ArticleProteomics2017
Data-Independent Acquisition of HLA Class I Peptidomes on the Q Exactive Mass Spectrometer Platform.
Article in Proteomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Koina: Democratizing machine learning for proteomics research.Nature communications · 2025Article
- HLA Ligand Atlas DIA: extending the benign immunopeptidomics resource with increased sensitivity through data-independent acquisition mass spectrometry.Journal for immunotherapy of cancer · 2025Article
- Toward the Development of a Novel Newborn Screening Modality: In-Depth Nontargeted Proteome Analysis of Dried Blood Spots with a Robotic Pipeline Using Low-Cost Iron Powders.Analytical chemistry · 2025Article
- Current perspectives on mass spectrometry-based immunopeptidomics: the computational angle to tumor antigen discovery.Journal for immunotherapy of cancer · 2023Review
- Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform.Nature communications · 2023Article
- Using mass spectrometry to identify neoantigens in autoimmune diseases: The type 1 diabetes example.Seminars in immunology · 2023Review
- Recent advances in immunopeptidomic-based tumor neoantigen discovery.Advances in immunology · 2023Article
- AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics.Nature communications · 2022Article
- Identification of tumor antigens with immunopeptidomics.Nature biotechnology · 2022Review
- Soluble HLA peptidome: A new resource for cancer biomarkers.Frontiers in oncology · 2022Review
- The Importance of Being Presented: Target Validation by Immunopeptidomics for Epitope-Specific Immunotherapies.Frontiers in immunology · 2022Review
- What Is the Role of HLA-I on Cancer Derived Extracellular Vesicles? Defining the Challenges in Characterisation and Potential Uses of This Ligandome.International journal of molecular sciences · 2021Review
- The Choice of Search Engine Affects Sequencing Depth and HLA Class I Allele-Specific Peptide Repertoires.Molecular & cellular proteomics : MCP · 2021Article
- Sensitive Immunopeptidomics by Leveraging Available Large-Scale Multi-HLA Spectral Libraries, Data-Independent Acquisition, and MS/MS Prediction.Molecular & cellular proteomics : MCP · 2021Article
- The Human Immunopeptidome Project: A Roadmap to Predict and Treat Immune Diseases.Molecular & cellular proteomics : MCP · 2020Article
- Identification of Tumor Antigens Among the HLA Peptidomes of Glioblastoma Tumors and Plasma.Molecular & cellular proteomics : MCP · 2019Article
- HLA-DO Modulates the Diversity of the MHC-II Self-peptidome.Molecular & cellular proteomics : MCP · 2019Article
- Identification of Tumor Antigens Among the HLA Peptidomes of Glioblastoma Tumors and Plasma.Molecular & cellular proteomics : MCP · 2018Article
- A tissue-based draft map of the murine MHC class I immunopeptidome.Scientific data · 2018Article
- Review
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Authors and funding
4 authors.
Funding
Abstract
The characterization of peptides presented by human leukocyte antigen (HLA) class I molecules is crucial for understanding immune processes, biomarker discovery, and the development of novel immunotherapies or vaccines. Mass spectrometry allows the direct identification of thousands of HLA-bound peptides from cell lines, blood, or tissue. In recent years, data-independent acquisition (DIA) mass spectrometry methods have evolved, promising to increase reproducibility and sensitivity over classical data-dependent acquisition (DDA) workflows. Here, we describe a DIA setup on the Q Exactive mass spectrometer, optimized regarding the unique properties of HLA class I peptides. The methodology enables sensitive and highly reproducible characterization of HLA peptidomes from individual cell lines. From up to 16 DDA analyses of 100 million human cells, more than 10 000 peptides could be confidently identified, serving as basis for the generation of spectral libraries. This knowledge enabled the subsequent interrogation of DIA data, leading to the identification of peptide sets with >90% overlap between replicate samples, a prerequisite for the comparative study of closely related specimens. Furthermore, >3000 peptides could be identified from just one million cells after DIA analysis using a library generated from 300 million cells. The reduction in sample quantity and the high reproducibility of DIA-based HLA peptidome analysis should facilitate personalized medicine applications.
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Registered trials
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