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PIRCHE-II: an algorithm to predict indirectly recognizable HLA epitopes in solid organ transplantation.

Kirsten GeneugelijkEric Spierings
Published in: Immunogenetics (2019)
Human leukocyte antigen (HLA) mismatches between donors and recipients may lead to alloreactivity after solid organ transplantation. Over the last few decades, our knowledge of the complexity of the HLA system has dramatically increased, as numerous new HLA alleles have been identified. As a result, the likelihood of alloreactive responses towards HLA mismatches after solid organ transplantation cannot easily be assessed. Algorithms are promising solutions to estimate the risk for alloreactivity after solid organ transplantation. In this review, we show that the recently developed PIRCHE-II (Predicted Indirectly ReCognizable HLA Epitopes) algorithm can be used to minimize alloreactivity towards HLA mismatches. Together with the use of other algorithms and simulation approaches, the PIRCHE-II algorithm aims for a better estimated alloreactive risk for individual patients and eventually an improved graft survival after solid organ transplantation.
Keyphrases
  • machine learning
  • deep learning
  • cell therapy
  • end stage renal disease
  • endothelial cells
  • newly diagnosed
  • chronic kidney disease
  • stem cells
  • mesenchymal stem cells
  • prognostic factors
  • bone marrow