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Single-Cell RNA-Seq Reveals Immunosuppressive Effects of Triple-Negative Breast Cancer–Derived Exosomes on NK Cell Responses

GSE303346 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2026/07/25 Platform GPL34284
At a glance

Single-cell RNA-seq · human · 16 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
16 samples: 8 × Gene expression of NK cells samples treated by TNBC-exosomes and one untreated NK cells sample, Well vs 8 × ADT expression NK cells samples treated by TNBC-exosomes and one untreated NK cells sample, WellGroups 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) is a highly aggressive and immunogenic subtype that lacks effective targeted therapies. Although tumor-derived exosomes are known to influence immune responses, their direct role in shaping human NK cell plasticity remains insufficiently characterized. In this study, we performed an integrative single-cell multiomic analysis of primary human NK cells following exposure to exosomes isolated from 17 genomically distinct TNBC cell lines.
Read the full summary ↓
By combining single-cell transcriptomics, we identified conserved and subtype-specific immunoregulatory programs elicited by TNBC-derived exosomes.
This dataset
Open GSE303346 in finder → Find more human RNA-seq 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 GSE303346_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 PRJNA1294879 and SRA study SRP602850. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 × Gene expression of NK cells samples treated by TNBC-exosomes and one untreated NK cells sample, Well vs 8 × ADT expression NK cells samples treated by TNBC-exosomes and one untreated NK cells sample, Well

Supports a between-group comparison across 16 samples.

How we read this: 2 replicated groups read from 16 sample titles; they account for 16 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
More Breast cancer datasets

Search all human RNA-seq datasets in GEO →

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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.