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Direct identification of clinically relevant neoepitopes presented on native human melanoma tissue by mass spectrometry

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  • Michal Bassani-Sternberg

    (Max Planck Institute of Biochemistry
    Present address: Department of Oncology, UNIL/CHUV, Ludwig Cancer Research Center, Epalinges 1066, Switzerland)

  • Eva Bräunlein

    (Klinikum rechts der Isar, Technische Universität München)

  • Richard Klar

    (Klinikum rechts der Isar, Technische Universität München)

  • Thomas Engleitner

    (Klinikum rechts der Isar, Technische Universität München
    German Cancer Consortium of Translational Cancer Research (DKTK) and German Cancer Research Center (DKFZ))

  • Pavel Sinitcyn

    (Max Planck Institute of Biochemistry)

  • Stefan Audehm

    (Klinikum rechts der Isar, Technische Universität München)

  • Melanie Straub

    (Institute of Pathology, Technische Universität München)

  • Julia Weber

    (Klinikum rechts der Isar, Technische Universität München
    German Cancer Consortium of Translational Cancer Research (DKTK) and German Cancer Research Center (DKFZ))

  • Julia Slotta-Huspenina

    (Institute of Pathology, Technische Universität München
    MRI-TUM-Biobank at the Institute of Pathology, Technische Universität München)

  • Katja Specht

    (Institute of Pathology, Technische Universität München)

  • Marc E. Martignoni

    (Klinikum rechts der Isar, Technische Universität München)

  • Angelika Werner

    (Klinikum rechts der Isar, Technische Universität München)

  • Rüdiger Hein

    (Klinikum rechts der Isar, Technische Universität München)

  • Dirk H. Busch

    (Institute for Medical Microbiology, Immunology and Hygiene, Technische Universität München)

  • Christian Peschel

    (Klinikum rechts der Isar, Technische Universität München
    German Cancer Consortium of Translational Cancer Research (DKTK) and German Cancer Research Center (DKFZ))

  • Roland Rad

    (Klinikum rechts der Isar, Technische Universität München
    German Cancer Consortium of Translational Cancer Research (DKTK) and German Cancer Research Center (DKFZ))

  • Jürgen Cox

    (Max Planck Institute of Biochemistry)

  • Matthias Mann

    (Max Planck Institute of Biochemistry)

  • Angela M. Krackhardt

    (Klinikum rechts der Isar, Technische Universität München
    German Cancer Consortium of Translational Cancer Research (DKTK) and German Cancer Research Center (DKFZ))

Abstract

Although mutations may represent attractive targets for immunotherapy, direct identification of mutated peptide ligands isolated from human leucocyte antigens (HLA) on the surface of native tumour tissue has so far not been successful. Using advanced mass spectrometry (MS) analysis, we survey the melanoma-associated immunopeptidome to a depth of 95,500 patient-presented peptides. We thereby discover a large spectrum of attractive target antigen candidates including cancer testis antigens and phosphopeptides. Most importantly, we identify peptide ligands presented on native tumour tissue samples harbouring somatic mutations. Four of eleven mutated ligands prove to be immunogenic by neoantigen-specific T-cell responses. Moreover, tumour-reactive T cells with specificity for selected neoantigens identified by MS are detected in the patient’s tumour and peripheral blood. We conclude that direct identification of mutated peptide ligands from primary tumour material by MS is possible and yields true neoepitopes with high relevance for immunotherapeutic strategies in cancer.

Suggested Citation

  • Michal Bassani-Sternberg & Eva Bräunlein & Richard Klar & Thomas Engleitner & Pavel Sinitcyn & Stefan Audehm & Melanie Straub & Julia Weber & Julia Slotta-Huspenina & Katja Specht & Marc E. Martignoni, 2016. "Direct identification of clinically relevant neoepitopes presented on native human melanoma tissue by mass spectrometry," Nature Communications, Nature, vol. 7(1), pages 1-16, December.
  • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms13404
    DOI: 10.1038/ncomms13404
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    Cited by:

    1. Hanqing Liao & Carolina Barra & Zhicheng Zhou & Xu Peng & Isaac Woodhouse & Arun Tailor & Robert Parker & Alexia Carré & Persephone Borrow & Michael J. Hogan & Wayne Paes & Laurence C. Eisenlohr & Rob, 2024. "MARS an improved de novo peptide candidate selection method for non-canonical antigen target discovery in cancer," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    2. Celina Tretter & Niklas Andrade Krätzig & Matteo Pecoraro & Sebastian Lange & Philipp Seifert & Clara Frankenberg & Johannes Untch & Gabriela Zuleger & Mathias Wilhelm & Daniel P. Zolg & Florian S. Dr, 2023. "Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    3. Jennifer G. Abelin & Erik J. Bergstrom & Keith D. Rivera & Hannah B. Taylor & Susan Klaeger & Charles Xu & Eva K. Verzani & C. Jackson White & Hilina B. Woldemichael & Maya Virshup & Meagan E. Olive &, 2023. "Workflow enabling deepscale immunopeptidome, proteome, ubiquitylome, phosphoproteome, and acetylome analyses of sample-limited tissues," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    4. Samuel Rivero-Hinojosa & Melanie Grant & Aswini Panigrahi & Huizhen Zhang & Veronika Caisova & Catherine M. Bollard & Brian R. Rood, 2021. "Proteogenomic discovery of neoantigens facilitates personalized multi-antigen targeted T cell immunotherapy for brain tumors," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    5. Jens Bauer & Natalie Köhler & Yacine Maringer & Philip Bucher & Tatjana Bilich & Melissa Zwick & Severin Dicks & Annika Nelde & Marissa Dubbelaar & Jonas Scheid & Marcel Wacker & Jonas S. Heitmann & S, 2022. "The oncogenic fusion protein DNAJB1-PRKACA can be specifically targeted by peptide-based immunotherapy in fibrolamellar hepatocellular carcinoma," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    6. Weilong Zhao & Xinwei Sher, 2018. "Systematically benchmarking peptide-MHC binding predictors: From synthetic to naturally processed epitopes," PLOS Computational Biology, Public Library of Science, vol. 14(11), pages 1-28, November.
    7. Naomi Hoenisch Gravel & Annika Nelde & Jens Bauer & Lena Mühlenbruch & Sarah M. Schroeder & Marian C. Neidert & Jonas Scheid & Steffen Lemke & Marissa L. Dubbelaar & Marcel Wacker & Anna Dengler & Rei, 2023. "TOFIMS mass spectrometry-based immunopeptidomics refines tumor antigen identification," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    8. Georges Bedran & Daniel A. Polasky & Yi Hsiao & Fengchao Yu & Felipe Veiga Leprevost & Javier A. Alfaro & Marcin Cieslik & Alexey I. Nesvizhskii, 2023. "Unraveling the glycosylated immunopeptidome with HLA-Glyco," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    9. Lei Xin & Rui Qiao & Xin Chen & Hieu Tran & Shengying Pan & Sahar Rabinoviz & Haibo Bian & Xianliang He & Brenton Morse & Baozhen Shan & Ming Li, 2022. "A streamlined platform for analyzing tera-scale DDA and DIA mass spectrometry data enables highly sensitive immunopeptidomics," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    10. Wen-Feng Zeng & Xie-Xuan Zhou & Sander Willems & Constantin Ammar & Maria Wahle & Isabell Bludau & Eugenia Voytik & Maximillian T. Strauss & Matthias Mann, 2022. "AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    11. Ashish Goyal & Jens Bauer & Joschka Hey & Dimitris N. Papageorgiou & Ekaterina Stepanova & Michael Daskalakis & Jonas Scheid & Marissa Dubbelaar & Boris Klimovich & Dominic Schwarz & Melanie Märklin &, 2023. "DNMT and HDAC inhibition induces immunogenic neoantigens from human endogenous retroviral element-derived transcripts," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    12. Yury Patskovsky & Aswin Natarajan & Larysa Patskovska & Samantha Nyovanie & Bishnu Joshi & Benjamin Morin & Christine Brittsan & Olivia Huber & Samuel Gordon & Xavier Michelet & Florian Schmitzberger , 2023. "Molecular mechanism of phosphopeptide neoantigen immunogenicity," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
    13. Kevin L. Yang & Fengchao Yu & Guo Ci Teo & Kai Li & Vadim Demichev & Markus Ralser & Alexey I. Nesvizhskii, 2023. "MSBooster: improving peptide identification rates using deep learning-based features," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

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