Prediction of cross-recognition of peptide-HLA A2 by Melan-A-specific cytotoxic T lymphocytes using three-dimensional quantitative structure-activity relationships.

The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.

Characterization of Melan-A reactive memory CD8+ T cells in a healthy donor.

Melan-A specific CD8+ T cells are thought to play an important role against the development of melanoma. Their in vivo expansion is often observed with advanced disease. In recent years, low levels of Melan-A reactive CD8+ T cells have also been found in HLA-A2 healthy donors, but these cells harbor naive characteristics and are thought to be mostly cross-reactive for the Melan-A antigen. Here, we report on a large population of CD8+ T cells reactive for the Melan-A antigen, identified in one donor with no evidence of melanoma. Interestingly, this population is oligoclonal and displays a clear memory phenotype. However, a detailed study of these cells indicated that they are unlikely to be directly specific for melanoma, so that their in vivo expansion may have been driven by an exogenous antigen. Screening of a Melan-A cross-reactive peptide library suggested that these cells may be specific for an epitope derived from a Mycobacterium protein, which would provide a further example of CD8+ T cell cross-reactivity between a pathogen antigen and a tumor antigen. Finally, we discuss potential perspectives regarding the role of such cells in heterologous immunity, by influencing the balance between protective immunity and pathology, e.g. in the case of melanoma development.

Immunogenicity of the carcinoembryonic antigen derived peptide 694 in HLA-A2 healthy donors and colorectal carcinoma patients.

Carcinoembryonic antigen (CEACAM5) is commonly overexpressed in human colon cancer. Several antigenic peptides recognized by cytolytic CD8+ T-cells have been identified and used in colon cancer phase-I vaccination clinical trials. The HLA-A*0201-binding CEA(694-702) peptide was recently isolated from acid eluted MHC-I associated peptides from a human colon tumor cell line. However, the immunogenicity of this peptide in humans remains unknown. We found that the peptide CEA(694-702) binds weakly to HLA-A*0201 molecules and is ineffective at inducing specific CD8+ T-cell responses in healthy donors. Immunogenic-altered peptide ligands with increased affinity for HLA-A*0201 were identified. Importantly, the elicited cytolytic T lymphocyte (CTL) lines and clones cross-reacted with the wild-type CEA(694-702) peptide. Tumor cells expressing CEA were recognized in a peptide and HLA-A*0201 restricted fashion, but high-CEA expression levels appear to be required for CTL recognition. Finally, CEA-specific T-cell precursors could be readily expanded by in vitro stimulation of peripheral blood mononuclear cell (PBMC) from colon cancer patients with altered CEA peptide. However, the CEA-specific CD8+ T-cell clones derived from cancer patients revealed low-functional avidity and impaired tumor-cell recognition. Together, using T-cells to demonstrate the processing and presentation of the peptide CEA694-702, we were able to corroborate its presentation by tumor cells. However, the low avidity of the specific CTLs generated from cancer patients as well as the high-antigen expression levels required for CTL recognition pose serious concerns for the use of CEA694-702 in cancer immunotherapy.

Impact of orthologous melan-A peptide immunizations on the anti-self melan-A/HLA-A2 T cell cross-reactivity.

In HLA-A2 individuals, the CD8 T cell response against the differentiation Ag Melan-A is mainly directed toward the peptide Melan-A26-35. The murine Melan-A24-33 sequence encodes a peptide that is identical with the human Melan-A26-35 decamer, except for a Thr-to-Ile substitution at the penultimate position. Here, we show that the murine Melan-A24-33 is naturally processed and presented by HLA-A2 molecules. Based on these findings, we compared the CD8 T cell response to human and murine Melan-A peptide by immunizing HLA-A2 transgenic mice. Even though the magnitude of the CTL response elicited by the murine Melan-A peptide was lower than the one elicited by the human Melan-A peptide, both populations of CTL recognized the corresponding immunizing peptide with the same functional avidity. Interestingly, CTL specific for the murine Melan-A peptide were completely cross-reactive against the orthologous human peptide, whereas anti-human Melan-A CTL recognized the murine Melan-A peptide with lower avidity. Structurally, this discrepancy could be explained by the fact that Ile32 of murine Melan-A24-33 created a larger TCR contact area than Thr34 of human Melan-A26-35. These data indicate that, even if immunizations with orthologous peptides can induce strong specific T cell responses, the quality of this response against syngeneic targets might be suboptimal due to the structure of the peptide-TCR contact surface.

Structural prediction of peptides bound to MHC class I.

An ab initio structure prediction approach adapted to the peptide-major histocompatibility complex (MHC) class I system is presented. Based on structure comparisons of a large set of peptide-MHC class I complexes, a molecular dynamics protocol is proposed using simulated annealing (SA) cycles to sample the conformational space of the peptide in its fixed MHC environment. A set of 14 peptide-human leukocyte antigen (HLA) A0201 and 27 peptide-non-HLA A0201 complexes for which X-ray structures are available is used to test the accuracy of the prediction method. For each complex, 1000 peptide conformers are obtained from the SA sampling. A graph theory clustering algorithm based on heavy atom root-mean-square deviation (RMSD) values is applied to the sampled conformers. The clusters are ranked using cluster size, mean effective or conformational free energies, with solvation free energies computed using Generalized Born MV 2 (GB-MV2) and Poisson-Boltzmann (PB) continuum models. The final conformation is chosen as the center of the best-ranked cluster. With conformational free energies, the overall prediction success is 83% using a 1.00 Angstroms crystal RMSD criterion for main-chain atoms, and 76% using a 1.50 Angstroms RMSD criterion for heavy atoms. The prediction success is even higher for the set of 14 peptide-HLA A0201 complexes: 100% of the peptides have main-chain RMSD values < or =1.00 Angstroms and 93% of the peptides have heavy atom RMSD values < or =1.50 Angstroms. This structure prediction method can be applied to complexes of natural or modified antigenic peptides in their MHC environment with the aim to perform rational structure-based optimizations of tumor vaccines.