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Changing dynamics of the fibroblast differentiation hierarchy during mammary gland morphogenesis and tumorigenesis [scRNA-Seq I]

GSE277228 Mus musculus (mouse) Single-cell RNA-seq 13 samples Submitted 2025/03/12 Platform GPL30172
At a glance

Single-cell RNA-seq · mouse · 13 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
13 samples: 13 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
Fibroblast hierarchy dynamics during mammary gland morphogenesis and tumorigenesisThe EMBO journal · 2025
Summary (written by the submitters)
Fibroblasts form a major component of the stroma in normal mammary tissue and breast tumors. Here we have applied single-cell transcriptome profiling to characterize fibroblasts in the mouse mammary gland across five different developmental stages and during mammary oncogenesis. In the normal gland, diverse stromal populations were resolved, including lobular-like fibroblasts, committed preadipocytes and adipogenesis-regulatory, as well as cycling fibroblasts in puberty and pregnancy.
Read the full summary ↓
These specialized cell types appear to emerge from CD34high mesenchymal progenitor cells, accompanied by elevated Hedgehog pathway activity. During late tumorigenesis, diverse cancer-associated fibroblasts were identified in different models of breast cancer, including a population of CD34– myCAFs that were transcriptionally and phenotypically similar to senescent CAFs. Moreover, Wnt9a was demonstrated to be a regulator of senescence in CD34– myCAFs. These findings reflect a diverse and hierarchically organized stromal compartment in the normal mammary gland that provides a framework to better understand fibroblasts in normal and cancerous states.
Published in
Fibroblast hierarchy dynamics during mammary gland morphogenesis and tumorigenesis
Pascual R, Cheng J, De Smet AH et al. · The EMBO journal 2025 · PMID 40216939 · doi:10.1038/s44318-025-00422-3
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 GSE277228_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 PRJNA1161402 and SRA study SRP532811. Searching any of these in the dataset finder brings you back here.

Study design
13 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 13 sample titles: 13 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
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