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Dynamic Chromatin Alteration Induces Oncogenic Hijacking by Nuclear Factor I Family Proteins for Medulloblastoma Progression

GSE241602 Mus musculus (mouse) RNA-seq (gene expression) 30 samples Submitted 2024/05/03 Platform GPL24247Platform GPL24676
At a glance

RNA-seq (gene expression) · mouse · 30 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
Mus musculus (mouse)
Topic
MedulloblastomaThis series is part of our curated briefing on it.
Samples
30 samples: 9 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
Cancer-specific epigenome identifies oncogenic hijacking by nuclear factor I family proteins for medulloblastoma progressionDevelopmental cell · 2024
Summary (written by the submitters)
The cancer-specific epigenome is the critical scaffold on which genetic programs work to positively promote cancer growth and progression. Understanding and appropriately disrupting this epigenome will lead to the discovery of new, more extensive and effective therapies in addition to conventional personalized medicine that relies on genomic mutations.
Read the full summary ↓
However, the epigenomic changes during the process from normal cells to cancer formation as well as the molecules involved in the maintenance of the aberrant epigenome are still poorly characterized, and the development of epigenome-based therapeutics is therefore undeniably stagnant. To address this issue, we here focus on SHH-subgroup medulloblastoma, a representative pediatric brain tumor for which we developed a reliable mouse model to capture the epigenomic changes that cerebellar granule cells, the cells of origin, undergo during tumorigenesis. By comparing the epigenomes of the different stages of transforming cells, we identified NFI family of developmental factors as oncogenic regulators in the epigenome of pre-cancerous and cancerous cells, which they also contribute to maintain. Furthermore, we report pharmacological experiments demonstrating that inhibition of NFIB methylation blocks tumor growth and increases sensitivity to molecularly targeted drugs by disrupting the cancer epigenome. Thus, this study is a unique example of how epigenomic studies of cancer have led directly to therapeutic insights, and similar approaches in various cancers would accelerate the establishment of novel therapies.
Published in
Cancer-specific epigenome identifies oncogenic hijacking by nuclear factor I family proteins for medulloblastoma progression
Shiraishi R, Cancila G, Kumegawa K et al. · Developmental cell 2024 · PMID 38834071 · doi:10.1016/j.devcel.2024.05.013
This dataset
Open GSE241602 in finder → Find more RNA-seq datasets → Medulloblastoma 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 GSE241602_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 PRJNA1008757 and SRA study SRP456820. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38834071) ↗
Study design
9 conditions, mostly in triplicate
PDX12, PDX, NC, biol ×4 PDX12, PDX, shNFIA, biol ×4 PDX12, PDX, shNFIB, biol ×4 BT084, PDX, NC, biol ×3 BT084, PDX, shNFIA, biol ×3 BT084, PDX, shNFIB, biol ×3 VDR, cell line, NC, biol ×3 VDR, cell line, shNFIA, biol ×3 +1 more

Supports a between-group comparison across 30 samples.

How we read this: 9 replicated groups read from 30 sample titles; they account for 30 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 Medulloblastoma datasets

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