Bioinformatics strategies for the comprehensive characterization of immunopeptidome landscapes. (October 2022)

• Record Type: Journal Article
• Authors: Bedran, Georges; Kote, Sachin; Mayordomo, Marcos Yébenes; Pawlicka, Kamila; Saxena, Satya; Goodlett, David; Dapic, Irena; Alfaro, Javier Antonio
• Is Part Of: Molecular immunology. Volume 150(2022)
• Page Start: 6
• Publication Date: 2022-10
• Subjects: Immunochemistry -- Periodicals; Molecular biology -- Periodicals; Immunochemistry -- Periodicals; Allergy and Immunology -- Periodicals; Molecular Biology -- Periodicals; Immunochimie -- Périodiques; Biologie moléculaire -- Périodiques; Immunochemistry; Molecular biology; Periodicals; Electronic journals; 571.96
• DOI: 10.1016/j.molimm.2022.05.030
• Languages: English
• ISSNs: 0161-5890

Abstract

Abstract : T cell recognition of antigen presenting cells depends on the expression of a spectrum of peptides bound to Major Histocompatibility Complex class I (MHC-I) and class II (MHC-II) molecules. These presented peptides, collectively called the immunopeptidome, have gained significant interest in the context of developing peptide vaccines. However, the immunopeptidome is notoriously difficult to study. State of the art mass-spectrometry strategies identify just a few thousands of presented peptides per experiment, while an estimated 100, 000 MHC molecules are known to be presented at the cell surface. The international center for cancer vaccine science is innovating experimental and bioinformatics pipelines to extract as much information as possible from a single experiment. Here we present a bioinformatics strategy for the comprehensive characterization of immunopeptidomes and an analysis highlighting recent high-quality datasets in PRIDE.