Journal Article

DKFZ-2024-01616

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png optiPRM: A targeted immunopeptidomics LC-MS workflow with ultra-high sensitivity for the detection of mutation-derived tumor neoepitopes from limited input material.

Salek, M. (First author)DKFZ* ; Förster, J. (First author)DKFZ* ; Becker, J. (First author)DKFZ* ; Meyer, M.DKFZ* ; Charoentong, P.DKFZ* ; Lyu, Y.DKFZ* ; Lindner, K.DKFZ* ; Lotsch, C.DKFZ* ; Volkmar, M. ; Momburg, F.DKFZ* ; Poschke, I.DKFZ* ; Fröhling, S.DKFZ* ; Schmitz, M.DKFZ* ; Offringa, R.DKFZ* ; Platten, M.DKFZ* ; Jäger, D.DKFZ* ; Zörnig, I.DKFZ* ; Riemer, A. (Last author)DKFZ*

2024
The American Society for Biochemistry and Molecular Biology Bethesda, Md.

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Please use a persistent id in citations: doi:10.1016/j.mcpro.2024.100825

Abstract: Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor (TCR)-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen (HLA) 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 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 (PDX) from as little as 2.5×106 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, which makes the identification of actionable neoepitopes possible from sample sizes usually available in the clinic.

Note: #EA:D410#LA:D410# / HI-TRON / 2024, 23(9), art. no. 100825

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Contributing Institute(s):

1. Immuntherapie und -prävention (D410)
2. AG Antigenpräsentation und T/NK-Zell-Akt (D121)
3. Angewandte Tumor-Immunität (D120)
4. DKTK HD zentral (HD01)
5. KKE Neuroimmunologie und Hirntumorimmunologie (D170)
6. Translationale Medizinische Onkologie (B340)
7. DKTK Koordinierungsstelle Dresden (DD01)
8. Molekulare Grundlagen Gastrointestinaler Tumoren (D200)

Research Program(s):

1. 314 - Immunologie und Krebs (POF4-314) (POF4-314)

Appears in the scientific report 2024

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