Poster session 2Peptide identification methodology introduces bias in the detected repertoire of MHC presented peptides

Abstract

Immunopeptidomic profiling with mass spectrometry has the capacity to directly identify peptide neo-antigens and provide a better understanding of the relationship between oncogenic processes, antigen presentation and immunity. Key to this is the use of search engines for the interpretation of mass spectra acquired after HLA peptide purification and LC-MS. In this study we present a comparison of three commonly used search engines across several immunopeptidomic datasets. We found that choice of search engine influences not only sensitivity but remarkably the repertoire of peptide sequences identified. Using NetMHC we validate our results showing that additional peptides identified are highly likely to be bound to a HLA protein. Based on this we investigate how search engine bias affects the outcome of an immunopeptidomic analyses given a background of different HLA alleles. We look in detail at this effect profiling several tumour samples with diverse HLA types.