High‐sensitivity HLA class I peptidome analysis enables a precise definition of peptide motifs and the identification of peptides from cell lines and patients’ sera

Abstract

The characterization of peptides bound to human leukocyte antigen (HLA) class I is of fundamental importance for understanding CD8+ T cell-driven immunological processes and for the development of immunomodulatory therapeutic strategies. However, until now, the mass spectrometric analysis of HLA-bound peptides has typically required billions of cells, still resulting in relatively few high-confidence peptide identifications. Capitalizing on the recent developments in mass spectrometry and bioinformatics, we have implemented a methodology for the efficient recovery of acid-eluted HLA peptides after purification with the pan-reactive antibody W6/32 and have identified a total of 27 862 unique peptides with high confidence (1% false discovery rate) from five human cancer cell lines. More than 93% of the identified peptides were eight to 11 amino acids in length and contained signatures that were in excellent agreement with published HLA binding motifs. Furthermore, by purifying soluble HLA class I complexes (sHLA) from sera of melanoma patients, up to 972 high-confidence peptides could be identified, including melanoma-associated antigens already described in the literature. Knowledge of the HLA class I peptidome should facilitate multiplex tetramer technology-based characterization of T cells, and allow the development of patient selection, stratification and immunomodulatory therapeutic strategies.

Purification of soluble HLA class I complexes from human serum or plasma deliver high quality immuno peptidomes required for biomarker discovery

“…B; all peptide identifications can be found in Supporting Information Tables 1–6). These numbers were significantly higher than in previous reports from our group and others . The peptide length distributions for both serum and plasma centered around nine amino acids (Fig.…”

Unsupervised HLA Peptidome Deconvolution Improves Ligand Prediction Accuracy and Predicts Cooperative Effects in Peptide–HLA Interactions

“…Although this approach is efficient for samples with common HLA alleles, it is unclear whether it could perform equally well for other alleles for which predictions are less reliable. In parallel, recent works have suggested that HLA-binding motifs can be detected by simply clustering the peptides using a simulated annealing algorithm (i.e., Gibbs Clustering) (20) and without relying on HLA-binding prediction tools (21)(22)(23).…”

Mapping the tumour human leukocyte antigen (HLA) ligandome by mass spectrometry

“…Elution of HLA complexes can be achieved either through treatment with a strong acid, such as 0·1–0·2% TFA, 10% acetic acid or with 0·1–0·2 N acetic acid followed by heat denaturation . Peptides are frequently separated from HLA fragments through ultrafiltration, employing a molecular weight filter.…”

“…Other separation methods employ C 18 fractionation through spin columns, cartridges, tips or in‐house‐generated columns . Sample concentration and purification is essential before mass spectrometry (MS), and it is usually achieved via C 18 or strong cation exchange (SCX) prefractionation …”