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Disordered DNA methylation leads to targetable transcriptional plasticity in ATRT [RNA-seq]

GSE301405 Homo sapiens (human) DNA methylation 48 samples Submitted 2025/11/14 Platform GPL24676
At a glance

DNA methylation · human · 48 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Samples
48 samples: 16 conditions, mostly in triplicateGroups 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.
Paper
Disordered DNA methylation leads to targetable transcriptional plasticity in ATRTActa neuropathologica communications · 2025
Summary (written by the submitters)
Atypical teratoid rhabdoid tumor (ATRT) is a highly aggressive but genetically simple pediatric central nervous system tumor, defined by biallelic inactivation of the chromatin regulator SMARCB1 with remarkably few other cooperating mutations. Despite its genetic homogeneity, ATRT exhibits profound clinical and epigenetic heterogeneity, with three major subgroups (ATRT-TYR, ATRT-MYC, and ATRT-SHH) defined by DNA methylation and transcriptional signatures.
Read the full summary ↓
Beyond these subgroup-defining features, we aimed to investigate epigenetic variability within tumors by applying whole-genome bisulfite sequencing and probabilistic modeling to quantify stochastic DNA methylation in primary ATRT samples encompassing all three subgroups. We show that ATRT exhibits a destabilized and increasingly stochastic methylome. While ATRT global methylation patterns diverge according to subgroup, some methylation perturbations, such as hypermethylation and increased methylation entropy over bivalent promoters, are consistent across subgroups. We find that methylation stochasticity alterations map onto potential drivers of ATRT, such as LIN28a, the HOXD cluster for ATRT-MYC, and OTX2 for ATRT-TYR, and identify actionable targets, such as hypermethylation of the tumor suppressor CDKN2a across all subgroups. We investigate the sensitivity of the aberrant DNA methylation landscape of ATRT to pharmacologic DNA methyltransferase inhibition and histone deacetylase inhibition (HDACi). We show that decitabine leads to profound demethylation of patient-derived ATRT cell lines, including reversal of hypermethylation at bivalent promoters and the CDKN2a locus. The addition of HDACi leads to dramatic gene expression changes, including upregulation of innate immune signaling pathways, such as STING/interferon signaling, genes under the regulation of bivalent promoters, and reactivation of the tumor suppressor CDKN2A. The combination of DNMTi and HDACi synergistically reduces cell viability. Taken together, we show that ATRT has a highly stochastic methylome sensitive to epigenetic manipulation.
Published in
Disordered DNA methylation leads to targetable transcriptional plasticity in ATRT
Tetens AR, Findlay TR, Craig-Schwartz J et al. · Acta neuropathologica communications 2025 · PMID 41408661 · doi:10.1186/s40478-025-02173-y
This dataset
Open GSE301405 in finder → Find more human RNA-seq 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 GSE301405_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 beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA1284941 and SRA study SRP596539. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41408661) ↗
Study design
16 conditions, mostly in triplicate
CHLA02_COMB ×3 CHLA02_DAC ×3 CHLA02_DMSO ×3 CHLA02_RG ×3 CHLA05_COMB ×3 CHLA05_DAC ×3 CHLA05_DMSO ×3 CHLA05_RG ×3 +8 more

Supports a between-group comparison across 48 samples.

How we read this: 16 replicated groups read from 48 sample titles; they account for 48 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

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