Evidence map›Paper›PMID 33362787›Full record

ReviewFrontiers in immunology2020

3D Tumor Models and Their Use for the Testing of Immunotherapies.

Nicolas Boucherit, Laurent Gorvel, Daniel Olive

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2020. 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
–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

120 citing papers in PubMed.

  1. Article
  2. Review
  3. Challenges in tracer development for tumor microenvironment (TME) imaging.European journal of nuclear medicine and molecular imaging · 2026
    Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Review
  11. Review
  12. Tumor organoid-immune cell co-culture systems for precision oncology.Frontiers in cell and developmental biology · 2026
    Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  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

3 authors.

Nicolas BoucheritCancer Research Center in Marseille, CRCM, Paoli Calmette Institute, Marseille, France.
Laurent GorvelCancer Research Center in Marseille, CRCM, Paoli Calmette Institute, Marseille, France.
Daniel OliveCancer Research Center in Marseille, CRCM, Paoli Calmette Institute, Marseille, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past decade, immunotherapy has become a powerful and evident tool in the fight against cancers. Notably, the rise of checkpoint blockade using monoclonal antibodies (anti-CTLA4, anti-PD1) to avoid interaction between inhibitory molecules allowed the betterment of patient care. Indeed, immunotherapies led to increased overall survival in forms of cutaneous melanoma or lung cancer. However, the percentage of patients responding varies from 20 to 40% depending on the type of cancer and on the expression of the target molecules by the tumor. This is due to the tumor microenvironment which allows the acquisition of resistance mechanisms to immunotherapies by tumor cells. These are closely linked to the architecture and cellular composition of the tumor microenvironment. This one acts on different parameters such as the immune cells infiltrate its composition and therefore, favors the recruitment of immunosuppressive cells as well as the tumor expression of checkpoint inhibitors such as Programmed Death Ligand-1 (PD-L1). Therefore, the analysis and modeling of the complexity of the microenvironment is an important parameter to consider, not only in the search for new therapies but also for the identification and stratification of patients likely to respond to immunotherapy. This is why the use of 3D culture models, reflecting the architecture and cellular composition of a tumor, is essential in immuno-oncology studies. Nowadays, there are several 3-D culture methods such as spheroids and organoids, which are applicable to immuno-oncology. In this review we evaluate 3D culture models as tools for the development of treatments in the field of immuno-oncology.

Indexed as

Cell CommunicationImmunotherapyTumor MicroenvironmentAnimalsCell Culture TechniquesCell Line, TumorHumansLab-On-A-Chip DevicesMicrofluidic Analytical TechniquesNeoplasmsOrganoidsPrinting, Three-DimensionalSpheroids, CellularTumor Cells, Cultured3D cultureimmune infiltrateimmunotherapyorganoidpatient derived organoidsspheroidtumor microenvironmenttumor on a chip

Identifiers

PMID33362787
PMCPMC7758240

What OpenQuestion holds

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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.