- Author
- Jonas Scheid, Steffen Lemke, Naomi Hoenisch-Gravel, Anna Dengler, Timo Sachsenberg, Arthur Declercq (UGent) , Ralf Gabriels (UGent) , Jens Bauer, Marcel Wacker, Leon Bichmann, Lennart Martens (UGent) , Marissa L. Dubbelaar, Sven Nahnsen and Juliane S. Walz
- Organization
- Project
-
- A novel era in proteomics-based protein PTM discovery through deep learning approaches
- Advanced AI-driven Bioinformatics Solutions for Performant Peptidomics
- ProteinContour: proteome-scale unraveling of the relation between post-translational modifications, biophysical properties, interactions and sub-cellular location of proteins.
- Improved data-driven bioinformatics tools to greatly extend neo- and xeno-epitope landscapes detected by immunopeptidomics.
- Immunopeptidomics-based Development of Next-Generation Bacterial mRNA Vaccines
- Proteomics-derived epitopes for dramatically improved anticancer and antibacterial vaccine development
- Abstract
- Confident identification of human leukocyte antigen (HLA)-presented peptides is crucial for advancing cancer immunotherapy. We present MHCquant2, a scalable and modular Nextflow pipeline integrated into nf-core as a reproducible, portable, and standardized workflow for immunopeptidomics. This integration allows a community-driven, robust solution for high-throughput analyses across operating systems and cloud infrastructures. MHCquant2 integrates open-source tools including OpenMS, DeepLC, and MS2PIP, improving peptide identifications by up to 27% across diverse MS platforms, particularly enriching low-abundant peptides. MHCquant2 demonstrates state-of-the-art performance on our novel benignMHCquant2 dataset (n = 92) and expands the benign human immunopeptidome by over 160,000 unique naturally presented HLA peptides.
- Keywords
- Immunopeptidomics, Nextflow, Nf-core, Pipeline, Mass spectrometry, HLA, Immunotherapy, Open-source, MONOCLONAL-ANTIBODIES, IDENTIFICATION, TOOLS
Downloads
-
publisher version.pdf
- full text (Published version)
- |
- open access
- |
- |
- 3.01 MB
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01K6DBB8FZFT4C5KN7KMA74RZ9
- MLA
- Scheid, Jonas, et al. “MHCquant2 Refines Immunopeptidomics Tumor Antigen Discovery.” GENOME BIOLOGY, vol. 26, no. 1, 2025, doi:10.1186/s13059-025-03763-8.
- APA
- Scheid, J., Lemke, S., Hoenisch-Gravel, N., Dengler, A., Sachsenberg, T., Declercq, A., … Walz, J. S. (2025). MHCquant2 refines immunopeptidomics tumor antigen discovery. GENOME BIOLOGY, 26(1). https://doi.org/10.1186/s13059-025-03763-8
- Chicago author-date
- Scheid, Jonas, Steffen Lemke, Naomi Hoenisch-Gravel, Anna Dengler, Timo Sachsenberg, Arthur Declercq, Ralf Gabriels, et al. 2025. “MHCquant2 Refines Immunopeptidomics Tumor Antigen Discovery.” GENOME BIOLOGY 26 (1). https://doi.org/10.1186/s13059-025-03763-8.
- Chicago author-date (all authors)
- Scheid, Jonas, Steffen Lemke, Naomi Hoenisch-Gravel, Anna Dengler, Timo Sachsenberg, Arthur Declercq, Ralf Gabriels, Jens Bauer, Marcel Wacker, Leon Bichmann, Lennart Martens, Marissa L. Dubbelaar, Sven Nahnsen, and Juliane S. Walz. 2025. “MHCquant2 Refines Immunopeptidomics Tumor Antigen Discovery.” GENOME BIOLOGY 26 (1). doi:10.1186/s13059-025-03763-8.
- Vancouver
- 1.Scheid J, Lemke S, Hoenisch-Gravel N, Dengler A, Sachsenberg T, Declercq A, et al. MHCquant2 refines immunopeptidomics tumor antigen discovery. GENOME BIOLOGY. 2025;26(1).
- IEEE
- [1]J. Scheid et al., “MHCquant2 refines immunopeptidomics tumor antigen discovery,” GENOME BIOLOGY, vol. 26, no. 1, 2025.
@article{01K6DBB8FZFT4C5KN7KMA74RZ9,
abstract = {{Confident identification of human leukocyte antigen (HLA)-presented peptides is crucial for advancing cancer immunotherapy. We present MHCquant2, a scalable and modular Nextflow pipeline integrated into nf-core as a reproducible, portable, and standardized workflow for immunopeptidomics. This integration allows a community-driven, robust solution for high-throughput analyses across operating systems and cloud infrastructures. MHCquant2 integrates open-source tools including OpenMS, DeepLC, and MS2PIP, improving peptide identifications by up to 27% across diverse MS platforms, particularly enriching low-abundant peptides. MHCquant2 demonstrates state-of-the-art performance on our novel benignMHCquant2 dataset (n = 92) and expands the benign human immunopeptidome by over 160,000 unique naturally presented HLA peptides.}},
articleno = {{290}},
author = {{Scheid, Jonas and Lemke, Steffen and Hoenisch-Gravel, Naomi and Dengler, Anna and Sachsenberg, Timo and Declercq, Arthur and Gabriels, Ralf and Bauer, Jens and Wacker, Marcel and Bichmann, Leon and Martens, Lennart and Dubbelaar, Marissa L. and Nahnsen, Sven and Walz, Juliane S.}},
issn = {{1474-760X}},
journal = {{GENOME BIOLOGY}},
keywords = {{Immunopeptidomics,Nextflow,Nf-core,Pipeline,Mass spectrometry,HLA,Immunotherapy,Open-source,MONOCLONAL-ANTIBODIES,IDENTIFICATION,TOOLS}},
language = {{eng}},
number = {{1}},
pages = {{17}},
title = {{MHCquant2 refines immunopeptidomics tumor antigen discovery}},
url = {{http://doi.org/10.1186/s13059-025-03763-8}},
volume = {{26}},
year = {{2025}},
}
- Altmetric
- View in Altmetric
- Web of Science
- Times cited: