Proteomics

Dataset Information

0

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.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Celina Tretter  

LAB HEAD: Angela Krackhardt

PROVIDER: PXD037655 | Pride | 2023-05-16

REPOSITORIES: Pride

Dataset's files

Source:
altmetric image

Publications

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

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

Nature communications 20230802 1


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 sequen  ...[more]

Similar Datasets

2024-01-31 | E-MTAB-13635 | biostudies-arrayexpress
2017-04-06 | PXD004894 | Pride
2024-11-07 | PXD054579 | Pride
2024-06-30 | E-MTAB-14130 | biostudies-arrayexpress
2023-03-21 | PXD034772 | Pride
2022-05-25 | PXD027766 | Pride
2023-12-01 | GSE248401 | GEO
2024-05-07 | PXD043737 | Pride
2024-06-18 | PXD053200 | Pride
2018-10-11 | E-MTAB-6993 | biostudies-arrayexpress