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

GSE289005 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/02/28 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
GlioblastomaThis series is part of our curated briefing on it.
Samples
18 samples: 6 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.
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
Open GSE289005 in finder → Find more human RNA-seq datasets → Glioblastoma landscape →
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 GSE289005_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1220592 and SRA study SRP562180. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
08-387 GSCs, shNT ×3 08-387 GSCs, shMCU#1 ×3 08-387 GSCs, shMCU#2 ×3 T4121 GSCs, shNT ×3 T4121 GSCs, shMCU#1 ×3 T4121 GSCs, shMCU#2 ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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
More Glioblastoma datasets

Search all human RNA-seq datasets in GEO →

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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.