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ZFTA–RELA ependymomas make itaconate to epigenetically drive fusion expression [ChIP-Seq]

GSE294955 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 18 samples Submitted 2025/11/17 Platform GPL24247Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 18 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
Mus musculus (mouse)
Samples
18 samples: 18 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.
Paper
ZFTA-RELA ependymomas make itaconate to epigenetically drive fusion expressionNature · 2026
Summary (written by the submitters)
ZFTA-RELA ependymomas are malignant brain tumors that are frequently lethal. They are defined by fusions formed between the putative chromatin remodeler ZFTA and the NFkB-mediator-RELA. We identified that ZFTA-RELA cells produced itaconate, a key macrophage-associated immunomodulator metabolite. However, itaconate production by tumor cells and its tumor-intrinsic role are not well-established.
Read the full summary ↓
Itaconate is synthesized by the enzyme Aconitate Decarboxylase-1 (ACOD1) and the ZFTA-RELA fusion upregulated ACOD1 in an NFkB-dependent manner. Additionally, itaconate production enabled a feed-forward system that maintained pathogenic ZFTA-RELA fusion expression through epigenetic activation. To supply the metabolic fuel needed to generate itaconate, these tumors epigenetically activated PI3K/mTOR signaling to enhance glutaminolysis, which provided the carbons necessary for itaconate synthesis. Consequently, antagonizing glutamine metabolism lowered pathogenic ZFTA-RELA levels and was potently therapeutic in multiple in vivo models. Finally, combining glutamine antagonism with PI3K/mTOR inhibition abrogated spinal metastasis. Our data demonstrate that ZFTA-RELA ependymomas subvert a macrophage-like itaconate metabolic pathway to maintain expression of the ZFTA-RELA fusion driver, implicating itaconate as an oncometabolite. Taken together, our results position itaconate upregulation as a previously unappreciated driver of ZFTA-RELA ependymomas. This study therefore has implications for future drug development for children with this devastating brain tumor and will further our understanding of oncometabolites as a novel class of therapeutic dependencies in cancers.
Published in
ZFTA-RELA ependymomas make itaconate to epigenetically drive fusion expression
Natarajan SK, Lum J, Skeans JH et al. · Nature 2026 · PMID 41639460 · doi:10.1038/s41586-025-10005-1
This dataset
Open GSE294955 in finder → Find more 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 GSE294955_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 PRJNA1252100 and SRA study SRP579537. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41639460) ↗
Study design
18 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 18 sample titles: 18 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
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