Back

High-purity stem cell-derived β-cells recapitulate key transcriptional and functional features of human islets

Fiancette, R.; Huang, J.; Stephens, C.; Hibbert, J. E.; Hewitt, G.; Carlein, C.; Shilleh, A. H.; Clinton, C.; De Abreu Queiros Osorio, L.; Tourigny, D.; Millership, S.; Salem, V.; Hodson, D. J.; Akerman, I.

2026-05-26 cell biology
10.64898/2026.05.22.726825 bioRxiv
Show abstract

Human pluripotent stem cell-derived islets (SC-islets) offer an excellent medium for human pancreatic disease modelling and mechanistic studies into diabetes. While substantial progress has been made in differentiation protocols, their implementation in different laboratories result in variable {beta}-cell proportions with contaminant non-endocrine and proliferative cell types. To date, no facility-level implementation exists for producing SC-islets that can be shipped and benchmarked across multiple sites. Here, we describe the scalable optimisation, standardization, and facility-level implementation of an established human stem cell differentiation strategy that consistently results in a high proportion of {beta}-cells, with up to 75% of cells co-expressing C-peptide and the pancreatic endocrine marker, ISL1. Functionally, SC-islets exhibit glucose-responsive calcium influx and insulin secretion, recapitulating key physiological {beta}-cell functions. Single-cell transcriptomic profiling reveals a simplified endocrine landscape dominated by {beta}-cells, with a striking transcriptional similarity to human primary {beta}-cells (Pearsons r2[~]0.9). We observe smaller fractions of - and enterochromaffin-like cells with very low levels of poly-hormonal or proliferating cell types (<3%). Taken together, we provide a well-defined, reproducible and accessible in vitro SC-islet platform benchmarked for functionality at multiple recipient sites.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Stem Cell Reports
130 papers in training set
Top 0.1%
19.5%
2
Diabetologia
44 papers in training set
Top 0.1%
10.2%
3
Nature Communications
5641 papers in training set
Top 20%
8.3%
4
Scientific Reports
3612 papers in training set
Top 14%
5.8%
5
Cell Reports Methods
165 papers in training set
Top 0.8%
2.9%
6
Stem Cells
31 papers in training set
Top 0.2%
2.8%
7
PLOS ONE
5266 papers in training set
Top 41%
2.6%
50% of probability mass above
8
Communications Biology
993 papers in training set
Top 10%
2.2%
9
Cell Stem Cell
62 papers in training set
Top 0.9%
1.8%
10
BMC Methods
15 papers in training set
Top 0.1%
1.8%
11
Stem Cell Research & Therapy
30 papers in training set
Top 0.3%
1.8%
12
iScience
1154 papers in training set
Top 22%
1.4%
13
Cell Reports
1498 papers in training set
Top 22%
1.2%
14
Wellcome Open Research
67 papers in training set
Top 0.9%
1.2%
15
Scientific Data
209 papers in training set
Top 2%
1.1%
16
Cell Communication and Signaling
51 papers in training set
Top 1.0%
1.1%
17
Biofabrication
36 papers in training set
Top 0.5%
1.0%
18
Advanced Science
286 papers in training set
Top 8%
1.0%
19
Science Advances
1243 papers in training set
Top 28%
1.0%
20
Stem Cell Research
16 papers in training set
Top 0.2%
0.9%
21
Cells
249 papers in training set
Top 6%
0.9%
22
Cell Discovery
57 papers in training set
Top 1%
0.9%
23
Communications Medicine
113 papers in training set
Top 4%
0.9%
24
Molecular Metabolism
112 papers in training set
Top 2%
0.9%
25
eLife
5828 papers in training set
Top 67%
0.6%
26
EMBO Molecular Medicine
95 papers in training set
Top 3%
0.6%
27
Advanced Healthcare Materials
85 papers in training set
Top 1%
0.6%
28
Diabetes
56 papers in training set
Top 0.9%
0.6%
29
npj Regenerative Medicine
24 papers in training set
Top 0.7%
0.6%
30
JCI Insight
277 papers in training set
Top 8%
0.6%