Alessia Giarraputo, Guillaume Coutance, Jignesh K Patel, Marny Fedrigo, Olivier Aubert, S. Varnous, Ilaria Barison, Chiara Castellani, Jean–Paul Duong Van Huyen, Jessy Dagobert, Fariza Mezine, Blaise Robin, Dina Zielinski, Philippe Rouvier, Pascal Leprince, Paul Achouh, Gino Gerosa, Virginie Verkarre, X. Jouven, Patrick Bruneval, Annalisa Angelini, Jon Kobashigawa, Alexandre Loupy
BACKGROUND AND AIMS: Tissular gene expression profiling applicable to formalin-fixed, paraffin-embedded (FFPE) endomyocardial biopsies (EMBs) may refine the diagnosis of cardiac rejection while being easily implemented in clinical practice. This study aimed to develop and validate the first FFPE-based molecular diagnostic system dedicated to heart transplant rejection. METHODS: An international study was conducted (NCT06436027), establishing a deeply phenotyped cohort of heart transplant recipients. EMBs were graded according to international classifications, and gene expression was analysed on FFPE-EMBs using the Banff Human Organ Transplant Panel. Molecular classifiers for antibody-mediated rejection (AMR) and acute cellular rejection (ACR) were developed, with discrimination and calibration assessed in internal and external validation cohorts. RESULTS: A total of 671 biopsies were included, with 591 in the main cohort (AMR: n = 188, ACR: n = 289, matched non-rejection: n = 114); this was split into a derivation set (n = 475) and an internal validation set (n = 116). The external validation cohort comprised 80 biopsies (AMR: n = 20, ACR: n = 32, non-rejection: n = 28). AMR was associated with significant transcripts related to the interferon-gamma pathway, endothelial activation, and monocyte-macrophage recruitment, while ACR was characterized by transcripts related to T-cell receptor signalling, CD3 receptor activation, and CD28 signalling. Molecular ACR and AMR models accurately identified rejection in the validation cohorts (internal: ROC-AUC: AMR = 0.812, ACR = 0.849; external: ROC-AUC: AMR = 0.822, ACR = 0.815) and were strongly associated with pathologic severity. Calibration was adequate. An automated report was developed to enhance the clinical applicability of these classifiers. CONCLUSIONS: A novel FFPE-based molecular diagnostic system accurately identified cardiac allograft rejection. This tool is readily applicable in clinical practice as a companion to pathology and has the potential to refine the diagnosis of rejection.