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Inhibition of NFAT after human uterus transplant promotes loss of tissue-resident NK cells and attendant pregnancy complications [CITE-seq]

GSE292829 Homo sapiens (human) Single-cell RNA-seq 58 samples Submitted 2026/03/10 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 58 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
58 samples: 58 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Inhibition of NFAT after human uterus transplant promotes loss of tissue-resident NK cells and attendant pregnancy complicationsScience translational medicine · 2026
Summary (written by the submitters)
Uterine natural killer (uNK) cells are a tissue-resident lymphocyte population critical for pregnancy success. Although mouse models have demonstrated that uNK cell deficiency results in abnormal placentation and poor pregnancy outcomes, the generalizability of this knowledge to humans remains unclear. Here, we compared tissue samples collected from a cohort of human recipients of uterus transplant (UTx) at high risk for pregnancy complications with healthy controls using flow cytometry, immunofluorescence microscopy, and single-cell RNA sequencing (scRNA-seq).
Read the full summary ↓
Subsets of tissue-resident uNK cells were reduced in endometrial and decidual samples from recipients of UTx compared with healthy control samples. Loss of tissue-resident uNK cells was associated with histopathologic evidence of maternal vascular malperfusion in placentas from recipients of UTx and related pregnancy complications including preeclampsia. scRNA-seq of UTx endometrial biopsies and deciduae further revealed that the NK cell reduction in recipients of UTx correlated with impaired transcriptional programming of NK tissue residency arising from the inhibition of signaling by nuclear factor of activated T cells (NFAT). In vitro culture of uNK cells from healthy controls with the NFAT inhibitor tacrolimus resulted in down-regulation of adhesion molecules. Together, these experiments suggested that NFAT-dependent genes modulate multiple molecular tissue residency programs in uNK cells, including early residency programs involving activator protein-1 (AP-1) family transcription factors and later residency programs characterized by up-regulation of surface integrins by transforming growth factor–β (TGF-β). Collectively, these data identify a previously undescribed role for NFAT in uNK tissue residency and provide mechanistic insights into the biologic basis of pregnancy complications due to alteration of tissue-resident NK cell subsets in humans.
Published in
Inhibition of NFAT after human uterus transplant promotes loss of tissue-resident NK cells and attendant pregnancy complications
Asiimwe R, Knott B, Greene ME et al. · Science translational medicine 2026 · PMID 41811989 · doi:10.1126/scitranslmed.adp2196
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE292829_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1241324 and SRA study SRP572755. Searching any of these in the dataset finder brings you back here.

Study design
58 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 58 sample titles: 58 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 18 more — browse all 58 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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