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Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification
Systemic pan-tumor analyses may reveal the significance of common features implicated in cancer immunogenicity and patient survival. Here, we provide a comprehensive multi-omics data set for 32 patients across 25 tumor types for proteogenomic-based discovery of neoantigens. By using an optimized com...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10397250/ https://www.ncbi.nlm.nih.gov/pubmed/37532709 http://dx.doi.org/10.1038/s41467-023-39570-7 |
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author | Tretter, Celina de Andrade Krätzig, Niklas Pecoraro, Matteo Lange, Sebastian Seifert, Philipp von Frankenberg, Clara Untch, Johannes Zuleger, Gabriela Wilhelm, Mathias Zolg, Daniel P. Dreyer, Florian S. Bräunlein, Eva Engleitner, Thomas Uhrig, Sebastian Boxberg, Melanie Steiger, Katja Slotta-Huspenina, Julia Ochsenreither, Sebastian von Bubnoff, Nikolas Bauer, Sebastian Boerries, Melanie Jost, Philipp J. Schenck, Kristina Dresing, Iska Bassermann, Florian Friess, Helmut Reim, Daniel Grützmann, Konrad Pfütze, Katrin Klink, Barbara Schröck, Evelin Haller, Bernhard Kuster, Bernhard Mann, Matthias Weichert, Wilko Fröhling, Stefan Rad, Roland Hiltensperger, Michael Krackhardt, Angela M. |
author_facet | Tretter, Celina de Andrade Krätzig, Niklas Pecoraro, Matteo Lange, Sebastian Seifert, Philipp von Frankenberg, Clara Untch, Johannes Zuleger, Gabriela Wilhelm, Mathias Zolg, Daniel P. Dreyer, Florian S. Bräunlein, Eva Engleitner, Thomas Uhrig, Sebastian Boxberg, Melanie Steiger, Katja Slotta-Huspenina, Julia Ochsenreither, Sebastian von Bubnoff, Nikolas Bauer, Sebastian Boerries, Melanie Jost, Philipp J. Schenck, Kristina Dresing, Iska Bassermann, Florian Friess, Helmut Reim, Daniel Grützmann, Konrad Pfütze, Katrin Klink, Barbara Schröck, Evelin Haller, Bernhard Kuster, Bernhard Mann, Matthias Weichert, Wilko Fröhling, Stefan Rad, Roland Hiltensperger, Michael Krackhardt, Angela M. |
author_sort | Tretter, Celina |
collection | PubMed |
description | Systemic pan-tumor analyses may reveal the significance of common features implicated in cancer immunogenicity and patient survival. Here, we provide a comprehensive multi-omics data set for 32 patients across 25 tumor types for proteogenomic-based discovery of neoantigens. By using an optimized computational approach, we discover a large number of tumor-specific and tumor-associated antigens. To create a pipeline for the identification of neoantigens in our cohort, we combine DNA and RNA sequencing with MS-based immunopeptidomics of tumor specimens, followed by the assessment of their immunogenicity and an in-depth validation process. We detect a broad variety of non-canonical HLA-binding peptides in the majority of patients demonstrating partially immunogenicity. Our validation process allows for the selection of 32 potential neoantigen candidates. The majority of neoantigen candidates originates from variants identified in the RNA data set, illustrating the relevance of RNA as a still understudied source of cancer antigens. This study underlines the importance of RNA-centered variant detection for the identification of shared biomarkers and potentially relevant neoantigen candidates. |
format | Online Article Text |
id | pubmed-10397250 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103972502023-08-04 Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification Tretter, Celina de Andrade Krätzig, Niklas Pecoraro, Matteo Lange, Sebastian Seifert, Philipp von Frankenberg, Clara Untch, Johannes Zuleger, Gabriela Wilhelm, Mathias Zolg, Daniel P. Dreyer, Florian S. Bräunlein, Eva Engleitner, Thomas Uhrig, Sebastian Boxberg, Melanie Steiger, Katja Slotta-Huspenina, Julia Ochsenreither, Sebastian von Bubnoff, Nikolas Bauer, Sebastian Boerries, Melanie Jost, Philipp J. Schenck, Kristina Dresing, Iska Bassermann, Florian Friess, Helmut Reim, Daniel Grützmann, Konrad Pfütze, Katrin Klink, Barbara Schröck, Evelin Haller, Bernhard Kuster, Bernhard Mann, Matthias Weichert, Wilko Fröhling, Stefan Rad, Roland Hiltensperger, Michael Krackhardt, Angela M. Nat Commun Article Systemic pan-tumor analyses may reveal the significance of common features implicated in cancer immunogenicity and patient survival. Here, we provide a comprehensive multi-omics data set for 32 patients across 25 tumor types for proteogenomic-based discovery of neoantigens. By using an optimized computational approach, we discover a large number of tumor-specific and tumor-associated antigens. To create a pipeline for the identification of neoantigens in our cohort, we combine DNA and RNA sequencing with MS-based immunopeptidomics of tumor specimens, followed by the assessment of their immunogenicity and an in-depth validation process. We detect a broad variety of non-canonical HLA-binding peptides in the majority of patients demonstrating partially immunogenicity. Our validation process allows for the selection of 32 potential neoantigen candidates. The majority of neoantigen candidates originates from variants identified in the RNA data set, illustrating the relevance of RNA as a still understudied source of cancer antigens. This study underlines the importance of RNA-centered variant detection for the identification of shared biomarkers and potentially relevant neoantigen candidates. Nature Publishing Group UK 2023-08-02 /pmc/articles/PMC10397250/ /pubmed/37532709 http://dx.doi.org/10.1038/s41467-023-39570-7 Text en © The Author(s) 2023 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Tretter, Celina de Andrade Krätzig, Niklas Pecoraro, Matteo Lange, Sebastian Seifert, Philipp von Frankenberg, Clara Untch, Johannes Zuleger, Gabriela Wilhelm, Mathias Zolg, Daniel P. Dreyer, Florian S. Bräunlein, Eva Engleitner, Thomas Uhrig, Sebastian Boxberg, Melanie Steiger, Katja Slotta-Huspenina, Julia Ochsenreither, Sebastian von Bubnoff, Nikolas Bauer, Sebastian Boerries, Melanie Jost, Philipp J. Schenck, Kristina Dresing, Iska Bassermann, Florian Friess, Helmut Reim, Daniel Grützmann, Konrad Pfütze, Katrin Klink, Barbara Schröck, Evelin Haller, Bernhard Kuster, Bernhard Mann, Matthias Weichert, Wilko Fröhling, Stefan Rad, Roland Hiltensperger, Michael Krackhardt, Angela M. Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification |
title | Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification |
title_full | Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification |
title_fullStr | Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification |
title_full_unstemmed | Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification |
title_short | Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification |
title_sort | proteogenomic analysis reveals rna as a source for tumor-agnostic neoantigen identification |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10397250/ https://www.ncbi.nlm.nih.gov/pubmed/37532709 http://dx.doi.org/10.1038/s41467-023-39570-7 |
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