SynthesisJournal of ovarian research2018
Identification of core genes in ovarian cancer by an integrative meta-analysis.
Synthesis in Journal of ovarian research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.
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Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- KIF2C/MCAK a prognostic biomarker and its oncogenic potential in malignant progression, and prognosis of cancer patients: a systematic review and meta-analysis as biomarker.Critical reviews in clinical laboratory sciences · 2024Pooled it
- Identification of lncRNAs Deregulated in Epithelial Ovarian Cancer Based on a Gene Expression Profiling Meta-Analysis.International journal of molecular sciences · 2023Pooled it
- Multifaceted Integrated Analysis of CDK1 and TOP2A Signaling Pathways for Multi-Target Therapeutic Intervention in Epithelial Ovarian Cancer.International journal of molecular sciences · 2026Article
- The insider's perspective: The intracellular complosome and immune cell dynamics in cancer.Clinical and translational medicine · 2026Review
- Identification of key candidate genes for ovarian cancer using integrated statistical and machine learning approaches.Briefings in bioinformatics · 2025Article
- In vitro properties of four benign meningioma cells derived from WHO grade 1 meningiomas.Human cell · 2025Article
- Functional genomics pipeline identifies CRL4 inhibition for the treatment of ovarian cancer.Clinical and translational medicine · 2025Article
- Recent Updates on Oncogenic Signaling of Aurora Kinases in Chemosensitive, Chemoresistant Cancers: Novel Medicinal Chemistry Approaches for Targeting Aurora Kinases.Current medicinal chemistry · 2024Review
- Article
- Phosphodiesterase 10A (PDE10A) as a novel target to suppress β-catenin and RAS signaling in epithelial ovarian cancer.Journal of ovarian research · 2022Article
- Human iPSC-derived fallopian tube organoids with BRCA1 mutation recapitulate early-stage carcinogenesis.Cell reports · 2021Article
- Identification of potential markers for differentiating epithelial ovarian cancer from ovarian low malignant potential tumors through integrated bioinformatics analysis.Journal of ovarian research · 2021Article
- Identification of the Hub Genes Associated with the Prognosis of Ovarian Cancer Patients via Integrated Bioinformatics Analysis and Experimental Validation.Cancer management and research · 2021Article
- Complement System: Promoter or Suppressor of Cancer Progression?Antibodies (Basel, Switzerland) · 2020Review
- Comprehensive analysis of mRNA-level and miRNA-level subpathway activities for identifying robust ovarian cancer prognostic signatures.Journal of cellular and molecular medicine · 2020Article
- Elevated mRNA Expression Levels of NCAPG are Associated with Poor Prognosis in Ovarian Cancer.Cancer management and research · 2020Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
backgroundEpithelial 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.
resultsSeven 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.
conclusionThe 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.
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Registered trials
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