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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/48592
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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 Técnicas2025-09-29T09:49:11Zoai: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:34982025-09-29 09:49:12.28CONICET 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 |
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CONICET Digital (CONICET) |
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CONICET Digital (CONICET) |
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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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13.070432 |