免疫原性
计算生物学
核糖核酸
鉴定(生物学)
生物
癌症
抗原
遗传学
基因
植物
作者
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 Bauer
标识
DOI:10.1038/s41467-023-39570-7
摘要
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.
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