Transplantation of a bioengineered tissue patch promotes uterine repair in the sheep

Innovative bioengineering strategies utilizing extracellular matrix (ECM) based scaffolds derived from decellularized tissue offer new prospects for restoring damaged uterine tissue. Despite successful fertility restoration in small animal models, the translation to larger and more clinically relevant models have not yet been assessed. Thus, our study investigated the feasibility to use a 6 cm² graft constructed from decellularized sheep uterine tissue, mimicking a future application to repair a uterine defect in women. Some grafts were also recellularized with fetal sheep bone marrow-derived mesenchymal stem cells (SF-MSCs). The animals were followed for six weeks post-surgery during which blood samples were collected to assess the systemic immune cell activation by fluorescence-activated cell sorting (FACS) analysis. Tissue regeneration was assessed by histology, immunohistochemistry, and gene expression analyses. There was a large intra-group variance which prompted us to implement a novel scoring system to comprehensively evaluate the regenerative outcomes. Based on the regenerative score each graft received, we focused our analysis to map potential differences that may have played a role in the success or failure of tissue repair following the transplantation therapy. Notably, three out of 15 grafts exhibited major regeneration that resembled native uterine tissue, and an additional three grafts showed substantial regenerative outcomes. For the better regenerated grafts, it was observed that the systemic T-cell subgroups were significantly different compared with the failing grafts. Hence, our data suggest that the T-cell response play an important role for determining the uterus tissue regeneration outcomes. The remarkable regeneration seen in the best-performing grafts after just six weeks following transplantation provides compelling evidence that decellularized tissue for uterine bioengineering holds great promise for clinically relevant applications.