Evidence map›Paper›PMID 35766417›Full record

ArticleCancer science2022

Evaluation of chimeric antigen receptor of humanized rabbit-derived T cell receptor-like antibody.

Tomoko Nakamura, Eiji Kobayashi, Hiroshi Hamana, Yoshihiro Hayakawa, Atsushi Muraguchi, Atsushi Hayashi, Tatsuhiko Ozawa, Hiroyuki Kishi

Open access · goldAbstract read
In one paragraph

Article in Cancer science, 2022. 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
0.1field-weighted citation impact, top 54% 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

2 citing papers in PubMed, 1 citations in OpenAlex.

  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

8 authors at 1 institution in 1 country.

Tomoko NakamuraDepartment of Immunology, Faculty of Medicine, Academic Assembly, University of Toyama, Toyama, Japan.
Eiji KobayashiDepartment of Immunology, Faculty of Medicine, Academic Assembly, University of Toyama, Toyama, Japan.ORCID https://orcid.org/0000-0002-7303-2797
Hiroshi HamanaDepartment of Immunology, Faculty of Medicine, Academic Assembly, University of Toyama, Toyama, Japan.ORCID https://orcid.org/0000-0002-6964-1020
Yoshihiro HayakawaSection of Host Defenses, Department of Bioscience, Institute of Natural Medicine, University of Toyama, Toyama, Japan.ORCID https://orcid.org/0000-0002-7921-1171
Atsushi MuraguchiDepartment of Immunology, Faculty of Medicine, Academic Assembly, University of Toyama, Toyama, Japan.
Atsushi HayashiDepartment of Ophthalmology, Faculty of Medicine, Academic Assembly, University of Toyama, Toyama, Japan.
Tatsuhiko OzawaDepartment of Immunology, Faculty of Medicine, Academic Assembly, University of Toyama, Toyama, Japan.ORCID https://orcid.org/0000-0002-3112-452X
Hiroyuki KishiDepartment of Immunology, Faculty of Medicine, Academic Assembly, University of Toyama, Toyama, Japan.ORCID https://orcid.org/0000-0002-8740-5371
University of Toyama · JP

Funding

Japan Society for the Promotion of Science KAKENHI JP16H06499Japan Society for the Promotion of Science KAKENHI JP18H02689Japan Society for the Promotion of Science KAKENHI JP21H02966Japan Society for the Promotion of Science KAKENHI JP21K18261Platform Project for Supporting Drug Discovery and Life Science Research (Basis for Supporting Innovative Drug Discovery and Life Science Research [BINDS]) from AMED JP21am0101077Practical Research for Innovative Cancer Control, Project for Cancer Research and Therapeutic Evolution (P-CREATE) from AMED JP17cm0106321Practical Research for Innovative Cancer Control, Project for Cancer Research and Therapeutic Evolution (P-CREATE) from AMED JP19cm0106337Practical Research for Innovative Cancer Control, Project for Cancer Research and Therapeutic Evolution (P-CREATE) from AMED JP21cm0106373
6 · The paper itself

Abstract

T-cell receptor (TCR)-like Abs that specifically recognize antigenic peptides presented on MHC molecules have been developed for next-generation cancer immunotherapy. Recently, we reported a rapid and efficient method to generate TCR-like Abs using a rabbit system. We humanized previously generated rabbit-derived TCR-like Abs reacting Epstein-Barr virus peptide (BRLF1p, TYPVLEEMF) in the context of HLA-A24 molecules, produced chimeric antigen receptor (CAR)-T cells, and evaluated their antitumor effects using in vitro and in vivo tumor models. Humanization of the rabbit-derived TCR-like Abs using the complementarity-determining region grafting technology maintained their specificity and affinity. We prepared a second-generation CAR using single-chain variable fragment of the humanized TCR-like Abs and then transduced them into human T cells. The CAR-T cells specifically recognized BRLF1p/MHC molecules and lysed the target cells in an antigen-specific manner in vitro. They also demonstrated antitumor activity in a mouse xenograft model. We report the generation of CAR-T cells using humanized rabbit-derived TCR-like Abs. Together with our established and efficient generation procedure for TCR-like Abs using rabbits, our platform for the clinical application of humanized rabbit-derived TCR-like Abs to CAR-T cells will help improve next-generation cancer immunotherapy.

Indexed as

Epstein-Barr Virus InfectionsNeoplasmsReceptors, Chimeric AntigenSingle-Chain AntibodiesAnimalsComplementarity Determining RegionsHerpesvirus 4, HumanHLA-A24 AntigenHumansMiceRabbitsReceptors, Antigen, T-CellComplementarity Determining RegionsHLA-A24 AntigenReceptors, Antigen, T-CellReceptors, Chimeric AntigenSingle-Chain Antibodieschimeric antigen receptor T-cellhumanized antibodyrabbit antibodyT-cell receptorT-cell receptor-like antibody

Identifiers

PMID35766417
PMCPMC10243493
OpenAlexW4283710341

What OpenQuestion holds

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LicenceCC BY-NC
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.