Evidence map›Paper›PMID 37220953›Full record

ReviewJournal for immunotherapy of cancer2023

Emerging organoid-immune co-culture models for cancer research: from oncoimmunology to personalized immunotherapies.

Luc Magré, Monique M A Verstegen, Sonja Buschow, Luc J W van der Laan, Maikel Peppelenbosch, Jyaysi Desai

Open access · goldAbstract readReview
In one paragraph

Review in Journal for immunotherapy of cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers.

0numbers the graph read from it
0cells of the map it votes in
120citing papers in PubMed
31.3field-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

120 citing papers in PubMed, 136 citations in OpenAlex.

  1. Article
  2. Review
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  4. Beyond DNA damage: 3D tumor models and the integrin mechanobiology of radioresistance.Journal of experimental & clinical cancer research : CR · 2026
    Review
  5. Review
  6. Article
  7. Article
  8. New developments and applications of human organoids.Nature reviews. Molecular cell biology · 2026
    Review
  9. Review
  10. GLS1 Orchestrates Exosome-Mediated Tumor-Endothelial Communication to Facilitate Angiogenesis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  11. Review
  12. Review
  13. Article
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  15. Article
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  20. Review

60 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

6 authors at 1 institution in 1 country.

Luc MagréGastroenterology and Hepatology, Erasmus Medical Center, Rotterdam, The Netherlands.
Monique M A VerstegenDepartment of Surgery, Erasmus Medical Center, Rotterdam, The Netherlands.
Sonja BuschowGastroenterology and Hepatology, Erasmus Medical Center, Rotterdam, The Netherlands.
Luc J W van der LaanDepartment of Surgery, Erasmus Medical Center, Rotterdam, The Netherlands.
Maikel PeppelenboschGastroenterology and Hepatology, Erasmus Medical Center, Rotterdam, The Netherlands.
Jyaysi DesaiGastroenterology and Hepatology, Erasmus Medical Center, Rotterdam, The Netherlands j.desai@erasmusmc.nl.
Erasmus MC · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the past decade, treatments targeting the immune system have revolutionized the cancer treatment field. Therapies such as immune checkpoint inhibitors have been approved as first-line treatment in a variety of solid tumors such as melanoma and non-small cell lung cancer while other therapies, for instance, chimeric antigen receptor (CAR) lymphocyte transfer therapies, are still in development. Although promising results are obtained in a small subset of patients, overall clinical efficacy of most immunotherapeutics is limited due to intertumoral heterogeneity and therapy resistance. Therefore, prediction of patient-specific responses would be of great value for efficient use of costly immunotherapeutic drugs as well as better outcomes. Because many immunotherapeutics operate by enhancing the interaction and/or recognition of malignant target cells by T cells, in vitro cultures using the combination of these cells derived from the same patient hold great promise to predict drug efficacy in a personalized fashion. The use of two-dimensional cancer cell lines for such cultures is unreliable due to altered phenotypical behavior of cells when compared with the in vivo situation. Three-dimensional tumor-derived organoids, better mimic in vivo tissue and are deemed a more realistic approach to study the complex tumor-immune interactions. In this review, we present an overview of the development of patient-specific tumor organoid-immune co-culture models to study the tumor-specific immune interactions and their possible therapeutic infringement. We also discuss applications of these models which advance personalized therapy efficacy and understanding the tumor microenvironment such as: (1) Screening for efficacy of immune checkpoint inhibition and CAR therapy screening in a personalized manner. (2) Generation of tumor reactive lymphocytes for adoptive cell transfer therapies. (3) Studying tumor-immune interactions to detect cell-specific roles in tumor progression and remission. Overall, these onco-immune co-cultures might hold a promising future toward developing patient-specific therapeutic approaches as well as increase our understanding of tumor-immune interactions.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsAntigen-Antibody ComplexCoculture TechniquesHumansImmune Checkpoint InhibitorsImmunotherapyOrganoidsTumor MicroenvironmentAntigen-Antibody ComplexImmune Checkpoint InhibitorsImmunotherapyLymphocytes, Tumor-InfiltratingTherapies, InvestigationalTranslational Medical ResearchTumor Microenvironment

Identifiers

PMID37220953
PMCPMC10231025
OpenAlexW4377940826

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.