ReviewCells2020
Role of microRNAs as Clinical Cancer Biomarkers for Ovarian Cancer: A Short Overview.
Review in Cells, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
49 citing papers in PubMed, 86 citations in OpenAlex.
- Differential Serum MicroRNA Profiling in Benign and Malignant Ovarian Tumours: An Exploratory Study Identifying hsa-miR-200c-3p as a Candidate Diagnostic Biomarker.Diagnostics (Basel, Switzerland) · 2026Article
- Analytical Techniques as Indicators of Biomarkers in Proteomics Cancer Diagnosis.Anti-cancer agents in medicinal chemistry · 2026Review
- Crosstalk between microRNA and oxidative stress in ovarian cancer: diagnosis, pathogenesis and therapeutic resistance.Medical oncology (Northwood, London, England) · 2025Review
- Ovarian Tumor Biomarkers: Correlation Between Tumor Type and Marker Expression, and Their Role in Guiding Therapeutic Strategies.International journal of molecular sciences · 2025Review
- Potential function of miRNA as a diagnostic biomarker for human ovarian cancer.Discover oncology · 2025Review
- Unraveling the Role of the microRNA-Mediated Regulation of Actin-Binding Proteins in Ovarian Cancer: A Narrative Review.Cancers · 2025Review
- miR-449, identified through antiandrogen exposure, mitigates functional biomarkers associated with ovarian cancer risk.Scientific reports · 2024Article
- Interplay of microRNAs and circRNAs in Epithelial Ovarian Cancer.Non-coding RNA · 2024Review
- Liposome-lentivirus for miRNA therapy with molecular mechanism study.Journal of nanobiotechnology · 2024Article
- Antiandrogen Flutamide-Induced Restoration of miR-449 Expression Mitigates Functional Biomarkers Associated with Ovarian Cancer Risk.medRxiv : the preprint server for health sciences · 2024Article
- Unlocking the 'ova'-coming power: immunotherapy's role in shaping the future of ovarian cancer treatment.Medical oncology (Northwood, London, England) · 2024Review
- Current strategies for early epithelial ovarian cancer detection using miRNA as a potential tool.Frontiers in molecular biosciences · 2024Review
- Diagnostic biomarkers in ovarian cancer: advances beyond CA125 and HE4.Therapeutic advances in medical oncology · 2024Review
- Identification of serum miR-1246 and miR-150-5p as novel diagnostic biomarkers for high-grade serous ovarian cancer.Scientific reports · 2023Article
- Immunogenic Biomarkers HMGB1 and sRAGE Are Potential Diagnostic Tools for Ovarian Malignancies.Cancers · 2023Article
- Extracellular urinary microRNAs as non-invasive biomarkers of endometrial and ovarian cancer.Journal of cancer research and clinical oncology · 2023Review
- Strategy for Pre-Clinical Development of Active Targeting MicroRNA Oligonucleotide Therapeutics for Unmet Medical Needs.International journal of molecular sciences · 2023Article
- Observational
- MicroRNA-409-5p inhibits cell proliferation, and induces GOncology letters · 2022Article
- miR-18a-5p derived from mesenchymal stem cells-extracellular vesicles inhibits ovarian cancer cell proliferation, migration, invasion, and chemotherapy resistance.Journal of translational medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ovarian cancer has the highest mortality rate among gynecological cancers. Early clinical signs are missing and there is an urgent need to establish early diagnosis biomarkers. MicroRNAs are promising biomarkers in this respect. In this paper, we review the most recent advances regarding the alterations of microRNAs in ovarian cancer. We have briefly described the contribution of miRNAs in the mechanisms of ovarian cancer invasion, metastasis, and chemotherapy sensitivity. We have also summarized the alterations underwent by microRNAs in solid ovarian tumors, in animal models for ovarian cancer, and in various ovarian cancer cell lines as compared to previous reviews that were only focused the circulating microRNAs as biomarkers. In this context, we consider that the biomarker screening should not be limited to circulating microRNAs per se, but rather to the simultaneous detection of the same microRNA alteration in solid tumors, in order to understand the differences between the detection of nucleic acids in early vs. late stages of cancer. Moreover, in vitro and in vivo models should also validate these microRNAs, which could be very helpful as preclinical testing platforms for pharmacological and/or molecular genetic approaches targeting microRNAs. The enormous quantity of data produced by preclinical and clinical studies regarding the role of microRNAs that act synergistically in tumorigenesis mechanisms that are associated with ovarian cancer subtypes, should be gathered, integrated, and compared by adequate methods, including molecular clustering. In this respect, molecular clustering analysis should contribute to the discovery of best biomarkers-based microRNAs assays that will enable rapid, efficient, and cost-effective detection of ovarian cancer in early stages. In conclusion, identifying the appropriate microRNAs as clinical biomarkers in ovarian cancer might improve the life quality of patients.
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What OpenQuestion holds
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.