高灵敏度靶向质谱实现HLA提呈抗原的定量，用于TCR-T治疗靶点的发现

Background Human leukocyte antigens (HLA) are key mediators of adaptive immunity, presenting antigenic peptides derived from self and non-self proteins for immune surveillance. Tumor-specific neoantigens generated by somatic mutations represent key determinants of immune recognition and are central to the development of targeted immunotherapies. Recent advances in immunopeptidomics have enabled systematic identification of these peptides; however, accurate quantification of immunogenic epitopes remains essential to assess their therapeutic relevance. Precise measurement of (neo)antigen abundance can inform the design of T-cell receptor (TCR)-based therapeutics, as well as personalized vaccines and cell therapies. Highly sensitive, quantitative methods for profiling peptide presentation across cell or tissue materials are therefore critical to advancing precision immuno-oncology and immune-modulatory therapies. Method Current methodologies to measure presented antigens are hampered by low sensitivity, and laborious optimization procedures. To overcome these issues, we applied a targeted mass spectrometry approach (FAIMS-PRM) combined with a one-step collision energy (CE) optimization, as described in a recent publication (Salek et al. 2024) workflow to systematically optimize collision energy and improve assay sensitivity. This streamlined method enables robust, cost- and time-efficient development and optimization of targeted assays for immunopeptides using minimal input material: 25 million cells or 15 mg of fresh-frozen tissue. Incorporating stable isotope-labeled internal standards (SIS peptides) allowed absolute quantification and estimation of copy number per cell. Results To demonstrate the performance of the optimized workflow, we quantified HLA I-presented (neo)antigens in multiple cell lines, including SK-MEL-5, Raji and HCT116. The analysis panel comprised peptides derived from well-established TCR-T and tumor-specific antigen (TSA) targets such as PRAME, MAGE-A1, and NY-ESO-1, alongside candidate antigens identified in prior discovery studies. Application of the collision energy-based optimization improved signal intensity for approximately 50% of targeted peptides compared with default settings. The method achieved lower limits of quantification (LLOQ) in the low single-digit range (1-3 copies per cell), enabling precise quantification of low-abundance immunopeptides. These results illustrate the sensitivity and robustness of the workflow for accurate measurement of clinically relevant HLA-presented targets. In conclusion, these advances provide a sensitive and efficient workflow for quantitative assessment of HLA-presented peptides across disease and healthy samples, supporting identification of promising targets for immunotherapy development.