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Genomic and transcriptomic profiling of whole-genome-doubled triple-negative breast cancer cell populations

GSE337023 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2026/07/05 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 24 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Breast cancerThis series is part of our curated briefing on it.
Samples
24 samples: 8 conditions, mostly in triplicateGroups 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)
To investigate whether the mechanism of whole-genome doubling (WGD) results in distinct genomic and transcriptomic phenotypes, we compared three routes to WGD against their respective parental aneuploid controls across two triple-negative breast cancer (TNBC) cell lines (HCC1806 and MDA-MB-231). WGD mechanisms included naturally occurring cell-cell fusion and two drug-induced cell-cycle error mechanisms: mitotic slippage (MS) and cytokinesis failure (CF).
Read the full summary ↓
All populations were profiled in biological triplicate by TagSeq (3' tag-based RNA-seq) for transcriptomic analysis and low-pass whole-genome sequencing (WGS) for copy-number profiling.
This dataset
Open GSE337023 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 GSE337023_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1482160 and SRA study SRP712697. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in triplicate
HCC1806 Control TagSeq ×3 HCC1806 Fusion-derived WGD TagSeq ×3 HCC1806 Mitotic slippage-induced WGD TagSeq ×3 HCC1806 Cytokinesis failure-induced WGD TagSeq ×3 MDA-MB-231 Control TagSeq ×3 MDA-MB-231 Fusion-derived WGD TagSeq ×3 MDA-MB-231 Mitotic slippage-induced WGD TagSeq ×3 MDA-MB-231 Cytokinesis failure-induced WGD Ta… ×3

Supports a case/control comparison: 12 samples read as cases, 6 as controls.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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.