EMERGE INDUSTRY Episode 1: Immunopeptidomics: Discovery of MHC class I and class II neoantigens

Human leukocyte antigen-associated peptides, known as immunopeptides, play an essential role in adaptive immunity by activating and ensuring the specificity of T-cells. The identification and quantification of the immunopeptidome bear the potential to enable personalized treatments, especially in cancers, vaccines, infectious, and autoimmune diseases. Here, we introduce a semi-automated workflow to robustly identify immunopeptides from low amounts of cultured cells and tissue samples by systematically optimizing each step of the sample preparation and acquisition.

We optimized the native lysis and immunoprecipitation workflow while ensuring scalability and reproducibility. The workflow was optimized on healthy lung tissue, is sensitive, and is 96-well compatible and automated thanks to the use of high capacity, ferromagnetic microparticles. We could identify over 2,800 class-I immunopeptides when processing as little as 2.5 mg and more than 11,000 class-I and more than 10,000 class-II immunopeptides when preparing 15 mg fresh frozen tissue.

We applied the pipeline to a cohort of 12 cancerous and matched healthy lung tissues from as little as 15 mg tissue, whereby we could identify more than 11,000 class-I immunopeptides and more than 9,000 class-II on average. For class-I, matched samples clustered together, while more than 3,000 immunopeptides were upregulated in the cancer tissues, with a significant enrichment for proteins related to lung cancer. Overall, we established a scalable, efficient pipeline for cell line and tissues immunopeptidomics for class-I and II that generates high-quality identifications and that only requires small amounts of input material and is ready to shed light into immunopeptidomics heterogeneity through large-scale profiling of patients.