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Multimodal Transcriptomic Profiling of T Cell Responses to Triple-Negative Breast Cancer-Derived Exosomes

GSE302399 Homo sapiens (human) Non-coding RNA profiling 73 samples Submitted 2026/04/12 Platform GPL34284
At a glance

Non-coding RNA profiling · human · 73 samples

What it is
Non-coding RNA profilingLevels of RNAs that do not code for proteins, such as miRNA or lncRNA.
Organism
Homo sapiens (human)
Topic
Breast cancerThis series is part of our curated briefing on it.
Samples
73 samples: 7 conditions, mostly with about 10 replicates eachGroups 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 T cell plasticity and antigen specificity remains insufficiently characterized. In this study, we performed an integrative single-cell multiomic analysis of primary human T cells following exposure to exosomes isolated from 17 genomically distinct TNBC cell lines.
Read the full summary ↓
By combining single-cell transcriptomics, T cell receptor (TCR) V(D)J sequencing, non-coding RNA profiling, and both bulk and single-cell cytokine analyses, we identified conserved and subtype-specific immunoregulatory programs elicited by TNBC-derived exosomes.
This dataset
Open GSE302399 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 GSE302399_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 ↗

Also filed as BioProject PRJNA1290339 and SRA study SRP600277. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 conditions, mostly with about 10 replicates each
Breast Cancer Patient ×28 TCRαβ samples from TNBC exosome-treated T cel… ×10 TCRγδ samples from TNBC exosome-treated T cel… ×10 exosomes extracted from HCC ×8 Healthy Control ×7 exosomes extracted from MDA-MB ×5 exosomes extracted from BT ×2 exosomes extracted from DU ×1 +2 more

Supports a case/control comparison: 28 samples read as cases, 7 as controls.

How we read this: 7 replicated groups read from 73 sample titles; they account for 70 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

+ 33 more — browse all 73 samples with per-sample file links →

More Breast cancer datasets

Search all human 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.