Evidence map›Paper›PMID 40574837›Full record

ReviewFrontiers in immunology2025

Unleashing the power of CAR-M therapy in solid tumors: a comprehensive review.

Ahsen Morva, Ana Belén Arroyo, Liudmila Andreeva, Ana Tapia-Abellán, Ginés Luengo-Gil

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Article
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  8. Hyperactive Rac converts sublethal to lethal trogocytosis in vivo.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  9. Review
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  15. Article
  16. Targeting Macrophages in Immunotherapy: The Ascent of CAR-Macrophages.International journal of molecular sciences · 2026
    Review
  17. Review
  18. Article
  19. Metabolic reprogramming and plasticity of cancer stem cells.Frontiers in cell and developmental biology · 2026
    Review
  20. 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

5 authors.

Ahsen MorvaBiotechnology Research Group, Climat & Life Sciences, TUBITAK Marmara Research Center, Kocaeli, Türkiye.
Ana Belén ArroyoPathology Department, Santa Lucía University General Hospital, Murcian Institute of Biosanitary Research (IMIB), Cartagena, Spain.
Liudmila AndreevaStructural Immuno-Oncology Research Group, Department of Medical Oncology and Pneumology, University Hospital Tübingen, Tübingen, Germany.
Ana Tapia-AbellánPathology Department, Santa Lucía University General Hospital, Murcian Institute of Biosanitary Research (IMIB), Cartagena, Spain.
Ginés Luengo-GilPathology Department, Santa Lucía University General Hospital, Murcian Institute of Biosanitary Research (IMIB), Cartagena, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chimeric antigen receptor (CAR) macrophage therapy represents a promising new frontier in cancer immunotherapy, with the potential to overcome the limitations of CAR-T cell approaches, particularly in solid tumours. This comprehensive review focuses on the current state and future prospects of CAR macrophage technology, emphasising its applications in solid malignancies across preclinical and early clinical development. The key topics covered included CAR design optimisation, macrophage sources and engineering strategies, mechanisms of antitumour activity,

Indexed as

Immunotherapy, AdoptiveMacrophagesNeoplasmsReceptors, Chimeric AntigenAnimalsHumansTumor MicroenvironmentReceptors, Chimeric Antigenadvances in researchCAR-Mcellular immunotherapychimeric antigen receptormacrophages

Identifiers

PMID40574837
PMCPMC12198237

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.