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Multi-step screening of neoantigens’ HLA- and TCR-interfaces improves prediction of survival

Improvement of risk stratification through prognostic biomarkers may enhance the personalization of cancer patient monitoring and treatment. We used Ancer, an immunoinformatic CD8, CD4, and regulatory T cell neoepitope screening system, to perform an advanced neoantigen analysis of genomic data deri...

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Autores principales: Richard, Guilhem, De Groot, Anne S., Steinberg, Gary D., Garcia, Tzintzuni I., Kacew, Alec, Ardito, Matthew, Martin, William D., Berdugo, Gad, Princiotta, Michael F., Balar, Arjun V., Sweis, Randy F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8113358/
https://www.ncbi.nlm.nih.gov/pubmed/33976291
http://dx.doi.org/10.1038/s41598-021-89016-7
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author Richard, Guilhem
De Groot, Anne S.
Steinberg, Gary D.
Garcia, Tzintzuni I.
Kacew, Alec
Ardito, Matthew
Martin, William D.
Berdugo, Gad
Princiotta, Michael F.
Balar, Arjun V.
Sweis, Randy F.
author_facet Richard, Guilhem
De Groot, Anne S.
Steinberg, Gary D.
Garcia, Tzintzuni I.
Kacew, Alec
Ardito, Matthew
Martin, William D.
Berdugo, Gad
Princiotta, Michael F.
Balar, Arjun V.
Sweis, Randy F.
author_sort Richard, Guilhem
collection PubMed
description Improvement of risk stratification through prognostic biomarkers may enhance the personalization of cancer patient monitoring and treatment. We used Ancer, an immunoinformatic CD8, CD4, and regulatory T cell neoepitope screening system, to perform an advanced neoantigen analysis of genomic data derived from the urothelial cancer cohort of The Cancer Genome Atlas. Ancer demonstrated improved prognostic stratification and five-year survival prediction compared to standard analyses using tumor mutational burden or neoepitope identification using NetMHCpan and NetMHCIIpan. The superiority of Ancer, shown in both univariate and multivariate survival analyses, is attributed to the removal of neoepitopes that do not contribute to tumor immunogenicity based on their homology with self-epitopes. This analysis suggests that the presence of a higher number of unique, non-self CD8- and CD4-neoepitopes contributes to cancer survival, and that prospectively defining these neoepitopes using Ancer is a novel prognostic or predictive biomarker.
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spelling pubmed-81133582021-05-12 Multi-step screening of neoantigens’ HLA- and TCR-interfaces improves prediction of survival Richard, Guilhem De Groot, Anne S. Steinberg, Gary D. Garcia, Tzintzuni I. Kacew, Alec Ardito, Matthew Martin, William D. Berdugo, Gad Princiotta, Michael F. Balar, Arjun V. Sweis, Randy F. Sci Rep Article Improvement of risk stratification through prognostic biomarkers may enhance the personalization of cancer patient monitoring and treatment. We used Ancer, an immunoinformatic CD8, CD4, and regulatory T cell neoepitope screening system, to perform an advanced neoantigen analysis of genomic data derived from the urothelial cancer cohort of The Cancer Genome Atlas. Ancer demonstrated improved prognostic stratification and five-year survival prediction compared to standard analyses using tumor mutational burden or neoepitope identification using NetMHCpan and NetMHCIIpan. The superiority of Ancer, shown in both univariate and multivariate survival analyses, is attributed to the removal of neoepitopes that do not contribute to tumor immunogenicity based on their homology with self-epitopes. This analysis suggests that the presence of a higher number of unique, non-self CD8- and CD4-neoepitopes contributes to cancer survival, and that prospectively defining these neoepitopes using Ancer is a novel prognostic or predictive biomarker. Nature Publishing Group UK 2021-05-11 /pmc/articles/PMC8113358/ /pubmed/33976291 http://dx.doi.org/10.1038/s41598-021-89016-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Richard, Guilhem
De Groot, Anne S.
Steinberg, Gary D.
Garcia, Tzintzuni I.
Kacew, Alec
Ardito, Matthew
Martin, William D.
Berdugo, Gad
Princiotta, Michael F.
Balar, Arjun V.
Sweis, Randy F.
Multi-step screening of neoantigens’ HLA- and TCR-interfaces improves prediction of survival
title Multi-step screening of neoantigens’ HLA- and TCR-interfaces improves prediction of survival
title_full Multi-step screening of neoantigens’ HLA- and TCR-interfaces improves prediction of survival
title_fullStr Multi-step screening of neoantigens’ HLA- and TCR-interfaces improves prediction of survival
title_full_unstemmed Multi-step screening of neoantigens’ HLA- and TCR-interfaces improves prediction of survival
title_short Multi-step screening of neoantigens’ HLA- and TCR-interfaces improves prediction of survival
title_sort multi-step screening of neoantigens’ hla- and tcr-interfaces improves prediction of survival
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8113358/
https://www.ncbi.nlm.nih.gov/pubmed/33976291
http://dx.doi.org/10.1038/s41598-021-89016-7
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