Evidence map›Paper›PMID 36768609›Full record

ReviewInternational journal of molecular sciences2023

Zebrafish Cancer Avatars: A Translational Platform for Analyzing Tumor Heterogeneity and Predicting Patient Outcomes.

Majd A Al-Hamaly, Logan T Turner, Angelica Rivera-Martinez, Analiz Rodriguez, Jessica S Blackburn

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Advancements in Zebrafish Models for Breast Cancer Research: Unveiling Biomarkers, Targeted Therapies, and Personalized Medicine.Medical science monitor : international medical journal of experimental and clinical research · 2023
    Pooled it
  2. Review
  3. The role of tumor types in immune-related adverse events.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
    Review
  4. Review
  5. Review
  6. Article
  7. The Role of the Neurotrophin Network in Skin Squamous Cell Cancer and the Novel Use of the Zebrafish System.JID innovations : skin science from molecules to population health · 2024
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. What value do zebrafish have to anticancer drug discovery?Expert opinion on drug discovery · 2024
    Article
  14. Review
  15. Article
  16. Breaking the mold: 3D cell cultures reshaping the future of cancer research.Frontiers in cell and developmental biology · 2024
    Review
  17. Review
  18. Review
  19. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Majd A Al-HamalyPharmacology and Nutritional Sciences, University of Kentucky, Lexington, KY 40356, USA.
Logan T TurnerMarkey Cancer Center, University of Kentucky, Lexington, KY 40536, USA.
Angelica Rivera-MartinezMolecular and Cellular Biochemistry, University of Kentucky, Lexington, KY 40356, USA.
Analiz RodriguezDepartment of Neurosurgery, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA.ORCID 0000-0003-3426-0508
Jessica S BlackburnMarkey Cancer Center, University of Kentucky, Lexington, KY 40536, USA.

Funding

Kentucky Center for Clinical and Translational ScienceUL1TR001998 · NCATS · UNIVERSITY OF KENTUCKY · PI HARTMANN, KATHERINE E, KERN, PHILIP A · 2016 to 2025
$34.2M
Appalachian Career Training in Oncology (ACTION) ProgramR25CA221765 · NCI · UNIVERSITY OF KENTUCKY · PI Nathan Lane Vanderford · 2018 to 2026
$3.7M
The Phosphatase PRL3 as a MYC Target and Pro-Survival Oncogene in Acute Lymphoblastic LeukemiaR37CA227656 · NCI · UNIVERSITY OF KENTUCKY · PI BLACKBURN, JESSICA S. · 2018 to 2024
$2.4M
Harnessing Single Cell Technology to Define Self-Renewal in Normal and Malignant Stem CellsDP2CA228043 · NCI · UNIVERSITY OF KENTUCKY · PI BLACKBURN, JESSICA S. · 2017 to 2017
$2.3M
The Role of Protein Tyrosine Phosphate PRL3 in Leukemia DevelopmentR00CA181500 · NCI · UNIVERSITY OF KENTUCKY · PI BLACKBURN, JESSICA S. · 2016 to 2018
$980k
NCI NIH HHS DP2 CA228043NCI NIH HHS R00 CA181500NCI NIH HHS R25 CA221765NCI NIH HHS R25CA221765NCI NIH HHS R37 CA227656NCI NIH HHS R37CA227656NIH HHS UL1TR001998
6 · The paper itself

Abstract

The increasing number of available anti-cancer drugs presents a challenge for oncologists, who must choose the most effective treatment for the patient. Precision cancer medicine relies on matching a drug with a tumor's molecular profile to optimize the therapeutic benefit. However, current precision medicine approaches do not fully account for intra-tumoral heterogeneity. Different mutation profiles and cell behaviors within a single heterogeneous tumor can significantly impact therapy response and patient outcomes. Patient-derived avatar models recapitulate a patient's tumor in an animal or dish and provide the means to functionally assess heterogeneity's impact on drug response. Mouse xenograft and organoid avatars are well-established, but the time required to generate these models is not practical for clinical decision-making. Zebrafish are emerging as a time-efficient and cost-effective cancer avatar model. In this review, we highlight recent developments in zebrafish cancer avatar models and discuss the unique features of zebrafish that make them ideal for the interrogation of cancer heterogeneity and as part of precision cancer medicine pipelines.

Indexed as

NeoplasmsZebrafishAnimalsHumansMiceXenograft Model Antitumor Assaysco-clinical trialsintra-tumoral heterogeneityprecision medicinexenograftzPDX

Identifiers

PMID36768609
PMCPMC9916713

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.