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The impact of Fulvestrant on Estrogen Receptor-Driven Chromatin Dynamics in Breast Cancer Cells [RNA-seq]

GSE310291 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2026/05/25 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 48 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
48 samples: 12 conditions, mostly with about 4 replicates eachGroups 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)
Background: Epigenetic dysregulations are linked to various diseases, including cancer. Among them, breast cancer is the second leading cause of cancer-related deaths in women with 50% of mortalities attributable to estrogen receptor-positive (ER+) tumors. Endocrine therapies targeting the ER such as Tamoxifen, Fulvestrant (FULV) and Aromatase inhibitors, are widely used in the clinic.
Read the full summary ↓
Among these therapeutic agents, FULV has been shown to fully antagonize ER activity, primarily through the rapid degradation and elimination of ER from target tissues. However, recent findings indicate that ER, when engaged with FULV, retains the ability to translocate to the nucleus and bind DNA whereas appearing transcriptionally inert. Results: In this study, we aimed to further investigate the effects of FULV and Estradiol (E2), the natural ER ligand, on ER cistrome, chromatin accessibility, gene transcription, and H3K27ac genome-wide patterns in ER+ breast cancer cell lines. Using the innovative CUT&Tag technology, we first confirmed that both FULV and E2 promote ER binding to DNA. Our findings revealed that E2 not only enhances chromatin accessibility and gene expression but also increases H3K27ac levels at ER binding sites. In contrast, FULV does not significantly alter chromatin accessibility or transcription but is not completely inert, as it induces increases in H3K27ac at a subset of ER binding sites. These observations indicate a decoupling between histone acetylation and transcriptional output under FULV treatment. Conclusions: This study provides new insights into the mechanistic impact of FULV on ER activity, highlighting its ability to modulate H3K27ac dynamics even in the absence of transcriptional changes. These findings underscore the complexity of ER signaling and suggest that FULV’s therapeutic effects may extend beyond simple antagonism of ER activity.
This dataset
Open GSE310291 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 GSE310291_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 PRJNA1365720 and SRA study SRP646278. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly with about 4 replicates each
RNA-seq in MCF7 cells, DMSO control, Time poi… ×4 RNA-seq in MCF7 cells, DMSO control, Time poi… ×4 RNA-seq in MCF7 cells, Estradiol treatment, T… ×4 RNA-seq in MCF7 cells, Estradiol treatment, T… ×4 RNA-seq in MCF7 cells, Fulvestrant treatment,… ×4 RNA-seq in MCF7 cells, Fulvestrant treatment,… ×4 RNA-seq in T47D cells, DMSO control, Time poi… ×4 RNA-seq in T47D cells, DMSO control, Time poi… ×4 +4 more

Supports a between-group comparison across 48 samples.

How we read this: 12 replicated groups read from 48 sample titles; they account for 48 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

+ 8 more — browse all 48 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.