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Mitochondrial calcium uniporter links acetyl-CoA metabolism and H3K27 acetylation to maintain glioblastoma stem cells [ChIP-Seq]

GSE289004 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 12 samples Submitted 2025/02/28 Platform GPL34284
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 12 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)
Topic
GlioblastomaThis series is part of our curated briefing on it.
Samples
12 samples: 12 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)
Glioblastoma stem cells (GSCs) exhibit remarkable metabolic and epigenetic adaptability, contributing to therapeutic resistance and tumor recurrence. However, the mechanisms underlying this plasticity remain incompletely understood. Here, we identify a novel metabolic-epigenetic axis centered on the mitochondrial calcium uniporter (MCU) that governs GSC fate and tumor initiation.
Read the full summary ↓
MCU is preferentially expressed in GSCs, and its knockdown significantly impairs GSC self-renewal and viability. Mechanistically, MCU enhances mitochondrial calcium uptake, promoting acetyl-CoA production via pyruvate dehydrogenase activation, which drives histone H3K27 acetylation at the TRIB3 locus to sustain stemness programs. In glioblastoma patients, higher MCU expression is correlated with increased acetyl-CoA levels, elevated H3K27 acetylation, enhanced TRIB3 expression, higher tumor grade, and poorer survival. Pharmacological inhibition of MCU with Berberine suppresses GSC growth and extends survival in mice. These findings establish MCU as a critical link between mitochondrial metabolism and epigenetic regulation, highlighting its potential as a therapeutic target for glioblastoma.
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 GSE289004_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 PRJNA1220593 and SRA study SRP562182. Searching any of these in the dataset finder brings you back here.

Study design
12 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 12 sample titles: 12 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
More Glioblastoma datasets

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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.