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scRNA-seq of induced pluripotent stem cell derived decidual natural killer cells

GSE302146 Homo sapiens Expression profiling by high throughput sequencing 4 samples Submitted 2026/01/09 Platform GPL24676
Summary
Decidual natural killer (dNK) cells are the most abundant immune cells at the maternal-placental interface in early gestation. The exploration of dNK cell heterogeneity and function is currently an active area of research, particularly as these differ across gestation and different regions of the placenta. We applied proteomic and transcriptomic single cell definitions of dNK cells and subtypes to characterize these cells at the chorioamniotic membranes (CAM) and basal plate (BP, maternal surface) regions of the placenta at term. We found that there is reduced abundance of low-effector-function dNK1 and increased abundance of high-effector-function dNK3 in term decidual compartments. At term, in comparison to BP-dNK, CAM-dNK had greater abundance of moderate-effector-function dNK2, decreased abundance of dNK3, and lower expression of inhibitory receptor CD9. At the same time, using our knowledge of dNK heterogeneity, we developed a protocol to differentiate induced pluripotent stem cells (iPSC) into dNK cells. In this manuscript, we detail a protocol to differentiate iPSC into dNK-like cells as characterized by scRNA-seq analyses and CD45+CD56brightCD16- protein expression. We further developed the protocol to enrich for dNK2 – the most abundant dNK cell type in first trimester and term CAM – while inducing expression of dNK marker proteins CD9 and CD103 with the addition of TGFß. This study reveals the shift in dNK subtypes underlying functional changes in dNK cells between first trimester and term and detail a protocol with which we can methodically differentiate iPSC into dNK cells and specifically induce the dNK2 subtype for mechanistic perturbation.
Published in
Derivation of functional early gestation decidual natural killer cell subtypes from induced pluripotent stem cells
Cheung VC, DaCosta C, Jaimez J et al. · bioRxiv : the preprint server for biology 2025 · PMID 41279445 · doi:10.1101/2025.11.03.685424
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Also filed as BioProject PRJNA1289067 and SRA study SRP599587. Searching any of these in the dataset finder brings you back here.

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