@article{9ddcae7fe1da40f98f1948e2a44a527e,
title = "Database search engines and target database features impinge upon the identification of post-translationally cis-spliced peptides in HLA class I immunopeptidomes",
abstract = "Unconventional epitopes presented by HLA class I complexes are emerging targets for T cell targeted immunotherapies. Their identification by mass spectrometry (MS) required development of novel methods to cope with the large number of theoretical candidates. Methods to identify post-translationally spliced peptides led to a broad range of outcomes. We here investigated the impact of three common database search engines – that is, Mascot, Mascot+Percolator, and PEAKS DB – as final identification step, as well as the features of target database on the ability to correctly identify non-spliced and cis-spliced peptides. We used ground truth datasets measured by MS to benchmark methods{\textquoteright} performance and extended the analysis to HLA class I immunopeptidomes. PEAKS DB showed better precision and recall of cis-spliced peptides and larger number of identified peptides in HLA class I immunopeptidomes than the other search engine strategies. The better performance of PEAKS DB appears to result from better discrimination between target and decoy hits and hence a more robust FDR estimation, and seems independent to peptide and spectrum features here investigated.",
keywords = "HLA, immunopeptidome, Mascot, PEAKS, peptide splicing",
author = "Michele Mishto and Yehor Horokhovskyi and Cormican, {John A.} and Xiaoping Yang and Steven Lynham and Henning Urlaub and Juliane Liepe",
note = "Funding Information: We thank for technical assistance M. Peakman, W. Scott and D. Muharemagic (KCL), P. Faridi, N. Croft and A. Purcell (Monash). The study was in part supported by: (i) MPI-BPC collaboration agreement 2018, Cancer Research UK (C67500; A29686) and National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy's and St Thomas{\textquoteright} NHS Foundation Trust and King's College London and/or the NIHR Clinical Research Facility to MM; (ii) European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 945528) to JL. YH and JAC are supported by the International Max-Planck Research School (IMPRS) for Genome Science. Funding Information: We thank for technical assistance M. Peakman, W. Scott and D. Muharemagic (KCL), P. Faridi, N. Croft and A. Purcell (Monash). The study was in part supported by: (i) MPI‐BPC collaboration agreement 2018, Cancer Research UK (C67500; A29686) and National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy's and St Thomas{\textquoteright} NHS Foundation Trust and King's College London and/or the NIHR Clinical Research Facility to MM; (ii) European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 945528) to JL. YH and JAC are supported by the International Max‐Planck Research School (IMPRS) for Genome Science. Publisher Copyright: {\textcopyright} 2022 The Authors. Proteomics published by Wiley-VCH GmbH.",
year = "2022",
month = may,
doi = "10.1002/pmic.202100226",
language = "English",
volume = "22",
journal = "Proteomics",
issn = "1615-9853",
publisher = "Wiley-VCH Verlag",
number = "10",
}