GEO series

ChIP-seq of GLTSCR1 and SS18::SSX fusion in HS-SY-II synovial sarcoma cells treated with the BRD9 PROTAC degrader WA-68 across a time course

GSE328411 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 14 samples Submitted 2026/06/24 Platform GPL34281

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 14 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: Soft tissue sarcomaThis series is part of our curated briefing on it.
Samples: 14 samples: 14 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.

Summary (written by the submitters)

Synovial sarcoma (SyS) is driven by the SS18::SSX fusion oncoprotein, which incorporates into GBAF chromatin remodeling complexes and creates a dependency on BRD9. To investigate the effects of BRD9 loss, we performed ChIP-seq, ATAC-seq, and RNA-seq in SyS models following BRD9 degradation. ChIP-seq shows reduced GBAF occupancy at target loci, while ATAC-seq reveals maintained or increased chromatin accessibility.

Read the full summary ↓

RNA-seq demonstrates sustained or elevated expression of target genes. These results indicate that BRD9 is not required for GBAF assembly but instead restrains its remodeling activity, providing a mechanistic explanation for the limited efficacy of BRD9-targeted therapies in SyS.

This dataset

Open GSE328411 in finder → Find more human ChIP / ATAC / CUT&Tag datasets → Soft tissue sarcoma 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 GSE328411_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 PRJNA1454927 and SRA study SRP692795. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

14 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 14 sample titles: 14 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

GSM9682400 HS-SY-II ChIP-seq GLTSCR1, DMSO
GSM9682401 HS-SY-II ChIP-seq GLTSCR1, WA-68 (100 nM), 12h
GSM9682402 HS-SY-II ChIP-seq GLTSCR1, WA-68 (100 nM), 24h
GSM9682403 HS-SY-II ChIP-seq GLTSCR1, WA-68 (100 nM), 48h
GSM9682404 HS-SY-II ChIP-seq GLTSCR1, WA-68 (100 nM), 96h
GSM9682405 HS-SY-II ChIP-seq SS18::SSX fusion (HA-tag), DMSO
GSM9682406 HS-SY-II ChIP-seq SS18::SSX fusion (HA-tag), WA-68 (100 nM), 12h
GSM9682407 HS-SY-II ChIP-seq SS18::SSX fusion (HA-tag), WA-68 (100 nM), 24h
GSM9682408 HS-SY-II ChIP-seq SS18::SSX fusion (HA-tag), WA-68 (100 nM), 48h
GSM9682409 HS-SY-II ChIP-seq input, DMSO
GSM9682410 HS-SY-II ChIP-seq input, WA-68 (100 nM), 12h
GSM9682411 HS-SY-II ChIP-seq input, WA-68 (100 nM), 24h
GSM9682412 HS-SY-II ChIP-seq input, WA-68 (100 nM), 48h
GSM9682413 HS-SY-II ChIP-seq input, WA-68 (100 nM), 96h

More Soft tissue sarcoma datasets

GSE292876 FANCM is Required for the PAX3::FOXO1-Driven Oncogenic Program in Rhabdomyosarcoma [ChIP-Seq] 18 samples same disease briefing · shares chip-seq
GSE329566 CDK8 Inhibition Releases the Muscle Differentiation Blockade in Fusion-driven Alveolar Rhabdomyosarcoma [ChIP-Seq] 8 samples same disease briefing · shares chip-seq
GSE332748 PAX3::FOXO1-Targeting PROTAC Induces Myogenic Differentiation of Fusion-Positive Rhabdomyosarcoma Cells 6 samples same disease briefing · shares protac
GSE303151 CDK8 Inhibition Releases the Muscle Differentiation Blockade in Fusion-driven Alveolar Rhabdomyosarcoma [CUT&RUN] 50 samples same disease briefing
GSE275736 A multitargeting approach rewires cell identity in fusion-negative rhabdomyosarcoma [bulk_ATACseq] 8 samples same disease briefing
GSE224170 Chromatin status of rhabdomyosarcoma (RMS) cell line RH30 in repsonse to MyoD CRISPR/Cas9 deletion [RMS ATAC-seq] 6 samples same disease briefing
GSE303149 CDK8 Inhibition Releases the Muscle Differentiation Blockade in Fusion-driven Alveolar Rhabdomyosarcoma [ATAC-seq] 6 samples same disease briefing
GSE312030 Combined inhibition of HRAS and MEK induces tumor regression and restores myogenic differentiation in HRAS-mutant rhabdomyosarcoma 159 samples same disease briefing

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.