GEO series

Combined epigenetic therapy with FACT and BET inhibitors remodels chromatin and disrupts oncogenic transcription in Diffuse Midline Glioma [RNA-seq]

GSE272131 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2025/12/22 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 24 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)
Samples: 24 samples: 8 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: Combined inhibition of FACT and BET disrupts transcription to suppress tumor growth in mouse models of diffuse midline gliomaScience translational medicine · 2026

Summary (written by the submitters)

Aberrant epigenetic regulation is a hallmark of Diffuse Midline Glioma (DMG), an incurable pediatric brain tumor. The H3K27M driver histone mutation leads to transcriptional dysregulation, indicating that targeting the epigenome and transcription may be a key therapeutic strategy against this highly aggressive cancer. One such target is the Facilitates Chromatin Transcription (FACT) histone chaperone.

Read the full summary ↓

We found FACT to be enriched at developmental gene promoters, coinciding with regions of open chromatin and binding motifs of core DMG regulatory transcription factors. Furthermore, FACT interacted and co-localized with the Bromodomain and Extra-Terminal Domain (BET) protein BRD4 at promoters and enhancers, suggesting functional cooperation between FACT and BRD4 in DMG. In vitro, a combinatorial therapeutic approach using the FACT inhibitor CBL0137, coupled with BET inhibition revealed potent and synergistic cytotoxicity across a range of DMG cultures, with H3K27M-mutant cells demonstrating heightened sensitivity. These results were recapitulated in vivo, significantly extending survival in three independent orthotopic PDX models of DMG. Mechanistically, we show that CBL0137 treatment decreased chromatin accessibility, synergizing with BET inhibition to disrupt transcription, silencing several key oncogenes including MYC, PDGFRA and MDM4, alongside alterations to the splicing landscape. Combined, these data highlight the therapeutic promise of simultaneously targeting FACT and BRD4 in DMG, proposing a novel strategy for combating this devastating pediatric brain tumor.

Published in

Combined inhibition of FACT and BET disrupts transcription to suppress tumor growth in mouse models of diffuse midline glioma

Holliday H, Khan A, Ehteda A et al. · Science translational medicine 2026 · PMID 41533777 · doi:10.1126/scitranslmed.adr1557

This dataset

Open GSE272131 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 GSE272131_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 PRJNA1135173 and SRA study SRP519672. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41533777) ↗

Study design

8 conditions, mostly in triplicate

DIPG7_RNA_Veh ×3 DIPG7_RNA_CBL0137 ×3 DIPG7_RNA_JQ1 ×3 DIPG7_RNA_Combo ×3 DIPG6_RNA_Veh ×3 DIPG6_RNA_CBL0137 ×3 DIPG6_RNA_JQ1 ×3 DIPG6_RNA_Combo ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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

GSM8393730 DIPG7_RNA_Veh_rep1 DIPG7_RNA_Veh
GSM8393731 DIPG7_RNA_Veh_rep2 DIPG7_RNA_Veh
GSM8393732 DIPG7_RNA_Veh_rep3 DIPG7_RNA_Veh
GSM8393733 DIPG7_RNA_CBL0137_rep1 DIPG7_RNA_CBL0137
GSM8393734 DIPG7_RNA_CBL0137_rep2 DIPG7_RNA_CBL0137
GSM8393735 DIPG7_RNA_CBL0137_rep3 DIPG7_RNA_CBL0137
GSM8393736 DIPG7_RNA_JQ1_rep1 DIPG7_RNA_JQ1
GSM8393737 DIPG7_RNA_JQ1_rep2 DIPG7_RNA_JQ1
GSM8393738 DIPG7_RNA_JQ1_rep3 DIPG7_RNA_JQ1
GSM8393739 DIPG7_RNA_Combo_rep1 DIPG7_RNA_Combo
GSM8393740 DIPG7_RNA_Combo_rep2 DIPG7_RNA_Combo
GSM8393741 DIPG7_RNA_Combo_rep3 DIPG7_RNA_Combo
GSM8393742 DIPG6_RNA_Veh_rep1 DIPG6_RNA_Veh
GSM8393743 DIPG6_RNA_Veh_rep2 DIPG6_RNA_Veh
GSM8393744 DIPG6_RNA_Veh_rep3 DIPG6_RNA_Veh
GSM8393745 DIPG6_RNA_CBL0137_rep1 DIPG6_RNA_CBL0137
GSM8393746 DIPG6_RNA_CBL0137_rep2 DIPG6_RNA_CBL0137
GSM8393747 DIPG6_RNA_CBL0137_rep3 DIPG6_RNA_CBL0137
GSM8393748 DIPG6_RNA_JQ1_rep1 DIPG6_RNA_JQ1
GSM8393749 DIPG6_RNA_JQ1_rep2 DIPG6_RNA_JQ1
GSM8393750 DIPG6_RNA_JQ1_rep3 DIPG6_RNA_JQ1
GSM8393751 DIPG6_RNA_Combo_rep1 DIPG6_RNA_Combo
GSM8393752 DIPG6_RNA_Combo_rep2 DIPG6_RNA_Combo
GSM8393753 DIPG6_RNA_Combo_rep3 DIPG6_RNA_Combo

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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.