An analysis of natural T cell responses to predicted tumor neoepitopes

Autores
Bjerregaard, Anne-Mette; Nielsen, Morten; Jurtz, Vanessa; Barra, Carolina M.; Hadrup, Sine Reker; Szallasi, Zoltan; Eklund, Aron Charles
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Personalization of cancer immunotherapies such as therapeutic vaccines and adoptive T-cell therapy may benefit from efficient identification and targeting of patient-specific neoepitopes. However, current neoepitope prediction methods based on sequencing and predictions of epitope processing and presentation result in a low rate of validation, suggesting that the determinants of peptide immunogenicity are not well understood. We gathered published data on human neopeptides originating from single amino acid substitutions for which T cell reactivity had been experimentally tested, including both immunogenic and non-immunogenic neopeptides. Out of 1,948 neopeptide-HLA (human leukocyte antigen) combinations from 13 publications, 53 were reported to elicit a T cell response. From these data, we found an enrichment for responses among peptides of length 9. Even though the peptides had been pre-selected based on presumed likelihood of being immunogenic, we found using NetMHCpan-4.0 that immunogenic neopeptides were predicted to bind significantly more strongly to HLA compared to non-immunogenic peptides. Investigation of the HLA binding strength of the immunogenic peptides revealed that the vast majority (96%) shared very strong predicted binding to HLA and that the binding strength was comparable to that observed for pathogen-derived epitopes. Finally, we found that neopeptide dissimilarity to self is a predictor of immunogenicity in situations where neo- and normal peptides share comparable predicted binding strength. In conclusion, these results suggest new strategies for prioritization of mutated peptides, but new data will be needed to confirm their value.
Fil: Bjerregaard, Anne-Mette. Technical University of Denmark; Dinamarca
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
Fil: Jurtz, Vanessa. Technical University of Denmark; Dinamarca
Fil: Barra, Carolina M.. 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
Fil: Hadrup, Sine Reker. Technical University of Denmark; Dinamarca
Fil: Szallasi, Zoltan. Technical University of Denmark; Dinamarca. Harvard Medical School; Estados Unidos
Fil: Eklund, Aron Charles. Technical University of Denmark; Dinamarca
Materia
IMMUNOGENICITY
MHC BINDING
MUTATIONS
NEOANTIGENS
NEOEPITOPES
PREDICTION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/48592
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/48592
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling An analysis of natural T cell responses to predicted tumor neoepitopesBjerregaard, Anne-MetteNielsen, MortenJurtz, VanessaBarra, Carolina M.Hadrup, Sine RekerSzallasi, ZoltanEklund, Aron CharlesIMMUNOGENICITYMHC BINDINGMUTATIONSNEOANTIGENSNEOEPITOPESPREDICTIONhttps://purl.org/becyt/ford/3.3https://purl.org/becyt/ford/3Personalization of cancer immunotherapies such as therapeutic vaccines and adoptive T-cell therapy may benefit from efficient identification and targeting of patient-specific neoepitopes. However, current neoepitope prediction methods based on sequencing and predictions of epitope processing and presentation result in a low rate of validation, suggesting that the determinants of peptide immunogenicity are not well understood. We gathered published data on human neopeptides originating from single amino acid substitutions for which T cell reactivity had been experimentally tested, including both immunogenic and non-immunogenic neopeptides. Out of 1,948 neopeptide-HLA (human leukocyte antigen) combinations from 13 publications, 53 were reported to elicit a T cell response. From these data, we found an enrichment for responses among peptides of length 9. Even though the peptides had been pre-selected based on presumed likelihood of being immunogenic, we found using NetMHCpan-4.0 that immunogenic neopeptides were predicted to bind significantly more strongly to HLA compared to non-immunogenic peptides. Investigation of the HLA binding strength of the immunogenic peptides revealed that the vast majority (96%) shared very strong predicted binding to HLA and that the binding strength was comparable to that observed for pathogen-derived epitopes. Finally, we found that neopeptide dissimilarity to self is a predictor of immunogenicity in situations where neo- and normal peptides share comparable predicted binding strength. In conclusion, these results suggest new strategies for prioritization of mutated peptides, but new data will be needed to confirm their value.Fil: Bjerregaard, Anne-Mette. Technical University of Denmark; DinamarcaFil: 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; DinamarcaFil: Jurtz, Vanessa. Technical University of Denmark; DinamarcaFil: Barra, Carolina M.. 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; ArgentinaFil: Hadrup, Sine Reker. Technical University of Denmark; DinamarcaFil: Szallasi, Zoltan. Technical University of Denmark; Dinamarca. Harvard Medical School; Estados UnidosFil: Eklund, Aron Charles. Technical University of Denmark; DinamarcaFrontiers Research Foundation2017-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/48592Bjerregaard, Anne-Mette; Nielsen, Morten; Jurtz, Vanessa; Barra, Carolina M.; Hadrup, Sine Reker; et al.; An analysis of natural T cell responses to predicted tumor neoepitopes; Frontiers Research Foundation; Frontiers in Immunology; 8; NOV; 11-2017; 1-91664-3224CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.3389/fimmu.2017.01566info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fimmu.2017.01566/fullinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:43:16Zoai:ri.conicet.gov.ar:11336/48592instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:43:16.33CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv An analysis of natural T cell responses to predicted tumor neoepitopes
title An analysis of natural T cell responses to predicted tumor neoepitopes
spellingShingle An analysis of natural T cell responses to predicted tumor neoepitopes
Bjerregaard, Anne-Mette
IMMUNOGENICITY
MHC BINDING
MUTATIONS
NEOANTIGENS
NEOEPITOPES
PREDICTION
title_short An analysis of natural T cell responses to predicted tumor neoepitopes
title_full An analysis of natural T cell responses to predicted tumor neoepitopes
title_fullStr An analysis of natural T cell responses to predicted tumor neoepitopes
title_full_unstemmed An analysis of natural T cell responses to predicted tumor neoepitopes
title_sort An analysis of natural T cell responses to predicted tumor neoepitopes
dc.creator.none.fl_str_mv Bjerregaard, Anne-Mette
Nielsen, Morten
Jurtz, Vanessa
Barra, Carolina M.
Hadrup, Sine Reker
Szallasi, Zoltan
Eklund, Aron Charles
author Bjerregaard, Anne-Mette
author_facet Bjerregaard, Anne-Mette
Nielsen, Morten
Jurtz, Vanessa
Barra, Carolina M.
Hadrup, Sine Reker
Szallasi, Zoltan
Eklund, Aron Charles
author_role author
author2 Nielsen, Morten
Jurtz, Vanessa
Barra, Carolina M.
Hadrup, Sine Reker
Szallasi, Zoltan
Eklund, Aron Charles
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv IMMUNOGENICITY
MHC BINDING
MUTATIONS
NEOANTIGENS
NEOEPITOPES
PREDICTION
topic IMMUNOGENICITY
MHC BINDING
MUTATIONS
NEOANTIGENS
NEOEPITOPES
PREDICTION
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.3
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Personalization of cancer immunotherapies such as therapeutic vaccines and adoptive T-cell therapy may benefit from efficient identification and targeting of patient-specific neoepitopes. However, current neoepitope prediction methods based on sequencing and predictions of epitope processing and presentation result in a low rate of validation, suggesting that the determinants of peptide immunogenicity are not well understood. We gathered published data on human neopeptides originating from single amino acid substitutions for which T cell reactivity had been experimentally tested, including both immunogenic and non-immunogenic neopeptides. Out of 1,948 neopeptide-HLA (human leukocyte antigen) combinations from 13 publications, 53 were reported to elicit a T cell response. From these data, we found an enrichment for responses among peptides of length 9. Even though the peptides had been pre-selected based on presumed likelihood of being immunogenic, we found using NetMHCpan-4.0 that immunogenic neopeptides were predicted to bind significantly more strongly to HLA compared to non-immunogenic peptides. Investigation of the HLA binding strength of the immunogenic peptides revealed that the vast majority (96%) shared very strong predicted binding to HLA and that the binding strength was comparable to that observed for pathogen-derived epitopes. Finally, we found that neopeptide dissimilarity to self is a predictor of immunogenicity in situations where neo- and normal peptides share comparable predicted binding strength. In conclusion, these results suggest new strategies for prioritization of mutated peptides, but new data will be needed to confirm their value.
Fil: Bjerregaard, Anne-Mette. Technical University of Denmark; Dinamarca
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
Fil: Jurtz, Vanessa. Technical University of Denmark; Dinamarca
Fil: Barra, Carolina M.. 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
Fil: Hadrup, Sine Reker. Technical University of Denmark; Dinamarca
Fil: Szallasi, Zoltan. Technical University of Denmark; Dinamarca. Harvard Medical School; Estados Unidos
Fil: Eklund, Aron Charles. Technical University of Denmark; Dinamarca
description Personalization of cancer immunotherapies such as therapeutic vaccines and adoptive T-cell therapy may benefit from efficient identification and targeting of patient-specific neoepitopes. However, current neoepitope prediction methods based on sequencing and predictions of epitope processing and presentation result in a low rate of validation, suggesting that the determinants of peptide immunogenicity are not well understood. We gathered published data on human neopeptides originating from single amino acid substitutions for which T cell reactivity had been experimentally tested, including both immunogenic and non-immunogenic neopeptides. Out of 1,948 neopeptide-HLA (human leukocyte antigen) combinations from 13 publications, 53 were reported to elicit a T cell response. From these data, we found an enrichment for responses among peptides of length 9. Even though the peptides had been pre-selected based on presumed likelihood of being immunogenic, we found using NetMHCpan-4.0 that immunogenic neopeptides were predicted to bind significantly more strongly to HLA compared to non-immunogenic peptides. Investigation of the HLA binding strength of the immunogenic peptides revealed that the vast majority (96%) shared very strong predicted binding to HLA and that the binding strength was comparable to that observed for pathogen-derived epitopes. Finally, we found that neopeptide dissimilarity to self is a predictor of immunogenicity in situations where neo- and normal peptides share comparable predicted binding strength. In conclusion, these results suggest new strategies for prioritization of mutated peptides, but new data will be needed to confirm their value.
publishDate 2017
dc.date.none.fl_str_mv 2017-11
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/48592
Bjerregaard, Anne-Mette; Nielsen, Morten; Jurtz, Vanessa; Barra, Carolina M.; Hadrup, Sine Reker; et al.; An analysis of natural T cell responses to predicted tumor neoepitopes; Frontiers Research Foundation; Frontiers in Immunology; 8; NOV; 11-2017; 1-9
1664-3224
CONICET Digital
CONICET
url http://hdl.handle.net/11336/48592
identifier_str_mv Bjerregaard, Anne-Mette; Nielsen, Morten; Jurtz, Vanessa; Barra, Carolina M.; Hadrup, Sine Reker; et al.; An analysis of natural T cell responses to predicted tumor neoepitopes; Frontiers Research Foundation; Frontiers in Immunology; 8; NOV; 11-2017; 1-9
1664-3224
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3389/fimmu.2017.01566
info:eu-repo/semantics/altIdentifier/url/https://www.frontiersin.org/articles/10.3389/fimmu.2017.01566/full
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Frontiers Research Foundation
publisher.none.fl_str_mv Frontiers Research Foundation
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.22299

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