Evidence map›Paper›PMID 38504137›Full record

ArticleNature protocols2024

BEHAV3D: a 3D live imaging platform for comprehensive analysis of engineered T cell behavior and tumor response.

Maria Alieva, Mario Barrera Román, Sam de Blank, Diana Petcu, Amber L Zeeman, Noël M M Dautzenberg, Annelisa M Cornel, Cesca van de Ven, Rob Pieters, Monique L den Boer and 8 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature protocols, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Review
  2. Leveraging Microphysiological Systems to Facilitate Neutrophil-Based Cancer Immunotherapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  3. Article
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  5. Article
  6. Review
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  8. Review
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  11. Organoids glimpse: the nexus for diverse tumor heterogeneity.Frontiers in cell and developmental biology · 2026
    Review
  12. Review
  13. Review
  14. Article
  15. Review
  16. Article
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  18. Review
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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

18 authors.

Maria AlievaPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands. malieva@iib.uam.es.ORCID 0000-0002-1425-9908
Mario Barrera Román *Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.ORCID 0000-0002-5919-2962
Sam de Blank *Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.ORCID 0000-0003-2191-5675
Diana PetcuPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Amber L ZeemanPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Noël M M DautzenbergPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.ORCID 0009-0001-7517-6006
Annelisa M CornelPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Cesca van de VenPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.ORCID 0000-0002-9797-9539
Rob PietersPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Monique L den BoerPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.ORCID 0000-0002-5795-2921
Stefan NierkensPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Friso G J CalkoenPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.ORCID 0000-0001-9059-0929
Hans CleversPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.ORCID 0000-0002-3077-5582
Jürgen KuballCenter for Translational Immunology, University Medical Centre (UMC) Utrecht, Utrecht, the Netherlands.
Zsolt SebestyénCenter for Translational Immunology, University Medical Centre (UMC) Utrecht, Utrecht, the Netherlands.
Ellen J WehrensPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Johanna F DekkersPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
Anne C RiosPrincess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands. a.c.rios@prinsesmaximacentrum.nl.ORCID 0000-0002-9082-8068

Funding

Expressive Writing as a Therapeutic Process for Drug Dependent WomenR36DA024021 · NIDA · VIRGINIA COMMONWEALTH UNIVERSITY · PI MESHBERG-COHEN, SARAH · 2008 to 2008
$54k
Consejería de Educación, Juventud y Deporte, Comunidad de Madrid (Consejería de Educación, Juventud y Deporte de la Comunidad de Madrid) 2022-T1/BMD-24021EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) 804412KWF Kankerbestrijding (Dutch Cancer Society) 14135
6 · The paper itself

Abstract

Modeling immuno-oncology by using patient-derived material and immune cell co-cultures can advance our understanding of immune cell tumor targeting in a patient-specific manner, offering leads to improve cellular immunotherapy. However, fully exploiting these living cultures requires analysis of the dynamic cellular features modeled, for which protocols are currently limited. Here, we describe the application of BEHAV3D, a platform that implements multi-color live 3D imaging and computational tools for: (i) analyzing tumor death dynamics at both single-organoid or cell and population levels, (ii) classifying T cell behavior and (iii) producing data-informed 3D images and videos for visual inspection and further insight into obtained results. Together, this enables a refined assessment of how solid and liquid tumors respond to cellular immunotherapy, critically capturing both inter- and intratumoral heterogeneity in treatment response. In addition, BEHAV3D uncovers T cell behavior involved in tumor targeting, offering insight into their mode of action. Our pipeline thereby has strong implications for comparing, prioritizing and improving immunotherapy products by highlighting the behavioral differences between individual tumor donors, distinct T cell therapy concepts or subpopulations. The protocol describes critical wet lab steps, including co-culture preparations and fast 3D imaging with live cell dyes, a segmentation-based image processing tool to track individual organoids, tumor and immune cells and an analytical pipeline for behavioral profiling. This 1-week protocol, accessible to users with basic cell culture, imaging and programming expertise, can easily be adapted to any type of co-culture to visualize and exploit cell behavior, having far-reaching implications for the immuno-oncology field and beyond.

Indexed as

Imaging, Three-DimensionalNeoplasmsT-LymphocytesCoculture TechniquesHumansImmunotherapy

Identifiers

What OpenQuestion holds

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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.