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Trajectory analysis reveals an uncommitted neuroblastic state in MYCN-driven neuroblastoma development

GSE247665 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2025/07/02 Platform GPL17021
At a glance

Single-cell RNA-seq · mouse · 12 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
12 samples: 10 × 3-week-old Th-MYCN+/-_biolGroups 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
Trajectory analysis reveals an uncommitted neuroblastic state in MYCN-driven neuroblastoma developmentNeuro-oncology · 2025
Summary (written by the submitters)
We analyzed the transcriptomic features of spontaneous regression in pre-cancerous neuroblasts using Th-MYCN mice, an animal model that closely resembles human neuroblastoma. Single-cell transcriptomic analysis of ganglion tissues from Th-MYCN mice was conducted to elucidate the cellular and molecular underpinnings. Trajectory analysis of pre-cancerous neuroblasts revealed a distinct subtype we designated as "uncommitted" cells, characterized by the expression of neuronal genes, indicative of a semi-differentiated state.
Read the full summary ↓
Samples with predicted failed tumorigenesis had a greater proportion of these uncommitted cells, hinting at their association with spontaneous regression.
Published in
Trajectory analysis reveals an uncommitted neuroblastic state in MYCN-driven neuroblastoma development
Tsubota S, Carter DR, Seneviratne JA et al. · Neuro-oncology 2025 · PMID 40580553 · doi:10.1093/neuonc/noaf129
This dataset
Open GSE247665 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 GSE247665_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 PRJNA1040130 and SRA study SRP471720. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40580553) ↗
Study design
10 × 3-week-old Th-MYCN+/-_biol

Supports a between-group comparison across 10 samples.

How we read this: 1 replicated groups read from 12 sample titles; they account for 10 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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