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Integrated bulk and single-cell transcriptome analysis reveals the impact of cyclophosphamide on tumor microenvironment in triple-negative breast cancer models

GSE317281 Mus musculus (mouse) Single-cell RNA-seq 14 samples Submitted 2026/07/09 Platform GPL34290

At a glance

Single-cell RNA-seq · mouse · 14 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: 14 samples: 5 × C100 vs 5 × C140 vs 4 × NCGroups 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.

Summary (written by the submitters)

Triple-negative breast cancer (TNBC) remains a formidable clinical challenge. Although preclinical investigations utilizing TNBC mouse models have demonstrated that intermittent cyclophosphamide (CTX) treatment yields superior anti-tumor effects, partly through immune stimulation, mechanisms by which CTX modulates the tumor microenvironment (TME) are not yet fully understood.

Read the full summary ↓

In this study, we assessed the impact of optimal (140 mg/kg every 6 days, C140) and suboptimal (100 mg/kg every 6 days, C100) CTX treatment regimens on 4T1 tumors, a widely utilized orthotopic TNBC mouse model. While the C100 regimen was better tolerated than the C140 regimen, it was less effective in inhibiting tumor growth. Through integrated bulk and single-cell RNA sequencing of tumor tissues, we discovered that CTX treatment not only inhibited cancer cell proliferation and epithelial-mesenchymal transition but also remodeled the TME by recruiting and reprogramming various immune cells, thereby enhancing the anticancer immune response in a dose-dependent manner. Although the C140 regimen demonstrated significant tumor suppression, it also induced notable extracellular matrix remodeling and led to the accumulation of cancer-associated fibroblasts within the tumor microenvironment. Furthermore, the C140 regimen caused considerable exhaustion of CD8+ T cells and was linked to increased expression of various immune checkpoint molecules, including PD-L1/PD-L2, CD39, and CD200. These effects may compromise therapeutic efficacy and potentially contribute to the development of drug resistance. Overall, our findings elucidate both cancer-cell-intrinsic and tumor microenvironment-dependent mechanisms of CTX action at both local and systemic levels, highlighting potential targets for optimizing chemoimmunotherapy in TNBC.

This dataset

Open GSE317281 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 GSE317281_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 PRJNA1406664 and SRA study SRP665588. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

5 × C100 vs 5 × C140 vs 4 × NC

Supports a between-group comparison across 14 samples.

How we read this: 3 replicated groups read from 14 sample titles; they account for 14 of them. 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

GSM9468547 NC_1 NC
GSM9468548 NC_2 NC
GSM9468549 NC_3 NC
GSM9468550 NC_4 NC
GSM9468551 C100_1 C100
GSM9468552 C100_2 C100
GSM9468553 C100_3 C100
GSM9468554 C100_4 C100
GSM9468555 C100_5 C100
GSM9468556 C140_1 C140
GSM9468557 C140_2 C140
GSM9468558 C140_3 C140
GSM9468559 C140_4 C140
GSM9468560 C140_5 C140

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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.