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Targeting the oncohistone-ASCL1 axis disrupts plasticity and suppresses pediatric gliomas [CUT&RUN]

GSE269555 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 39 samples Submitted 2026/07/10 Platform GPL30173
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 39 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
39 samples: 11 conditions, mostly in duplicateGroups 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)
Phenotypic plasticity, a hallmark of cancer facilitated by epigenomic reprogramming, represents a significant challenge but also therapeutic opportunity for cancer treatment. How plasticity is regulated in diffuse midline gliomas (DMGs), incurable pediatric brain tumors characterized by oncogenic H3K27M histone mutations, is not understood.
Read the full summary ↓
Here we demonstrate that H3K27M-driven plasticity requires the lineage-specific, pioneer transcription factor (TF) ASCL1. Prolonged differentiation reveals clinically relevant plasticity in DMGs, which segregate into ASCL1-high, neural progenitor cell (NPC)-like gliomaspheres and ASCL1-low, mesenchymal (MES)-like adherent subpopulations. Direct transcriptional activation by ASCL1 enables super enhancers to sustain NPC programs de-repressed by H3K27M. H3K27M loss induces an irreversible MES-like state, suppresses plasticity by abolishing the ASCL1-high state, and is largely phenocopied by loss of ASCL1. Knocking out ASCL1 in DMG lines robustly inhibited tumor growth and significantly extended survival of recipient mice. Our results suggest targeting epigenetic plasticity to suppress master TF-driven progenitor states as a general therapeutic opportunity in cancer.
This dataset
Open GSE269555 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 GSE269555_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 PRJNA1122515 and SRA study SRP513152. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
11 conditions, mostly in duplicate
CnR_ASCL1_Control_TSM ×3 CnR_ASCL1_K27MKO_TSM ×3 CnR_BRG1_ASCL1KO_Day3 ×3 CnR_BRG1_Control_Day3 ×3 CnR_BRG1_DKO_Day3 ×3 CnR_ASCL1_Control_Adh_Wk10 ×2 CnR_ASCL1_Control_Day3 ×2 CnR_ASCL1_Control_Sph_Wk10 ×2 +15 more

Supports a between-group comparison across 27 samples.

How we read this: 11 replicated groups read from 39 sample titles; they account for 27 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
Datasets on a similar topic

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