Application of the pMHC array to characterise tumour antigen specific T cell populations in leukaemia patients at disease diagnosis

Immunotherapy treatments for cancer are becoming increasingly successful, however to further improve our understanding of the T-cell recognition involved in effective responses and to encourage moves towards the development of personalised treatments for leukaemia immunotherapy, precise antigenic targets in individual patients have been identified. Cellular arrays using peptide-MHC (pMHC) tetramers allow the simultaneous detection of different antigen specific T-cell populations naturally circulating in patients and normal donors. We have developed the pMHC array to detect CD8+ T-cell populations in leukaemia patients that recognise epitopes within viral antigens (cytomegalovirus (CMV) and influenza (Flu)) and leukaemia antigens (including Per Arnt Sim domain 1 (PASD1), MelanA, Wilms’ Tumour (WT1) and tyrosinase). We show that the pMHC array is at least as sensitive as flow cytometry and has the potential to rapidly identify more than 40 specific T-cell populations in a small sample of T-cells (0.8–1.4 x 106). Fourteen of the twenty-six acute myeloid leukaemia (AML) patients analysed had T cells that recognised tumour antigen epitopes, and eight of these recognised PASD1 epitopes. Other tumour epitopes recognised were MelanA (n = 3), tyrosinase (n = 3) and WT1126-134 (n = 1). One of the seven acute lymphocytic leukaemia (ALL) patients analysed had T cells that recognised the MUC1950-958 epitope. In the future the pMHC array may be used provide point of care T-cell analyses, predict patient response to conventional therapy and direct personalised immunotherapy for patients

Class I major histocompatibility complexes loaded by a periodate trigger

Class I major histocompatibility complexes (MHCs) present peptide ligands on the cell surface for recognition by appropriate cytotoxic T cells. The unstable nature of unliganded MHC necessitates the production of recombinant class I complexes through in vitro refolding reactions in the presence of an added excess of peptides. This strategy is not amenable to high-throughput production of vast collections of class I complexes. To address this issue, we recently designed photocaged MHC ligands that can be cleaved by a UV light trigger in the MHC bound state under conditions that do not affect the integrity of the MHC structure. The results obtained with photocaged MHC ligands demonstrate that conditional MHC ligands can form a generally applicable concept for the creation of defined peptide−MHCs. However, the use of UV exposure to mediate ligand exchange is unsuited for a number of applications, due to the lack of UV penetration through cell culture systems and due to the transfer of heat upon UV irradiation, which can induce evaporation. To overcome these limitations, here, we provide proof-of-concept for the generation of defined peptide−MHCs by chemical trigger-induced ligand exchange. The crystal structure of the MHC with the novel chemosensitive ligand showcases that the ligand occupies the expected binding site, in a conformation where the hydroxyl groups should be reactive to periodate. We proceed to validate this technology by producing peptide−MHCs that can be used for T cell detection. The methodology that we describe here should allow loading of MHCs with defined peptides in cell culture devices, thereby permitting antigen-specific T cell expansion and purification for cell therapy. In addition, this technology will be useful to develop miniaturized assay systems for performing high-throughput screens for natural and unnatural MHC ligands

Constraints on the pMSSM from searches for squarks and gluinos by ATLAS

We study the impact of the jets and missing transverse momentum SUSY analyses of the ATLAS experiment on the phenomenological MSSM (pMSSM). We investigate sets of SUSY models with a flat and logarithmic prior in the SUSY mass scale and a mass range up to 1 and 3 TeV, respectively. These models were found previously in the study 'Supersymmetry without Prejudice'. Removing models with long-lived SUSY particles, we show that 99% of 20000 randomly generated pMSSM model points with a flat prior and 87% for a logarithmic prior are excluded by the ATLAS results. For models with squarks and gluinos below 600 GeV all models of the pMSSM grid are excluded. We identify SUSY spectra where the current ATLAS search strategy is less sensitive and propose extensions to the inclusive jets search channel

Abundances of the elements in the solar system

A review of the abundances and condensation temperatures of the elements and their nuclides in the solar nebula and in chondritic meteorites. Abundances of the elements in some neighboring stars are also discussed.Comment: 42 pages, 11 tables, 8 figures, chapter, In Landolt- B\"ornstein, New Series, Vol. VI/4B, Chap. 4.4, J.E. Tr\"umper (ed.), Berlin, Heidelberg, New York: Springer-Verlag, p. 560-63

NetMHCpan, a Method for Quantitative Predictions of Peptide Binding to Any HLA-A and -B Locus Protein of Known Sequence

Binding of peptides to Major Histocompatibility Complex (MHC) molecules is the single most selective step in the recognition of pathogens by the cellular immune system. The human MHC class I system (HLA-I) is extremely polymorphic. The number of registered HLA-I molecules has now surpassed 1500. Characterizing the specificity of each separately would be a major undertaking.Here, we have drawn on a large database of known peptide-HLA-I interactions to develop a bioinformatics method, which takes both peptide and HLA sequence information into account, and generates quantitative predictions of the affinity of any peptide-HLA-I interaction. Prospective experimental validation of peptides predicted to bind to previously untested HLA-I molecules, cross-validation, and retrospective prediction of known HIV immune epitopes and endogenous presented peptides, all successfully validate this method. We further demonstrate that the method can be applied to perform a clustering analysis of MHC specificities and suggest using this clustering to select particularly informative novel MHC molecules for future biochemical and functional analysis.Encompassing all HLA molecules, this high-throughput computational method lends itself to epitope searches that are not only genome- and pathogen-wide, but also HLA-wide. Thus, it offers a truly global analysis of immune responses supporting rational development of vaccines and immunotherapy. It also promises to provide new basic insights into HLA structure-function relationships. The method is available at http://www.cbs.dtu.dk/services/NetMHCpan

Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method

<p>Abstract</p> <p>Background</p> <p>Antigen presenting cells (APCs) sample the extra cellular space and present peptides from here to T helper cells, which can be activated if the peptides are of foreign origin. The peptides are presented on the surface of the cells in complex with major histocompatibility class II (MHC II) molecules. Identification of peptides that bind MHC II molecules is thus a key step in rational vaccine design and developing methods for accurate prediction of the peptide:MHC interactions play a central role in epitope discovery. The MHC class II binding groove is open at both ends making the correct alignment of a peptide in the binding groove a crucial part of identifying the core of an MHC class II binding motif. Here, we present a novel stabilization matrix alignment method, SMM-align, that allows for direct prediction of peptide:MHC binding affinities. The predictive performance of the method is validated on a large MHC class II benchmark data set covering 14 HLA-DR (human MHC) and three mouse H2-IA alleles.</p> <p>Results</p> <p>The predictive performance of the SMM-align method was demonstrated to be superior to that of the Gibbs sampler, TEPITOPE, SVRMHC, and MHCpred methods. Cross validation between peptide data set obtained from different sources demonstrated that direct incorporation of peptide length potentially results in over-fitting of the binding prediction method. Focusing on amino terminal peptide flanking residues (PFR), we demonstrate a consistent gain in predictive performance by favoring binding registers with a minimum PFR length of two amino acids. Visualizing the binding motif as obtained by the SMM-align and TEPITOPE methods highlights a series of fundamental discrepancies between the two predicted motifs. For the DRB1*1302 allele for instance, the TEPITOPE method favors basic amino acids at most anchor positions, whereas the SMM-align method identifies a preference for hydrophobic or neutral amino acids at the anchors.</p> <p>Conclusion</p> <p>The SMM-align method was shown to outperform other state of the art MHC class II prediction methods. The method predicts quantitative peptide:MHC binding affinity values, making it ideally suited for rational epitope discovery. The method has been trained and evaluated on the, to our knowledge, largest benchmark data set publicly available and covers the nine HLA-DR supertypes suggested as well as three mouse H2-IA allele. Both the peptide benchmark data set, and SMM-align prediction method (<it>NetMHCII</it>) are made publicly available.</p