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Histone H4 lysine 20 tri-methylation safeguards breast cancer lineage fidelity and unfolded protein response

GSE289193 Mus musculus (mouse) DNA methylation 160 samples Submitted 2026/04/26 Platform GPL24676Platform GPL24247
At a glance

DNA methylation · mouse · 160 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Mus musculus (mouse)
Topic
Breast cancerThis series is part of our curated briefing on it.
Samples
160 samples: 74 conditions, mostly in duplicateGroups 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.
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
This dataset
Open GSE289193 in finder → Find more 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 GSE289193_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: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA1221875 and SRA study SRP562928. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
74 conditions, mostly in duplicate
SUM149_Xenograft_Vehicle_Tumo ×4 SUM149_Xenograft_A196_Tumo ×4 SUM149_Xenograft_17AAG_Tumo ×3 SUM149_Xenograft_Combination_Tumo ×3 4T1_DMSO_Tumo ×3 4T1_A196_Tumo ×3 EMT6_DMSO_Tumo ×3 EMT6_A196_Tumo ×3 +68 more

Supports a between-group comparison across 158 samples.

How we read this: 74 replicated groups read from 160 sample titles; they account for 158 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

+ 120 more — browse all 160 samples with per-sample file links →

More Breast cancer datasets

Search all 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.