Transplantation of bioengineered rat lungs recellularized with endothelial and adipose-derived stromal cells

Bioengineered lungs consisting of a decellularized lung scaffold that is repopulated with a patient’s own cells could provide desperately needed donor organs in the future. This approach has been tested in rats, and has been partially explored in porcine and human lungs. However, existing bioengineered lungs are fragile, in part because of their immature vascular structure. Herein, we report the application of adipose-derived stem/stromal cells (ASCs) for engineering the pulmonary vasculature in a decellularized rat lung scaffold. We found that pre-seeded ASCs differentiated into pericytes and stabilized the endothelial cell (EC) monolayer in nascent pulmonary vessels, thereby contributing to EC survival in the regenerated lungs. The ASC-mediated stabilization of the ECs clearly reduced vascular permeability and suppressed alveolar hemorrhage in an orthotopic transplant model for up to 3?h after extubation. Fibroblast growth factor 9, a mesenchyme-targeting growth factor, enhanced ASC differentiation into pericytes but overstimulated their proliferation, causing a partial obstruction of the vasculature in the regenerated lung. ASCs may therefore provide a promising cell source for vascular regeneration in bioengineered lungs, though additional work is needed to optimize the growth factor or hormone milieu for organ culture

Broader Geographic Sharing of Pediatric Donor Lungs Improves Pediatric Access to Transplant

US pediatric transplant candidates have limited access to lung transplant due to the small number of donors within current geographic boundaries, leading to assertions that the current lung allocation system does not adequately serve pediatric patients. We hypothesized that broader geographic sharing of pediatric (adolescent, 12â 17 years; child, <12 years) donor lungs would increase pediatric candidate access to transplant. We used the thoracic simulated allocation model to simulate broader geographic sharing. Simulation 1 used current allocation rules. Simulation 2 offered adolescent donor lungs across a wider geographic area to adolescents. Simulation 3 offered child donor lungs across a wider geographic area to adolescents. Simulation 4 combined simulations 2 and 3. Simulation 5 prioritized adolescent donor lungs to children across a wider geographic area. Simulation 4 resulted in 461 adolescent transplants per 100 patientâ years on the waiting list (range 417â 542), compared with 206 (range 180â 228) under current rules. Simulation 5 resulted in 388 adolescent transplants per 100 patientâ years on the waiting list (range 348â 418) and likely increased transplant rates for children. Adult transplant rates, waitlist mortality, and 1â year posttransplant mortality were not adversely affected. Broader geographic sharing of pediatric donor lungs may increase pediatric candidate access to lung transplant.This study addresses the problem of US pediatric transplant candidatesâ limited access to lung transplants and shows that broader geographic sharing of pediatric donor lungs can increase pediatric transplant rates without adversely impacting adult patients.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134263/1/ajt13507_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134263/2/ajt13507.pd

Variables of importance in the Scientific Registry of Transplant Recipients database predictive of heart transplant waitlist mortality

The prelisting variables essential for creating an accurate heart transplant allocation score based on survival are unknown. To identify these we studied mortality of adults on the active heart transplant waiting list in the Scientific Registry of Transplant Recipients database from January 1, 2004 to August 31, 2015. There were 33 069 candidates awaiting heart transplantation: 7681 UNOS Status 1A, 13 027 Status 1B, and 12 361 Status 2. During a median waitlist follow‐up of 4.3 months, 5514 candidates died. Variables of importance for waitlist mortality were identified by machine learning using Random Survival Forests. Strong correlates predicting survival were estimated glomerular filtration rate (eGFR), serum albumin, extracorporeal membrane oxygenation, ventricular assist device, mechanical ventilation, peak oxygen capacity, hemodynamics, inotrope support, and type of heart disease with less predictive variables including antiarrhythmic agents, history of stroke, vascular disease, prior malignancy, and prior tobacco use. Complex interactions were identified such as an additive risk in mortality based on renal function and serum albumin, and sex‐differences in mortality when eGFR >40 mL/min/1.73 m. Most predictive variables for waitlist mortality are in the current tiered allocation system except for eGFR and serum albumin which have an additive risk and complex interactions. The most predictive variables for waitlist mortality in adults on the active heart transplant waitlist in the Scientific Registry of Transplant Recipients database from January 1, 2004–August 31, 2015, are in the current tiered allocation system, except for eGFR and serum albumin, which have an additive risk and complex interactions

Heart Transplantation

This study aims to understand the complex factors affecting heart transplant survival and to determine the importance of possible sex-specific risk factors. Heart transplant allocation is primarily focused on preventing waitlist mortality. To prevent organ wastage, future allocation must balance risk of waitlist mortality with post-transplantation mortality. However, more information regarding risk factors after heart transplantation is needed. We included all adults (30,606) in the Scientific Registry of Transplant Recipients database who underwent isolated heart transplantation from January 1, 2004, to July 1, 2018. Mortality (8,278 deaths) was verified with the complete Social Security Death Index with a median follow-up of 3.9 years. Temporal decomposition was used to identify phases of survival and phase-specific risk factors. The random survival forests method was used to determine importance of mortality risk factors and their interactions. We identified 3 phases of mortality risk: early post-transplantation, constant, and late. Sex was not a significant risk factor. There were several interactions predicting early mortality such as pretransplantation mechanical ventilation with presence of end-organ function (bilirubin, renal function) and interactions predicting later mortality such as diabetes and older age (donor and recipient). More complex interactions predicting early-, mid-, and late-mortality existed and were identified with machine learning (i.e., elevated bilirubin, mechanical ventilation, and dialysis). Post–heart transplant mortality risk is complex and dynamic, changing with time and events. Sex is not an important mortality risk factor. To prevent organ wastage, end-organ dysfunction should be resolved before transplantation as much as possible. [Display omitted