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Single cell RNA sequencing for longitudinal human peripheral blood from HR+ breast cancer patients treated with immunotherapy

GSE300475 Homo sapiens (human) Single-cell RNA-seq 32 samples Submitted 2025/07/09 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 32 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Topic
Breast cancerThis series is part of our curated briefing on it.
Samples
32 samples: 25 distinct titles, 2 of them repeatedGroups 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
Dynamic single-cell systemic immune responses in immunotherapy-treated early-stage HR+ breast cancer patientsNPJ breast cancer · 2025
Summary (written by the submitters)
The limited benefit of immune checkpoint inhibitor in breast cancer indicates the pressing need to identify biomarkers of response to minimize risk and maximize benefit. In this study, we performed single cell RNA sequencing and T cell receptor sequencing on peripheral blood mononuclear cells to monitor the peripheral immune dynamics of an exploratory cohort of hormone receptor positive breast cancer patients treated with neoadjuvant nab-paclitaxel+pembrolizumab with the ultimate goal of identifying potential peripheral blood predictive biomarkers.
Published in
Dynamic single-cell systemic immune responses in immunotherapy-treated early-stage HR+ breast cancer patients
Sun X, Axelrod ML, Waks AG et al. · NPJ breast cancer 2025 · PMID 40610460 · doi:10.1038/s41523-025-00776-1
This dataset
Open GSE300475 in finder → Find more human datasets → Breast cancer landscape →
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 GSE300475_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 PRJNA1281033 and SRA study SRP594088. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40610460) ↗
Study design
25 distinct titles, 2 of them repeated
scRNAseq PT ×7 scRNAseq Week ×2

How we read this: Read from 32 sample titles: 25 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
More Breast cancer datasets

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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.