{"doi":"10.1016/j.mcpro.2023.100563","title":"Sensitive, High-Throughput HLA-I and HLA-II Immunopeptidomics Using Parallel Accumulation-Serial Fragmentation Mass Spectrometry","abstract":"Comprehensive and in-depth identification of the human leukocyte antigen class I (HLA-I) and class II (HLA-II) tumor immunopeptidome can inform the development of cancer immunotherapies. Mass spectrometry (MS) is a powerful technology for direct identification of HLA peptides from patient-derived tumor samples or cell lines. However, achieving sufficient coverage to detect rare and clinically relevant antigens requires highly sensitive MS-based acquisition methods and large amounts of sample. While immunopeptidome depth can be increased by off-line fractionation prior to MS, its use is impractical when analyzing limited amounts of primary tissue biopsies. To address this challenge, we developed and applied a high-throughput, sensitive, and single-shot MS-based immunopeptidomics workflow that leverages trapped ion mobility time-of-flight MS on the Bruker timsTOF single-cell proteomics system (SCP). We demonstrate greater than twofold improved coverage of HLA immunopeptidomes relative to prior methods with up to 15,000 distinct HLA-I and HLA-II peptides from 4e7 cells. Our optimized single-shot MS acquisition method on the timsTOF SCP maintains high coverage, eliminates the need for off-line fractionation, and reduces input requirements to as few as 1e6 A375 cells for >800 distinct HLA-I peptides. This depth is sufficient to identify HLA-I peptides derived from cancer-testis antigen and noncanonical proteins. We also apply our optimized single-shot SCP acquisition methods to tumor-derived samples, enabling sensitive, high-throughput, and reproducible immunopeptidome profiling with detection of clinically relevant peptides from less than 4e7 cells or 15 mg wet weight tissue.","journal":"Molecular & Cellular Proteomics","year":2023,"id":320234,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":50,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9606,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1019628,"name":"Claudia Ctortecka","orcid":"0000-0002-6886-8936","position":1,"is_corresponding":false},{"id":640583,"name":"Alvaro Sebastian Vaca Jácome","orcid":"0000-0001-7664-4660","position":2,"is_corresponding":false},{"id":44968,"name":"Susan Klaeger","orcid":"0000-0002-0074-5163","position":3,"is_corresponding":false},{"id":1030767,"name":"Eva K. Verzani","orcid":"0009-0004-0846-4878","position":4,"is_corresponding":false},{"id":1030768,"name":"Gabrielle M. Hernandez","orcid":"0009-0005-0494-0467","position":5,"is_corresponding":false},{"id":6645,"name":"Namrata D. Udeshi","orcid":"0000-0001-5312-1402","position":6,"is_corresponding":false},{"id":2216,"name":"Karl R. Clauser","orcid":"0000-0002-1052-9456","position":7,"is_corresponding":false},{"id":554219,"name":"Jennifer G. Abelin","orcid":"0000-0001-5262-7241","position":8,"is_corresponding":false},{"id":2226,"name":"Steven A. Carr","orcid":"0000-0002-7203-4299","position":9,"is_corresponding":false},{"id":1031450,"name":"Kshiti Meera Phulphagar","orcid":null,"position":0,"is_corresponding":true}],"reference_count":59,"raw_metadata":null,"created_at":"2026-07-19T01:07:22.377587Z","pmid":"37142057","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}