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Clinical Trial Summary

Microvascular inflammation, the hallmark histological criteria of antibody-mediated rejection in kidney transplantation, remains an issue in routine practice, due to a lack of reproducibility in its recognition by pathologists and an incomplete comprehension of its pathophysiology, leading to a poor treatment efficacy. The main objective of this study is to assess the performances of tissue proteic signatures designed for the diagnosis of microvascular inflammation in kidney transplantation, from formalin-fixed and paraffin-embedded (FFPE) allograft biopsies analyzed by mass spectrometry-based proteomics.


Clinical Trial Description

Antibody-mediated rejection (ABMR) is due to pathogenic antibodies produced by the donor (donor-specific antibodies, DSA) that are directed against Human Leukocyte Antigens (HLA) or other antigens (non HLA) of the graft. ABMR is currently the leading cause of long-term kidney allograft failure. Histological lesions of microvascular inflammation (MVI) are the hallmark criteria of ABMR according to the 2019 Banff classification. Lack of reproducibility in the scoring of MVI by pathologists is still an issue of the diagnosis of ABMR in routine practice, while the understood pathophysiological mechanisms of MVI (anti-HLA DSA, DSA against non HLA antigens and/or NK cell-mediated) are poorly assessed in practice, possibly explaining the wide variability of treatment efficacy. In a prior study, the investigators confirmed the value of mass spectrometry for the analysis of the glomerular proteome during ABMR, compared to the one of stable grafts, from FFPE biopsies. The investigators identified 82 proteins, particularly involved in leukocyte activation and the interferons pathways, in accordance with transcriptomic approaches. Five proteins were validated by immunohistochemistry. The investigators now propose to analyze kidney allograft FFPE biopsies of 92 patients by mass spectrometry, including 32 with MVI (with and without anti-HLA DSA) and 60 with relevant differential diagnoses. The main objective is to assess the diagnostic performances of tissue proteic signatures designed by machine-learning methods for the diagnosis of microvascular inflammation, the reference standard being the 2019 Banff classification. One of the secondary objectives includes the comparison of the protein profile of MVI with and without anti-HLA DSA, but also the proteomic analysis of 60 urine samples from the same population, in order to assess the performances of mass spectrometry in the non-invasive diagnosis of MVI in kidney transplantation. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT04851145
Study type Interventional
Source University Hospital, Bordeaux
Contact Bertrand CHAUVEAU, Dr
Phone 5 56 72 21 24
Email bertrand.chauveau@chu-bordeaux.fr
Status Recruiting
Phase N/A
Start date November 8, 2021
Completion date May 2024

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