TY  - JOUR
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  - Börries, 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
TI  - Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification.
JO  - Nature Communications
VL  - 14
IS  - 1
SN  - 2041-1723
CY  - [London]
PB  - Nature Publishing Group UK
M1  - DKFZ-2023-01572
SP  - 4632
PY  - 2023
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.
LB  - PUB:(DE-HGF)16
C6  - pmid:37532709
DO  - DOI:10.1038/s41467-023-39570-7
UR  - https://inrepo02.dkfz.de/record/277913
ER  -