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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...

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Autores principales: Trincado, Juan L., Reixachs-Solé, Marina, Pérez-Granado, Judith, Fugmann, Tim, Sanz, Ferran, Yokota, Jun, Eyras, Eduardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8478223/
https://www.ncbi.nlm.nih.gov/pubmed/34529669
http://dx.doi.org/10.1371/journal.pcbi.1009411
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author Trincado, Juan L.
Reixachs-Solé, Marina
Pérez-Granado, Judith
Fugmann, Tim
Sanz, Ferran
Yokota, Jun
Eyras, Eduardo
author_facet Trincado, Juan L.
Reixachs-Solé, Marina
Pérez-Granado, Judith
Fugmann, Tim
Sanz, Ferran
Yokota, Jun
Eyras, Eduardo
author_sort Trincado, Juan L.
collection PubMed
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.
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spelling pubmed-84782232021-09-29 ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer Trincado, Juan L. Reixachs-Solé, Marina Pérez-Granado, Judith Fugmann, Tim Sanz, Ferran Yokota, Jun Eyras, Eduardo PLoS Comput Biol Research Article 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. Public Library of Science 2021-09-16 /pmc/articles/PMC8478223/ /pubmed/34529669 http://dx.doi.org/10.1371/journal.pcbi.1009411 Text en © 2021 Trincado et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Trincado, Juan L.
Reixachs-Solé, Marina
Pérez-Granado, Judith
Fugmann, Tim
Sanz, Ferran
Yokota, Jun
Eyras, Eduardo
ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer
title 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_short ISOTOPE: ISOform-guided prediction of epiTOPEs in cancer
title_sort isotope: isoform-guided prediction of epitopes in cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8478223/
https://www.ncbi.nlm.nih.gov/pubmed/34529669
http://dx.doi.org/10.1371/journal.pcbi.1009411
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