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Mutation position is an important determinant for predicting cancer neoantigens
Tumor-specific mutations can generate neoantigens that drive CD8 T cell responses against cancer. Next-generation sequencing and computational methods have been successfully applied to identify mutations and predict neoantigens. However, only a small fraction of predicted neoantigens are immunogenic...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Rockefeller University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7144530/ https://www.ncbi.nlm.nih.gov/pubmed/31940002 http://dx.doi.org/10.1084/jem.20190179 |
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author | Capietto, Aude-Hélène Jhunjhunwala, Suchit Pollock, Samuel B. Lupardus, Patrick Wong, Jim Hänsch, Lena Cevallos, James Chestnut, Yajun Fernandez, Ajay Lounsbury, Nicolas Nozawa, Tamaki Singh, Manmeet Fan, Zhiyuan de la Cruz, Cecile C. Phung, Qui T. Taraborrelli, Lucia Haley, Benjamin Lill, Jennie R. Mellman, Ira Bourgon, Richard Delamarre, Lélia |
author_facet | Capietto, Aude-Hélène Jhunjhunwala, Suchit Pollock, Samuel B. Lupardus, Patrick Wong, Jim Hänsch, Lena Cevallos, James Chestnut, Yajun Fernandez, Ajay Lounsbury, Nicolas Nozawa, Tamaki Singh, Manmeet Fan, Zhiyuan de la Cruz, Cecile C. Phung, Qui T. Taraborrelli, Lucia Haley, Benjamin Lill, Jennie R. Mellman, Ira Bourgon, Richard Delamarre, Lélia |
author_sort | Capietto, Aude-Hélène |
collection | PubMed |
description | Tumor-specific mutations can generate neoantigens that drive CD8 T cell responses against cancer. Next-generation sequencing and computational methods have been successfully applied to identify mutations and predict neoantigens. However, only a small fraction of predicted neoantigens are immunogenic. Currently, predicted peptide binding affinity for MHC-I is often the major criterion for prioritizing neoantigens, although little progress has been made toward understanding the precise functional relationship between affinity and immunogenicity. We therefore systematically assessed the immunogenicity of peptides containing single amino acid mutations in mouse tumor models and divided them into two classes of immunogenic mutations. The first comprises mutations at a nonanchor residue, for which we find that the predicted absolute binding affinity is predictive of immunogenicity. The second involves mutations at an anchor residue; here, predicted relative affinity (compared with the WT counterpart) is a better predictor. Incorporating these features into an immunogenicity model significantly improves neoantigen ranking. Importantly, these properties of neoantigens are also predictive in human datasets, suggesting that they can be used to prioritize neoantigens for individualized neoantigen-specific immunotherapies. |
format | Online Article Text |
id | pubmed-7144530 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Rockefeller University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-71445302020-10-06 Mutation position is an important determinant for predicting cancer neoantigens Capietto, Aude-Hélène Jhunjhunwala, Suchit Pollock, Samuel B. Lupardus, Patrick Wong, Jim Hänsch, Lena Cevallos, James Chestnut, Yajun Fernandez, Ajay Lounsbury, Nicolas Nozawa, Tamaki Singh, Manmeet Fan, Zhiyuan de la Cruz, Cecile C. Phung, Qui T. Taraborrelli, Lucia Haley, Benjamin Lill, Jennie R. Mellman, Ira Bourgon, Richard Delamarre, Lélia J Exp Med Article Tumor-specific mutations can generate neoantigens that drive CD8 T cell responses against cancer. Next-generation sequencing and computational methods have been successfully applied to identify mutations and predict neoantigens. However, only a small fraction of predicted neoantigens are immunogenic. Currently, predicted peptide binding affinity for MHC-I is often the major criterion for prioritizing neoantigens, although little progress has been made toward understanding the precise functional relationship between affinity and immunogenicity. We therefore systematically assessed the immunogenicity of peptides containing single amino acid mutations in mouse tumor models and divided them into two classes of immunogenic mutations. The first comprises mutations at a nonanchor residue, for which we find that the predicted absolute binding affinity is predictive of immunogenicity. The second involves mutations at an anchor residue; here, predicted relative affinity (compared with the WT counterpart) is a better predictor. Incorporating these features into an immunogenicity model significantly improves neoantigen ranking. Importantly, these properties of neoantigens are also predictive in human datasets, suggesting that they can be used to prioritize neoantigens for individualized neoantigen-specific immunotherapies. Rockefeller University Press 2020-01-15 /pmc/articles/PMC7144530/ /pubmed/31940002 http://dx.doi.org/10.1084/jem.20190179 Text en © 2020 Capietto et al. http://www.rupress.org/terms/https://creativecommons.org/licenses/by-nc-sa/4.0/This article is distributed under the terms of an Attribution–Noncommercial–Share Alike–No Mirror Sites license for the first six months after the publication date (see http://www.rupress.org/terms/). After six months it is available under a Creative Commons License (Attribution–Noncommercial–Share Alike 4.0 International license, as described at https://creativecommons.org/licenses/by-nc-sa/4.0/). |
spellingShingle | Article Capietto, Aude-Hélène Jhunjhunwala, Suchit Pollock, Samuel B. Lupardus, Patrick Wong, Jim Hänsch, Lena Cevallos, James Chestnut, Yajun Fernandez, Ajay Lounsbury, Nicolas Nozawa, Tamaki Singh, Manmeet Fan, Zhiyuan de la Cruz, Cecile C. Phung, Qui T. Taraborrelli, Lucia Haley, Benjamin Lill, Jennie R. Mellman, Ira Bourgon, Richard Delamarre, Lélia Mutation position is an important determinant for predicting cancer neoantigens |
title | Mutation position is an important determinant for predicting cancer neoantigens |
title_full | Mutation position is an important determinant for predicting cancer neoantigens |
title_fullStr | Mutation position is an important determinant for predicting cancer neoantigens |
title_full_unstemmed | Mutation position is an important determinant for predicting cancer neoantigens |
title_short | Mutation position is an important determinant for predicting cancer neoantigens |
title_sort | mutation position is an important determinant for predicting cancer neoantigens |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7144530/ https://www.ncbi.nlm.nih.gov/pubmed/31940002 http://dx.doi.org/10.1084/jem.20190179 |
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