ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer.

Immunotherapies provide effective treatments for previously untreatable tumors and identifying tumor-specific epitopes can help elucidate the molecular determinants of therapy response. Here, we describe a pipeline, ISOTOPE (ISOform-guided prediction of epiTOPEs In Cancer), for the comprehensive ide...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Juan L Trincado, Marina Reixachs-Solé, Judith Pérez-Granado, Tim Fugmann, Ferran Sanz, Jun Yokota, Eduardo Eyras
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/18b91b59c3034de09c1d3b6bbc285879
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:18b91b59c3034de09c1d3b6bbc285879
record_format	dspace
spelling	oai:doaj.org-article:18b91b59c3034de09c1d3b6bbc2858792021-12-02T19:57:47ZISOTOPE: ISOform-guided prediction of epiTOPEs in cancer.1553-734X1553-735810.1371/journal.pcbi.1009411https://doaj.org/article/18b91b59c3034de09c1d3b6bbc2858792021-09-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009411https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Immunotherapies provide effective treatments for previously untreatable tumors and identifying tumor-specific epitopes can help elucidate the molecular determinants of therapy response. Here, we describe a pipeline, ISOTOPE (ISOform-guided prediction of epiTOPEs In Cancer), for the comprehensive identification of tumor-specific splicing-derived epitopes. Using RNA sequencing and mass spectrometry for MHC-I associated proteins, ISOTOPE identified neoepitopes from tumor-specific splicing events that are potentially presented by MHC-I complexes. Analysis of multiple samples indicates that splicing alterations may affect the production of self-epitopes and generate more candidate neoepitopes than somatic mutations. Although there was no difference in the number of splicing-derived neoepitopes between responders and non-responders to immune therapy, higher MHC-I binding affinity was associated with a positive response. Our analyses highlight the diversity of the immunogenic impacts of tumor-specific splicing alterations and the importance of studying splicing alterations to fully characterize tumors in the context of immunotherapies. ISOTOPE is available at https://github.com/comprna/ISOTOPE.Juan L TrincadoMarina Reixachs-SoléJudith Pérez-GranadoTim FugmannFerran SanzJun YokotaEduardo EyrasPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 9, p e1009411 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Juan L Trincado Marina Reixachs-Solé Judith Pérez-Granado Tim Fugmann Ferran Sanz Jun Yokota Eduardo Eyras ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer.
description	Immunotherapies provide effective treatments for previously untreatable tumors and identifying tumor-specific epitopes can help elucidate the molecular determinants of therapy response. Here, we describe a pipeline, ISOTOPE (ISOform-guided prediction of epiTOPEs In Cancer), for the comprehensive identification of tumor-specific splicing-derived epitopes. Using RNA sequencing and mass spectrometry for MHC-I associated proteins, ISOTOPE identified neoepitopes from tumor-specific splicing events that are potentially presented by MHC-I complexes. Analysis of multiple samples indicates that splicing alterations may affect the production of self-epitopes and generate more candidate neoepitopes than somatic mutations. Although there was no difference in the number of splicing-derived neoepitopes between responders and non-responders to immune therapy, higher MHC-I binding affinity was associated with a positive response. Our analyses highlight the diversity of the immunogenic impacts of tumor-specific splicing alterations and the importance of studying splicing alterations to fully characterize tumors in the context of immunotherapies. ISOTOPE is available at https://github.com/comprna/ISOTOPE.
format	article
author	Juan L Trincado Marina Reixachs-Solé Judith Pérez-Granado Tim Fugmann Ferran Sanz Jun Yokota Eduardo Eyras
author_facet	Juan L Trincado Marina Reixachs-Solé Judith Pérez-Granado Tim Fugmann Ferran Sanz Jun Yokota Eduardo Eyras
author_sort	Juan L Trincado
title	ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer.
title_short	ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer.
title_full	ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer.
title_fullStr	ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer.
title_full_unstemmed	ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer.
title_sort	isotope: isoform-guided prediction of epitopes in cancer.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/18b91b59c3034de09c1d3b6bbc285879
work_keys_str_mv	AT juanltrincado isotopeisoformguidedpredictionofepitopesincancer AT marinareixachssole isotopeisoformguidedpredictionofepitopesincancer AT judithperezgranado isotopeisoformguidedpredictionofepitopesincancer AT timfugmann isotopeisoformguidedpredictionofepitopesincancer AT ferransanz isotopeisoformguidedpredictionofepitopesincancer AT junyokota isotopeisoformguidedpredictionofepitopesincancer AT eduardoeyras isotopeisoformguidedpredictionofepitopesincancer
_version_	1718375765392752640

ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer.

Ejemplares similares