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A Molecular Switch from Tumor Suppressor to Oncogene in ER-Positive Breast Cancer: Role of Androgen Receptor, JAK-STAT, and Lineage Plasticity

GSE274731 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 102 samples Submitted 2024/10/16 Platform GPL18573Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 102 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
102 samples: 70 distinct titles, 9 of them repeatedGroups 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
A molecular switch from tumor suppressor to oncogene in ER+ve breast cancer: Role of androgen receptor, JAK-STAT, and lineage plasticityProceedings of the National Academy of Sciences of the United States of America · 2024
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
Published in
A molecular switch from tumor suppressor to oncogene in ER+ve breast cancer: Role of androgen receptor, JAK-STAT, and lineage plasticity
Asemota S, Effah W, Holt J et al. · Proceedings of the National Academy of Sciences of the United States of America 2024 · PMID 39312663 · doi:10.1073/pnas.2406837121
This dataset
Open GSE274731 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 GSE274731_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 PRJNA1147721 and SRA study SRP526085. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39312663) ↗
Study design
70 distinct titles, 9 of them repeated
T47D_G4 ×7 WHIM23_G4 ×7 T47D_G1 ×4 T47D_G2 ×4 WHIM23_G2 ×4 ZR-75-1 parental enobosarm ×4 ZR-75-1 enobosarm resistant enobosarm ×4 ZR-75-1 enobosarm resistant enobosarm + ruxol… ×4 +1 more

How we read this: Read from 102 sample titles: 70 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

+ 62 more — browse all 102 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.