Characterizing the Immune Response in Pig-to-Human Heart Xenografts Using a Multimodal Diagnostic System.

Abstract

Porcine genome editing has revolutionized xenotransplantation, recently enabling the first pig-to-human heart xenotransplants. However, the xenoimmune response in heart xenografts remains largely unexplored. This study aimed to precisely characterize the xenoimmune response and injury in 2 heart xenografts transplanted from 10-gene-edited pigs into brain-dead human recipients. We analyzed xenograft biopsy specimens 66 hours after reperfusion using a multimodal phenotyping approach combining morphological evaluation, immunophenotyping, ultrastructural assessment, automated quantification of multiplex immunofluorescence staining, and gene expression profiling. Xenografts before implantation and wild-type pig hearts with and without ischemia/reperfusion injury and brain death were used as controls. Both xenografts showed evidence of endothelial activation and mild microvascular inflammation without capillary C4d deposition. Immune infiltrates were mainly composed of CD15+ and CD68+ innate immune cells. Ultrastructural assessment showed endothelial swelling with occasional intravascular leucocytes. Deep learning-based automated multiplex immunofluorescence analysis confirmed that microvascular inflammation was primarily associated with CD15+ and CD68+ innate immune cells. Both xenografts showed increased expression of genes and pathways associated with monocyte/macrophage activation, neutrophil activation, interferon-gamma response, natural killer cell burden, endothelial activation, apoptosis, and injury repair. This phenotype was absent in all control pig hearts independent of ischemia/reperfusion injury and brain death. Multimodal phenotyping of pig-to-human heart xenografts revealed early signs of xenoimmune response, characterized by mild innate microvascular inflammation, endothelial activation, and a molecular signature characteristic of antibody-mediated rejection. Developing such a precision diagnostic system could improve graft monitoring in future clinical settings.