optiPRM: A Targeted Immunopeptidomics LC-MS Workflow With Ultra-High Sensitivity for the Detection of Mutation-Derived Tumor Neoepitopes From Limited Input Material

Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen 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 the 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 from as little as 2.5 × 10<sup>6</sup> cells input. Application of the workflow on small patient tumor samples allowed for the detection of five mutation-derived neoepitopes in three patients. One neoepitope was confirmed to be recognized by patient T cells. In conclusion, optiPRM, a targeted MS workflow reaching ultra-high sensitivity by per peptide parameter optimization, makes the identification of actionable neoepitopes possible from sample sizes usually available in the clinic.

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Publication Details

Journal
Molecular & Cellular Proteomics
Published
2024-08-05
DOI
https://doi.org/10.1016/j.mcpro.2024.100825
Citations
8
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
1.87

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article

optiPRM: A Targeted Immunopeptidomics LC-MS Workflow With Ultra-High Sensitivity for the Detection of Mutation-Derived Tumor Neoepitopes From Limited Input Material

Pornpimol Charoentong, Stefan Fröhling, Jonas D. Förster, Rienk Offringa et al.
8 citations
Molecular & Cellular Proteomics
Advanced biosensing and bioanalysis techniques
1.87
article

optiPRM: A Targeted Immunopeptidomics LC-MS Workflow With Ultra-High Sensitivity for the Detection of Mutation-Derived Tumor Neoepitopes From Limited Input Material

Pornpimol Charoentong, Stefan Fröhling, Jonas D. Förster, Rienk Offringa, Katharina A.M. Lindner, Inka Zörnig, Dirk Jäger, Marten Meyer, Jonas Philipp Becker, Isabel Poschke, Catharina Lotsch, Michael Volkmar, Michael Platten, Mogjiborahman Salek, Marc Schmitz, Frank Momburg, Yanhong Lyu, Angelika Beate Riemer
article en
8 citations

Abstract

Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen 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 the 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 from as little as 2.5 × 10<sup>6</sup> cells input. Application of the workflow on small patient tumor samples allowed for the detection of five mutation-derived neoepitopes in three patients. One neoepitope was confirmed to be recognized by patient T cells. In conclusion, optiPRM, a targeted MS workflow reaching ultra-high sensitivity by per peptide parameter optimization, makes the identification of actionable neoepitopes possible from sample sizes usually available in the clinic.

Molecular & Cellular ProteomicsVol. 23(9)
German Cancer Research Center (DE), Johannes Gutenberg University Mainz (DE), Heidelberg University (DE), University Hospital Heidelberg (DE), National Center for Tumor Diseases (DE), Helmholtz Institute Mainz (DE), German Center for Infection Research (DE), DKFZ-ZMBH Alliance (DE), University Hospital Carl Gustav Carus (DE)
Deutsches Krebsforschungszentrum, Dietmar Hopp Stiftung
Openalex Percentile: Top 14%
Advanced biosensing and bioanalysis techniques
1.87
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