Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification

Celina Tretter; Niklas de Andrade Krätzig; Matteo Pecoraro; Sebastian Lange; Philipp Seifert; Clara von Frankenberg; Johannes Untch; Gabriela Zuleger; Mathias Wilhelm; Daniel P. Zolg; Florian S. Dreyer; Eva Bräunlein; Thomas Engleitner; Sebastian Uhrig; Melanie Boxberg; Katja Steiger; Julia Slotta-Huspenina; Sebastian Ochsenreither; Nikolas von Bubnoff; Sebastian Bauer; Melanie Boerries; Philipp J. Jost; Kristina Schenck; Iska Dresing; Florian Bassermann; Helmut Friess; Daniel Reim; Konrad Grützmann; Katrin Pfütze; Barbara Klink; Evelin Schröck; Bernhard Haller; Bernhard Kuster; Matthias Mann; Wilko Weichert; Stefan Fröhling; Roland Rad; Michael Hiltensperger; Angela M. Krackhardt

doi:10.1038/s41467-023-39570-7

Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification

Celina Tretter, Niklas de Andrade Krätzig, Matteo Pecoraro, Sebastian Lange, Philipp Seifert, Clara von Frankenberg, Johannes Untch, Gabriela Zuleger, Mathias Wilhelm, Daniel P. Zolg, Florian S. Dreyer, Eva Bräunlein, Thomas Engleitner, Sebastian Uhrig, Melanie Boxberg, Katja Steiger, Julia Slotta-Huspenina, Sebastian Ochsenreither, Nikolas von Bubnoff, Sebastian BauerMelanie Boerries, Philipp J. Jost, Kristina Schenck, Iska Dresing, Florian Bassermann, Helmut Friess, Daniel Reim, Konrad Grützmann, Katrin Pfütze, Barbara Klink, Evelin Schröck, Bernhard Haller, Bernhard Kuster, Matthias Mann, Wilko Weichert, Stefan Fröhling, Roland Rad, Michael Hiltensperger, Angela M. Krackhardt^*

^*Corresponding author for this work

33 Citations (Scopus)

Abstract

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.

Original language	English
Article number	4632
Journal	Nature Communications
Volume	14
Issue number	1
ISSN	1751-8628
DOIs	https://doi.org/10.1038/s41467-023-39570-7
Publication status	Published - 12.2023

Funding

We thank G. Swinerd and S. Mall for the preliminary organization of sample collection, the measurement of some patient samples, and the preliminary assembly of flow-cytometry antibody panels. We thank the virology department of MRI of U. Protzer for technical support and advice with ELISpot measurements and analysis. Many thanks to J. Gagneur for the helpful discussions. We especially thank A. Stelzl for logistics organization, measurement of patient samples, and experimental support. We thank the NCT Molecular Precision Oncology Program for technical support and funding through project number 21. A.M.K. was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—SFB-TRR 338/1 2021–452881907 (to A.M.K./A03) and the German Cancer Consortium (DKTK) Joint Funding Program (ImmuNEO MASTER). N.v.B. was supported by the DFG (Project ID 386260575) and the German Federal Ministry of Education and Research (BMBF) within the OUTLIVE consortium (Project ID 01KD2103A). S.F. was supported by the NCT Molecular Precision Oncology Program and the DKTK Joint Funding Program.

Research Areas and Centers

Research Area: Luebeck Integrated Oncology Network (LION)
Centers: University Cancer Center Schleswig-Holstein (UCCSH)

DFG Research Classification Scheme

2.22-14 Hematology, Oncology
2.21-05 Immunology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1038/s41467-023-39570-7

Cite this

Tretter, C., de Andrade Krätzig, N., Pecoraro, M., Lange, S., Seifert, P., von Frankenberg, C., Untch, J., Zuleger, G., Wilhelm, M., Zolg, D. P., Dreyer, F. S., Bräunlein, E., Engleitner, T., Uhrig, S., Boxberg, M., Steiger, K., Slotta-Huspenina, J., Ochsenreither, S., von Bubnoff, N., ... Krackhardt, A. M. (2023). Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification. Nature Communications, 14(1), Article 4632. https://doi.org/10.1038/s41467-023-39570-7

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title = "Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification",

abstract = "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.",

author = "Celina Tretter and \{de Andrade Kr{\"a}tzig\}, Niklas and Matteo Pecoraro and Sebastian Lange and Philipp Seifert and \{von Frankenberg\}, Clara and Johannes Untch and Gabriela Zuleger and Mathias Wilhelm and Zolg, \{Daniel P.\} and Dreyer, \{Florian S.\} and Eva Br{\"a}unlein and Thomas Engleitner and Sebastian Uhrig and Melanie Boxberg and Katja Steiger and Julia Slotta-Huspenina and Sebastian Ochsenreither and \{von Bubnoff\}, Nikolas and Sebastian Bauer and Melanie Boerries and Jost, \{Philipp J.\} and Kristina Schenck and Iska Dresing and Florian Bassermann and Helmut Friess and Daniel Reim and Konrad Gr{\"u}tzmann and Katrin Pf{\"u}tze and Barbara Klink and Evelin Schr{\"o}ck and Bernhard Haller and Bernhard Kuster and Matthias Mann and Wilko Weichert and Stefan Fr{\"o}hling and Roland Rad and Michael Hiltensperger and Krackhardt, \{Angela M.\}",

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Tretter, C, de Andrade Krätzig, N, Pecoraro, M, Lange, S, Seifert, P, von Frankenberg, C, Untch, J, Zuleger, G, Wilhelm, M, Zolg, DP, Dreyer, FS, Bräunlein, E, Engleitner, T, Uhrig, S, Boxberg, M, Steiger, K, Slotta-Huspenina, J, Ochsenreither, S, von Bubnoff, N, Bauer, S, Boerries, M, Jost, PJ, Schenck, K, Dresing, I, Bassermann, F, Friess, H, Reim, D, Grützmann, K, Pfütze, K, Klink, B, Schröck, E, Haller, B, Kuster, B, Mann, M, Weichert, W, Fröhling, S, Rad, R, Hiltensperger, M & Krackhardt, AM 2023, 'Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification', Nature Communications, vol. 14, no. 1, 4632. https://doi.org/10.1038/s41467-023-39570-7

TY - JOUR

T1 - Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification

AU - Tretter, Celina

AU - de Andrade Krätzig, Niklas

AU - Pecoraro, Matteo

AU - Lange, Sebastian

AU - Seifert, Philipp

AU - von Frankenberg, Clara

AU - Untch, Johannes

AU - Zuleger, Gabriela

AU - Wilhelm, Mathias

AU - Zolg, Daniel P.

AU - Dreyer, Florian S.

AU - Bräunlein, Eva

AU - Engleitner, Thomas

AU - Uhrig, Sebastian

AU - Boxberg, Melanie

AU - Steiger, Katja

AU - Slotta-Huspenina, Julia

AU - Ochsenreither, Sebastian

AU - von Bubnoff, Nikolas

AU - Bauer, Sebastian

AU - Boerries, Melanie

AU - Jost, Philipp J.

AU - Schenck, Kristina

AU - Dresing, Iska

AU - Bassermann, Florian

AU - Friess, Helmut

AU - Reim, Daniel

AU - Grützmann, Konrad

AU - Pfütze, Katrin

AU - Klink, Barbara

AU - Schröck, Evelin

AU - Haller, Bernhard

AU - Kuster, Bernhard

AU - Mann, Matthias

AU - Weichert, Wilko

AU - Fröhling, Stefan

AU - Rad, Roland

AU - Hiltensperger, Michael

AU - Krackhardt, Angela M.

PY - 2023/12

Y1 - 2023/12

N2 - 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.

AB - 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.

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DO - 10.1038/s41467-023-39570-7

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SN - 1751-8628

VL - 14

JO - Nature Communications

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M1 - 4632

ER -

Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification

Abstract

Funding

Research Areas and Centers

DFG Research Classification Scheme

UN SDGs

Access to Document

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