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High-dimensional analysis reveals increased chromatin heterogeneity and reduced histone acetylation driven by mutant-IDH1 [Cut&Run]

GSE238104 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2024/12/13 Platform GPL18573
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 10 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
10 samples: 10 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
Oncogenic IDH1(mut) drives robust loss of histone acetylation and increases chromatin heterogeneityProceedings of the National Academy of Sciences of the United States of America · 2025
Summary (written by the submitters)
Malignant gliomas are heterogeneous tumors arising in the central nervous system (CNS) driven by epigenetic and metabolic aberrations. Mutations in Isocitrate DeHydrogenase (IDH1/2) enzymes, highly frequent in adult gliomas, confer a gain-of-function activity that favors the conversion of a-ketoglutarate (α-KG) to the oncometabolite 2-hydroxyglutarate (2-HG), a competitive inhibitor of α-KG-dependent enzymes.
Read the full summary ↓
These include DNA and histone lysine demethylases, resulting in an aberrant hypermethylation phenotype in mutant-IDH-expressing cells. Leveraging epigenetic-focused cytometry by time-of-flight (CyTOF) analysis, we profiled the effect of mutant-IDH1 expression on a broad panel of histone modifications. This analysis revealed extensive remodeling of chromatin patterns by mutant-IDH, with a global reduction in histone acetylation being the most prominent alteration. The loss of histone acetylation occurs rapidly following mutant-IDH1 induction and affects acetylation patterns over enhancers and intergenic regions. Furthermore, cells expressing mutant-IDH1 showed higher epigenetic heterogeneity, which may support the tumorigenic potential of these cells. Our study underscores the tight interaction between chromatin and metabolism dysregulation in glioma, highlighting novel epigenetic pathways affected by mutant-IDH1-driven metabolic rewiring.
Published in
Oncogenic IDH1(mut) drives robust loss of histone acetylation and increases chromatin heterogeneity
Furth N, Cohen N, Spitzer A et al. · Proceedings of the National Academy of Sciences of the United States of America 2025 · PMID 39793065 · doi:10.1073/pnas.2403862122
This dataset
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.

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 GSE238104_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA997972 and SRA study SRP451129. Searching any of these in the dataset finder brings you back here.

Study design
10 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 10 sample titles: 10 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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