Integrating Bibliometrics and Bioinformatics to Map Knowledge Structure, Trends, and Genetic Insights in Polycystic Ovary Syndrome and Tumors (2015–2024)
By integrating bibliometric analysis with bioinformatics, this study systematically maps the knowledge structure, emerging trends, and molecular mechanisms linking PCOS and cancer. Our findings specifically highlight the association between PCOS and endometrial cancer, may driven by dysregulation of the TP53 and PI3K/AKT signaling pathways. This work provides valuable insights for researchers to understand the foundational knowledge framework, identify emerging trends, potential collaborators, and mechanistic targets for future studies.
Authors
- Ying Xiong (ORCID: https://orcid.org/0000-0002-5680-9269)
- Jun Yuan (ORCID: https://orcid.org/0000-0001-6542-4654)
- Shaohua Zhang (ORCID: https://orcid.org/0000-0002-3911-2398)
- Meng Liu (ORCID: https://orcid.org/0000-0003-2513-7866)
- Zhiqiang Cheng (ORCID: https://orcid.org/0000-0002-4371-0104)
Institutions
- Beijing University of Chinese Medicine (CN)
- China-Japan Friendship Hospital (CN)
Publication Details
- Journal
- Journal of Multidisciplinary Healthcare
- Published
- 2025-08-01
- DOI
- https://doi.org/10.2147/jmdh.s536122
- Citations
- 3
- Primary Topic
- Ovarian cancer diagnosis and treatment
- Type
- article
- Field-Weighted Citation Impact
- 5.09