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CBFA2T3-GLIS2 fusion-mediated mSWI/SNF chromatin remodeler disruption generates cancer-specific dependencies in AMKL [Cut & Run M-07e]

GSE328419 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 34 samples Submitted 2026/04/22 Platform GPL34284
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 34 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)
Samples
34 samples: 34 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)
Transcription factor (TF) fusion oncoproteins are frequently associated with poor prognosis and remain challenging therapeutic targets. Here we show that the CBFA2T3-GLIS2 (C/G) fusion oncoprotein present in lethal pediatric acute megakaryocytic leukemias (AMKLs) co-opts mSWI/SNF chromatin remodeling complexes, reprogramming regulatory element architecture to sustain aberrant cell cycle progression.
Read the full summary ↓
The C/G fusion binds to and redistributes mSWI/SNF complexes via the SMARCD1 SWIFT domain and targets complexes to oncogenic enhancers including those bound by ETS family TFs and the G1 cyclin CCND2, a C/G AML-specific dependency. Pharmacologic inhibition of mSWI/SNF-mediated G1 cell cycle phasing via FHD-286 suppresses C/G-driven gene expression programs, induces G1 arrest and apoptosis in cells, and reduces leukemic burden and extends survival in aggressive C/G AML in vivo. These findings define an oncogenic mSWI/SNF–G1 axis in C/G AML and establish a therapeutic framework for targeting chromatin dysfunction-mediated cell cycle aberrancy in high-risk pediatric leukemias.
This dataset
Open GSE328419 in finder → Find more human ChIP / ATAC / CUT&Tag datasets →
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 GSE328419_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 PRJNA1454948 and SRA study SRP692805. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
34 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 34 sample titles: 34 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
Datasets on a similar topic

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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.