ArticleTranslational cancer research2021
Identification of hub genes in key hallmarks of ovarian cancer via bioinformatics analysis.
Article in Translational cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A bioinformatics approach to identify potential biomarkers of high-grade ovarian cancer.Journal of the Turkish German Gynecological Association · 2026Article
- Identification of key candidate genes for ovarian cancer using integrated statistical and machine learning approaches.Briefings in bioinformatics · 2025Article
- Expression profiling of KRAS and NOXA genes as prospective biomarkers in ovarian carcinoma.Scientific reports · 2025Article
- Functional genomics pipeline identifies CRL4 inhibition for the treatment of ovarian cancer.Clinical and translational medicine · 2025Article
- Pan-Cancer Drug Response Prediction Using Integrative Principal Component Regression.Statistics in biosciences · 2024Article
- Integrated analysis of spatial transcriptomics and CT phenotypes for unveiling the novel molecular characteristics of recurrent and non-recurrent high-grade serous ovarian cancer.Biomarker research · 2024Article
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5 authors.
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Abstract
backgroundOvarian cancer is one of the most lethal malignant gynecologic tumors worldwide. We aimed to identify critical hallmarks of the surface epithelium between normal ovaries and serous ovarian carcinomas and then obtain the hub genes associated with these critical hallmarks.
methodsWe chose GSE36668, GSE54388 and GSE69428 as data sources and then determined the common gene sets through gene set enrichment analysis (GSEA) to explore essential hallmarks and hub genes driving normal ovarian cells to evolve progressively into a neoplastic state. The differentially expressed genes (DEGs) extracted separately in each gene set were analyzed again through the Metascape website. Kaplan-Meier plotter was used to obtain significant prognostic information. The hub genes were obtained through protein-protein interaction (PPI) network by Cytoscape. Hub genes were confirmed to have higher mRNA and protein expression levels in ovarian cancer tissues than in normal tissues through public databases [Gene Expression Profiling Interactive Analysis (GEPIA) and The Human Protein Atlas]. Correlation analysis of six hub genes showed a strong correlation via R.
resultsWe obtained 11 common hallmarks from GSEA of the three mentioned datasets and 22 hub genes that showed a significant association with poor survival.
conclusionsNot only the gene sets enriched by GSEA but also the hub genes extracted by the PPI network indicate that the most fundamental trait of ovarian cancer cells involves their ability to sustain chronic proliferation.
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