ArticleMethods in molecular biology (Clifton, N.J.)2024
PIRCHE-II Risk and Acceptable Mismatch Profile Analysis in Solid Organ Transplantation.
Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Simulation of prospective PIRCHE-II molecular matching in Canada: a feasibility study.Frontiers in immunology · 2026Article
- Article
- Predicted indirectly recognizable HLA epitopes scores and clinical outcomes after haploidentical stem cell transplantation in pediatric patients with relapsed neuroblastoma.Frontiers in immunology · 2025Article
- Quantifying uncertainty of molecular mismatch introduced by mislabeled ancestry using haplotype-based HLA genotype imputation.Frontiers in genetics · 2024Article
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Authors and funding
3 authors.
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Abstract
To optimize outcomes in solid organ transplantation, the HLA genes are regularly compared and matched between the donor and recipient. However, in many cases a transplant cannot be fully matched, due to widespread variation across populations and the hyperpolymorphism of HLA alleles. Mismatches of the HLA molecules in transplanted tissue can be recognized by immune cells of the recipient, leading to immune response and possibly organ rejection. These adverse outcomes are reduced by analysis using epitope-focused models that consider the immune relevance of the mismatched HLA.PIRCHE, an acronym for Predicted Indirectly ReCognizable HLA Epitopes, aims to categorize and quantify HLA mismatches in a patient-donor pair by predicting HLA-derived T cell epitopes. Specifically, the algorithm predicts and counts the HLA-derived peptides that can be presented by the host HLA, known as indirectly-presented T cell epitopes. Looking at the immune-relevant epitopes within HLA allows a more biologically relevant understanding of immune response, and provides an expanded donor pool for a more refined matching strategy compared with allele-level matching. This PIRCHE algorithm is available for analysis of single transplantations, as well as bulk analysis for population studies and statistical analysis for comparison of probability of organ availability and risk profiles.
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