Evidence map›Paper›PMID 40169839›Full record

ArticleNPJ precision oncology2025

Zebrafish Avatar testing preclinical study predicts chemotherapy response in breast cancer.

Raquel V Mendes, Joana M Ribeiro, Helena Gouveia, Cátia Rebelo de Almeida, Mireia Castillo-Martin, Maria José Brito, Rita Canas-Marques, Eva Batista, Celeste Alves, Berta Sousa and 5 more

Abstract read
In one paragraph

Article in NPJ precision oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. A Novel Zebrafish Liver-Specific Metastasis Model Reveals c-Met as a Driver of Liver Tropism.Liver international : official journal of the International Association for the Study of the Liver · 2026
    Article
  6. Review
  7. Article
  8. Review
  9. Review
  10. Review
  11. Article
  12. Zebrafish as a Model for Translational Immuno-Oncology.Journal of personalized medicine · 2025
    Review
  13. 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

15 authors.

Raquel V MendesChampalimaud Research, Champalimaud Foundation, Lisbon, Portugal.
Joana M Ribeiro *Gustave Roussy, Département de Médecine Oncologique, Villejuif, France.
Helena Gouveia *Breast Unit, Champalimaud Clinical Center, Champalimaud Foundation, Lisbon, Portugal.
Cátia Rebelo de AlmeidaChampalimaud Research, Champalimaud Foundation, Lisbon, Portugal.
Mireia Castillo-MartinChampalimaud Research, Champalimaud Foundation, Lisbon, Portugal.
Maria José BritoService of Pathology, Champalimaud Clinical Center, Champalimaud Foundation, Lisbon, Portugal.
Rita Canas-MarquesService of Pathology, Champalimaud Clinical Center, Champalimaud Foundation, Lisbon, Portugal.
Eva BatistaBreast Unit, Champalimaud Clinical Center, Champalimaud Foundation, Lisbon, Portugal.
Celeste AlvesBreast Unit, Champalimaud Clinical Center, Champalimaud Foundation, Lisbon, Portugal.
Berta SousaBreast Unit, Champalimaud Clinical Center, Champalimaud Foundation, Lisbon, Portugal.
Pedro GouveiaBreast Unit, Champalimaud Clinical Center, Champalimaud Foundation, Lisbon, Portugal.
Miguel Godinho FerreiraInstitute for Research on Cancer and Aging of Nice (IRCAN), CNRS UMR7284 INSERM U1081, Université Côte d'Azur, 06107, Nice, France.
Maria João CardosoBreast Unit, Champalimaud Clinical Center, Champalimaud Foundation, Lisbon, Portugal.
Fatima CardosoBreast Unit, Champalimaud Clinical Center, Champalimaud Foundation, Lisbon, Portugal.
Rita FiorChampalimaud Research, Champalimaud Foundation, Lisbon, Portugal. rita.fior@research.fchampalimaud.org.

Funding

Congento LISBOA-01-0145-FEDER-022170, co-financed by FCT/Lisboa2020)Fundação para a Ciência e a Tecnologia 2021/08619/BDFundação para a Ciência e a Tecnologia FCT-PTDC/MEC-ONC/31627/2017
6 · The paper itself

Abstract

Chemotherapy remains the mainstay in most high-risk breast cancer (BC) settings, with several equivalent options of treatment. However, the efficacy of each treatment varies between patients and there is currently no test to determine which option will be the most effective for each individual patient. Here, we developed a fast in-vivo test for BC therapy screening: the zebrafish patient-derived-xenograft model (zAvatars), where in-vivo results can be obtained in just 10 days. To determine the predictive value of the BC zAvatars we performed a preclinical study, where zAvatars were treated with the same therapy as the donor-patient and their response to therapy was compared. Our data show a 100% concordance (18 out of 18) between the zAvatar-test and the corresponding patient's clinical response to treatment. Altogether, our results suggest that the zAvatar model constitutes a promising in-vivo assay to optimize cancer treatments in a truly personalized manner.

Identifiers

PMID40169839
PMCPMC11961725

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.