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dc.contributor.author
Attermann, Anders Steenholdt
dc.contributor.author
Barra, Carolina
dc.contributor.author
Reynisson, Birkir
dc.contributor.author
Schultz, Heidi Schiøler
dc.contributor.author
Leurs, Ulrike
dc.contributor.author
Lamberth, Kasper
dc.contributor.author
Nielsen, Morten
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dc.date.available
2022-12-27T12:48:33Z
dc.date.issued
2021-02
dc.identifier.citation
Attermann, Anders Steenholdt; Barra, Carolina; Reynisson, Birkir; Schultz, Heidi Schiøler; Leurs, Ulrike; et al.; Improved prediction of HLA antigen presentation hotspots: Applications for immunogenicity risk assessment of therapeutic proteins; Wiley Blackwell Publishing, Inc; Immunology; 162; 2; 2-2021; 208-219
dc.identifier.issn
0019-2805
dc.identifier.uri
http://hdl.handle.net/11336/182476
dc.description.abstract
Immunogenicity risk assessment is a critical element in protein drug development. Currently, the risk assessment is most often performed using MHC-associated peptide proteomics (MAPPs) and/or T-cell activation assays. However, this is a highly costly procedure that encompasses limited sensitivity imposed by sample sizes, the MHC repertoire of the tested donor cohort and the experimental procedures applied. Recent work has suggested that these techniques could be complemented by accurate, high-throughput and cost-effective prediction of in silico models. However, this work covered a very limited set of therapeutic proteins and eluted ligand (EL) data. Here, we resolved these limitations by showcasing, in a broader setting, the versatility of in silico models for assessment of protein drug immunogenicity. A method for prediction of MHC class II antigen presentation was developed on the hereto largest available mass spectrometry (MS) HLA-DR EL data set. Using independent test sets, the performance of the method for prediction of HLA-DR antigen presentation hotspots was benchmarked. In particular, the method was showcased on a set of protein sequences including four therapeutic proteins and demonstrated to accurately predict the experimental MS hotspot regions at a significantly lower false-positive rate compared with other methods. This gain in performance was particularly pronounced when compared to the NetMHCIIpan-3.2 method trained on binding affinity data. These results suggest that in silico methods trained on MS HLA EL data can effectively and accurately be used to complement MAPPs assays for the risk assessment of protein drugs.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Wiley Blackwell Publishing, Inc
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dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
HLA ANTIGEN PRESENTATION
dc.subject
HLA ELUTED LIGANDS
dc.subject
IMMUNOGENICITY ASSESSMENT
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PREDICTION
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PROTEIN IMMUNOGENICITY
dc.subject.classification
Otras Ciencias de la Salud
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dc.subject.classification
Ciencias de la Salud
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dc.subject.classification
CIENCIAS MÉDICAS Y DE LA SALUD
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dc.title
Improved prediction of HLA antigen presentation hotspots: Applications for immunogenicity risk assessment of therapeutic proteins
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2022-09-20T11:07:02Z
dc.journal.volume
162
dc.journal.number
2
dc.journal.pagination
208-219
dc.journal.pais
Reino Unido
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dc.journal.ciudad
Londres
dc.description.fil
Fil: Attermann, Anders Steenholdt. Technical University of Denmark; Dinamarca
dc.description.fil
Fil: Barra, Carolina. Technical University of Denmark; Dinamarca
dc.description.fil
Fil: Reynisson, Birkir. Technical University of Denmark; Dinamarca
dc.description.fil
Fil: Schultz, Heidi Schiøler. Novo Nordisk A/s; Dinamarca
dc.description.fil
Fil: Leurs, Ulrike. Novo Nordisk A/s; Dinamarca
dc.description.fil
Fil: Lamberth, Kasper. Novo Nordisk A/s; Dinamarca
dc.description.fil
Fil: Nielsen, Morten. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina. Technical University of Denmark; Dinamarca
dc.journal.title
Immunology
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dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1111/imm.13274
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/10.1111/imm.13274
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