Lots of immunotherapeutic approaches use respective tumour antigens to induce anti-tumour T cell responses. It means that identifying antigens that are present on the tumour cell surface naturally and are tumour-exclusive is a key step. Reference databases of such benign tissue derived HLA ligands is limited and MS-Based immunopeptidomics is the best available solution. However, the low sensitivity of shotgun MS discovery approaches remains the bottle neck of this method that limits the comprehensive analysis of immunopeptidome.
Ion mobility separation (IMS) coupled with MS adds an additional separation dimension that can improve sensitivity and speed of analysis for large cohort samples. multiple ion mobility resolved MS scans in addition to retention time, fragment spectra and mass-to-charge ratio can improve resolution. This paper reports on the implementation of TOF-IMS-MS for immunopeptidomics and its application for next-generation tumour antigen discovery. This approach not only enabled the large-scale expansion of benign reference databases, but also, could discover the not yet described tumour antigens using de novo.
How was PEAKS used?
Database searches were performed using PEAKS Studio 10.6 against a database containing 20,385 reviewed human UniProt entries downloaded on 2020-10-14. For the HNSCC the corresponding mutations were added to the reference database. The enzyme specificity was set to “none”, precursor peptide mass error tolerances were set to 5 ppm (orbitrap MS data) or 20 ppm (TOFIMS data) and 0.02 Da for fragment ions. Oxidized methionine was set as variable modification, with three possible modifications allowed per peptide. Peptide lengths were set to 8–16 amino acids for HLA class I and 8–30 amino acids for HLA class II. A 1% false discovery rate (FDR) was calculated using a decoy database search approach.
Hoenisch Gravel, Naomi, et al. “TOFIMS mass spectrometry-based immunopeptidomics refines tumor antigen identification.” Nature Communications 14.1 (2023): 7472. https://doi.org/10.1038/s41467-023-42692-7
Abstract
T cell recognition of human leukocyte antigen (HLA)-presented tumor-associated peptides is central for cancer immune surveillance. Mass spectrometry (MS)-based immunopeptidomics represents the only unbiased method for the direct identification and characterization of naturally presented tumor-associated peptides, a key prerequisite for the development of T cell-based immunotherapies. This study reports on the implementation of ion mobility separation-based time-of-flight (TOFIMS) MS for next-generation immunopeptidomics, enabling high-speed and sensitive detection of HLA-presented peptides. Applying TOFIMS-based immunopeptidomics, a novel extensive benignTOFIMS dataset was generated from 94 primary benign samples of solid tissue and hematological origin, which enabled the expansion of benign reference immunopeptidome databases with > 150,000 HLA-presented peptides, the refinement of previously described tumor antigens, as well as the identification of frequently presented self antigens and not yet described tumor antigens comprising low abundant mutation-derived neoepitopes that might serve as targets for future cancer immunotherapy development.