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H2A.Z histone variants facilitate HDACi-dependent removal of H3.3K27M mutant protein in paediatric high-grade glioma cells

GSE232283 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 47 samples Submitted 2024/05/01 Platform GPL24676Platform GPL11154
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 47 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
47 samples: 37 distinct titles, 5 of them repeatedGroups 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
H2A.Z histone variants facilitate HDACi-dependent removal of H3.3K27M mutant protein in pediatric high-grade glioma cellsCell reports · 2024
Summary (written by the submitters)
Diffuse intrinsic pontine gliomas (DIPG) are paediatric malignant gliomas developing in the brainstem, where resection is unattainable, leaving palliative radiotherapy as the major standard of care. Patients with DIPG have dismal prognosis of 9-12 months of survival and currently there is no effective therapy. Over 80% of DIPGs harbour a mutation in histone 3 (H3.3 or H3.1) resulting in a lysine to methionine substitution (H3K27M).
Read the full summary ↓
H3K27M causes global epigenetic alterations (a loss of H3K27 trimethylation and an increase H3K27 acetylation) resulting in aberrant gene expression. To date, no therapeutic strategy exists to suppress the levels of oncogenic H3K27M. We show that pan-HDAC inhibitors (HDACi) lead to the temporary but significant reduction in the H3.3K27M protein (up to 80%) in multiple glioma cell lines expressing the H3.3K27M histone variant, without changes in the H3F3A mRNA expression. The H3.3K27M occupancy at the chromatin is greatly reduced upon HDACi (SB939) treatment, as shown by ChIPseq analysis. H3.3K27M loss is most striking at SB939-upregulated genes suggesting re-expression of repressed genes. Certain H3K27M-dependent genes become downregulated in response to SB939 treatment. We discover that the SB939-mediated loss of H3.3K27M is partially blocked by a lysosomal inhibitor chloroquine. Moreover, the loss of H3.3K27M is facilitated by co-occurrence of H2A.Z, as evidenced by the knock-down of H2A.Z histone isoforms. ChIPseq analysis confirms the occupancy of H3.3K27M and H2A.Z at the same SB939-inducible genes. Altogether, we provide new insight into disease-specific mechanism of HDAC inhibition and demonstrate pharmacological modulation of the oncogenic H3.3K27M protein levels. These findings open a new possibility to directly target the H3.3K27M oncohistone, which may be exploited in future therapies.
Published in
H2A.Z histone variants facilitate HDACi-dependent removal of H3.3K27M mutant protein in pediatric high-grade glioma cells
Leszczynska KB, Freitas-Huhtamäki A, Jayaprakash C et al. · Cell reports 2024 · PMID 38306270 · doi:10.1016/j.celrep.2024.113707
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 GSE232283_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 PRJNA971530 and SRA study SRP437096. Searching any of these in the dataset finder brings you back here.

Study design
37 distinct titles, 5 of them repeated
DIPGXIII, RNA-seq, DMSO, ×3 DIPGXIII, RNA-seq, 3h after SB939, ×3 DIPGXIII, RNA-seq, 16h after SB939, ×3 DIPGXIII, RNA-seq, 48h after SB939, ×3 DIPGXIII, RNA-seq, 72h after SB939, ×3

How we read this: Read from 47 sample titles: 37 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

+ 7 more — browse all 47 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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