Computer-Assisted Definition of the Inflammatory Infiltrates in Patients With Different Categories of Banff Kidney Allograft Rejection

Copyright © 2019 Aguado-Domínguez, Cabrera-Pérez, Suarez-Benjumea, AbadMolina, Núñez-Roldán and Aguilera.
Currently, the diagnosis of kidney allograft rejection relies on individual histological assessments made by expert pathologists according to the Banff classification. In this study, we applied new Computer-Assisted System Technology (newCAST™) by Visiopharm® with the aim of identifying and quantifying the immune cells in inflammatory infiltrates. We searched for distinctive cellular profiles that could be assigned to each rejection category of the Banff schema: antibody-mediated rejection (active and chronic active), borderline, T cell-mediated rejection (TCMR), and mixed rejection. This study was performed with 49 biopsy samples, 42 from patients with rejection and 7 from patients with clinical signs of dysfunction but an absence of histological findings of rejection. Plasma cells, B and T lymphocytes, natural killer cells, and macrophages, with a special focus on the M1 and M2 subsets, were studied. A major difference among the Banff rejection groups was in the total amount of cells/mm2 tissue. Principal component analysis identified some distinctive associations. The borderline category grouped with CD4+ lymphocytes and M1 macrophages, and active antibody-mediated rejection (aAMR) clustered with natural killer cells. Despite these findings, the search for characteristic profiles linked to the rejection types proved to be a very difficult task since the cellular composition varied significantly among individuals within the same diagnostic category. The results of this study will be analyzed from the perspective of reconciling the classic way of diagnosing rejection and the immune situation “in situ” at the time of diagnosis.
This study was supported by the Spanish Ministry of Economy, Instituto de Salud Carlos III, Grants 17/1403 and the Andalusian government, Consejería de Economía, Innovación, Ciencia y Empleo, Proyecto de Excelencia CTS-7846, and was co-funded by FEDER from the Regional Development European Funds (European Union).