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

Journal: Journal of immunological methods 2016;425():10-20

PMID: 26056938

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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.

Published by Elsevier B.V.

Address: Laboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: [email protected].; Laboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: [email protected].; Laboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: [email protected].; Laboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: [email protected].

DOI: 10.1016/j.jim.2015.06.003