optiPRM: A targeted immunopeptidomics LC-MS workflow with ultra-high sensitivity for the detection of mutation-derived tumor neoepitopes from limited input material.
Journal
Molecular & cellular proteomics : MCP
ISSN: 1535-9484
Titre abrégé: Mol Cell Proteomics
Pays: United States
ID NLM: 101125647
Informations de publication
Date de publication:
05 Aug 2024
05 Aug 2024
Historique:
received:
26
04
2024
revised:
17
07
2024
accepted:
01
08
2024
medline:
8
8
2024
pubmed:
8
8
2024
entrez:
7
8
2024
Statut:
aheadofprint
Résumé
Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor (TCR)-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen (HLA) class I molecules to cytotoxic T cells. Such neoepitopes can for example arise from somatic mutations and their identification is crucial for the rational design of new therapeutic interventions. Liquid chromatography mass spectrometry (LC-MS)-based immunopeptidomics is the only method to directly prove actual peptide presentation and we have developed a parameter optimization workflow to tune targeted assays for maximum detection sensitivity on a per peptide basis, termed optiPRM. Optimization of collision energy using optiPRM allows for improved detection of low abundant peptides that are very hard to detect using standard parameters. Applying this to immunopeptidomics, we detected a neoepitope in a patient-derived xenograft (PDX) from as little as 2.5×10
Identifiants
pubmed: 39111711
pii: S1535-9476(24)00115-4
doi: 10.1016/j.mcpro.2024.100825
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
100825Informations de copyright
Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
COMPETING INTERESTS The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.