Evidence map›Paper›PMID 40230599›Full record

ArticleImmunoTargets and therapy2025

Selective Deletion of HLA-B, and -C Class I Genes Promotes Immunocompatibility of Humanized Skin Graft Model.

Laura Cobos-Figueroa, Laura Notario, Carmen Mir, Carlos Molpeceres, Sara Lauzurica, Daniel López, Elena Lorente, Pilar Lauzurica

Abstract read
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Article in ImmunoTargets and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

1 citing paper in PubMed.

  1. 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

8 authors.

Laura Cobos-Figueroa *Centro Nacional de Microbiología, Insituto de Salud Carlos III, Majadahonda, Madrid, Spain.ORCID 0000-0002-0091-8693
Laura Notario *Centro Nacional de Microbiología, Insituto de Salud Carlos III, Majadahonda, Madrid, Spain.ORCID 0000-0001-8940-1916
Carmen MirCentro Nacional de Microbiología, Insituto de Salud Carlos III, Majadahonda, Madrid, Spain.
Carlos MolpeceresCentro Láser, Universidad Politécnica de Madrid, Madrid, Madrid, Spain.
Sara LauzuricaCentro Láser, Universidad Politécnica de Madrid, Madrid, Madrid, Spain.
Daniel LópezCentro Nacional de Microbiología, Insituto de Salud Carlos III, Majadahonda, Madrid, Spain.
Elena Lorente *Centro Nacional de Microbiología, Insituto de Salud Carlos III, Majadahonda, Madrid, Spain.
Pilar Lauzurica *Centro Nacional de Microbiología, Insituto de Salud Carlos III, Majadahonda, Madrid, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The treatment of extensive burns requires rapid allogeneic skin transplantation, but HLA diversity poses a significant challenge in finding histocompatible donor-recipient matches. Methods: In this study, we developed a humanized skin graft model using HLA class I transgenic mice to closely examine the HLA-mediated immune response in skin transplantation. Additionally, this model was used to analyse the response against a human lymphoblastoid cell line, JY, with HLA-B and -C genes knocked out by a single-step CRISPR-Cas9 strategy, retaining the most common HLA class I allele, HLA-A*02:01. Results: Mice expressing the HLA-A02:01 allele alone or in combination with HLA-B07:02 do not reject the skin of animals expressing only HLA-A02:01. However, skin from HLA-A02:01/B07:02 mice transplanted into HLA-A02:01 mice is rejected, triggering a strong specific CD8 T cell response mediated by the HLA-B*07:02 molecule. In these latter mice, unlike the parental JY cell line, the edited cells did not induce a CD8 T cell response in vitro, suggesting that the selective deletion of HLA-B and -C may contribute to improve skin graft compatibility. Conclusion: This genetic engineering approach, repeated without modification for the five HLA-A class I most common alleles known to be associated with HLA-B7 and -C7 in the same haplotype, would cover 83.4% of the world population. Our findings offer a scalable HLA-compatible skin graft model, potentially improving practices in burn units worldwide.

Indexed as

allorejectionCRISPRgenetic engineeringhistocompatibilitytransplant

Identifiers

PMID40230599
PMCPMC11994478

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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.