic acid cycle. Furthermore, the univariate and multivariate Cox proportional hazards regression showed that ZWINT was independent prognostic indictor among EOC patients. The genes and pathways discovered in the above studies may open a new direction for EOC treatment.

摘要

上皮性卵巢癌(EOC)是女性恶性肿瘤之一,其死亡率最高。然而,微观层面的机制尚未得到详细探讨。从基因表达综合数据库下载了包括188个肿瘤样本和52个非肿瘤样本的表达谱GSE27651、GSE38666、GSE40595和GSE66957。使用R软件筛选差异表达基因(DEG),并使用clusterProfiler进行功能分析。利用Cytoscape软件、分子复合物检测插件和STRING数据库分析DEG以构建蛋白质-蛋白质相互作用网络。我们鉴定出116个DEG,包括81个上调的和35个下调的DEG。功能分析表明,它们在细胞外区域和氨基酸生物合成中显著富集。接下来,我们基于连接性图谱鉴定了四种生物活性化合物(伏立诺他、LY-294002、曲古抑菌素A和坦西莫司)。然后在蛋白质-蛋白质相互作用中获得了114个节点。检测到三个最相关的模块。此外,根据度≥10,鉴定出14个核心基因,包括FOXM1、CXCR4、KPNA2、NANOG、UBE2C、KIF11、ZWINT、CDCA5、DLGAP5、KIF15、MCM2、MELK、SPP1和TRIP13。Kaplan-Meier分析、Oncomine和基因表达谱交互式分析表明,FOXM1、SPP1、UBE2C、KIF11、ZWINT、CDCA5、UBE2C和KIF15的过表达与EOC患者的不良预后相关。CDCA5、FOXM1、KIF15、MCM2和ZWINT与分期相关。受试者工作特征(ROC)曲线表明,这五个基因的信使RNA水平对正常组织和肿瘤组织具有较好的诊断效率。进行了人类蛋白质图谱数据库查询。与正常组织相比,这五个基因的蛋白质水平在肿瘤组织中显著更高。功能富集分析表明,所有枢纽基因在柠檬酸循环(三羧酸循环)中起关键作用。此外,单因素和多因素Cox比例风险回归表明,ZWINT是EOC患者的独立预后指标。上述研究中发现的基因和途径可能为EOC治疗开辟新方向。

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