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Identification of core genes in ovarian cancer by an integrative meta-analysis.

ABSTRACT: BACKGROUND:Epithelial ovarian cancer is one of the most ?severe public health threats in women. Since it is still challenging to screen in early stages, identification of core genes that play an essential role in epithelial ovarian cancer initiation and progression is of vital importance. RESULTS:Seven gene expression datasets (GSE6008, GSE18520, GSE26712, GSE27651, GSE29450, GSE36668, and GSE52037) containing 396 ovarian cancer samples and 54 healthy control samples were analyzed to identify the significant differentially expressed genes (DEGs). We identified 563 DEGs, including 245 upregulated and 318 downregulated genes. Enrichment analysis based on the gene ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways showed that the upregulated genes were significantly enriched in cell division, cell cycle, tight junction, and oocyte meiosis, while the downregulated genes were associated with response to endogenous stimuli, complement and coagulation cascades, the cGMP-PKG signaling pathway, and serotonergic synapse. Two significant modules were identified from a protein-protein interaction network by using the Molecular Complex Detection (MCODE) software. Moreover, 12 hub genes with degree centrality more than 29 were selected from the protein-protein interaction network, and module analysis illustrated that these 12 hub genes belong to module 1. Furthermore, Kaplan-Meier analysis for overall survival indicated that 9 of these hub genes was correlated with poor prognosis of epithelial ovarian cancer patients. CONCLUSION:The present study systematically validates the results of previous studies and fills the gap regarding a large-scale meta-analysis in the field of epithelial ovarian cancer. Furthermore, hub genes that could be used as a novel biomarkers to facilitate early diagnosis and therapeutic approaches are evaluated, providing compelling evidence for future genomic-based individualized treatment of epithelial ovarian cancer.

SUBMITTER: Li W

PROVIDER: S-EPMC6240943 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Identification of core genes in ovarian cancer by an integrative meta-analysis.

Li Wenyu W Liu Zheran Z Liang Bowen B Chen Siyang S Zhang Xinping X Tong Xiaoqin X Lou Weiming W Le Lulu L Tang Xiaoli X Fu Fen F

Journal of ovarian research 20181119 1

<h4>Background</h4>Epithelial ovarian cancer is one of the most severe public health threats in women. Since it is still challenging to screen in early stages, identification of core genes that play an essential role in epithelial ovarian cancer initiation and progression is of vital importance.<h4>Results</h4>Seven gene expression datasets (GSE6008, GSE18520, GSE26712, GSE27651, GSE29450, GSE36668, and GSE52037) containing 396 ovarian cancer samples and 54 healthy control samples were analyzed ...[more]

PMID: 30453999

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Project description:Tumor recurrence occurs in more than 70% of ovarian cancer patients, and the majority eventually becomes refractory to treatments. Ovarian Cancer Stem Cells (OCSCs) are believed to be responsible for the tumor relapse and drug resistance. Therefore, eliminating ovarian CSCs is important to improve the prognosis of ovarian cancer patients. However, there is a lack of effective drugs to eliminate OCSCs because the core signaling pathways regulating OCSCs remain unclear. Also it is often hard for biologists to identify a few testable targets and infer driver signaling pathways regulating CSCs from a large number of differentially expression genes in an unbiased manner. In this study, we propose a straightforward and integrative analysis to identify potential core signaling pathways of OCSCs by integrating transcriptome data of OCSCs isolated based on two distinctive markers, ALDH and side population, with regulatory network (Transcription Factor (TF) and Target Interactome) and signaling pathways. We first identify the common activated TFs in two OCSC populations integrating the gene expression and TF-target Interactome; and then uncover up-stream signaling cascades regulating the activated TFs. In specific, 22 activated TFs are identified. Through literature search validation, 15 of them have been reported in association with cancer stem cells. Additionally, 10 TFs are found in the KEGG signaling pathways, and their up-stream signaling cascades are extracted, which also provide potential treatment targets. Moreover, 40 FDA approved drugs are identified to target on the up-stream signaling cascades, and 15 of them have been reported in literatures in cancer stem cell treatment. In conclusion, the proposed approach can uncover the activated up-stream signaling, activated TFs and up-regulated target genes that constitute the potential core signaling pathways of ovarian CSC. Also drugs and drug combinations targeting on the core signaling pathways might be able to eliminate OCSCs. The proposed approach can also be applied for identifying potential activated signaling pathways of other types of cancers.

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Identification of core genes in ovarian cancer by an integrative meta-analysis.

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Identification of core genes in ovarian cancer by an integrative meta-analysis.

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