GEO series

The Multi-Layered Transcriptional Architecture of Glioblastoma Ecosystems [10X]

GSE274546 Homo sapiens (human) Single-nucleus RNA-seq 121 samples Submitted 2025/01/01 Platform GPL24676

At a glance

Single-nucleus RNA-seq · human · 121 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). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Topic: GlioblastomaThis series is part of our curated briefing on it.
Samples: 121 samples: 121 samples, each with a distinct title — no replicated groupsGroups 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: Deciphering the longitudinal trajectories of glioblastoma ecosystems by integrative single-cell genomicsNature genetics · 2025

Summary (written by the submitters)

To comprehensively define the cellular heterogeneity of glioblastoma (GBM), the GBM CARE (Cellular Analysis of Resistance and Evolution) consortium set out to profile 121 GBMs with extensive clinical annotation, by single-nucleus RNA-sequencing and bulk tumor DNA sequencing. The resulting dataset enabled us to characterize GBM heterogeneity at three levels.

Read the full summary ↓

First, GBMs are classified by their cellular composition, encompassing malignant, immune, neuronal and glial cell types. Second, within each cell type, and particularly among the malignant cells, we describe the diversity of cellular states and their pathway-based functional activities. Third, after controlling for the frequencies of cellular states, we find that the remaining variation between GBMs highlights three baseline gene expression programs which we labeled Neuronal, Glial, and Extracellular Matrix. These three layers of heterogeneity are inter-related and partially associated with specific genetic aberrations, thereby defining three stereotypic ecosystems in GBM. This work provides an unparalleled view of the multi-layered transcriptional architecture of GBM.

Published in

Deciphering the longitudinal trajectories of glioblastoma ecosystems by integrative single-cell genomics

Spitzer A, Johnson KC, Nomura M et al. · Nature genetics 2025 · PMID 40346362 · doi:10.1038/s41588-025-02168-4

This dataset

Open GSE274546 in finder → Find more human RNA-seq datasets → Glioblastoma 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 GSE274546_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 PRJNA1147185. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40346362) ↗

Study design

121 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 121 sample titles: 121 distinct titles with little repetition. 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

GSM8452584 Patient 1, Timepoint 1, Chromium gene expression
GSM8452585 Patient 1, Timepoint 2, Chromium gene expression
GSM8452586 Patient 2, Timepoint 1, Chromium gene expression
GSM8452587 Patient 2, Timepoint 2, Chromium gene expression
GSM8452588 Patient 3, Timepoint 1, Chromium gene expression
GSM8452589 Patient 3, Timepoint 2, Chromium gene expression
GSM8452590 Patient 4, Timepoint 1, Chromium gene expression
GSM8452591 Patient 4, Timepoint 2, Chromium gene expression
GSM8452592 Patient 5, Timepoint 1, Chromium gene expression
GSM8452593 Patient 5, Timepoint 2, Chromium gene expression
GSM8452594 Patient 6, Timepoint 1, Chromium gene expression
GSM8452595 Patient 6, Timepoint 2, Chromium gene expression
GSM8452596 Patient 8, Timepoint 1, Chromium gene expression
GSM8452597 Patient 8, Timepoint 2, Chromium gene expression
GSM8452598 Patient 9, Timepoint 1, Chromium gene expression
GSM8452599 Patient 9, Timepoint 2, Chromium gene expression
GSM8452600 Patient 20, Timepoint 1, Chromium gene expression
GSM8452601 Patient 20, Timepoint 2, Chromium gene expression
GSM8452602 Patient 20, Timepoint 3, Chromium gene expression
GSM8452603 Patient 21, Timepoint 1, Chromium gene expression
GSM8452604 Patient 21, Timepoint 2, Chromium gene expression
GSM8452605 Patient 22, Timepoint 1, Chromium gene expression
GSM8452606 Patient 22, Timepoint 2, Chromium gene expression
GSM8452607 Patient 23, Timepoint 1, Chromium gene expression
GSM8452608 Patient 23, Timepoint 2, Chromium gene expression
GSM8452609 Patient 24, Timepoint 1, Chromium gene expression
GSM8452610 Patient 24, Timepoint 2, Chromium gene expression
GSM8452611 Patient 25, Timepoint 1, Chromium gene expression
GSM8452612 Patient 25, Timepoint 2, Chromium gene expression
GSM8452613 Patient 26, Timepoint 1, Chromium gene expression
GSM8452614 Patient 26, Timepoint 2, Chromium gene expression
GSM8452615 Patient 27, Timepoint 1, Chromium gene expression
GSM8452616 Patient 27, Timepoint 2, Chromium gene expression
GSM8452617 Patient 28, Timepoint 1, Chromium gene expression
GSM8452618 Patient 28, Timepoint 2, Chromium gene expression
GSM8452619 Patient 29, Timepoint 1, Chromium gene expression
GSM8452620 Patient 29, Timepoint 2, Chromium gene expression
GSM8452621 Patient 30, Timepoint 1, Chromium gene expression
GSM8452622 Patient 30, Timepoint 2, Chromium gene expression
GSM8452623 Patient 31, Timepoint 1, Chromium gene expression

+ 81 more — browse all 121 samples with per-sample file links →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.