Evidence map›Paper›PMID 36223560›Full record

ArticleBlood2023

Genome-edited allogeneic donor "universal" chimeric antigen receptor T cells.

Waseem Qasim

Open access · hybridAbstract read
In one paragraph

Article in Blood, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
5.4field-weighted citation impact, top 3% of its field
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

46 citing papers in PubMed, 57 citations in OpenAlex.

  1. Review
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  11. Challenges and opportunities of human iPSC-derived NK as "Off-the-shelf" cellular therapies.Journal of experimental & clinical cancer research : CR · 2025
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  17. Immunosenescence: signaling pathways, diseases and therapeutic targets.Signal transduction and targeted therapy · 2025
    Review
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  20. Quadruple adenine base-edited allogeneic CAR T cells outperform CRISPR/Cas9 nuclease-engineered T cells.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Waseem QasimUCL Great Ormond Street Institute of Child Health, Zayed Centre for Research, London, United Kingdom.ORCID 0000-0001-8353-4494
University College London · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

αβ T cell receptor (TCRαβ) T cells modified to express chimeric antigen receptors (CAR), are now available as authorized therapies for certain B-cell malignancies. However the process of autologous harvest and generation of patient-specific products is costly, with complex logistics and infrastructure requirements. Premanufactured banks of allogeneic donor-derived CAR T cells could help widen applicability if the challenges of HLA-mismatched T-cell therapy can be addressed. Genome editing is being applied to overcome allogeneic barriers, most notably, by disrupting TCRαβ to prevent graft-versus-host disease, and multiple competing editing technologies, including CRISPR/Cas9 and base editing, have reached clinical phase testing. Improvements in accuracy and efficiency have unlocked applications for a wider range of blood malignancies, with multiplexed editing incorporated to target HLA molecules, shared antigens and checkpoint pathways. Clinical trials will help establish safety profiles and determine the durability of responses as well as the role of consolidation with allogeneic transplantation.

Indexed as

Hematopoietic Stem Cell TransplantationNeoplasmsReceptors, Chimeric AntigenGene EditingHumansImmunotherapy, AdoptiveReceptors, Antigen, T-CellReceptors, Antigen, T-Cell, alpha-betaT-LymphocytesReceptors, Antigen, T-CellReceptors, Antigen, T-Cell, alpha-betaReceptors, Chimeric Antigen

Identifiers

PMID36223560
PMCPMC10651779
OpenAlexW4304807853

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.