Evidence map›Paper›PMID 41141364›Full record

ArticleMolecular therapy. Oncology2025

Lentiviral-mediated panErbB CAR-T cell therapy against head and neck squamous cell carcinomas for patients with Fanconi anemia.

Andrea López, David Charbonnier, Paula Vela, Begoña Díez, Paula Río, Rebeca Sánchez, Omaira Alberquilla, Beatriz Martín-Antonio, Jordi Minguillón, Esperanza Esquinas and 11 more

Abstract read
In one paragraph

Article in Molecular therapy. Oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

21 authors.

Andrea LópezBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.
David CharbonnierBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.
Paula VelaBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.
Begoña DíezBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.
Paula RíoBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.
Rebeca SánchezBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.
Omaira AlberquillaBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.
Beatriz Martín-AntonioInstituto de Salud Carlos III, Madrid, Spain.
Jordi MinguillónBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.
Esperanza EsquinasInstituto de Investigaciones Sanitarias, Fundación Jiménez Díaz, Madrid, Spain.
Ramón García-EscuderoBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.
Ricardo ErrazquinBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.
Sonia Del MarroBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.
Ania PascualBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.
Corina LorzBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.
Ángeles JuarranzDepartmento de Biología, Universidad Autónoma de Madrid, Madrid, Spain.
Andrea BarahonaDepartmento de Biología, Universidad Autónoma de Madrid, Madrid, Spain.
Judith BalmañaVall d'Hebron Insititute of Oncology (VHIO) and Medical Oncology Department Hospital Vall d'Hebron, Barcelona, Spain.
John MaherKing's College London, School of Cancer and Pharmaceutical Sciences, CAR Mechanics Lab, Guy's Cancer Centre, Great Maze Pond, London SE1 9RT, UK.
Juan A BuerenBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.
José Antonio CasadoBiomedical Innovation Unit, Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fanconi anemia (FA) is a DNA repair syndrome characterized by bone marrow failure and cancer predisposition, including acute myeloid leukemia and solid tumors such as head and neck squamous cell carcinoma (HNSCC). Due to the exacerbated toxicity of radio-chemotherapy in FA patients with HNSCC, there is an urgent need of safer and more efficient antitumoral therapies for these patients, such as those based on chimeric antigen receptor (CAR)-T cells. Here, we show that HNSCC cell lines from both the general population and patients with FA express ErbB family members, which can be recognized by the T1E panErbB ligand. The generation of a lentiviral vector encoding for a second-generation T1E-CAR allowed us to generate panErbB CAR-T cells from healthy donors (HDs) and patients with FA. Despite the molecular and cellular defects characteristic of FA cells, a similar efficacy of CAR-T generation was observed, regardless of the donor origin. In all cases, panErbB CAR-T cells exerted potent cytotoxicity against all HNSCC cell lines tested

Indexed as

CAR-T cellsEGFRErbB receptorsFanconi anemiahead and neck squamous carcinomaimmunotherapyMT: Regular Issue

Identifiers

PMID41141364
PMCPMC12547774

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.