GEO series

ERRα-KDM5C Restrains STING Enhancer Activity to Modulate Type I Interferon Signaling in Breast Cancer Progression

GSE300441 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2026/02/17 Platform GPL24676Platform GPL11154Platform GPL29480

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 10 samples

What it is: ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism: Homo sapiens (human)
Topic: Breast cancerThis series is part of our curated briefing on it.
Samples: 10 samples: 10 samples, each with a distinct title — no replicated groupsGroups 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: ERRα-KDM5C restrains STING enhancer activity to modulate type I interferon signaling in breast cancer progressionCell death & disease · 2026

Summary (written by the submitters)

Regulation of enhancer activity plays a pivotal role in governing gene expression and cellular behaviors. However, the precise mechanisms underlying dynamic control of active enhancers remain incompletely defined. Here, we demonstrate that the nuclear receptor estrogen-related receptor α (ERRα) forms a functional complex with the H3K4me3-specific demethylase KDM5C to co-occupy a large set of active enhancers, including the locus of STING.

Read the full summary ↓

In breast cancer cells, ERRα depletion induces STING enhancer hyperactivation, evidenced by H3K4me3 deposition, decreased H3K4me1, and increased enhancer RNA (eRNA) transcription. Accordingly, depletion of ERR leads to further activation of STING gene transcription and TBK1-IRF3 pathway, accompanied by increased type I interferon (IFN) and IFN-stimulated gene (ISG) expression, as confirmed by transcriptomic analysis. Notably, depleting ERRα markedly attenuates breast tumor cell growth in vitro and in vivo, and our in vitro evidence indicates this occurs in part through activating STING signaling. These findings establish that the ERRα-KDM5C serves as a critical checkpoint for STING enhancer activity, revealing a regulatory mechanism of STING enhancer activity in breast tumor progression.

Published in

ERRα-KDM5C restrains STING enhancer activity to modulate type I interferon signaling in breast cancer progression

Xu ZH, Chen J, He Y et al. · Cell death & disease 2026 · PMID 41708589 · doi:10.1038/s41419-026-08499-2

This dataset

Open GSE300441 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 GSE300441_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 peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1280050 and SRA study SRP593359. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41708589) ↗

Study design

10 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 10 sample titles: 10 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

GSM9060717 RNA-seq-shCTL-MCF7
GSM9060718 RNA-seq-shESRRA-MCF7
GSM9060719 RNA-seq-shKDM5C-MCF7
GSM9301112 ChIP-seq-Input-MCF7
GSM9301113 ChIP-seq-H3K4me3-shCTL-MCF7
GSM9301114 ChIP-seq-H3K4me3-shESRRA1-MCF7
GSM9301115 ChIP-seq-H3K4me3-shESRRA2-MCF7
GSM9301116 ChIP-seq-H3K4me3-shKDM5C1-MCF7
GSM9301117 ChIP-seq-H3K4me3-shKDM5C2-MCF7
GSM9301118 Gro-seq-MCF7

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