Evidence map›Paper›PMID 31316521›Full record

ArticleFrontiers in immunology2019

Key Features Relevant to Select Antigens and TCR From the MHC-Mismatched Repertoire to Treat Cancer.

Stefan Audehm, Manuel Glaser, Matteo Pecoraro, Eva Bräunlein, Sabine Mall, Richard Klar, Manuel Effenberger, Julian Albers, Henrique de Oliveira Bianchi, Janet Peper and 6 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Adoptive T-cell Immunotherapy: Perfecting Self-Defenses.Experientia supplementum (2012) · 2022
    Article
  4. Article
  5. Synthesis and Preclinical Evaluation of aJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2021
    Article
  6. Review
  7. Review
  8. Review
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

16 authors at 6 institutions in 1 country.

Stefan AudehmKlinik und Poliklinik für Innere Medizin III, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
Manuel GlaserCenter for Integrated Protein Science at the Department for Biosciences, Technische Universität München, Freising, Germany.
Matteo PecoraroDepartment of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
Eva BräunleinKlinik und Poliklinik für Innere Medizin III, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
Sabine MallKlinik und Poliklinik für Innere Medizin III, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
Richard KlarKlinik und Poliklinik für Innere Medizin III, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
Manuel EffenbergerInstitut für Medizinische Mikrobiologie, Immunologie und Hygiene, Technische Universität München, Munich, Germany.
Julian AlbersKlinik und Poliklinik für Innere Medizin III, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
Henrique de Oliveira BianchiKlinik und Poliklinik für Innere Medizin III, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
Janet PeperEberhard Karls University Tübingen, Interfaculty Institute for Cell Biology, Tübingen, Germany.
Nahid YusufiNuklearmedizin, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
Dirk H BuschInstitut für Medizinische Mikrobiologie, Immunologie und Hygiene, Technische Universität München, Munich, Germany.
Stefan StevanovićEberhard Karls University Tübingen, Interfaculty Institute for Cell Biology, Tübingen, Germany.
Matthias MannDepartment of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
Iris AntesCenter for Integrated Protein Science at the Department for Biosciences, Technische Universität München, Freising, Germany.
Angela M KrackhardtKlinik und Poliklinik für Innere Medizin III, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
Technical University of Munich · DEKlinikum rechts der Isar · DEMax Planck Institute of Biochemistry · DECenter for Integrated Protein Science Munich · DEDeutschen Konsortium für Translationale Krebsforschung · DEUniversity of Tübingen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adoptive transfer of T cells transgenic for tumor-reactive T-cell receptors (TCR) is an attractive immunotherapeutic approach. However, clinical translation is so far limited due to challenges in the identification of suitable target antigens as well as TCRs that are concurrent safe and efficient. Definition of key characteristics relevant for effective and specific tumor rejection is essential to improve current TCR-based adoptive T-cell immunotherapies. We here characterized in-depth two TCRs derived from the human leukocyte antigen (HLA)-mismatched allogeneic repertoire targeting two different myeloperoxidase (MPO)-derived peptides presented by the same HLA-restriction element side by side comprising state of the art biochemical and cellular

Indexed as

AnimalsCell LineCytokinesHLA AntigensHumansMajor Histocompatibility ComplexMice, TransgenicModels, MolecularNeoplasmsPeptidesPeroxidaseReceptors, Antigen, T-CellCytokinesHLA AntigensPeptidesPeroxidaseReceptors, Antigen, T-Celladoptive T-cell transfer therapypeptide-MHC modeling (p-MHC modeling)target antigen characterizationT-cell receptor (TCR)TCR cell therapyTCR characterizationTCR identificationtrimolecular complex (TCR-p-MHC)

Identifiers

PMID31316521
PMCPMC6611213
OpenAlexW2949614708

What OpenQuestion holds

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LicenceCC BY
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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.