Can We Use Eplets (or Molecular) Mismatch Load Analysis to Improve Organ Allocation? The Hope and the Hype. Issue 3 (27th September 2022)

• Record Type: Journal Article
• Authors: Tambur, Anat R.; Das, Rajdeep
• Is Part Of: Transplantation. Volume 107:Issue 3(2023)
• Page Start: 605
• Page End: 615
• Publication Date: 2022-09-27
• Subjects: Transplantation of organs, tissues, etc -- Periodicals; Transplantation immunology -- Periodicals; 617.95
• DOI: 10.1097/TP.0000000000004307
• Languages: English
• ISSNs: 0041-1337

Abstract

Abstract : In recent years, there have been calls for implementation of "epitope matching" in deceased-donor organ allocation policies (later changed to "eplet matching"). Emerging data indeed support the use of molecular mismatch load analysis in specific patient groups, with the objective of posttransplant stratification into different treatment arms. For this purpose, the expectation is to statistically categorize patients as low- or high-immune-risk. Importantly, these patients will continue to be monitored‚ and their risk category, as well as their management, can be adjusted according to on-going findings. However, when discussing deceased donor organ allocation and matching algorithms, where the decision is not modifiable and has lasting impact on outcomes, the situation is fundamentally different. The goal of changing allocation schemes is to achieve the best possible HLA compatibility between donor and recipient. Immunologically speaking, this is a very different objective. For this purpose, the specific interplay of immunogenicity between the donor and any potential recipient must be understood. In seeking compatibility, the aim is not to redefine matching but to identify those mismatches that are "permissible" or‚ in other words, less immunogenic. In our eagerness to improve transplant outcome, unfortunately, we have conflated the hype with the hope. Terminology is used improperly, and new terms are created in the process with no sufficient support. Here, we call for a cautious evaluation of baseline assumptions and a critical review of the evidence to minimize unintended consequences. Abstract :