Reference
Reference TypeLiterature
TitleMass Spectrometry Profiling of HLA-Associated Peptidomes in Mono-allelic Cells Enables More Accurate Epitope Prediction.
AuthorsJennifer G Abelin; Derin B Keskin; Siranush Sarkizova; Christina R Hartigan; Wandi Zhang; John Sidney; Jonathan Stevens; William Lane; Guang Lan Zhang; Thomas M Eisenhaure; Karl R Clauser; Nir Hacohen; Michael S Rooney; Steven A Carr; Catherine J Wu
AffiliationsBroad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA; Harvard Medical School, Boston, MA, 02115, USA; Department of Computer Science, Metropolitan College, Boston University, Boston, MA, 02215, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02142, USA; La Jolla Institute for Allergy and Immunology, 92037, La Jolla, CA; Tissue Typing Laboratory, Brigham and Women's Hospital, Boston, MA, 02115, USA; Center for Cancer Immunology, Massachusetts General Hospital, Boston, MA, 02114, USA. Electronic address: nhacohen@mgh.harvard.edu; Harvard/MIT Division of Health Sciences and Technology, Cambridge, Massachusetts, 02139 USA; Neon Therapeutics, Cambridge, MA, 02139, USA. Electronic address: mrooney@neontherapeutics.com; Broad Institute of MIT and Harvard, Cambridge, MA, USA. Electronic address: scarr@broad.mit.edu; Harvard Medical School, Boston, MA, 02115, USA. Electronic address: cwu@partners.org.
JournalImmunity
Year2017
AbstractIdentification of human leukocyte antigen (HLA)-bound peptides by liquid chromatography-tandem mass spectrometry (LC-MS/MS) is poised to provide a deep understanding of rules underlying antigen presentation. However, a key obstacle is the ambiguity that arises from the co-expression of multiple HLA alleles. Here, we have implemented a scalable mono-allelic strategy for profiling the HLA peptidome. By using cell lines expressing a single HLA allele, optimizing immunopurifications, and developing an application-specific spectral search algorithm, we identified thousands of peptides bound to 16 different HLA class I alleles. These data enabled the discovery of subdominant binding motifs and an integrative analysis quantifying the contribution of factors critical to epitope presentation, such as protein cleavage and gene expression. We trained neural-network prediction algorithms with our large dataset (>24,000 peptides) and outperformed algorithms trained on datasets of peptides with measured affinities. We thus demonstrate a strategy for systematically learning the rules of endogenous antigen presentation.
Curation Last Updated2025-02-10 19:33:17
Related Information
Epitopes
Bcell Assays0
Tcell Assays0
MHC Ligand Assays