Evidence map›Paper›PMID 40610404›Full record

ReviewSignal transduction and targeted therapy2025

CAR-T cell therapy for cancer: current challenges and future directions.

Inés Zugasti, Lady Espinosa-Aroca, Klaudyna Fidyt, Vladimir Mulens-Arias, Marina Diaz-Beya, Manel Juan, Álvaro Urbano-Ispizua, Jordi Esteve, Talia Velasco-Hernandez, Pablo Menéndez

Abstract readReview
In one paragraph

Review in Signal transduction and targeted therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 174 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
174citing papers in PubMed, 4 pooled it
–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

174 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Guideline
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Review
  7. Review
  8. Article
  9. Overcoming T cell exhaustion and senescence in CAR T cell therapy for solid tumors.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  10. Review
  11. Review
  12. Review
  13. Article
  14. CAR-engineered neutrophils derived from induced pluripotent stem cells: a new frontier in cellular immunotherapy.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  15. Review
  16. Review
  17. Review
  18. Review
  19. Article
  20. Article

114 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

10 authors.

Inés ZugastiHematology Department, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain. izugasti@clinic.cat.ORCID 0000-0002-7666-5055
Lady Espinosa-ArocaJosep Carreras Leukemia Research Institute, Barcelona, Spain.
Klaudyna FidytJosep Carreras Leukemia Research Institute, Barcelona, Spain.
Vladimir Mulens-AriasJosep Carreras Leukemia Research Institute, Barcelona, Spain.
Marina Diaz-BeyaHematology Department, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
Manel JuanRed Española de Terapias Avanzadas (TERAV), Instituto de Salud Carlos III, Madrid, Spain.ORCID 0000-0002-3064-1648
Álvaro Urbano-IspizuaHematology Department, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
Jordi EsteveHematology Department, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
Talia Velasco-HernandezJosep Carreras Leukemia Research Institute, Barcelona, Spain.ORCID 0000-0003-2183-7443
Pablo MenéndezJosep Carreras Leukemia Research Institute, Barcelona, Spain. pmenendez@carrerasresearch.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chimeric antigen receptor T (CAR-T) cell therapies have transformed the treatment of relapsed/refractory (R/R) B-cell malignancies and multiple myeloma by redirecting activated T cells to CD19- or BCMA-expressing tumor cells. However, this approach has yet to be approved for acute myeloid leukemia (AML), the most common acute leukemia in adults and the elderly. Simultaneously, CAR-T cell therapies continue to face significant challenges in the treatment of solid tumors. The primary challenge in developing CAR-T cell therapies for AML is the absence of an ideal target antigen that is both effective and safe, as AML cells share most surface antigens with healthy hematopoietic stem and progenitor cells (HSPCs). Simultaneously targeting antigen expression on both AML cells and HSPCs may result in life-threatening on-target/off-tumor toxicities such as prolonged myeloablation. In addition, the immunosuppressive nature of the AML tumor microenvironment has a detrimental effect on the immune response. This review begins with a comprehensive overview of CAR-T cell therapy for cancer, covering the structure of CAR-T cells and the history of their clinical application. It then explores the current landscape of CAR-T cell therapy in both hematologic malignancies and solid tumors. Finally, the review delves into the specific challenges of applying CAR-T cell therapy to AML, highlights ongoing global clinical trials, and outlines potential future directions for developing effective CAR-T cell-based treatments for relapsed/refractory AML.

Indexed as

Immunotherapy, AdoptiveLeukemia, Myeloid, AcuteNeoplasmsReceptors, Chimeric AntigenHumansTumor MicroenvironmentReceptors, Chimeric Antigen

Identifiers

PMID40610404
PMCPMC12229403

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.