Despite intense efforts over the past 30 years, human pancreatic β cell lines have not been available. Here, we describe a robust technology for producing a functional human β cell line using targeted oncogenesis in human fetal tissue. Human fetal pancreatic buds were transduced with a lentiviral vector that expressed SV40LT under the control of the insulin promoter. The transduced buds were then grafted into SCID mice so that they could develop into mature pancreatic tissue. Upon differentiation, the newly formed SV40LT-expressing β cells proliferated and formed insulinomas. The resulting β cells were then transduced with human telomerase reverse transcriptase (hTERT), grafted into other SCID mice, and finally expanded in vitro to generate cell lines. One of these cell lines, EndoC-βH1, expressed many β cell–specific markers without any substantial expression of markers of other pancreatic cell types. The cells secreted insulin when stimulated by glucose or other insulin secretagogues, and cell transplantation reversed chemically induced diabetes in mice. These cells represent a unique tool for large-scale drug discovery and provide a preclinical model for cell replacement therapy in diabetes. This technology could be generalized to generate other human cell lines when the cell type–specific promoter is available.
Philippe Ravassard, Yasmine Hazhouz, Séverine Pechberty, Emilie Bricout-Neveu, Mathieu Armanet, Paul Czernichow, Raphael Scharfmann
Usage data is cumulative from November 2023 through November 2024.
Usage | JCI | PMC |
---|---|---|
Text version | 1,623 | 973 |
346 | 253 | |
Figure | 424 | 47 |
Supplemental data | 60 | 32 |
Citation downloads | 77 | 0 |
Totals | 2,530 | 1,305 |
Total Views | 3,835 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.