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The identification of T cell epitopes derived from tumour specific antigens remains a significant challenge for the development of peptide-based vaccines and immunotherapies. The use of mass spectrometry-based approaches (immunopeptidomics) can provide powerful new avenues for the identification of such epitopes. In this study we report the use of complementary peptide antigen enrichment methods and a comprehensive mass spectrometric acquisition strategy to provide in-depth immunopeptidome data for the THP-1 cell line, a cell line used widely as a model of human leukaemia. To accomplish this, we combined robust experimental workflows that incorporated ultrafiltration or off-line reversed phase chromatography to enrich peptide ligand as well as a multifaceted data acquisition strategy using an Orbitrap Fusion LC-MS instrument. Using the combined datasets from the two ligand enrichment methods we gained significant depth in immunopeptidome coverage by identifying a total of 41,816 HLA class I peptides from THP-1 cells, including a significant number of peptides derived from different oncogenes or over expressed proteins associated with cancer. The physicochemical properties of the HLA-bound peptides dictated their recovery using the two ligand enrichment approaches and their distribution across the different precursor charge states considered in the data acquisition strategy. The data highlight the complementarity of the two enrichment procedures, and in cases where sample is not limiting, suggest that the combination of both approaches will yield the most comprehensive immunopeptidome information.

Original publication

DOI

10.1016/j.molimm.2020.04.008

Type

Journal article

Journal

Molecular immunology

Publication Date

07/2020

Volume

123

Pages

7 - 17

Addresses

Department of Biochemistry and Molecular Biology and Infection and Immunity Program, Biomedicine Discovery Institute, Monash University, Clayton 3800, VIC, Australia.

Keywords

Cells, Cultured, Humans, Peptides, Peptide Library, Proteome, Antigens, Neoplasm, Epitopes, T-Lymphocyte, Ligands, Immunotherapy, Chromatography, Liquid, Proteomics, Databases, Protein, Mass Spectrometry, Leukemia, Myeloid, Acute, Data Mining, THP-1 Cells