학술논문

Development of a scalable method to isolate subsets of stem cell-derived pancreatic islet cells
Document Type
article
Source
Stem Cell Reports. 17(4)
Subject
Biochemistry and Cell Biology
Biological Sciences
Stem Cell Research - Nonembryonic - Non-Human
Diabetes
Regenerative Medicine
Biotechnology
Transplantation
Stem Cell Research - Nonembryonic - Human
Stem Cell Research
Stem Cell Research - Induced Pluripotent Stem Cell
Stem Cell Research - Embryonic - Human
Stem Cell Research - Induced Pluripotent Stem Cell - Human
Autoimmune Disease
5.2 Cellular and gene therapies
Development of treatments and therapeutic interventions
Metabolic and endocrine
Cell Differentiation
Glucose
Humans
Insulin
Insulin Secretion
Insulin-Secreting Cells
Islets of Langerhans
Pluripotent Stem Cells
cell therapy
diabetes
directed differentiation
pancreatic beta cells
regenerative medicine
Clinical Sciences
Biochemistry and cell biology
Language
Abstract
Cell replacement therapy using β cells derived from stem cells is a promising alternative to conventional diabetes treatment options. Although current differentiation methods produce glucose-responsive β cells, they can also yield populations of undesired endocrine progenitors and other proliferating cell types that might interfere with long-term islet function and safety of transplanted cells. Here, we describe the generation of an array of monoclonal antibodies against cell surface markers that selectively label stem cell-derived islet cells. A high-throughput screen identified promising candidates, including three clones that mark a high proportion of endocrine cells in differentiated cultures. A scalable magnetic sorting method was developed to enrich for human pluripotent stem cell (hPSC)-derived islet cells using these three antibodies, leading to the formation of islet-like clusters with improved glucose-stimulated insulin secretion and reduced growth upon transplantation. This strategy should facilitate large-scale production of functional islet clusters from stem cells for disease modeling and cell replacement therapy.