Predicting MHC I restricted T cell epitopes in mice with NAP-CNB, a novel online tool

Abstract Lack of a dedicated integrated pipeline for neoantigen discovery in mice hinders cancer immunotherapy research. Novel sequential approaches through recurrent neural networks can improve the accuracy of T-cell epitope binding affinity predictions in mice, and a simplified variant selection p...

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Autores principales:	Carlos Wert-Carvajal, Rubén Sánchez-García, José R Macías, Rebeca Sanz-Pamplona, Almudena Méndez Pérez, Ramon Alemany, Esteban Veiga, Carlos Óscar S. Sorzano, Arrate Muñoz-Barrutia
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/038361e19c14470f97f51c3ee01ac5bc
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spelling	oai:doaj.org-article:038361e19c14470f97f51c3ee01ac5bc2021-12-02T16:53:19ZPredicting MHC I restricted T cell epitopes in mice with NAP-CNB, a novel online tool10.1038/s41598-021-89927-52045-2322https://doaj.org/article/038361e19c14470f97f51c3ee01ac5bc2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89927-5https://doaj.org/toc/2045-2322Abstract Lack of a dedicated integrated pipeline for neoantigen discovery in mice hinders cancer immunotherapy research. Novel sequential approaches through recurrent neural networks can improve the accuracy of T-cell epitope binding affinity predictions in mice, and a simplified variant selection process can reduce operational requirements. We have developed a web server tool (NAP-CNB) for a full and automatic pipeline based on recurrent neural networks, to predict putative neoantigens from tumoral RNA sequencing reads. The developed software can estimate H-2 peptide ligands, with an AUC comparable or superior to state-of-the-art methods, directly from tumor samples. As a proof-of-concept, we used the B16 melanoma model to test the system’s predictive capabilities, and we report its putative neoantigens. NAP-CNB web server is freely available at http://biocomp.cnb.csic.es/NeoantigensApp/ with scripts and datasets accessible through the download section.Carlos Wert-CarvajalRubén Sánchez-GarcíaJosé R MacíasRebeca Sanz-PamplonaAlmudena Méndez PérezRamon AlemanyEsteban VeigaCarlos Óscar S. SorzanoArrate Muñoz-BarrutiaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Carlos Wert-Carvajal Rubén Sánchez-García José R Macías Rebeca Sanz-Pamplona Almudena Méndez Pérez Ramon Alemany Esteban Veiga Carlos Óscar S. Sorzano Arrate Muñoz-Barrutia Predicting MHC I restricted T cell epitopes in mice with NAP-CNB, a novel online tool
description	Abstract Lack of a dedicated integrated pipeline for neoantigen discovery in mice hinders cancer immunotherapy research. Novel sequential approaches through recurrent neural networks can improve the accuracy of T-cell epitope binding affinity predictions in mice, and a simplified variant selection process can reduce operational requirements. We have developed a web server tool (NAP-CNB) for a full and automatic pipeline based on recurrent neural networks, to predict putative neoantigens from tumoral RNA sequencing reads. The developed software can estimate H-2 peptide ligands, with an AUC comparable or superior to state-of-the-art methods, directly from tumor samples. As a proof-of-concept, we used the B16 melanoma model to test the system’s predictive capabilities, and we report its putative neoantigens. NAP-CNB web server is freely available at http://biocomp.cnb.csic.es/NeoantigensApp/ with scripts and datasets accessible through the download section.
format	article
author	Carlos Wert-Carvajal Rubén Sánchez-García José R Macías Rebeca Sanz-Pamplona Almudena Méndez Pérez Ramon Alemany Esteban Veiga Carlos Óscar S. Sorzano Arrate Muñoz-Barrutia
author_facet	Carlos Wert-Carvajal Rubén Sánchez-García José R Macías Rebeca Sanz-Pamplona Almudena Méndez Pérez Ramon Alemany Esteban Veiga Carlos Óscar S. Sorzano Arrate Muñoz-Barrutia
author_sort	Carlos Wert-Carvajal
title	Predicting MHC I restricted T cell epitopes in mice with NAP-CNB, a novel online tool
title_short	Predicting MHC I restricted T cell epitopes in mice with NAP-CNB, a novel online tool
title_full	Predicting MHC I restricted T cell epitopes in mice with NAP-CNB, a novel online tool
title_fullStr	Predicting MHC I restricted T cell epitopes in mice with NAP-CNB, a novel online tool
title_full_unstemmed	Predicting MHC I restricted T cell epitopes in mice with NAP-CNB, a novel online tool
title_sort	predicting mhc i restricted t cell epitopes in mice with nap-cnb, a novel online tool
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/038361e19c14470f97f51c3ee01ac5bc
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Predicting MHC I restricted T cell epitopes in mice with NAP-CNB, a novel online tool

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