Gene Expression at the Pluripotency Stage Predicts Pancreatic Endocrine Differentiation in iPSC Clones

Background Induced pluripotent stem cell (iPSC)-derived β cells hold great promise for cell replacement therapy in type 1 diabetes. However, the reprogramming process generates iPSC clones with variable differentiation capacity, hindering the selection of optimal cell lines. This study aimed to identify an early-stage transcriptional signature capable of predicting the β cell differentiation potential of donor-matched iPSC clones. Methods Eleven iPSC clones derived from a single donor were differentiated to the definitive endoderm (DE) stage; six were further driven toward pancreatic progenitors (PP) and insulin-producing β cells. Differentiation efficiency was evaluated by flow cytometry and qPCR at iPSC, DE, PP, and β cell stages. At the pluripotent stage, expression profiling of 770 genes related to pluripotency and trilineage specification was performed to identify predictive molecular markers. Results Transcriptomic analysis segregated the clones into two groups (Gr1 and Gr2) with significantly different differentiation outcomes. Gr2 clones exhibited superior DE efficiency (Cxcr4⁺: 90.1 ± 5.6% vs. 79.8 ± 3.6%; P = 0.027) and higher expression of PP markers (Pdx1⁺, Nkx6.1⁺, and double-positive cells; P ≤ 0.05). At the β cell stage, Gr2 clones showed increased frequencies of Pdx1⁺/Ins⁺ and Nkx6.1⁺/Ins⁺ cells (P ≤ 0.05), along with enhanced glucose-stimulated insulin secretion. A set of 73 differentially expressed genes, enriched in pathways related to naïve/primed pluripotency, endoderm commitment, and metabolism, was identified. From this, a ten-gene signature validated by qPCR strongly correlated with pancreatic marker expression at all stages. Conclusions An early gene expression signature at the pluripotent stage predicts the pancreatic endocrine differentiation potential of iPSC clones. This molecular screening approach may enable rapid preselection of high-performing clones, thereby accelerating the development of personalized stem cell–based therapies for diabetes.