Evidence map›Paper›PMID 32312681›Full record

ReviewTrends in cancer2020

Zebrafish Xenografts for Drug Discovery and Personalized Medicine.

Jerry Xiao, Eric Glasgow, Seema Agarwal

Open access · greenAbstract readReview
In one paragraph

Review in Trends in cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed
9.0field-weighted citation impact, top 1% of its field
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

67 citing papers in PubMed, 113 citations in OpenAlex.

  1. Review
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  7. Synthesis and Antitumor Potency of 2International journal of molecular sciences · 2026
    Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Zebrafish as a Model for Translational Immuno-Oncology.Journal of personalized medicine · 2025
    Review
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  14. Review
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article

7 more citing papers are in PubMed but not listed here.

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

3 authors at 1 institution in 1 country.

Jerry XiaoLombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA.
Eric GlasgowDepartment of Oncology, Georgetown University Medical Center, Washington, DC 20057, USA. Electronic address: eg239@georgetown.edu.
Seema AgarwalDepartment of Pathology, Center for Cell Reprogramming, Georgetown University Medical Center, Washington, DC 20007, USA. Electronic address: sa1137@georgetown.edu.
Georgetown University · US

Funding

Tissue Culture Shared ResourceP30CA051008 · NCI · GEORGETOWN UNIVERSITY · PI Louis M Weiner · 1990 to 2026
$71.5M
NCI NIH HHS P30 CA051008
6 · The paper itself

Abstract

Cancer is the second leading cause of death in the world. Given that cancer is a highly individualized disease, predicting the best chemotherapeutic treatment for individual patients can be difficult. Ex vivo models such as mouse patient-derived xenografts (PDX) and organoids are being developed to predict patient-specific chemosensitivity profiles before treatment in the clinic. Although promising, these models have significant disadvantages including long growth times that introduce genetic and epigenetic changes to the tumor. The zebrafish xenograft assay is ideal for personalized medicine. Imaging of the small, transparent fry is unparalleled among vertebrate organisms. In addition, the speed (5-7 days) and small patient tissue requirements (100-200 cells per animal) are unique features of the zebrafish xenograft model that enable patient-specific chemosensitivity analyses.

Indexed as

ZebrafishAnimalsAnimals, Genetically ModifiedAntineoplastic AgentsCell Culture TechniquesCell Line, TumorDrug DiscoveryEmbryo, NonmammalianHigh-Throughput Screening AssaysHumansMiceNeoplasmsPrecision MedicineTime FactorsTransplantation ChimeraXenograft Model Antitumor AssaysAntineoplastic Agentscancer therapydrug screenpersonalized medicinexenotransplantationzebrafishzebrafish xenografts

Identifiers

PMID32312681
PMCPMC9012325
OpenAlexW3017039682

What OpenQuestion holds

Textmetadata
LicenceTDM
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.