Literature DB >> 29464898

Matching donor and recipient based on predicted indirectly recognizable human leucocyte antigen epitopes.

K Geneugelijk1, E Spierings1.   

Abstract

The predicted indirectly recognizable human leucocyte antigen (HLA) epitopes (PIRCHE) algorithm is a novel in silico algorithm to determine donor-recipient compatibility. The PIRCHE algorithm determines donor-recipient compatibility by counting the number of mismatched HLA-derived epitopes that are involved in indirect T-cell alloimmune responses; these epitopes are designated as PIRCHE. Over the last few years, the PIRCHE algorithm has been investigated in both hematopoietic stem cell transplantation and solid organ transplantation. This review describes the theory of the algorithm, its application in transplantation, and highlights the future perspectives on the clinical application of the PIRCHE algorithm.
© 2018 John Wiley & Sons Ltd.

Entities:  

Keywords:  PIRCHE; epitopes; histocompatibility; human leucocyte antigen; matching; transplantation

Mesh：

Substances：

Year:  2018        PMID： 29464898     DOI： 10.1111/iji.12359

Source DB:  PubMed          Journal:  Int J Immunogenet        ISSN： 1744-3121            Impact factor:   1.466


  10 in total

Review 1.  T cell optimization for graft-versus-leukemia responses.

Authors:  Melinda A Biernacki; Vipul S Sheth; Marie Bleakley
Journal:  JCI Insight       Date:  2020-05-07

2.  Predicting kidney transplant outcomes with partial knowledge of HLA mismatch.

Authors:  Charles F Manski; Anat R Tambur; Michael Gmeiner
Journal:  Proc Natl Acad Sci U S A       Date:  2019-09-23       Impact factor: 11.205

Review 3.  Emerging monitoring technologies in kidney transplantation.

Authors:  Abdulla Ehlayel; K'joy J A Simms; Isa F Ashoor
Journal:  Pediatr Nephrol       Date:  2021-02-01       Impact factor: 3.714

4.  Exploratory Study of Predicted Indirectly ReCognizable HLA Epitopes in Mismatched Hematopoietic Cell Transplantations.

Authors:  Kirsten Geneugelijk; Kirsten A Thus; Hanneke W M van Deutekom; Jorg J A Calis; Eric Borst; Can Keşmir; Machteld Oudshoorn; Bronno van der Holt; Ellen Meijer; Sacha Zeerleder; Marco R de Groot; Peter A von dem Borne; Nicolaas Schaap; Jan Cornelissen; Jürgen Kuball; Eric Spierings
Journal:  Front Immunol       Date:  2019-04-24       Impact factor: 7.561

5.  Can PIRCHE-II Matching Outmatch Traditional HLA Matching?

Authors:  Christian Unterrainer; Bernd Döhler; Matthias Niemann; Nils Lachmann; Caner Süsal
Journal:  Front Immunol       Date:  2021-02-26       Impact factor: 7.561

6.  Snowflake: A deep learning-based human leukocyte antigen matching algorithm considering allele-specific surface accessibility.

Authors:  Matthias Niemann; Benedict M Matern; Eric Spierings
Journal:  Front Immunol       Date:  2022-07-29       Impact factor: 8.786

7.  PIRCHE-II scores prove useful as a predictive biomarker among kidney transplant recipients with rejection: An analysis of indication and follow-up biopsies.

Authors:  Tahm Spitznagel; Laurenz S Matter; Yves L Kaufmann; Jakob Nilsson; Seraina von Moos; Thomas Schachtner
Journal:  Front Immunol       Date:  2022-08-17       Impact factor: 8.786

8.  Computational Eurotransplant kidney allocation simulations demonstrate the feasibility and benefit of T-cell epitope matching.

Authors:  Matthias Niemann; Nils Lachmann; Kirsten Geneugelijk; Eric Spierings
Journal:  PLoS Comput Biol       Date:  2021-07-27       Impact factor: 4.475

Review 9.  The long and winding road towards epitope matching in clinical transplantation.

Authors:  Cynthia S M Kramer; Moshe Israeli; Arend Mulder; Ilias I N Doxiadis; Geert W Haasnoot; Sebastiaan Heidt; Frans H J Claas
Journal:  Transpl Int       Date:  2018-11-26       Impact factor: 3.782

10.  Analysis of T and B Cell Epitopes to Predict the Risk of de novo Donor-Specific Antibody (DSA) Production After Kidney Transplantation: A Two-Center Retrospective Cohort Study.

Authors:  Shintaro Sakamoto; Kenta Iwasaki; Toshihide Tomosugi; Matthias Niemann; Eric Spierings; Yuko Miwa; Kosei Horimi; Asami Takeda; Norihiko Goto; Shunji Narumi; Yoshihiko Watarai; Takaaki Kobayashi
Journal:  Front Immunol       Date:  2020-08-27       Impact factor: 7.561
  10 in total

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