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Integrated proteogenomic deep sequencing and analytics accurately identify non-canonical peptides in tumor immunopeptidomes

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Item Type:Preprint
Title:Integrated proteogenomic deep sequencing and analytics accurately identify non-canonical peptides in tumor immunopeptidomes
Creators Name:Chong, C. and Müller, M. and Pak, H.S. and Harnett, D. and Huber, F. and Grun, D. and Leleu, M. and Auger, A. and Arnaud, M. and Stevenson, B.J. and Michaux, J. and Bilic, I. and Hirsekorn, A. and Calviello, L. and Simó-Riudalbas, L. and Planet, E. and Lubiński, J. and Bryśkiewicz, M. and Wiznerowicz, M. and Xenarios, I. and Zhang, L. and Trono, D. and Harari, A. and Ohler, U. and Coukos, G. and Bassani-Sternberg, M.
Abstract:Efforts to precisely identify tumor human leukocyte antigen (HLA) bound peptides capable of mediating T cell-based tumor rejection still face important challenges. Recent studies suggest that non-canonical tumor-specific HLA peptides that derive from annotated non-coding regions could elicit anti-tumor immune responses. However, sensitive and accurate mass-spectrometry (MS)-based proteogenomics approaches are required to robustly identify these non-canonical peptides. We present an MS-based analytical approach that characterizes the non-canonical tumor HLA peptide repertoire, by incorporating whole exome sequencing, bulk and single cell transcriptomics, ribosome profiling, and a combination of two MS/MS search tools. This approach results in the accurate identification of hundreds of shared and tumor-specific non-canonical HLA peptides and of an immunogenic peptide from a downstream reading frame in the melanoma stem cell marker gene ABCB5. It holds great promise for the discovery of novel cancer antigens for cancer immunotherapy.
Source:bioRxiv
Publisher:Cold Spring Harbor Laboratory Press (U.S.A.)
Article Number:758680
Date:6 September 2019
Official Publication:https://doi.org/10.1101/758680

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