ArticleScientific reports2025
Diagnostic and prognostic biomarkers associated with histotype in advanced epithelial ovarian cancer.
Article in Scientific reports, 2025. 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.
- Deciphering the Dysregulated Pathways and Candidate Therapeutic Compounds for Primary Ovarian Cancer Using Whole Transcriptomics Data and Next Generation Knowledge Discovery Strategies.Journal of cellular and molecular medicine · 2026Article
- Liquid Biopsy-Based Metabolomics in Epithelial Ovarian Cancer: Challenges, Methodological Advances and Translational Considerations.Diagnostics (Basel, Switzerland) · 2026Review
- An overview of the DNA damage response in female reproductive system and breast cancers: A narrative review.International journal of reproductive biomedicine · 2026Review
- A machine learning-based basement membrane gene signature model for predicting ovarian cancer survival.Translational cancer research · 2026Article
- Multimodal deep learning using preoperative CT and ultrasound for recurrence risk prediction in high-grade serous ovarian carcinoma.BMC medical imaging · 2026Article
- Artificial intelligence (AI) and machine learning (ML) in ovarian cancer: transforming detection, treatment, and prevention.Journal of ovarian research · 2026Review
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Authors and funding
11 authors.
Funding
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Abstract
Despite advances in cancer treatments, epithelial ovarian cancer (EOC) remains the leading cause of death among gynecologic cancers. EOC is stratified into five main histopathological subtypes: high-grade serous carcinoma (HGSC), low-grade serous carcinoma (LGSC), endometrioid carcinoma (EC), clear cell carcinoma (CCC), and mucinous carcinoma (MC). However, personalized treatment strategies and reliable biomarkers for all histotypes remain elusive. Building on our previous work with early-stage EOC, we aim to explore diagnostic and prognostic biomarkers in advanced-stage EOC, updated to the latest World Health Organization classification guidelines from 2020, using comprehensive transcriptomic profiling from total RNA sequencing of 146 EOCs. Differential expression analysis identified top 9 histotype-specific gene panels for HGSC, CCC, MC, and EC, including S100A1 (HGSC), ARID3A (CCC), LGALS4 (MC), and PAX9 (EC). We also identified gene candidates associated with overall survival and disease-specific survival, reflecting both favorable (e.g., OTOF, EEF1E1-BLOC1S5, and STAC3) and unfavorable (e.g., SMOC1, GDPGP1, EPRS1) clinical outcome. Additionally, enrichment analysis revealed tumor progression-related pathways unique to each histotype, offering insights into the molecular mechanisms underlying disease progression and potential therapeutic targets. These findings provide valuable insights into the molecular landscape of advanced-stage EOC, paving the way for more effective diagnostic and prognostic tools across diverse histotypes.
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