GEO series

Single nucleus transcriptomics of spinal ependymoma subtypes recognizes intratumoral heterogeneity [snRNA-seq]

GSE298501 Homo sapiens (human) Single-nucleus RNA-seq 14 samples Submitted 2025/09/12 Platform GPL24676Platform GPL30173

At a glance

Single-nucleus RNA-seq · human · 14 samples

What it is: Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
Organism: Homo sapiens (human)
Samples: 14 samples: 8 × BAM file of sample MPE-A vs 2 × BAM file of sample SP-EPN-BGroups 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-nucleus transcriptomics of spinal ependymoma subtypes recognizes intratumoral heterogeneityNeuro-oncology · 2026

Summary (written by the submitters)

The two most prevalent types of spinal ependymal tumors are myxopapillary ependymomas (MPE) and spinal ependymomas (SP-EPN). Based on molecular data from bulk tumor samples, we previously identified clinically relevant subtypes with poor (MPE-A; SP-EPN-A) and favorable progression-free survival (MPE-B; SP-EPN-B). However, detailed cellular compositions, molecular heterogeneity, and features of tumor progression are largely unknown.

Read the full summary ↓

We performed single nucleus transcriptomic sequencing of 25 formalin-fixed and paraffin-embedded spinal ependymal tumors including all MPE and SP-EPN subtypes as well as six paired primary and relapsed MPE-A. Ependymoma subtypes presented with a broad, but comparable tumor microenvironment. Furthermore, neoplastic cells demonstrated inter- and intratumoral heterogeneity regarding cancer cell state composition. Overall, MPE tumors exhibited a significantly higher abundance of the astrocytic state, whereas a ciliated state was more prevalent in SP-EPN. Also, transcriptome-inferred copy number profiles revealed tumor cell clusters with distinct chromosomal alterations across tumors, suggesting subclonal neoplastic growth. Compared to normal human spinal cord cell populations, MPE tumor cells displayed similarities to astrocytes and ependymal cells, whereas SP-EPN exclusively matched ependymal cells. MPE-A demonstrated a distinct profile, being similar to the roof and floor plate of the developing spinal cord. Paired primary and relapsed MPE-A revealed mostly similar histology, epigenetics, copy number profiles, and cellular composition of neoplastic cells. Single nucleus transcriptomic sequencing provides valuable insights into the molecular composition of spinal ependymoma types and subtypes and may pave the way for a better understanding of tumor evolution and identification of therapeutic targets.

Published in

Single-nucleus transcriptomics of spinal ependymoma subtypes recognizes intratumoral heterogeneity

Hack K, Jauch-Speer SL, Kresbach C et al. · Neuro-oncology 2026 · PMID 41273179 · doi:10.1093/neuonc/noaf210

This dataset

Open GSE298501 in finder → Find more human 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 GSE298501_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 PRJNA1269562 and SRA study SRP588618. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41273179) ↗

Study design

8 × BAM file of sample MPE-A vs 2 × BAM file of sample SP-EPN-B

Supports a between-group comparison across 10 samples.

How we read this: 2 replicated groups read from 14 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

GSM9015499 Pooled library of MPE-A 1 (BC-001), MPE-A 2 (BC-002), MPE-B 1 (BC-003) and MPE-B 2 (BC-004)
GSM9015500 Pooled library of MPE-A 3 (BC-001), MPE-B 3 (BC-002), SP-EPN-A 1 (BC-003), and SP-EPN-A 2 (BC-004)
GSM9015501 Pooled library of SP-EPN-A 3 (BC-001), SP-EPN-A 4 (BC-002), SP-EPN-B 1 (BC-003), and SP-EPN-B 2 (BC-004)
GSM9015502 Pooled library of MPE-A 8 (BC-001), MPE-A 9 (BC-002), MPE-A 10 (BC-003), and MPE-A 11 (BC-004)
GSM9015503 BAM file of sample SP-EPN-B 3 BAM file of sample SP-E…
GSM9015504 BAM file of sample SP-EPN-B 4 BAM file of sample SP-E…
GSM9015505 BAM file of sample MPE-A 4 BAM file of sample MPE-A
GSM9015506 BAM file of sample MPE-A 5 BAM file of sample MPE-A
GSM9015507 BAM file of sample MPE-A 6 BAM file of sample MPE-A
GSM9015508 BAM file of sample MPE-A 7 BAM file of sample MPE-A
GSM9015509 BAM file of sample MPE-A 12 BAM file of sample MPE-A
GSM9015510 BAM file of sample MPE-A 13 BAM file of sample MPE-A
GSM9015511 BAM file of sample MPE-A 14 BAM file of sample MPE-A
GSM9015512 BAM file of sample MPE-A 15 BAM file of sample MPE-A

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