GEO series

Identification of genomic features that uniquely impact estrogen receptor alpha binding and its effects on gene expression in endometrial cancer [SOX17_ChIPseq]

GSE312323 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 2 samples Submitted 2025/12/08 Platform GPL24676

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 2 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: Endometrial cancerThis series is part of our curated briefing on it.
Samples: 2 samples
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)

Estrogen receptor alpha (ER) is an established oncogenic transcription factor in breast and endometrial cancer; however, more is known about the mechanisms controlling ER behavior in breast cancer, and therapies targeting ER have only been successful in breast cancer patients. To address this disparity, we sought to identify genomic features that control ER in endometrial cancer and determine to what extent these factors differ from those in breast cancer.

Read the full summary ↓

We focused on the locations of estrogen response elements (EREs), ER’s preferred DNA binding motif, throughout the human genome. To identify factors that predict ER genomic binding and effects on target gene expression, we applied machine learning to genomic data for each ERE in Ishikawa cells (ER+ endometrial cancer) and T-47D cells (ER+ breast cancer). Many of these factors, such as chromatin accessibility and histone modifications, were predictive of ER activity in both cell lines. However, the transcription factors that predict ER activity were found to be cell type-specific, including FOXA1 and GATA3 in T-47D cells, and ETV4 and SOX17 in Ishikawa cells. In addition, the features that predict ER binding and effects on gene expression differed, with transcription at EREs in the absence of estrogen being predictive of regulatory activity. To verify our findings in the Ishikawa cells, we performed a CRISPR knockout screen, which confirmed the discovery that SOX17 controls ER activity in endometrial cancer cells. These results identify important genomic features of ER binding and regulatory activity and how they differ between endometrial cancer and breast cancer cells.

This dataset

Open GSE312323 in finder → Find more human ChIP / ATAC / CUT&Tag datasets → Endometrial 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 GSE312323_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 PRJNA1373033 and SRA study SRP650989. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 2 more — browse all 2 samples with per-sample file links →

More Endometrial cancer datasets

GSE312906 Identification of genomic features that uniquely impact estrogen receptor alpha binding and its effects on gene expression in endometrial cancer 37 samples same disease briefing · shares endometrial, features, uniquely, estrogen, receptor, binding
GSE334100 Identification of genomic features that uniquely impact estrogen receptor alpha binding and its effects on gene expression in endometrial cancer [RNA-seq] 16 samples same disease briefing · shares endometrial, features, uniquely, estrogen, receptor, binding
GSE303681 Pre-receptor regulation of 11-oxyandrogens differs between normal and cancerous endometrium and across endometrial cancer grades and molecular subtypes 18 samples same disease briefing · shares endometrial, receptor
GSE275223 A distinct mechanism of epigenetic reprogramming silences PAX2 and initiates endometrial carcinogenesis 20 samples same disease briefing · shares endometrial
GSE275222 A distinct mechanism of epigenetic reprogramming silences PAX2 and initiates endometrial carcinogenesis 14 samples same disease briefing · shares endometrial
GSE294692 A distinct mechanism of epigenetic reprogramming silences PAX2 and initiates endometrial carcinogenesis 4 samples same disease briefing · shares endometrial
GSE319248 Histone Demethylase KDM4A Activates ERRγ-Dependent Cell Cycle Progression to Promote Endometrial Cancer Progression 4 samples same disease briefing · shares endometrial
GSE275221 A distinct mechanism of epigenetic reprogramming silences PAX2 and initiates endometrial carcinogenesis 3 samples same disease briefing · shares endometrial

Search all human ChIP / ATAC / CUT&Tag 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.