The traditional run will take place on Thursday, June 1st from 07:00 till 09:00.
The running distance is 5 km. Information about the exact route will follow soon.
People can also join if they want to walk, instead of running. Participants can pick up their running shirts at GenDx booth. At the end of the run three prizes will be given to the best runners and all participants will receive a small souvenir. Water, bananas and muesli bars will be provided at the Finish.
Participants can register here http://efi2017.org/scientific-program/social-events/
HLA matching of donor and recipient is beneficial for the outcome of most types of solid organ transplants. However, the enormous polymorphism of the HLA system makes the selection of an HLA identical unrelated donor very difficult. Already from the very beginning of the HLA story, it became clear that antibodies induced by a certain HLA mismatch like for instance HLA-A2 often cross react with other HLA antigens like HLA-A28 or B17. In the meantime, molecular HLA typing has led to the identification of almost 15,000 HLA alleles but also to the identification of crucial amino acids on the HLA molecules, that are responsible for the induction and reactivity of HLA antibodies: the HLA epitopes. It is clear now that every HLA molecules carries a unique set of antibody epitopes but the individual epitopes are often shared with other HLA alleles. As a consequence, the immunogenicity of HLA mismatches will differ. HLA antigens with many epitope differences compared to the HLA antigens of a patient are more likely to induce antibodies than HLA antigens which share many epitopes with the patient.
In this teaching session, different strategies to determine the likelihood that a mismatched donor HLA antigen will induce antibodies will be discussed, including examples of clinical studies suggestive for a beneficial effect of HLA epitope matching.
A second application of epitope matching could be in virtual crossmatching for patients with already existing antibodies. By careful analysis of the epitopes recognized by the antibodies, one could predict which HLA alleles will lead to positive and negative crossmatches. These analyses are more complicated than the ones aiming at the determination of the immunogenicity of an HLA mismatch. Only a few amino-acid differences may be the trigger for antibody formation but the actual antibody may need up to 6 crucial contact sites with the HLA molecule in order to react with the mismatched HLA molecule.
The most relevant HLA antibodies are of the IgG class, which implies that B cells should be triggered to switch from the production of IgM antibodies to IgG antibodies. CD4+ T cells are crucial for such a class switch. In order for a CD4+ T cell to be able to help a B cell, it must recognize a peptide derived from the same HLA molecule as the one recognized by the B cell. Peptides derived from this HLA molecule can indeed be presented as peptides by class II molecules of the B cells to cognate helper T-cells, which then provide signals and cytokines to these B cells to undergo activation and differentiation. In this teaching session, the predicted indirectly recognizable HLA epitopes (PIRCHE) computational algorithm will be discussed, which is designed to predict indirectly recognizable HLA-derived donor peptides that are likely to induce the production of donor specific anti-HLA IgG antibodies. High number of PIRCHE, likely to represent a higher number of epitopes that can be presented by HLA class-II molecules correlate with a higher incidence of antibody formation, suggestive that the relevant T cell epitopes are included in this algorithm.
It is clear that epitope matching has more potential than classical HLA antigen matching, especially for the prediction of antibody formation after transplantation. However, there are still many shortcomings, which will be discussed. On the population level, the current approaches seem to be useful for the prediction of antibody formation but the final goal should be a reliable prediction for an individual patient.
With kind support of STEMCELL Technologies
With kind support of One Lambda
With kind support of Histogenetics LLC
With kind support of Linkage Biosciences
With kind support of Illumina