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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Rockefeller University Press 2020
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.
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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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