NetMHCIIpan-3.0, a common pan-specific MHC class II prediction method including all three human MHC class II isotypes, HLA-DR, HLA-DP and HLA-DQ

Abstract

Major histocompatibility complex class II (MHCII) molecules play an important role in cell-mediated immunity. They present specific peptides derived from endosomal proteins for recognition by T helper cells. The identification of peptides that bind to MHCII molecules is therefore of great importance for understanding the nature of immune responses and identifying T cell epitopes for the design of new vaccines and immunotherapies. Given the large number of MHC variants, and the costly experimental procedures needed to evaluate individual peptide–MHC interactions, computational predictions have become particularly attractive as first-line methods in epitope discovery. However, only a few so-called pan-specific prediction methods capable of predicting binding to any MHC molecule with known protein sequence are currently available, and all of them are limited to HLA-DR. Here, we present the first pan-specific method capable of predicting peptide binding to any HLA class II molecule with a defined protein sequence. The method employs a strategy common for HLA-DR, HLA-DP and HLA-DQ molecules to define the peptide-binding MHC environment in terms of a pseudo sequence. This strategy allows the inclusion of new molecules even from other species. The method was evaluated in several benchmarks and demonstrates a significant improvement over molecule-specific methods as well as the ability to predict peptide binding of previously uncharacterised MHCII molecules. To the best of our knowledge, the NetMHCIIpan-3.0 method is the first pan-specific predictor covering all HLA class II molecules with known sequences including HLA-DR, HLA-DP, and HLA-DQ. The NetMHCpan-3.0 method is available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.0.

Long-peptide vaccination with driver gene mutations in p53 and Kras induces cancer mutation-specific effector as well as regulatory T cell responses

“…To address the question, which epitopes within the long peptide sequences (mutated and non-mutated), could elicit T cell responses in the analyzed patients, epitope prediction was performed employing the NetMHC 57,58 algorithms. Within the present patient cohort HLA typing was solely performed for the HLA-A2 allele and 5 five of the 26 patients were tested positive (Supplementary Table 3).…”

“…After identification of the two most immunogenic mutated Kras and p53 derived peptide sequences (2 out of the total 19 mutated peptide sequences tested), we next determined possible epitopes that could be processed from the long peptides and presented in the employed HLA context. To identify HLA binding minimal epitopes, the two long peptide sequences were subjected to in silico prediction algorithms of the NetMHC 57,58 and the SYFPEITHI 59 databases. Affinity scores for all overlapping 9-mer, 10-mer and 15-mer small peptides possibly processed from the long peptides and binding to HLA-A*0201 and HLA-DRB1*0101 were predicted and affinity scores for wt and mutated sequences were compared.…”

“…Stocks were aliquoted (25 µl, 50 µl) and stored at −20°C. Possible HLA-A*0201 and HLA-DRB1*0101 ligands that might be processed from the long peptides were predicted using the SYFPEITHI 59 and NetMHC 57,58 algorithms. Lists of peptides used can be found in the Supplementary Tables 1, 4 and 4.…”

Diversifying Selection Analysis Predicts Antigenic Evolution of 2009 Pandemic H1N1 Influenza A Virus in Humans

“…occur within a high-affinity T-cell epitope using representative prepandemic and pandemic sequences as input (31). Likewise, site 468 experienced diversifying selection in the prepandemic, was found to be significantly mutation during postpandemic evolution, but was not located in any previously defined B-cell/Ab epitope, suggesting that it is experiencing some other kind of diversifying pressure.…”

Genomic and Transcriptomic Features of Response to Anti-PD-1 Therapy in Metastatic Melanoma

“…To ensure concordance, we manually compared ATHLATES' calls of the normal versus tumor samples and ascertained there was at least no two-digit HLA typing discrepancy between any normaltumor pair. For each non-synonymous coding mutation from a tumor, we predicted its impact on the patient's HLA class I and II binding using the stand-alone version of the programs NetMHCpan v2.8 (Hoof et al, 2009;Nielsen et al, 2007) and NetMHCIIpan v3.0 (Karosiene et al, 2013), respectively. Specifically, for HLA class I binding prediction using netMHCpan v2.8, we tested all 9-11-mer peptides containing the mutated amino acids for binding to the patient's HLA-A, -B and -C. A peptide was defined as a neoepitope based on two criteria : i) predicted binding affinity ≤ 500nM, and ii) rank percentage ≤ 2% (default cutoff).…”