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Autologous cell therapy with CD133+ bone marrow-derived stem cells for Asherman Syndrome: a phase 1/2 trial [biopsies]

GSE311899 Homo sapiens (human) Single-cell RNA-seq 35 samples Submitted 2025/12/10 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 35 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
35 samples: 35 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
Autologous cell therapy with CD133+ bone marrow-derived stem cells for Asherman Syndrome: a phase 1/2 trialNature communications · 2026
Summary (written by the submitters)
Asherman Syndrome (AS) is an acquired pathological condition affecting women’s reproductive health, triggered by the substitution of a bona fide endometrium with intrauterine adhesions that cause the uterine walls to adhere to each other. Clinically, AS results in menstrual abnormalities (amenorrhea or oligomenorrhea), pelvic pain, infertility, recurrent miscarriage and abnormal placentation.
Read the full summary ↓
Autologous CD133+ bone marrow-derived stem cell (BMDSC) therapy has been designated as an Orphan Drug by the EMA and FDA for the treatment of AS. This phase 1/2, non-randomized, open-label, single-arm trial (EudraCT: 2016-003975-23) assessed the safety and efficacy of this novel therapy in 20 infertile women with moderate to severe AS, unresponsive to prior hysteroscopic treatments. Single-cell RNA sequencing of endometrium and organoids revealed partial reversion of AS-related changes, and mitochondrial variant tracking offered insights of CD133+ BMDSCs engraftment. These findings suggest that autologous CD133+ BMDSC therapy is a safe and effective treatment for AS.
Published in
Autologous cell therapy with CD133+ bone marrow-derived stem cells for Asherman Syndrome: a phase 1/2 trial
Santamaria X, Pardo-Figuerez M, González-Fernández J et al. · Nature communications 2026 · PMID 41484096 · doi:10.1038/s41467-025-67850-x
This dataset
Open GSE311899 in finder → Find more human RNA-seq datasets →
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.

Series matrix ↓
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 GSE311899_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA1371900. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41484096) ↗
Study design
35 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 35 sample titles: 35 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
Datasets on a similar topic

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.