Abstract
Gene profiling methods have been widely useful for delineating changes in gene expression as an approach for gaining insight into the mechanism of rejection or disease pathology. Herein, we use gene profiling to compare changes in gene expression associated with different orthotopic cardiac xenotransplantation (OCXTx) outcomes and to identify potential effects of OCXTx on cardiac physiology. We used the Affymetrix GeneChip Porcine Genomic Array to characterize three types of orthotopic cardiac xenograft outcomes: 1) rejected hearts that underwent delayed xenograft rejection (DXR); 2) survivor hearts in which the xenograft was not rejected and recipient death was due to model complications; and 3) hearts which failed to provide sufficient circulatory support within the first 48 h of transplant, termed "perioperative cardiac xenograft dysfunction" (PCXD). Gene expression in each group was compared to control, not transplanted pig hearts, and changes in gene expression > 3 standard deviations (±3SD) from the control samples were analyzed. A bioinformatics analysis was used to identify enrichments in genes involved in Kyoto Encyclopedia of Genes and Genomes pathways and gene ontogeny molecular functions. Changes in gene expression were confirmed by quantitative RT-PCR. The ±3SD data set contained 260 probes, which minimally exhibited a 3.5-fold change in gene expression compared to control pig hearts. Hierarchical cluster analysis segregated rejected, survivor and PCXD samples, indicating a unique change in gene expression for each group. All transplant outcomes shared a set of 21 probes with similarly altered expression, which were indicative of ongoing myocardial inflammation and injury. Some outcome-specific changes in gene expression were identified. Bioinformatics analysis detected an enrichment of genes involved in protein, carbohydrate and branched amino acid metabolism, extracellular matrix-receptor interactions, focal adhesion, and cell communication. This is the first genome wide assessment of changes in cardiac gene expression after OCXTx. Hierarchical cluster analysis indicates a unique gene profile for each transplant outcome but additional samples will be required to define the unique classifier probe sets. Quantitative RT-PCR confirmed that all transplants exhibited strong evidence of ongoing inflammation and myocardial injury consistent with the effects of cytokines and vascular antibody-mediated inflammation. This was also consistent with bioinformatic analysis suggesting ongoing tissue repair in survivor and PCXD samples. Bioinformatics analysis suggests for the first time that xenotransplantation may affect cardiac metabolism in survivor and rejected samples. This study highlights the potential utility of molecular analysis to monitor xenograft function, to identify new molecular markers and to understand processes, which may contribute to DXR.
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