Evidence map›Paper›PMID 26056938›Full record

ArticleJournal of immunological methods2015

Poor correlation between T-cell activation assays and HLA-DR binding prediction algorithms in an immunogenic fragment of Pseudomonas exotoxin A.

Ronit Mazor, Chin-Hsien Tai, Byungkook Lee, Ira Pastan

Abstract read
In one paragraph

Article in Journal of immunological methods, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 13% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
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  5. Article
  6. Article
  7. Immunogenicity of Immunotoxins ContainingFrontiers in immunology · 2020
    Review
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  20. Augmented Binary Substitution: Single-pass CDR germ-lining and stabilization of therapeutic antibodies.Proceedings of the National Academy of Sciences of the United States of America · 2015
    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

4 authors at 2 institutions in 1 country.

Ronit MazorLaboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: mazorr@mail.nih.gov.
Chin-Hsien TaiLaboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: TaiC@mail.nih.gov.
Byungkook LeeLaboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: BKLee@mail.nih.gov.
Ira PastanLaboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: pastani@mail.nih.gov.
National Institutes of Health · USNational Cancer Institute · US

Funding

Immunotoxin Therapy of Solid and Hematopoietic Tumors: Preclinical StudiesZIABC008753 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI PASTAN, IRA · 2009 to 2024
$33.1M
Structural BioinformaticsZIABC011233 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI LEE, BYUNGKOOK · 2009 to 2015
$4.4M
Intramural NIH HHS ZIA BC008753
6 · The paper itself

Abstract

The ability to identify immunogenic determinants that activate T-cells is important for the development of new vaccines, allergy therapy and protein therapeutics. In silico MHC-II binding prediction algorithms are often used for T-cell epitope identification. To understand how well those programs predict immunogenicity, we computed HLA binding to peptides spanning the sequence of PE38, a fragment of an anti-cancer immunotoxin, and compared the predicted and experimentally identified T-cell epitopes. We found that the prediction for individual donors did not correlate well with the experimental data. Furthermore, prediction of T-cell epitopes in an HLA heterogenic population revealed that the two strongest epitopes were predicted at multiple cutoffs but the third epitope was predicted negative at all cutoffs and overall 4/9 epitopes were missed at several cutoffs. We conclude that MHC class-II binding predictions are not sufficient to predict the T-cell epitopes in PE38 and should be supplemented by experimental work.

Indexed as

ADP Ribose TransferasesAlgorithmsAmino Acid SequenceAntibody FormationBacterial ToxinsBinding SitesEpitopes, T-LymphocyteExotoxinsHLA-DR AntigensHumansLymphocyte ActivationMolecular Sequence DataPeptidesProtein BindingPseudomonasPseudomonas aeruginosa Exotoxin AADP Ribose TransferasesBacterial ToxinsEpitopes, T-LymphocyteExotoxinsHLA-DR AntigensPeptidesPseudomonas aeruginosa Exotoxin AVirulence FactorsHLA binding algorithmHLA binding predictionImmunogenicityMHC allelesT-cell activationT-cell epitope

Identifiers

PMID26056938
PMCPMC4604018
OpenAlexW614463525

What OpenQuestion holds

Textmetadata
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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.