Dataset Information

Identification of MHC ligands through allele guided isolation combined with machine learning for specific MHC assignment

ABSTRACT: Isolation of MHC ligands and subsequent analysis by mass spectrometry is considered the gold standard for defining targets for T cell-based immunotherapies. However, as many targets of high tumor-specificity are only presented at low abundance on the cell surface of tumor cells, the efficient isolation of these peptides is crucial for their successful detection. Furthermore, since multiple MHC alleles can present the same MHC ligand, improving the prediction and assignment to a specific MHC allele is highly desirable. Here, we demonstrate how optimizations of the MHC ligand isolation strategy support the identification of specific MHC ligands and how the hydrophobicity of presented peptides as well as their post-translational modifications need to be considered as exemplified by, the detection of cysteinylated MHC ligands from cancer germline antigens or point-mutated neoepitopes. To further improve the identification and characterization of MHC ligands, we developed a novel MHC class I ligand prediction algorithm (ARDisplay-I) that outperforms the current state-of-the-art. Moreover, ARDisplay-I facilitates the assignment of peptides to the appropriate MHC allele, especially if multiple alleles have to be considered. Implementing these strategies can augment the development of T cell receptor-based therapies by facilitating the identification of novel immunotherapy targets and enriching the resources available in the computational immunology field.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Suspension Culture

SUBMITTER: Martin Klatt

LAB HEAD: Martin Klatt

PROVIDER: PXD061101 | Pride | 2026-06-08

REPOSITORIES: Pride

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			Action	DRS
	Elmo_20221104_OP_MaKl_MHC_proj6_JJN3_class_I_20perc_rep1.raw	Raw
	Elmo_20221104_OP_MaKl_MHC_proj6_JJN3_class_I_20perc_rep1.raw_20250219_Byonic.mgf	Mgf
	Elmo_20221104_OP_MaKl_MHC_proj6_JJN3_class_I_20perc_rep1.raw_20250219_Byonic.mzid	Mzid
	Elmo_20221104_OP_MaKl_MHC_proj6_JJN3_class_I_20perc_rep2.raw	Raw
	Elmo_20221104_OP_MaKl_MHC_proj6_JJN3_class_I_20perc_rep2.raw_20250219_Byonic.mgf	Mgf

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Publications

Identification of MHC Ligands Through Allele-Guided Isolation Combined With Machine Learning for Improved MHC Assignment Using ARDisplay-I.

Mecklenbräuker Shima S Skoczylas Piotr P Biernat Paweł P Zaghla Badeel Kh Q BKQ Atay Bilge B Hossam Mai M Król-Józaga Bartłomiej B Jasiński Maciej M Pienkowski Victor Murcia VM Sanecka-Duin Anna A Popp Oliver O Haji Mohamed M Szatanek Rafał R Mertins Philipp P Kaczmarczyk Jan J Keller Ulrich U Blum Agnieszka A Klatt Martin G MG

Molecular & cellular proteomics : MCP 20260327 5

The isolation of major histocompatibility complex (MHC) ligands and subsequent analysis by mass spectrometry is considered the gold standard for defining targets for T cell-based immunotherapies. However, as many targets of high tumor specificity are only presented at low abundance on the cell surface of tumor cells, the efficient isolation of these peptides is crucial for their successful detection. Here, we demonstrate how optimizing the MHC ligand isolation strategy, based on both the present ...[more]

PMID: 41903651

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Project description:The majority of peptides presented by MHC class I results from proteasomal protein turnover. The specialized immunoproteasome, which is induced during inflammation, plays a major role in antigenic peptide generation. However, other cellular proteases can, either alone or together with the proteasome, contribute peptides for MHC class I loading non-canonically. We used an im-munopeptidomics workflow combined with a prediction software for proteasomal cleavage probabilities to analyze how inflammatory conditions affect proteasomal processing of immune epitopes presented by A549 cells. Treatment of A549 cells with IFNγ enhanced proteasomal cleavage probability of MHC class I ligands for both, the constitutive proteasome and the im-munoproteasome. Furthermore, IFNγ alters the contribution of the different HLA allotypes to the immunopeptidome. When we calculated HLA allotype-specific proteasomal cleavage probabili-ties for MHC class I ligands, peptides presented by HLA-A*30:01 showed characteristics hinting at a reduced C-terminal proteasomal cleavage probability independently of the type of proteasome. This was confirmed by HLA-A*30:01 ligands from the immune epitope database, which also showed this effect. Furthermore, two additional HLA allotypes, namely HLA-A*03:01 and HLA-A*11:01, presented peptides with a markedly reduced C-terminal proteasomal cleavage probability. Peptides eluted from all three HLA allotypes shared a peptide binding motif with a C-terminal lysine residue suggesting that this lysine residue impairs proteasome-dependent HLA ligand production and might, in turn, favor peptide generation by other cellular proteases. The mass spectrometry raw files used in this study were originally produced for a previous publication, where they were utilized to address the influence of cigarette smoke on the antiviral T-cell immune response. Here, we have reanalyzed the data to investigate processing of MHC class I ligands by c20S or i20S, respectively. Original publication: Chen, J.; Wang, X.; Schmalen, A.; Haines, S.; Wolff, M.; Ma, H.; Zhang, H.; Stoleriu, M.G.; Nowak, J.; Nakayama, M.; et al. Antiviral CD8(+) T cell immune responses are impaired by cigarette smoke and in COPD. Eur Respir J 2023, doi:10.1183/13993003.01374-2022.