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
3 Citations (Scopus)


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 languageEnglish
Article number4632
JournalNature Communications
Issue number1
Publication statusPublished - 12.2023

Research Areas and Centers

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

DFG Research Classification Scheme

  • 205-14 Haematology, Oncology

Cite this