GEO series

Recognition of a pediatric glioblastoma-associated histone mutation by chromatin reader ZMYND8 promotes tumorigenesis

GSE99979 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2024/04/14 Platform GPL17021

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 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: Mus musculus (mouse)
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.

Summary (written by the submitters)

Histone H3 point mutations have recently been identified in pediatric brain cancers, including missense mutations on histone H3 at positions 27 (lysine to methionine; K27M) and 34 (glycine to arginine, G34R), respectively. H3K27M mutations are associated with a majority of pediatric Diffuse Intrinsic Pontine Pediatric Glioma (DIPG) cases, while H3.3G34R is found in pediatric glioblastoma (GBM) arising in the cerebral cortex1,2.

Read the full summary ↓

While the mechanisms of H3K27M-driven tumorigenesis are beginning to unravel, much less is known about the H3.3G34R mutation. Here, we provide both biochemical and structural evidence that the PHD (plant homedomain) domain of the enhancer-binding protein, RACK7 (ZMYND8), recognizes H3.3G34R mutant histone via a mechanism distinct from other PHD domains. In an H3.3G34R-expressing neuronal precursor cell line, we demonstrate that RACK7 is aberrantly recruited to enhancers bound by H3.3G34R, resulting in the down-regulation of many neuronal genes, and the up-regulation of oncogenes such as MYC. Neural precursor cells expressing H3.3G34R showed enhanced tumor growth when injected subcutaneously. Inhibiting RACK7 binding to H3.3G34R reduces tumor size and alters gene expression, suggesting that H3.3G34R regulation of enhancers via RACK7 promotes tumorigenesis. Specifically, we show that both the gene expression and tumor size regulation are critically dependent on the physical interaction of H3.3G34R with RACK7. Both regulations are compromised in the absence of RACK7, and can be rescued by wildtype, but not an H3.3G34R-binding defective, RACK7. Taken together, we have identified a reader for H3.3G34R and demonstrate that RACK7 binding to H3.3G34R alters enhancer activity to directly suppress neural gene transcription and to increase oncogenic propensity of neural precursor cells, thus providing a potential molecular basis for pediatric GBM driven by the H3.3G34R mutation.

This dataset

Open GSE99979 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE99979_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA390255 and SRA study SRP109086. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

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

GSM2666918 H3.3WT_HA_ChIP
GSM2666919 H3.3G34R_HA_ChIP
GSM2666920 H3.3WT_Rack7_ChIP
GSM2666921 H3.3G34R_Rack7_ChIP
GSM2666922 H3.3WT_H3K4me1_ChIP
GSM2666923 H3.3G34R_H3K4me1_ChIP
GSM2666924 H3.3WT_H3K27Ac_ChIP
GSM2666925 H3.3G34R_H3K27Ac_ChIP
GSM2666926 H3.3WT_input
GSM2666927 H3.3G34R_input

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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.