表5_通过整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

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• 源站标题：Table_5_Identification of Potential Biomarkers in Association With Progression and Prognosis in Epithelial Ovarian Cancer by Integrated Bioinformatics Analysis.docx
• DOI：10.3389/fgene.2019.01031.s009
• 发布日期：2019-10-24
• 文件数：1 个
• 文件总体积：18.61 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table_5_Identification_of_Potential_Biomarkers_in_Association_With_Progression_and_Prognosis_in_Epithelial_Ovarian_Cancer_by_Integrated_Bioinformatics_Analysis_docx/10033142

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curl -L -o "Table_5_Identification of Potential Biomarkers in Association With Progression and Prognosis in Epithelial Ovarian Cancer by Integrated Bioinformatics.docx" "https://ndownloader.figshare.com/files/18090338"

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• Table_5_Identification of Potential Biomarkers in Association With Progression and Prognosis in Epithelial Ovarian Cancer by Integrated Bioinformatics.docx（18.61 KB）

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数据说明

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 n

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引用

学术使用请引用 DOI 10.3389/fgene.2019.01031.s009（source: https://frontiersin.figshare.com/articles/dataset/Table_5_Identification_of_Potential_Biomarkers_in_Association_With_Progression_and_Prognosis_in_Epithelial_Ovarian_Cancer_by_Integrated_Bioinformatics_Analysis_docx/10033142）。