Abstract

Composite tissue allotransplantation (CTA) has been recently introduced as a potential treatment for tissue loss secondary to burns, injuries, or resections. However, the optimal strategies to prevent CTA rejection remain undefined. Presently, no CTA model exists to evaluate human-specific immunosuppressants or the relative immunogenicity of all CTA tissues. We established a NHP CTA model utilizing a sensate osteomyocutaneous radial forearm flap that avoids functional impairment even in the case of graft loss. The model was evaluated in19 monkeys that underwent auto- or allotransplantation, with or without subtherapeutic immunosuppression to temporarily characterize rejection. Autografts showed no evidence of rejection. Nonimmunosuppressed allografts were rapidly rejected showing a perivenular T-cell infiltrate. This was associated with subsequent alloantibody formation and led to graft thrombosis without prominent dermal infiltration. Subtherapeutically immunosuppressed animals also developed alloantibody and rejected in a delayed fashion exhibiting a marked dermal lymphocytic infiltrate similar in magnitude and distribution to previously reported human cases. Our NHP model for CTA is well tolerated by NHPs, results in allosensitization, is responsive to immunosuppression, allows for the evaluation of CTA histology and can be used for the systematic preclinical evaluation of therapeutic maneuvers to improve allograft survival.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.