Graft Survival

Xenotransplantation represents a possible solution to the organ shortage crisis and is an imminent clinical reality with long-term xenograft survival in pig-to-nonhuman primate (NHP) heart and kidney large animal models, and short-term success in recent human decedent and clinical studies. However, concerns remain about safe clinical translation of these results, given the inconsistency in published survival as well as key differences between preclinical procurement and immunosuppression and clinical standards-of-care. Notably, no studies of solid organ pig-to-NHP transplantation have achieved xenograft survival longer than one month without CD40/CD154 costimulatory blockade, which is not currently an FDA-approved immunosuppression strategy. We now present consistent survival in consecutive cases of pig-to-NHP kidney xenotransplantation, including long-term survival after >3 hours of xenograft cold preservation time as well as long-term survival using FDA-approved immunosuppression. These data provide critical supporting evidence for the safety and feasibility of clinical kidney xenotransplantation. Moreover, long-term survival without CD40/CD154 costimulatory blockade may provide important insights for immunosuppression regimens to be considered for first-in-human clinical trials.

Transplantation (Tx) remains the optimal therapy for end-stage disease (ESD) of various solid organs. Although alloimmune events remain the leading cause of long-term allograft loss, many patients develop innate and adaptive immune responses leading to graft tolerance. The focus of this review is to provide an overview of selected aspects of the effects of inflammation on this delicate balance following solid organ transplantation. Initially, we discuss the inflammatory mediators detectable in an ESD patient. Then, the specific inflammatory mediators found post-Tx are elucidated. We examine the reciprocal relationship between donor-derived passenger leukocytes (PLs) and those of the recipient, with additional emphasis on extracellular vesicles, specifically exosomes, and we examine their role in determining the balance between tolerance and rejection. The concept of recipient antigen-presenting cell "cross-dressing" by donor exosomes is detailed. Immunological consequences of the changes undergone by cell surface antigens, including HLA molecules in donor and host immune cells activated by proinflammatory cytokines, are examined. Inflammation-mediated donor endothelial cell (EC) activation is discussed along with the effect of donor-recipient EC chimerism. Finally, as an example of a specific inflammatory mediator, a detailed analysis is provided on the dynamic role of Interleukin-6 (IL-6) and its receptor post-Tx, especially given the potential for therapeutic interdiction of this axis with monoclonal antibodies. We aim to provide a holistic as well as a reductionist perspective of the inflammation-impacted immune events that precede and follow Tx. The objective is to differentiate tolerogenic inflammation from that enhancing rejection, for potential therapeutic modifications. (Words 247).

BackgroundKidney transplantation is the optimal treatment for patients with end-stage renal disease. Short- and long-term kidney graft survival is influenced by a number of donor and recipient factors. Predicting the success of kidney transplantation is important for optimizing kidney allocation.ObjectiveThe aim of this study was to predict the risk of kidney graft failure across three temporal cohorts (within 1 year, within 5 years, and after 5 years following a transplant) based on donor and recipient characteristics. We analyzed a large data set comprising over 50,000 kidney transplants covering an approximate 20-year period.MethodsWe applied machine learning-based classification algorithms to develop prediction models for the risk of graft failure for three different temporal cohorts. Deep learning-based autoencoders were applied for data dimensionality reduction, which improved the prediction performance. The influence of features on graft survival for each cohort was studied by investigating a new nonoverlapping patient stratification approach.ResultsOur models predicted graft survival with area under the curve scores of 82% within 1 year, 69% within 5 years, and 81% within 17 years. The feature importance analysis elucidated the varying influence of clinical features on graft survival across the three different temporal cohorts.ConclusionsIn this study, we applied machine learning to develop risk prediction models for graft failure that demonstrated a high level of prediction performance. Acknowledging that these models performed better than those reported in the literature for existing risk prediction tools, future studies will focus on how best to incorporate these prediction models into clinical care algorithms to optimize the long-term health of kidney recipients.

T-cell-mediated rejection (TCMR) remains a major cause of kidney transplant failure, despite being considered treatable. Its impact reflects a limited understanding of the underlying molecular mechanisms and their clinical consequences. To address this, we induced acute TCMR in mouse kidney transplants and profiled molecular changes using single-nucleus RNA sequencing (snRNA-seq), spatial transcriptomics and immunofluorescence. Results were compared with human snRNA-seq data from TCMR and stable allografts, as well as single-cell deconvolution analysis of bulk transcriptomic data from kidney transplant biopsies. Here we show that TCMR induces injured epithelial cell states in mouse kidney allografts, particularly in proximal tubules and thick ascending limbs. Spatial transcriptomics of these injured epithelial states demonstrated heterogeneous localization, interactions with immune cells and cellular microenvironments. Cross-species analysis confirmed similar severely injured epithelial states in human samples, whose abundances correlated with transplant survival and persisted despite TCMR resolution. Collectively, our results identify epithelial injury cell states as a determinant of outcome after TCMR.