NetMHC-3.0: accurate web accessible predictions of human, mouse and monkey MHC class I affinities for peptides of length 8–11

NetMHC-3.0 is trained on a large number of quantitative peptide data using both affinity data from the Immune Epitope Database and Analysis Resource (IEDB) and elution data from SYFPEITHI. The method generates high-accuracy predictions of major histocompatibility complex (MHC): peptide binding. The predictions are based on artificial neural networks trained on data from 55 MHC alleles (43 Human and 12 non-human), and position-specific scoring matrices (PSSMs) for additional 67 HLA alleles. As only the MHC class I prediction server is available, predictions are possible for peptides of length 8–11 for all 122 alleles. artificial neural network predictions are given as actual IC50 values whereas PSSM predictions are given as a log-odds likelihood scores. The output is optionally available as download for easy post-processing. The training method underlying the server is the best available, and has been used to predict possible MHC-binding peptides in a series of pathogen viral proteomes including SARS, Influenza and HIV, resulting in an average of 75–80% confirmed MHC binders. Here, the performance is further validated and benchmarked using a large set of newly published affinity data, non-redundant to the training set. The server is free of use and available at: http://www.cbs.dtu.dk/services/NetMHC

A combined prediction strategy increases identification of peptides bound with high affinity and stability to porcine MHC class I molecules SLA-1*04:01, SLA-2*04:01, and SLA-3*04:01

Affinity and stability of peptides bound by major histocompatibility complex (MHC) class I molecules are important factors in presentation of peptides to cytotoxic T lymphocytes (CTLs). In silico prediction methods of peptide-MHC binding followed by experimental analysis of peptide-MHC interactions constitute an attractive protocol to select target peptides from the vast pool of viral proteome peptides. We have earlier reported the peptide binding motif of the porcine MHC-I molecules SLA-1*04:01 and SLA-2*04:01, identified by an ELISA affinity-based positional scanning combinatorial peptide library (PSCPL) approach. Here, we report the peptide binding motif of SLA-3*04:01 and combine two prediction methods and analysis of both peptide binding affinity and stability of peptide-MHC complexes to improve rational peptide selection. Using a peptide prediction strategy combining PSCPL binding matrices and in silico prediction algorithms (NetMHCpan), peptide ligands from a repository of 8900 peptides were predicted for binding to SLA-1*04:01, SLA-2*04:01, and SLA-3*04:01 and validated by affinity and stability assays. From the pool of predicted peptides for SLA-1*04:01, SLA-2*04:01, and SLA-3*04:01, a total of 71, 28, and 38 % were binders with affinities below 500 nM, respectively. Comparison of peptide-SLA binding affinity and complex stability showed that peptides of high affinity generally, but not always, produce complexes of high stability. In conclusion, we demonstrate how state-of-the-art prediction and in vitro immunology tools in combination can be used for accurate selection of peptides for MHC class I binding, hence providing an expansion of the field of peptide-MHC analysis also to include pigs as a livestock experimental model.Fil: Pedersen, Lasse Eggers. Technical University of Denmark; DinamarcaFil: Rasmussen, Michael. Universidad de Copenhagen; DinamarcaFil: Harndahl, Mikkel. Universidad de Copenhagen; DinamarcaFil: Nielsen, Morten. Technical University of Denmark; Dinamarca. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas (subsede Chascomús) | Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas (subsede Chascomús); ArgentinaFil: Buus, Søren. Universidad de Copenhagen; DinamarcaFil: Jungersen, Gregers. Technical University of Denmark; Dinamarc

Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity

Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. Peptide-MHC-I interactions have traditionally been quantified by the strength of the interaction, that is, the binding affinity, yet it has been shown that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared with binding affinity. In this study, we have experimentally analyzed peptide-MHC-I complex stability of a large panel of human MHC-I allotypes and generated a body of data sufficient to develop a neural network-based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural network predictors of peptide-MHC-I complex stability with state-of-the-art predictors of peptide-MHC-I binding is shown to significantly improve the prediction of CTL epitopes. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCstabpan.Fil: Rasmussen, Michael. Universidad de Copenhagen; DinamarcaFil: Fenoy, Luis Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; ArgentinaFil: Harndahl, Mikkel. Universidad de Copenhagen; DinamarcaFil: Kristensen, Anne Bregnballe. Universidad de Copenhagen; DinamarcaFil: Nielsen, Ida Kallehauge. Universidad de Copenhagen; DinamarcaFil: Nielsen, Morten. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Copenhagen; DinamarcaFil: Buus, Søren. Universidad de Copenhagen; Dinamarc

Drug hypersensitivity caused by alteration of the MHC-presented self-peptide repertoire

Idiosyncratic adverse drug reactions are unpredictable, dose independent and potentially life threatening; this makes them a major factor contributing to the cost and uncertainty of drug development. Clinical data suggest that many such reactions involve immune mechanisms, and genetic association studies have identified strong linkage between drug hypersensitivity reactions to several drugs and specific HLA alleles. One of the strongest such genetic associations found has been for the antiviral drug abacavir, which causes severe adverse reactions exclusively in patients expressing the HLA molecular variant B*57:01. Abacavir adverse reactions were recently shown to be driven by drug-specific activation of cytokine-producing, cytotoxic CD8+ T cells that required HLA-B*57:01 molecules for their function. However, the mechanism by which abacavir induces this pathologic T cell response remains unclear. Here we show that abacavir can bind within the F-pocket of the peptide-binding groove of HLA-B*57:01 thereby altering its specificity. This supports a novel explanation for HLA-linked idiosyncratic adverse drug reactions; namely that drugs can alter the repertoire of self-peptides presented to T cells thus causing the equivalent of an alloreactive T cell response. Indeed, we identified specific self-peptides that are presented only in the presence of abacavir, and that were recognized by T cells of hypersensitive patients. The assays we have established can be applied to test additional compounds with suspected HLA linked hypersensitivities in vitro. Where successful, these assays could speed up the discovery and mechanistic understanding of HLA linked hypersensitivities as well as guide the development of safer drugs

Establishing the pig as a large animal model for vaccine development against human cancer

Immunotherapy has increased overall survival of metastatic cancer patients, and cancer antigens are promising vaccine targets. To fulfill the promise, appropriate tailoring of the vaccine formulations to mount in vivo cytotoxic T cell (CTL) responses towards co-delivered cancer antigens is essential. Previous development of therapeutic cancer vaccines has largely been based on studies in mice, and the majority of these candidate vaccines failed to induce therapeutic responses in the subsequent human clinical trials. Given that antigen dose and vaccine volume in pigs are translatable to humans and the porcine immunome is more closely related to the human counterpart, we here introduce pigs as a supplementary large animal model for human cancer vaccine development. IDO and RhoC, both important in human cancer development and progression, were used as vaccine targets and 12 pigs were immunized with overlapping 20-mer peptides spanning the entire porcine IDO and RhoC sequences formulated in CTL-inducing adjuvants: CAF09, CASAC, Montanide ISA 51 VG or PBS. Taking advantage of recombinant swine MHC class I molecules (SLAs), the peptide-SLA complex stability were measured for 198 IDO- or RhoC-derived 9-11mer peptides predicted to bind to SLA-1*04:01, -1*07:02, -2*04:01, -2*05:02 and/or -3*04:01. This identified 89 stable (t½ ≥ 0.5 hour) peptide-SLA complexes. By IFN-γ release in PBMC cultures we monitored the vaccine-induced peptide-specific CTL responses, and found responses to both IDO- and RhoC-derived peptides across all groups with no adjuvant being superior. These findings support the further use of pigs as a large animal model for vaccine development against human cancer

Constant regulation for stable CD8 T-cell functional avidity and its possible implications for cancer immunotherapy.

The functional avidity (FA) of cytotoxic CD8 T cells impacts strongly on their functional capabilities and correlates with protection from infection and cancer. FA depends on TCR affinity, downstream signaling strength, and TCR affinity-independent parameters of the immune synapse, such as costimulatory and inhibitory receptors. The functional impact of coreceptors on FA remains to be fully elucidated. Despite its importance, FA is infrequently assessed and incompletely understood. There is currently no consensus as to whether FA can be enhanced by optimized vaccine dose or boosting schedule. Recent findings suggest that FA is remarkably stable in vivo, possibly due to continued signaling modulation of critical receptors in the immune synapse. In this review, we provide an overview of the current knowledge and hypothesize that in vivo, codominant T cells constantly "equalize" their FA for similar function. We present a new model of constant FA regulation, and discuss practical implications for T-cell-based cancer immunotherapy

Human Leukocyte Antigen (HLA) Class I Restricted Epitope Discovery in Yellow Fewer and Dengue Viruses: Importance of HLA Binding Strength

Epitopes from all available full-length sequences of yellow fever virus (YFV) and dengue fever virus (DENV) restricted by Human Leukocyte Antigen class I (HLA-I) alleles covering 12 HLA-I supertypes were predicted using the NetCTL algorithm. A subset of 179 predicted YFV and 158 predicted DENV epitopes were selected using the EpiSelect algorithm to allow for optimal coverage of viral strains. The selected predicted epitopes were synthesized and approximately 75% were found to bind the predicted restricting HLA molecule with an affinity, KD, stronger than 500 nM. The immunogenicity of 25 HLA-A*02:01, 28 HLA-A*24:02 and 28 HLA-B*07:02 binding peptides was tested in three HLA-transgenic mice models and led to the identification of 17 HLA-A*02:01, 4 HLA-A*2402 and 4 HLA-B*07:02 immunogenic peptides. The immunogenic peptides bound HLA significantly stronger than the non-immunogenic peptides. All except one of the immunogenic peptides had KD below 100 nM and the peptides with KD below 5 nM were more likely to be immunogenic. In addition, all the immunogenic peptides that were identified as having a high functional avidity had KD below 20 nM. A*02:01 transgenic mice were also inoculated twice with the 17DD YFV vaccine strain. Three of the YFV A*02:01 restricted peptides activated T-cells from the infected mice in vitro. All three peptides that elicited responses had an HLA binding affinity of 2 nM or less. The results indicate the importance of the strength of HLA binding in shaping the immune response