Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
SHR Neuro Krebs Kardio Lipid Stoffw Microb
Tretter, C; Kratzig, ND; Pecoraro, M; Lange, S; Seifert, P; von Frankenberg, C; Untch, J; Zuleger, G; Wilhelm, M; Zolg, DP; Dreyer, FS; Braunlein, 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; Grutzmann, K; Pfutze, K; Klink, B; Schrock, E; Haller, B; Kuster, B; Mann, M; Weichert, W; Frohling, S; Rad, R; Hiltensperger, M; Krackhardt, AM.
Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification
NAT COMMUN. 2023; 14(1): 4632
Doi: 10.1038/s41467-023-39570-7
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- Co-Autor*innen der Med Uni Graz
- Jost Philipp
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- Abstract:
- RNA variants derived from cancer-associated RNA editing events can be a source of neoantigens. Here, based on a proteogenomic pipeline combining DNA and RNA sequencing with MS-based immunopeptidomics, the authors identity and validate potential neoantigen candidates in patients with different tumor entities, highlighting RNA as important neoantigen source. 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.