Evidence map›Paper›PMID 34919147›Full record

ArticleNeuro-oncology2022

Real-time evaluation of glioblastoma growth in patient-specific zebrafish xenografts.

Elin Almstedt, Emil Rosén, Marleen Gloger, Rebecka Stockgard, Neda Hekmati, Katarzyna Koltowska, Cecilia Krona, Sven Nelander

Open access · bronzeAbstract read
In one paragraph

Article in Neuro-oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 2 pooled it
3.4field-weighted citation impact, top 7% 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

31 citing papers in PubMed, 2 syntheses or guidelines pooled it, 42 citations in OpenAlex.

  1. Pooled it
  2. Glioblastoma research on zebrafish xenograft models: a systematic review.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2024
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  10. Zebrafish as a Model for Translational Immuno-Oncology.Journal of personalized medicine · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Elin AlmstedtDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-1946-9138
Emil RosénDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-1664-2257
Marleen GlogerDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Rebecka StockgardDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Neda HekmatiDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Katarzyna KoltowskaDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.ORCID 0000-0002-6841-8900
Cecilia KronaDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Sven NelanderDepartment of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Uppsala University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatient-derived xenograft (PDX) models of glioblastoma (GBM) are a central tool for neuro-oncology research and drug development, enabling the detection of patient-specific differences in growth, and in vivo drug response. However, existing PDX models are not well suited for large-scale or automated studies. Thus, here, we investigate if a fast zebrafish-based PDX model, supported by longitudinal, AI-driven image analysis, can recapitulate key aspects of glioblastoma growth and enable case-comparative drug testing.

methodsWe engrafted 11 GFP-tagged patient-derived GBM IDH wild-type cell cultures (PDCs) into 1-day-old zebrafish embryos, and monitored fish with 96-well live microscopy and convolutional neural network analysis. Using light-sheet imaging of whole embryos, we analyzed further the invasive growth of tumor cells.

resultsOur pipeline enables automatic and robust longitudinal observation of tumor growth and survival of individual fish. The 11 PDCs expressed growth, invasion and survival heterogeneity, and tumor initiation correlated strongly with matched mouse PDX counterparts (Spearman R = 0.89, p < 0.001). Three PDCs showed a high degree of association between grafted tumor cells and host blood vessels, suggesting a perivascular invasion phenotype. In vivo evaluation of the drug marizomib, currently in clinical trials for GBM, showed an effect on fish survival corresponding to PDC in vitro and in vivo marizomib sensitivity.

conclusionsZebrafish xenografts of GBM, monitored by AI methods in an automated process, present a scalable alternative to mouse xenograft models for the study of glioblastoma tumor initiation, growth, and invasion, applicable to patient-specific drug evaluation.

Indexed as

Brain NeoplasmsGlioblastomaAnimalsCell Line, TumorDisease Models, AnimalHeterograftsHumansXenograft Model Antitumor AssaysZebrafish3Rconvolutional neural networkpatient-derived xenograftsperivascular invasionprecision medicine

Identifiers

PMID34919147
PMCPMC9071311
OpenAlexW4200088811

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.