ArticleJournal of ovarian research2025
Exosomal insights into ovarian cancer stem cells: revealing the molecular hubs.
Article in Journal of ovarian research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- Extracellular matrix polysaccharides and glycoproteins in ovarian cancer: structural-functional macromolecular perspectives and potential exosome-derived biomarkers.Cell communication and signaling : CCS · 2026Review
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ovarian cancer is a deadly disease, often diagnosed at advanced stages due to a lack of reliable biomarkers. Exosomes, which carry a variety of molecules such as proteins, lipids, DNA, and non-coding RNAs, have recently emerged as promising tools for early cancer detection. While exosomes have been studied in various cancer types, comprehensive network analyses of exosome proteins in ovarian cancer remain limited. In this study, we used a protein-protein interaction (PPI) network. Using the Clustermaker2 app and the MCODE algorithm, we identified six significant clusters within the network, highlighting regions involved in functional pathways. A four-fold algorithmic approach, including MCC, DMNC, Degree, and EPC, identified 12 common hub genes. STRING analysis and visualization techniques provided a detailed understanding of the biological processes associated with these hub genes. Notably, 91.7% of the identified hub genes were involved in translational processes, showing an important role in protein synthesis regulation in ovarian cancer. In addition, we identified the miRNAs and LncRNAs carried by ovarian cancer exosomes. These findings highlight potential biomarkers for early detection and therapeutic targets.
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