GEO series

SOX9 and SEMA7A Regulate Epithelial Cell Plasticity in the Postpartum Mammary Gland with Implications for Postpartum Breast Cancer

GSE313223 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2026/05/19 Platform GPL34328

At a glance

Single-cell RNA-seq · mouse · 2 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: Mus musculus (mouse)
Samples: 2 samples
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.

Summary (written by the submitters)

The mammary gland is a dynamic tissue that undergoes most of its development postnatally to accommodate milk production during lactation and then, after weaning, undergoes postpartum involution, a coordinated process of epithelial cell death, remodeling, and inflammation that returns the tissue to a near pre-pregnant state. Yet, the mechanisms employed by some mammary cells to survive for subsequent lactation are not fully understood.

Read the full summary ↓

Multiple studies suggest that involution is a driver of postpartum breast cancers (PPBCs), or those diagnosed within ten years of childbirth, that exhibit disproportionately high metastatic risk. Prior work implicates SEMA7A in mammary epithelial cell survival during involution and in metastasis of PPBC. We utilized single-cell RNA sequencing of mouse mammary glands during lactation and involution to delineate Sema7a-expressing populations during tissue development and remodeling. We found that Sema7a is expressed in a small subset of epithelial cells but is more predominantly expressed in endothelial and pericyte populations, whereas the developmentally regulated transcription factor Sox9 is highly expressed in epithelial subsets. We further show that SOX9 and SEMA7A expression changes across lactation and involution in mouse and in a unique set of human breast tissues collected from healthy donors during lactation and post-weaning. Using in vitro models of lactogenic differentiation and involution, we demonstrate a relationship between SOX9 and SEMA7A whereby knockdown of Sox9 in mammary epithelial cells increases SEMA7A expression and induces epithelial/mesenchymal hybrid phenotypes, identifying a potential regulatory axis in which SOX9 restrains SEMA7A-driven epithelial plasticity. Since SEMA7A is a driver of PPBC recurrence, we analyzed breast cancer datasets for SEMA7A and SOX9 to reveal that co-expression of SOX9 and SEMA7A correlates with metastatic risk in TNBC. Together, these findings define a previously unrecognized SOX9–SEMA7A relationship in the postpartum mammary gland and illustrate how studies of normal development can identify cellular mechanisms that may be susceptible to transformation and contribute to PPBC progression. This project aims to characterize transcriptomic changes in mouse mammary gland tissue across the reproductive stages of lactation and involution in wild-type mice. The goal is to understand cell-type-specific gene expression changes, with a focus on immune and epithelial compartments, and explore the potential role of SOX9 and SEMA7A in these processes.

This dataset

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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 GSE313223_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 PRJNA1378940 and SRA study SRP654298. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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+ 2 more — browse all 2 samples with per-sample file links →

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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.