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

被引:31
作者
Liu, Jinhui [1 ]
Meng, Huangyang [1 ]
Li, Siyue [1 ]
Shen, Yujie [2 ]
Wang, Hui [1 ]
Shan, Wu [1 ]
Qiu, Jiangnan [1 ]
Zhang, Jie [1 ]
Cheng, Wenjun [1 ]
机构
[1] Nanjing Med Univ, Affiliated Hosp 1, Dept Gynecol, Nanjing, Jiangsu, Peoples R China
[2] Nanjing Med Univ, Affiliated Hosp 1, Dept Otorhinolaryngol, Nanjing, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
epithelial ovarian cancer; bioinformatical analysis; differentially expressed genes; prognosis; Cmap; protein-protein interaction; biomarker; CYCLE-ASSOCIATED; 5; GENE; EXPRESSION; NETWORKS; SORORIN; FAMILY; GROWTH; ARRAY; MCM2; TSA;
D O I
10.3389/fgene.2019.01031
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
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.
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页数:16
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