Development of a diagnostic model for ovarian cancer based on machine learning algorithms and functional analysis of key biomarker SOX17
Our multivariable diagnostic model based on five genes through logistic regression optimization, demonstrated robust discriminative capacity for OC. SOX17 functions as a suppressor and potential therapeutic target for OC.
Authors
- Shoucai Zhang
- Yongyuan Liang
- Li Song (ORCID: https://orcid.org/0000-0001-9078-5742)
- Guixi Zheng (ORCID: https://orcid.org/0000-0003-2856-9592)
- Hongxi Zhao (ORCID: https://orcid.org/0000-0002-3468-5322)
- Zeyu Zhang (ORCID: https://orcid.org/0000-0002-9095-2667)
- Yingjie Liu (ORCID: https://orcid.org/0000-0003-1634-3115)
- Shichao Liu (ORCID: https://orcid.org/0009-0006-0366-5480)
- Xueyan Geng
- Maopeng Yin
Institutions
- Shandong Lianxing Energy Group (China) (CN)
- Qilu Hospital of Shandong University (CN)
Publication Details
- Journal
- Journal of Ovarian Research
- Published
- 2025-11-04
- DOI
- https://doi.org/10.1186/s13048-025-01809-w
- Citations
- 1
- Primary Topic
- Ferroptosis and cancer prognosis
- Type
- article
- Field-Weighted Citation Impact
- 1.52
Funders
- National Natural Science Foundation of China