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Chromatin Modification Abnormalities by CHD7 and KMT2C Loss Promote Medulloblastoma Progression [scRNA-seq]

GSE293000 Mus musculus (mouse) Single-cell RNA-seq 1 samples Submitted 2025/03/30 Platform GPL21626
At a glance

Single-cell RNA-seq · mouse · 1 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
1 samples
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)
Medulloblastoma, a common malignant pediatric brain tumor that typically originating from the cerebellum, is characterized by mutations in chromatin modifiers, highlighting the significance of epigenomic abnormalities in their progression. To prove this significance, the development and use of animal models that closely recapitulate the disease have been highly effective.
Read the full summary ↓
However, due to substantial time and cost limitations of developing genetically engineered mouse models, a complete understanding of the oncogenic potential of chromatin modifiers’ mutations found in human medulloblastomas is still elusive. In this study, we address this by CRISPR-mediated gene editing platform to knock out chromatin modifiers mutated human in SHH-subgroup medulloblastoma as well as the Ptch1 gene in cerebellar granule neuron progenitors. We functionally screened molecules involved tumor formation, identifying CHD7 and KMT2C as tumor suppressor genes. Multi-layered omics analysis revealed that these molecules epigenetically regulate the expression of Neurod1 that encodes a transcription factor crucial for neuronal differentiation, through histone H3 modification. Mutations impairing these factors suppress Neurod1, accelerating tumor growth. Conversely, forced expression of Neurod1 inhibits proliferation and promotes differentiation, underscoring its role as a key regulator in medulloblastoma aggressiveness. These findings not only demonstrate converging epigenomic abnormalities in SHH-subgroup medulloblastoma but also hold significant potential for evaluating epigenetic drugs targeting medulloblastoma, advancing the development of novel treatments.
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 GSE293000_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1242324 and SRA study SRP573322. Searching any of these in the dataset finder brings you back here.

Samples in this study

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