ReviewGynecologic oncology2017
The role of MicroRNA molecules and MicroRNA-regulating machinery in the pathogenesis and progression of epithelial ovarian cancer.
Review in Gynecologic oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed.
- The Hidden Layer of MicroRNA Regulation in Gynecologic Cancers: IsomiRs, Arm Switching, and RNA Epitranscriptomic Modifications.International journal of molecular sciences · 2026Review
- The role of microRNAs in modulating Wnt signaling pathway dynamics and their therapeutic implications in non-small cell lung cancer.Discover oncology · 2026Review
- The microRNA Let-7 and its exosomal form: Epigenetic regulators of gynecological cancers.Cell biology and toxicology · 2024Review
- Potential shared gene signatures and molecular mechanisms between recurrent pregnancy loss and ovarian cancer.Frontiers in oncology · 2024Article
- Transcriptomic analyses of ovarian clear-cell carcinoma with concurrent endometriosis.Frontiers in endocrinology · 2023Article
- Network-Based Integration of Multi-Omics Data Identifies the Determinants of miR-491-5p Effects.Cancers · 2021Article
- SP1-induced lncRNA DANCR contributes to proliferation and invasion of ovarian cancer.The Kaohsiung journal of medical sciences · 2021Article
- Pten and Dicer1 loss in the mouse uterus causes poorly differentiated endometrial adenocarcinoma.Oncogene · 2020Article
- From the Argonauts Mythological Sailors to the Argonautes RNA-Silencing Navigators: Their Emerging Roles in Human-Cell Pathologies.International journal of molecular sciences · 2020Review
- A Polyethylene Glycol-Based Method for Enrichment of Extracellular Vesicles from Culture Supernatant of Human Ovarian Cancer Cell Line A2780 and Body Fluids of High-Grade Serous Carcinoma Patients.Cancer management and research · 2020Article
- MicroRNA-936 targets FGF2 to inhibit epithelial ovarian cancer aggressiveness by deactivating the PI3K/Akt pathway.OncoTargets and therapy · 2019Article
- Branched rolling circle amplification method for measuring serum circulating microRNA levels for early breast cancer detection.Cancer science · 2018Article
- Review
- MicroRNA-125a-5p enhances the sensitivity of esophageal squamous cell carcinoma cells to cisplatin by suppressing the activation of the STAT3 signaling pathway.International journal of oncology · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
MicroRNA molecules are small, single-stranded RNA molecules that function to regulate networks of genes. They play important roles in normal female reproductive tract biology, as well as in the pathogenesis and progression of epithelial ovarian cancer. DROSHA, DICER, and Argonaute proteins are components of the microRNA-regulatory machinery and mediate microRNA production and function. This review discusses aberrant expression of microRNA molecules and microRNA-regulating machinery associated with clinical features of epithelial ovarian cancer. Understanding the regulation of microRNA molecule production and function may facilitate the development of novel diagnostic and therapeutic strategies to improve the prognosis of women with epithelial ovarian cancer. Additionally, understanding microRNA molecules and microRNA-regulatory machinery associations with clinical features may influence prevention and early detection efforts.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.