パイロットスタディ:非ヒト霊長類におけるCXCL12を組み込んだアルギン酸塩でマイクロカプセル化されたヒト幹細胞由来膵島様の機能的生存率(全身免疫抑制なし)
Kento Kawai1, Fatma Dogan1, David A Alagpulinsa1
1Vaccine and Immunotherapy Center, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA.
Abstract:
Glucose-responsive insulin-secreting stem cell-derived islet-like cells (SC-islets) are a promising source for beta cell replacement to treat type 1 diabetes (T1D). However, immune rejection and limited function of SC-islets post-transplantation are key barriers to this treatment. We previously reported glycemic control and prolonged function of SC-islets microencapsulated in alginate that incorporates the pro-survival and immunomodulatory chemokine CXCL12 in immunocompetent diabetic mice without systemic immune suppression. Here, in a pilot study, we translated this SC-islet microencapsulation approach in nonhuman primates (NHPs) via transplantation of a therapeutic dose of SC-islets microencapsulated in alginate incorporating CXCL12 into the greater omental sac of a healthy and a diabetic NHP. We demonstrate that treatment did not cause metabolic dysfunction over a 6-month period in the NHPs. The healthy NHP maintained stable C-peptide and blood glucose levels, while the diabetic NHP had detectable serum C-peptide through 13 weeks post-transplant and a significant reduction in exogenous insulin requirements compared with a corresponding diabetic NHP recipient in the absence of immunosuppressive treatment. Serum biochemistry as well as hematological and immunological parameters of the NHPs remained normal throughout the post-transplantation period. At termination, the retrieved microencapsulated SC-islets were predominantly free floating without pericapsular fibrotic overgrowth and were glucose-responsive, expressing all major endocrine cell markers, albeit a significant decrease in viability compared with pre-transplant levels. Overall, these findings demonstrate feasibility, safety, and function of microencapsulated SC-islets in two NHPs in this small pilot study and our dataset supports further investigation of this approach toward clinical translation.


