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Single-cell multi-omics analysis identifies metabolism-linked epigenetic reprogramming as a driver of therapy-resistant medulloblastoma [Multiome]

GSE283619 Homo sapiens (human) Single-cell RNA-seq 30 samples Submitted 2025/09/01 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 30 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
30 samples: 6 conditions, mostly with about 4 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
Single-cell multi-omics identifies metabolism-linked epigenetic reprogramming as a driver of therapy-resistant medulloblastomaNature communications · 2025
Summary (written by the submitters)
We perform scMultiomic sequencing on matched patient primary and recurrent tumors. We identify a unique population of cells that is metabolically and epigenetically altered. We recapitulate this population of cells in in vivo radiation resistant models. Disruption of this population with wtIDH1 inhibitors suppresses growth and re-sensitizes cells to irradiation.
Published in
Single-cell multi-omics identifies metabolism-linked epigenetic reprogramming as a driver of therapy-resistant medulloblastoma
Veo B, Wang D, DeSisto J et al. · Nature communications 2025 · PMID 41290646 · doi:10.1038/s41467-025-65466-9
This dataset
Open GSE283619 in finder → Find more human 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 GSE283619_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: 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 PRJNA1194622 and SRA study SRP549663. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41290646) ↗
Study design
6 conditions, mostly with about 4 replicates each
Vibhakar_1520 ×4 Vibhakar_1520_two ×4 Vibhakar_655 ×4 Vibhakar_655_two ×4 1_1433_ATAC ×4 2_1433X_ATAC ×4 Vibhakar_1520_GEX ×1 Vibhakar_1520_two_GEX ×1 +4 more

Supports a between-group comparison across 24 samples.

How we read this: 6 replicated groups read from 30 sample titles; they account for 24 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
Datasets on a similar topic

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