GEO series

Spatially-Resolved Multiomic Atlas of Leiomyosarcoma Identifies Two Clinically Relevant Epigenetically-Driven Cell States [CUT&RUN]

GSE324171 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 24 samples Submitted 2026/06/22 Platform GPL18573

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 24 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: 24 samples: 24 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)

Leiomyosarcoma is a smooth muscle–derived malignancy marked by significant clinical heterogeneity. The extent and nature of cellular heterogeneity and molecular underpinnings remain poorly understood. To address this at transcriptomic and epigenomic levels, we performed single-nucleus multiome sequencing on untreated primary leiomyosarcoma tissues.

Read the full summary ↓

Malignant cells segregated almost exclusively into two previously unrecognized and epigenetically distinct states: a dedifferentiated, mesenchymal-like subtype (MES) and a differentiated smooth muscle–enriched subtype (SMC). Chromatin accessibility profiling revealed strong enrichment of nuclear factor I (NFI) transcription factor motifs in MES cells, whereas AP-1 family motifs—most prominently FOSL2—were selectively accessible in SMC cells. Established leiomyosarcoma cell lines faithfully recapitulated these subtypes, and targeted depletion of NFI or AP-1 factors suppressed proliferation, invasion, and in vivo tumor growth, demonstrating functional dependency on these transcriptional programs. Spatial transcriptomics across 328 tissue cores from 128 leiomyosarcomas showed that immunosuppressive macrophages preferentially cluster around MES regions, revealing a subtype-specific tumor–immune niche. Clinically, MES-dominant tumors were associated with significantly worse patient outcomes. Through an epigenetic inhibitor screen, we identify and validate SMARCA4/2 inhibition as a promising therapeutic vulnerability for MES leiomyosarcomas. Together, this work defines two epigenetically driven, transcription factor–regulated, and clinically relevant states of leiomyosarcoma, revealing mechanistic underpinnings of tumor heterogeneity and uncovering actionable therapeutic strategies.

This dataset

Open GSE324171 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 GSE324171_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 PRJNA1433558 and SRA study SRP681849. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

24 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 24 sample titles: 24 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

GSM9570442 CUT&RUN IgG control in Leio012
GSM9570443 CUT&RUN H3K4me3 in Leio012
GSM9570444 CUT&RUN NFIA in Leio012
GSM9570445 CUT&RUN NFIB in Leio012
GSM9570446 CUT&RUN NFIC in Leio012
GSM9570447 CUT&RUN NFIX in Leio012
GSM9570448 CUT&RUN BACH2 in Leio012
GSM9570449 CUT&RUN FOSL2 in Leio012
GSM9570450 CUT&RUN IgG control in SKLMS01
GSM9570451 CUT&RUN H3K4me3 in SKLMS01
GSM9570452 CUT&RUN NFIA in SKLMS01
GSM9570453 CUT&RUN NFIB in SKLMS01
GSM9570454 CUT&RUN NFIC in SKLMS01
GSM9570455 CUT&RUN NFIX in SKLMS01
GSM9570456 CUT&RUN BACH2 in SKLMS01
GSM9570457 CUT&RUN FOSL2 in SKLMS01
GSM9570458 CUT&RUN IgG control in SKUT1B
GSM9570459 CUT&RUN H3K4me3 in SKUT1B
GSM9570460 CUT&RUN NFIA in SKUT1B
GSM9570461 CUT&RUN NFIB in SKUT1B
GSM9570462 CUT&RUN NFIC in SKUT1B
GSM9570463 CUT&RUN NFIX in SKUT1B
GSM9570464 CUT&RUN BACH2 in SKUT1B
GSM9570465 CUT&RUN FOSL2 in SKUT1B

More Soft tissue sarcoma datasets

GSE303151 CDK8 Inhibition Releases the Muscle Differentiation Blockade in Fusion-driven Alveolar Rhabdomyosarcoma [CUT&RUN] 50 samples same disease briefing · shares cut, run
GSE287694 Integration of whole genome sequencing analysis with unique patient-derived models reveals clinically relevant drug targets in TFCP2 fusion-defined intraosseous rhabdomyosarcoma 2 samples same disease briefing · shares clinically
GSE292876 FANCM is Required for the PAX3::FOXO1-Driven Oncogenic Program in Rhabdomyosarcoma [ChIP-Seq] 18 samples same disease briefing
GSE275736 A multitargeting approach rewires cell identity in fusion-negative rhabdomyosarcoma [bulk_ATACseq] 8 samples same disease briefing
GSE329566 CDK8 Inhibition Releases the Muscle Differentiation Blockade in Fusion-driven Alveolar Rhabdomyosarcoma [ChIP-Seq] 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.