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Fasting boosts breast cancer therapy efficacy via glucocorticoid activation

GSE260486 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 85 samples Submitted 2025/10/14 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 85 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
85 samples: 24 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.
Paper
Fasting boosts breast cancer therapy efficacy via glucocorticoid activationNature · 2026
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
Published in
Fasting boosts breast cancer therapy efficacy via glucocorticoid activation
Padrão N, Severson TM, Gregoricchio S et al. · Nature 2026 · PMID 41372410 · doi:10.1038/s41586-025-09869-0
This dataset
Open GSE260486 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 GSE260486_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 PRJNA1081869 and SRA study SRP492378. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41372410) ↗
Study design
24 conditions, mostly in triplicate
MCF7_TMXplusFasting_ER ×6 MCF7_TMXplusFasting_H3K27ac ×6 MCF7_TMXplusFasting ×6 MCF7_Control_ER ×3 MCF7_TMX_ER ×3 MCF7_Fasting_ER ×3 MCF7_Control_H3K27ac ×3 MCF7_TMX_H3K27ac ×3 +20 more

Supports a between-group comparison across 81 samples.

How we read this: 24 replicated groups read from 85 sample titles; they account for 81 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

+ 45 more — browse all 85 samples with per-sample file links →

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.