OncoPro 类肿瘤模型的免疫肽组学分析实现 MHC-I 富集与新抗原靶点发现

Cancer immunotherapy leverages the immune system's capacity to recognize and eliminate tumor cells through peptides presented by major histocompatibility complexes (MHCs). Immunopeptidomics, the large-scale identification of MHC-bound peptides, provides critical insights into tumor antigen presentation and supports the discovery of targets for personalized immunotherapies. Here, we describe a reproducible workflow for enrichment and profiling of MHC-I peptides from patient-derived tumoroid (also known as cancer organoid) models that recapitulate the complexity and heterogeneity of primary tumors. A panel of OncoPro™ Tumoroid Cell Lines was analyzed using LC-MS-based global proteomics. MHC-I profiling demonstrated high enrichment of HLA-A, HLA-B, and HLA-C proteins in the endometrial donor line HuEn033122, which was selected for immunopeptidome characterization. Tumoroids were cultured in OncoPro™ Tumoroid Culture Medium, pre-treated with 10 ng/mL interferon-gamma for 18 hours prior to sample collection to enhance expression of MHC-I expression and antigen presentation capacity, and collected as frozen cell pellets. Pellets of ten million cells were processed per the manufacturer's instructions for the different lysis buffers: Thermo Scientific™ Mem-PER™ Plus Membrane Solubilization Buffer, Thermo Scientific™ Pierce™ IP Lysis Buffer, Thermo Scientific™ T-PER Tissue Protein Extraction Reagent, and Thermo Scientific™ Pierce™ GPCR Extraction and Solubilization Buffer. MHC peptide complexes were immunoprecipitated with W6/32 antibody-coupled supports, eluted with 1% TFA, and analyzed by nanoLC-MS/MS on Thermo Scientific ™ Orbitrap™ instruments. Data was analyzed using PEAKS® Studio 12.5 using the DeepNovo Peptidome workflow (6-30 mers, 1% FDR, DeepNovo score ≥ 70%). Immunopeptidomic profiling revealed a dominant 9-mer peptide population (~53%), consistent with canonical MHC-I binding and confirming high-quality enrichment. This 9-mer dominance serves as a robust quality control indicator of workflow specificity and reproducibility. Integration of immunopeptidomic data with whole-exome and RNA sequencing, and bulk proteomics will enable identification of expressed, mutation-derived neoantigens unique to each tumoroid model. Collectively, this platform establishes a physiologically relevant and reproducible approach for neoantigen discovery, advancing precision cancer immunotherapies.