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Germline ELP1 deficiency sensitizes cerebellar granule neuron progenitors to SHH medulloblastoma [bulkRNA]

GSE260623 Mus musculus (mouse) RNA-seq (gene expression) 91 samples Submitted 2025/04/10 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 91 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)
Samples
91 samples: 12 conditions, mostly with about 5 replicates eachGroups 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
Genetic modeling of ELP1-associated Sonic hedgehog medulloblastoma identifies MDM2 as a selective therapeutic targetCancer cell · 2025
Summary (written by the submitters)
Germline loss-of-function (LOF) variants in Elongator complex protein 1 (ELP1) are the most prevalent predisposing genetic events in childhood medulloblastoma (MB), accounting for ~30% of the Sonic Hedgehog (SHH) 3 subtype. The underlying mechanism(s) by which germline ELP1 deficiency provokes SHH-MB pathogenesis remain unknown.
Read the full summary ↓
Genetically engineered mice mimicking heterozygous Elp1 LOF (Elp1HET) seen in affected germline carriers exhibit hallmark features of cancer predisposition in cerebellar granule neuron progenitors (GNPs), including increased DNA replication stress, genomic instability, accelerated cell cycle, and stalled differentiation. Orthotopic transplantation of Elp1HET GNPs harboring somatic Ptch1 inactivation yielded SHH-MB-like tumors with compromised p53 signaling, providing an explanation for the exclusivity of ELP1-associated tumors in SHH-3. Preclinical treatment of ELP1-mutant patient-derived xenografts with an FDA-approved MDM2 inhibitor reactivated p53-dependent apoptosis and extended survival. Our findings functionally substantiate the role of ELP1 deficiency in SHH-MB predisposition and nominate therapeutics that overcome p53 inhibition as a rational treatment option.
Published in
Genetic modeling of ELP1-associated Sonic hedgehog medulloblastoma identifies MDM2 as a selective therapeutic target
Ahmad ST, Li Y, Garcia-Lopez J et al. · Cancer cell 2025 · PMID 40378836 · doi:10.1016/j.ccell.2025.04.014
This dataset
Open GSE260623 in finder → Find more mouse 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 GSE260623_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 PRJNA1082362 and SRA study SRP492679. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40378836) ↗
Study design
12 conditions, mostly with about 5 replicates each
tumor_s ×23 tumor_JH35 ×21 80S_WT ×5 Di-trisome_WT ×5 Polysome_WT ×5 80S_MUT ×5 Di-trisome_MUT ×5 Polysome_MUT ×5 +4 more

Supports a between-group comparison across 91 samples.

How we read this: 12 replicated groups read from 91 sample titles; they account for 91 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

+ 51 more — browse all 91 samples with per-sample file links →

Datasets on a similar topic

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