GEO series

Epithelial-mesenchymal transition is associated with altered immune composition and cytotoxic function in triple-negative breast cancer

GSE303505 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2026/02/13 Platform GPL30172

At a glance

Single-cell RNA-seq · mouse · 12 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: 12 samples: 12 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: Epithelial-Mesenchymal Transition is Associated with Altered Immune Composition and Cytotoxic Function in Triple-Negative Breast CancerbioRxiv : the preprint server for biology · 2025

Summary (written by the submitters)

Epithelial–mesenchymal transition (EMT) is a dynamic process that contributes to breast cancer progression, metastasis, and therapy resistance. EMT also influences the tumor immune microenvironment, shaping immune cell infiltration and function. Although the immunological features of fully epithelial or fully mesenchymal tumor states have been characterized, the immune landscape associated with intermediate or partial EMT states remains poorly understood.

Read the full summary ↓

To address this gap, we established five single-cell–derived clonal populations from the triple-negative 4T1 mouse mammary tumor cell line, representing a spectrum of EMT phenotypes, and analyzed tumors derived from these clones using single-cell RNA sequencing. Here, we show that tumors derived from these clones retained their relative EMT states in vivo and that EMT progression is associated with a graded reduction in tumor immunogenicity, accompanied by alterations in immune cell composition and function. Specifically, along the EMT spectrum, tumor cells exhibited progressive downregulation of MHC class I and II gene expression, along with decreased infiltration of cytotoxic CD8+ T cells and reduced expression of key effector and trafficking genes (Gzmb, Ccr5, Cxcr6). B cell composition also shifted, with decreased frequencies of IgG1-producing plasma cells and an enrichment of regulatory-like B cells. Natural killer (NK) cells similarly demonstrated progressive functional suppression, marked by reduced expression of cytotoxic molecules and downregulation of key effector pathways. Together, these findings reveal that EMT is associated with immune cell recruitment and function in a graded manner, providing a rationale for integrating EMT phenotyping into therapeutic strategies to overcome immune resistance in breast cancer.

Published in

Epithelial-Mesenchymal Transition is Associated with Altered Immune Composition and Cytotoxic Function in Triple-Negative Breast Cancer

Lu H, Bagheri M, Kolling FW et al. · bioRxiv : the preprint server for biology 2025 · PMID 41280107 · doi:10.1101/2025.10.22.683714

This dataset

Open GSE303505 in finder → Find more mouse 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 GSE303505_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 PRJNA1295536 and SRA study SRP603060. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41280107) ↗

Study design

12 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 12 sample titles: 12 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

GSM9128192 Clone E Total
GSM9128193 Clone E CD45
GSM9128194 Clone EM1 Total
GSM9128195 Clone EM1 CD45
GSM9128196 Clone EM2 Total
GSM9128197 Clone EM2 CD45
GSM9128198 Clone EM3 Total
GSM9128199 Clone EM3 CD45
GSM9128200 Clone M Total
GSM9128201 Clone M CD45
GSM9128202 Parental 4T1 Total
GSM9128203 Parental 4T1 CD45

Datasets on a similar topic

GSE272476 Neutrophils exposed to a cholesterol metabolite secrete extracellular vesicles that promote epithelial-mesenchymal transition and stemness in breast cancer cells [RNA-seq] 30 samples shares epithelial-mesenchymal, transition, breast
GSE292013 Impact of PD-L1 overexpression on immune checkpoint inhibitor efficacy in triple-negative breast cancer using a 4T1 murine model. 12 samples shares triple-negative, breast
GSE239716 SOX9 suppresses colon cancer via inhibiting epithelial-mesenchymal transition and SOX2 induction 39 samples shares epithelial-mesenchymal, transition
GSE273940 Low Molecular Weight Cyclin E Confers a Vulnerability to PKMYT1 Inhibition in Triple-Negative Breast Cancer 33 samples shares triple-negative, breast
GSE311488 Chemotherapeutic Induction of Single-Stranded DNA Accumulation Sensitizes Triple-Negative Breast Cancer to Immunotherapy [scRNA-seq] 32 samples shares triple-negative, breast
GSE294999 Obesity-driven inflammation enables triple-negative breast cancer progression through immunosuppression [scRNA-Seq] 16 samples shares triple-negative, breast
GSE276098 Immunosuppressive microenvironment restrains chemotherapy efficacy in liver metastases of triple-negative breast cancer 16 samples shares triple-negative, breast
GSE317281 Integrated bulk and single-cell transcriptome analysis reveals the impact of cyclophosphamide on tumor microenvironment in triple-negative breast cancer models 14 samples shares triple-negative, breast

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.