SynthesisMedical science monitor : international medical journal of experimental and clinical research2023
Advancements in Zebrafish Models for Breast Cancer Research: Unveiling Biomarkers, Targeted Therapies, and Personalized Medicine.
Synthesis in Medical science monitor : international medical journal of experimental and clinical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 10 citations in OpenAlex.
- Preclinical models of breast cancer metastasis: strengths, limitations, and clinical relevance.NPJ breast cancer · 2026Review
- From Phytochemistry to Oncology: The Role of Bakuchiol in the Treatment of Breast Cancer.Biomolecules · 2026Review
- Article
- Targeting platelet-tumor cell interactions via thromboxane AExperimental hematology & oncology · 2025Article
- Uveal Melanoma Zebrafish Xenograft Models Illustrate the Mutation Status-Dependent Effect of Compound Synergism or Antagonism.Investigative ophthalmology & visual science · 2024Article
- Repurposing proteasome inhibitors for improved treatment of triple-negative breast cancer.Cell death discovery · 2024Article
- Zebrafish as an Emerging Model for Sarcopenia: Considerations, Current Insights, and Future Directions.International journal of molecular sciences · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer (BC) is the most frequently diagnosed malignancy in women worldwide. Despite the wide variety of therapeutic methods for BC, their results are not satisfying, especially in triple-negative breast cancer (TNBC) patients. One of the main challenges in efficient oncology is achieving optimal conditions to evaluate a molecular genotype and phenotype of a tumor. Therefore, new therapeutic strategies are urgently needed. Animal models are an important tool for the molecular and functional characterization of BC, and for the development of targeted BC therapies. Zebrafish, as a promising screening model organism, has been widely applied in the development of patient-derived xenografts (PDX) for the discovery of novel potential antineoplastic drugs. Moreover, the generation of BC xenografts in zebrafish embryos/larvae allows for a description of the tumor growth, cell invasion, and systemic interaction between tumor and host in vivo without immunogenic rejection of transplanted cancer cells. Interestingly, zebrafish can be genetically manipulated and their genome has been fully sequenced. Genetic studies in zebrafish have described new genes and molecular pathways involved in BC carcinogenesis. Thus, the zebrafish in vivo model is becoming an exquisite alternative for metastatic research and for discovering new active agents for BC therapy. Herein, we systematically reviewed the recent cutting-edge advances in zebrafish BC models for carcinogenesis, metastasis, and drug screening. This article aims to review the current status of the role of the zebrafish (Danio reiro) in preclinical and clinical models of biomarker identification and drug targeting, and developments in personalized medicine in BC.
Indexed as
Identifiers
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.