ArticleTurkish journal of obstetrics and gynecology2023
Integrated analysis of differentially expressed genes implicated in ovarian cancer progression.
Article in Turkish journal of obstetrics and gynecology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Repurposing natural compounds: computational evaluation ofFrontiers in bioinformatics · 2026Article
- Identification of key candidate genes for ovarian cancer using integrated statistical and machine learning approaches.Briefings in bioinformatics · 2025Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
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Abstract
Objective: Ovarian cancer (OC) is a common gynecological malignancy associated with high morbidity and generally poor prognosis despite treatment. The aim of this study was to understand the influence of gene expression differences and pathways in OC development and progression. Materials and Methods: One hundred and thirty-three OC samples and 34 normal ovarian tissues were included in the study from the Gene Expression Omnibus database. GeneSpring Software was used to obtain differentially expressed genes (DEGs) in all stages comparing tumor and normaltissue. DEGs were analyzed using the DAVID interface for Kyoto Encyclopedia of Genes and Genomes pathway analysis. Most most connected genes were selected as hub genes for each stage using the STRING application in Cytoscape software. Results: DEGs were found to be associated with cell cycle and herpes simplex virus infection pathways. A total of 19 genes ( Conclusion: The results of the current study may provide new insights into OC pathogenesis and suggest potential prognostic and therapeutic targets.
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