Abstract 5376: Quantitative profiling of HLA class I and class II antigens and neoantigens in tissue biopsy and PBMC samples using an optimized mass spectrometry-based workflow
Authors: Ilja E. Shapiro, Marco Tognetti, Tikira Temu, Oliver M. Bernhardt, Daniel Redfern, Yuehan Feng, Roland Bruderer, Lukas Reiter
Journal: Cancer Research (2024)

Abstract Major histocompatibility complex (MHC) molecules play a central role in orchestrating immune responses by presenting antigenic peptides derived from both self and foreign proteins. In the context of cancer, understanding the repertoire of tumor-associated antigens (TAAs) presented by MHC molecules (or HLA molecules in human) is crucial for deciphering how the immune system recognizes and responds to malignant cells. The identification of neoantigens, unique to individual tumors due to somatic mutations, has become a focal point in immunopeptidomic studies. One significant hurdle in systematic immunopeptidomics analysis is the high input material requirement. Here, we present a semi-automated workflow to robustly identify and quantify immunopeptides from reduced amounts of clinical tissue biopsy and peripheral blood mononuclear cell samples. At the core of immunopeptidomics is the enrichment of HLA-associated peptides, followed by identification using mass spectrometry and bioinformatics tools. We optimized the native lysis and a sequential immunoprecipitation workflow for both class I and class II immunopeptides while ensuring scalability and reproducibility. Leveraging the magnetic properties of the beads, 1,000 samples can be processed within a week by a single operator. For both tissue and PBMC samples, we performed a systematic ramping experiment starting with as little as 2.5mg tissue or 5 million PBMCs. In all experiments, The established sample preparation offers high reproducibility and identifications of good quality: 1) Class-I immunopeptides: &amp;gt;60% of the peptides identified are 9-mers, &amp;gt;80% predicted strong binders, and the expected amino acids are enriched at the anchor positions; 2) Class-II immunopeptides, &amp;gt;50% of the peptides identified are 14-to-16-mers, and &amp;gt;50% are predicted strong binders. Furthermore, the pipeline is highly sensitive as we could still identify over 2,800 class-I immunopeptides when processing 2.5 mg fresh frozen tissue and 2,000 - 3,000 class-I immunopeptides when starting from 5 million PBMCs. Furthermore, the developed immunopeptidomics workflow was deployed to profile a cohort of 12 cancerous and matched healthy lung tissue samples. Their Class-I immunopeptidomes clearly displayed a pattern where matched tissues from each subject cluster together, further underlining the fact that the intricate immune-tumor interface is highly personalized. Overall, we established a robust pipeline for for class-I and II immunopeptidome profiling from clinically relevant sample types. Taking advantage of the nature of mass spectrometry-based methods, customized targeted assays can be developed without the need for affinity reagent, allowing specific and absolute quantification of any immunopeptide of interest. Citation Format: Ilja E. Shapiro, Marco Tognetti, Tikira Temu, Oliver M. Bernhardt, Daniel Redfern, Yuehan Feng, Roland Bruderer, Lukas Reiter. Quantitative profiling of HLA class I and class II antigens and neoantigens in tissue biopsy and PBMC samples using an optimized mass spectrometry-based workflow [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5376.