Relationship between peptide selectivities of human transporters associated with antigen processing and HLA class I molecules

Efficiency of presentation of a peptide epitope by a MHC class I molecule depends on two parameters: its binding to the MHC molecule and its generation by intracellular Ag processing. In contrast to the former parameter, the mechanisms underlying peptide selection in Ag processing are poorly understood. Peptide translocation by the TAP transporter is required for presentation of most epitopes and may modulate peptide supply to MHC class I molecules. To study the role of human TAP for peptide presentation by individual HLA class I molecules, we generated artificial neural networks capable of predicting the affinity of TAP for random sequence 9-mer peptides. Using neural network-based predictions of TAP affinity, we found that peptides eluted from three different HLA class I molecules had higher TAP affinities than control peptides with equal binding affinities for the same HLA class I molecules, suggesting that human TAP may contribute to epitope selection. In simulated TAP binding experiments with 408 HLA class I binding peptides, HLA class I molecules differed significantly with respect to TAP affinities of their ligands, As a result, some class I molecules, especially HLA-B27, may be particularly efficient in presentation of cytosolic peptides with low concentrations, while most class I molecules may predominantly present abundant cytosolic peptides.

Prediction of promiscuous peptides that bind HLA class I molecules

Promiscuous T-cell epitopes make ideal targets for vaccine development. We report here a computational system, multipred, for the prediction of peptide binding to the HLA-A2 supertype. It combines a novel representation of peptide/MHC interactions with a hidden Markov model as the prediction algorithm. multipred is both sensitive and specific, and demonstrates high accuracy of peptide-binding predictions for HLA-A*0201, *0204, and *0205 alleles, good accuracy for *0206 allele, and marginal accuracy for *0203 allele. multipred replaces earlier requirements for individual prediction models for each HLA allelic variant and simplifies computational aspects of peptide-binding prediction. Preliminary testing indicates that multipred can predict peptide binding to HLA-A2 supertype molecules with high accuracy, including those allelic variants for which no experimental binding data are currently available.

Virtual models of the HLA class I antigen processing pathway

Antigen recognition by cytotoxic CD8 T cells is dependent upon a number of critical steps in MHC class I antigen processing including proteosomal cleavage, TAP transport into the endoplasmic reticulum, and MHC class 1 binding. Based on extensive experimental data relating to each of these steps there is now the capacity to model individual antigen processing steps with a high degree of accuracy. This paper demonstrates the potential to bring together models of individual antigen processing steps, for example proteosome cleavage, TAP transport, and MHC binding, to build highly informative models of functional pathways. In particular, we demonstrate how an artificial neural network model of TAP transport was used to mine a HLA-binding database so as to identify H LA-binding peptides transported by TAP. This integrated model of antigen processing provided the unique insight that HLA class I alleles apparently constitute two separate classes: those that are TAP-efficient for peptide loading (HLA-B27, -A3, and -A24) and those that are TAP-inefficient (HLA-A2, -B7, and -B8). Hence, using this integrated model we were able to generate novel hypotheses regarding antigen processing, and these hypotheses are now capable of being tested experimentally. This model confirms the feasibility of constructing a virtual immune system, whereby each additional step in antigen processing is incorporated into a single modular model. Accurate models of antigen processing have implications for the study of basic immunology as well as for the design of peptide-based vaccines and other immunotherapies. (C) 2004 Elsevier Inc. All rights reserved.

Generation and phenotypic characterization of new human ovarian cancer cell lines with the identification of antigens potentially recognizable by HLA-restricted cytotoxic T cells

This study describes a simple method for long-term establishment of human ovarian tumor lines and prediction of T-cell epitopes that could be potentially useful in the generation of tumor-specific cytotoxic T lymphocytes (CTLs), Nine ovarian tumor lines (INT.Ov) were generated from solid primary or metastatic tumors as well as from ascitic fluid, Notably all lines expressed HLA class I, intercellular adhesion molecule-1 (ICAM-1), polymorphic epithelial mucin (PEM) and cytokeratin (CK), but not HLA class II, B7.1 (CD80) or BAGE, While of the 9 lines tested 4 (INT.Ov1, 2, 5 and 6) expressed the folate receptor (FR-alpha) and 6 (INT.Ov1, 2, 5, 6, 7 and 9) expressed the epidermal growth factor receptor (EGFR); MAGE-1 and p185(HER-2/neu) were only found in 2 lines (INT.Ov1 and 2) and GAGE-1 expression in 1 line (INT.Ov2). The identification of class I MHC ligands and T-cell epitopes within protein antigens was achieved by applying several theoretical methods including: 1) similarity or homology searches to MHCPEP; 2) BIMAS and 3) artificial neural network-based predictions of proteins MACE, GAGE, EGFR, p185(HER-2/neu) and FR-alpha expressed in INT.Ov lines, Because of the high frequency of expression of some of these proteins in ovarian cancer and the ability to determine HLA binding peptides efficiently, it is expected that after appropriate screening, a large cohort of ovarian cancer patients may become candidates to receive peptide based vaccines. (C) 1997 Wiley-Liss, Inc.

HLA class II antigens positively and negatively associated with hepatosplenic schistosomiasis in a Chinese population

To identify possible associations between host genetic factors and the onset of liver fibrosis following Schistosoma japonicum infection, the major histocompatibility class II alleles of 84 individuals living on an island (Jishan) endemic for schistosomiasis japonica in the Poyang Lake Region of Southern China were determined. Forty patients exhibiting advanced schistosomiasis, characterised by extensive liver fibrosis, and 44 age and sex-matched control subjects were assessed for the class II haplotypes HLA-DRBI and HLA-DQB1. Two HLA-DRB1 alleles, HLA-DRB1*0901 (P = 0.012) and *1302 (P = 0.039), and two HLA-DQB1 alleles, HLA-DQB1*0303 (P = 0.012) and *0609 (P = 0.037), were found to be significantly associated with susceptibility to fibrosis. These associated DRB1 and DQB1 alleles are in very strong linkage disequilibrium, with DRB1*0901-DQB1*0303 and DRB1*1302-DQB1*0609 found as: common haplotypes in this population. In contrast, the alleles HLA-DRB1*1501 (P = 0.025) and HLA-DQB 1*0601 (P = 0.022) were found to be associated with resistance to hepatosplenic disease. Moreover, the alleles DQB1*0303 and DRB1*0901 did not increase susceptibility in the presence of DQB1*0601, indicating that DQB1*0601 is dominant over DQB1*0303 and DRB1*0901. The study has thus identified both positive and negative associations between HLA class II alleles and the risk of individuals developing moderate to severe liver fibrosis following schistosome infection. (C) 2001 Australian Society for Parasitology Inc. Published by Elsevier Science Ltd. All rights reserved.

Contrasting Epstein-Barr virus-specific cytotoxic T cell responses to HLA A2-restricted epitopes in humans and HLA transgenic mice: implications for vaccine design

This study investigates the hierarchy of cytotoxic T cell (CTL) responses to twelve HLA A2-restricted epitopes from the latent, lytic and structural proteins of Epstein–Barr virus (EBV) in acute infectious mononucleosis and in healthy seropositive donors and the relative immunogenecity of these epitopes in transgenic mice. Responses to the lytic epitope were uniformly strong in all healthy seropositive individuals and acute infectious mononucleosis donors while moderate or low responses were observed to the latent and structural epitopes, respectively in both groups studied. In contrast, when HLA A2/Kb transgenic mice were immunised with these peptide epitopes, CTL responses were observed to all epitopes with a maximal response to the epitopes within the structural proteins and low to moderate responses to the latent epitopes. This hierarchy of CTL responses in mice was also reflected in an MHC stabilisation analysis. These contrasting CTL responses in humans following natural infection compared to the immunogenicity of these epitopes and their ability to stabilise MHC may need to be considered when designing an EBV vaccine.

Design of a polyepitope construct for the induction of HLA-A0201-restricted HIV 1-specific CTL responses using HLA-A*0201 transgenic, H-2 class IKO mice

HLA-A*0201 transgenic, H-2D(b)/mouse beta2-microglobulin double-knockout mice were used to compare and optimize the immunogenic potential of 17HIV 1-derived, HLA-A0201-restricted epitopic peptides. A tyrosine substitution in position 1 of the epitopic peptides, which increases both their affinity for and their HLA-A0201 molecule stabilizing capacity, was introduced in a significant proportion, having verified that such modifications enhance their immunogenicity in respect of their natural antigenicity. Based on these results, a 13-polyepitope construct was inserted in the pre-S2 segment of the hepatitis B middle glycoprotein and used for DNA immunization. Long-lasting CTL responses against most of the inserted epitopes could be elicited simultaneously in a single animal with cross-recognition in several cases of their most common natural variants.

Limitations of HLA-transgenic mice in presentation of HLA-restricted cytotoxic T-cell epitopes from endogenously processed human papillomavirus type 16 E7 protein

We investigated the use of mice transgenic for human leucocyte antigen (HLA) A*0201 antigen-binding domains to test vaccines composed of defined HLA A*0201-restricted cytotoxic T-lymphocyte (CTL) epitopes of human papillomavirus (HPV) type 16 E7 oncoprotein. HPV is detected in >90% of cervical carcinomas. HPV16 E7 oncoprotein transforms cells of the uterine cervix and functions as a tumour-associated antigen to which immunotherapeutic strategies may be directed. We report that although the HLA A*0201 E7 epitope peptides function both to prime for E7 CTL responses, and to sensitize target cells for E7-directed CTL killing in situations where antigen processing is not required, the epitopes are not processed out of either endogenously expressed or immunization-introduced E7, by the mouse antigen-processing and presentation machinery. Thus (1) CTL induced by HLA A*0201 peptide immunization killed E7 peptide-pulsed target cells, but did not kill target cells expressing whole E7; (2) immunization with whole E7 protein did not elicit CTL directed to HLA A*0201-restricted E7 CTL epitopes; (3) HLA A*0201-restricted CTL epitopes expressed in the context of a DNA polytope vaccine did not activate E7-specific T cells either in 'conventional' HLA A*0201 transgenic (A2.1K(b) ) mice, or in HHD transgenic mice in which expression of endogenous H-2 class 1 is precluded; and (4) HLA A*0201 E7 peptide epitope immunization was incapable of preventing the growth of an HLA A*0201- and E7-expressing tumour. There are generic implications for the universal applicability of HLA-class 1 transgenic mice for studies of human CTL epitope presentation in murine models of human infectious disease where recognition of endogenously processed antigen is necessary. There are also specific implications for the use of HLA A2 transgenic mice for the development of E7-based therapeutic vaccines for cervical cancer.

Antiserum raised against the Epstein-Barr virus BARF0 protein reacts to HLA-DR beta chain

The role that Epstein-Barr virus plays in nasopharyngeal carcinoma and Burkitt's lymphoma has been under intense study for many years. With only a limited set of viral genes being expressed in these tumours it has been difficult to understand how the virus could cause/aid in the generation of the tumours. In 1997 a paper was published by Fries et al. [Fries et al. (1997) Identification of a novel protein encoded by the BamHI A region of the Epstein-Barr virus. J Virol 71: 2765-2771.] in which a rabbit serum was generated and used to identify protein products (RK-BARF0) encoded from the BamH1 A region of EBV. In this paper we have isolated these proteins from two-dimensional gels and identified them, using mass spectrometry, as components of HLA DR.

A naturally selected dimorphism within the HLA-B44 supertype alters class I structure, peptide repertoire, and T cell recognition

HLA-B*4402 and B*4403 are naturally occurring MHC class I alleles that are both found at a hi,,h frequency in all human populations, and vet they only differ by one residue on the alpha2 helix (B*4402 Aspl56-->B*4403 Leu156) CTLs discriminate between HLA-B*4402 and B*4403, and these allotypes stimulate strong mutual allogeneic responses reflecting their known barrier to hemopoeitic stem cell transplantation. Although HLA-B*4402 and B*4403 share >95% of their peptide repertoire, B*4403 presents more unique peptides than B*4402, consistent with the stronger T cell alloreactivity observed toward B*4403 compared with B*4402. Crystal structures of B*4402 and B*4403 show how the polymorphisin at position 156 is completely buried and yet alters both the peptide and the heavy chain conformation, relaxing ligand selection by B*4403 compared with B*4402. Thus, the polymorphism between HLA-B*4402 and B 4403 modifies both peptide repertoire and T cell recognition, and is reflected lit the paradoxically powerful alloreactivity that occurs across this minimal mismatch. The findings suggest that these closely related class I genes are maintained lit diverse human populations through their differential impact on the selection of peptide ligands and the T cell repertoire.

Promiscuous CTL recognition of viral epitopes on multiple human leukocyte antigens: Biological validation of the proposed HLA A24 supertype

Multiple HLA class I alleles can bind peptides with common sequence motifs due to structural similarities in the peptide binding cleft, and these groups of alleles have been classified into supertypes. Nine major HLA supertypes have been proposed, including an A24 supertype that includes A*2301, A*2402, and A*3001. Evidence for this A24 supertype is limited to HLA sequence homology and/or similarity in peptide binding motifs for the alleles. To investigate the immunological relevance of this proposed supertype, we have examined two viral epitopes (from EBV and CMV) initially defined as HLA-A*2301-binding peptides. The data clearly demonstrate that each peptide could be recognized by CTL clones in the context of A*2301 or A*2402; thus validating the inclusion of these three alleles within an A24 supertype. Furthermore, CTL responses to the EBV epitope were detectable in both A*2301(+) and A*2402(+) individuals who had been previously exposed to this virus. These data substantiate the biological relevance of the A24 supertype, and the identification of viral epitopes with the capacity to bind promiscuously across this supertype could aid efforts to develop CTL-based vaccines or immunotherapy. The degeneracy in HLA restriction displayed by some T cells in this study also suggests that the dogma of self-MHC restriction needs some refinement to accommodate foreign peptide recognition in the context of multiple supertype alleles.

Potent T cell response to a class I-binding 13-mer viral epitope and the influence of HLA micropolymorphism in controlling epitope length

The BZLF1 antigen of Epstein-Barr virus includes three overlapping sequences of different lengths that conform to the binding motif of human leukocyte antigen (HLA) B*3501. These 9-mer ((56)LPOGQLTAy(64)), 11-mer ((54)EPLPQGQLTAy(64)), and 13-mer ((52)LPEPLPQGQLTAY(64)) peptides all bound well to B*3501; however, the CTL response in individuals expressing this HILA allele was directed strongly and exclusively towards the 11-mer peptide. In contrast, EBV-exposed donors expressing HLA B*3503 showed no significant CTL response to these peptides because the single amino acid difference between B*3501 and B*3503 within the F pocket inhibited HLA binding by these peptides. The extraordinarily long 13-mer peptide was the target for the CTL response in individuals expressing B*3508, which differs from B*3501 at a single position within the D pocket (B*3501, 156 Leucine; B*3508, 156 Arginine). This minor difference was shown to enhance binding of the 13-mer peptide, presumably through a stabilizing interaction between the negatively charged glutamate at position 3 of the peptide and the positively charged arginine at HLA position 156. The 13-mer epitope defined in this study represents the longest class I-binding viral epitope identified to date as a minimal determinant. Furthermore, the potency of the response indicates that peptides of this length do not present a major structural barrier to CTL recognition.

MULTIPRED: A computational system for prediction of promiscuous HLA binding peptides

MULTIPRED is a web-based computational system for the prediction of peptide binding to multiple molecules ( proteins) belonging to human leukocyte antigens (HLA) class I A2, A3 and class II DR supertypes. It uses hidden Markov models and artificial neural network methods as predictive engines. A novel data representation method enables MULTIPRED to predict peptides that promiscuously bind multiple HLA alleles within one HLA supertype. Extensive testing was performed for validation of the prediction models. Testing results show that MULTIPRED is both sensitive and specific and it has good predictive ability ( area under the receiver operating characteristic curve A(ROC) > 0.80). MULTIPRED can be used for the mapping of promiscuous T-cell epitopes as well as the regions of high concentration of these targets termed T-cell epitope hotspots. MULTIPRED is available at http:// antigen.i2r.a-star.edu.sg/ multipred/.

A population of HLA-DR+ immature cells accumulates in the blood dendritic cell compartment of patients with different types of cancer

Dendritic cell (DC) defects are an important component of immunosuppression in cancer. Here, we assessed whether cancer could affect circulating DC populations and its correlation with tumor progression. The blood DC compartment was evaluated in 136 patients with breast cancer, prostate cancer, and malignant glioma. Phenotypic, quantitative, and functional analyses were performed at various stages of disease. Patients had significantly fewer circulating myeloid (CD11c(+)) and plasmacytoid (CD123(+)) DC, and a concurrent accumulation of CD11c(-)CD123(-) immature cells that expressed high levels of HLA-DR+ immature cells (DR+IC). Although DR+IC exhibited a limited expression of markers ascribed to mature hematopoietic lineages, expression of HLA-DR, CD40, and CD86 suggested a role as antigen-presenting cells. Nevertheless, DR+IC had reduced capacity to capture antigens and elicited poor proliferation and interferon-gamma secretion by T-lymphocytes. Importantly, increased numbers of DR+IC correlated with disease status. Patients with metastatic breast cancer showed a larger number of DR+IC in the circulation than patients with local/nodal disease. Similarly, in patients with fully resected glioma, the proportion of DR+IC in the blood increased when evaluation indicated tumor recurrence. Reduction of blood DC correlating with accumulation of a population of immature cells with poor immunologic function may be associated with increased immunodeficiency observed in cancer.

Extreme learning machine for predicting HLA-peptide binding

Machine learning techniques have been recognized as powerful tools for learning from data. One of the most popular learning techniques, the Back-Propagation (BP) Artificial Neural Networks, can be used as a computer model to predict peptides binding to the Human Leukocyte Antigens (HLA). The major advantage of computational screening is that it reduces the number of wet-lab experiments that need to be performed, significantly reducing the cost and time. A recently developed method, Extreme Learning Machine (ELM), which has superior properties over BP has been investigated to accomplish such tasks. In our work, we found that the ELM is as good as, if not better than, the BP in term of time complexity, accuracy deviations across experiments, and most importantly - prevention from over-fitting for prediction of peptide binding to HLA.