Describing the Peptide Binding Specificity of HLA-C

Human leukocyte antigen (HLA) presents peptides to T-cells for immune scrutiny. Whereas HLA-A and -B have been described in great detail, HLA-C has received much less attention. Here, to increase the coverage of HLA-C and the accuracy of the corresponding tools, we have generated HLA-C molecules; peptide-binding assays, data and predictors; and tetramers; representing the most prevalent HLA-C molecules. We have combined positional scanning combinatorial peptide library (PSCPL) with a homogenous high-throughput dissociation assay and generated specificity matrices for 11 different HLA-C molecules. We find preference for hydrophobic residues at the peptide C-terminus for all HLA-C molecules. Most molecules were found to have an additional strong anchor at P2 or P3, with auxiliary anchor observed at P1, P2, P3, and P7. The binding affinity is measured for peptides fitting the specificity matrix for 5 HLA-C molecules and for all, but one, molecule we find a high frequency of binders, >70%, among these peptides. To extend the examined peptide space, we use bioinformatic prediction tools to search for additional binders. Finally, we update our prediction tool, NetMHCpan, with the HLA-C affinity data and show that the predictive performance for HLA-C molecules now is increased to a level comparable withthat of HLA-A and -B. These novel HLA-C molecules and predictors are successfully used to generate HLA-C tetramers and validate HLA-C-restricted T cell responses.