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Astrocyte-driven suppression of tumor-specific T-cell immunity in glioblastoma

GSE246293 Homo sapiens (human) Single-cell RNA-seq 102 samples Submitted 2025/05/21 Platform GPL20795Platform GPL21273Platform GPL24247
At a glance

Single-cell RNA-seq · human · 102 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
Homo sapiens (human)
Topic
GlioblastomaThis series is part of our curated briefing on it.
Samples
102 samples: 92 distinct titles, 2 of them repeatedGroups 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
Glioblastoma-instructed astrocytes suppress tumour-specific T cell immunityNature · 2025
Summary (written by the submitters)
Glioblastoma (GBM) is the most common and aggressive brain cancer, showing minimal response to available therapies. A highly immunosuppressive tumor microenvironment (TME) contributes to the limited therapeutic response of GBM. Astrocytes are major components of the central nervous system (CNS), with important immunoregulatory roles. However, little is known about the role of astrocytes and their subsets in the immune response to GBM.
Read the full summary ↓
Using single-cell and bulk RNA sequencing in GBM clinical samples and mouse pre-clinical models, in combination with multiplexed immunofluorescence microscopy, in vivo CRISPR-based cell-specific genetic perturbations, and in vitro mouse and human experimental systems we identified an astrocyte subset that limits tumor-specific immunity by inducing CD8+ and CD4+ T-cell apoptosis via the death receptor ligand TRAIL. Moreover, we identified IL-11 produced by tumor cells as a driver of STAT3-dependent TRAIL expression in GBM-associated astrocytes. pSTAT3+ TRAIL+ astrocytes were co-localized with apoptotic T cells in human GBM samples and were associated with a shorter time to recurrence and overall decreased survival in GBM patients. Conversely, genetic inactivation of the IL-11 receptor or TRAIL in astrocytes extended survival in GBM mouse models and boosted tumor-specific T cells and tumor-associated macrophage responses. Finally, a GBM-targeting oncolytic HSV-1 virus engineered to express a TRAIL-blocking single-chain antibody in the TME extended survival and boosted tumor-specific immunity in GBM pre-clinical models. In summary, we established that IL-11/STAT3-driven astrocytes suppress GBM-specific protective immunity by inducing TRAIL-dependent T-cell apoptosis, and we developed engineered therapeutic viruses to target this novel mechanism of astrocyte-driven tumor immunoevasion.
Published in
Glioblastoma-instructed astrocytes suppress tumour-specific T cell immunity
Faust Akl C, Andersen BM, Li Z et al. · Nature 2025 · PMID 40399681 · doi:10.1038/s41586-025-08997-x
This dataset
Open GSE246293 in finder → Find more 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 GSE246293_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 PRJNA1032462 and SRA study SRP468554. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40399681) ↗
Study design
92 distinct titles, 2 of them repeated
Tumo ×6 Non-Tumo ×6

How we read this: Read from 102 sample titles: 92 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

+ 62 more — browse all 102 samples with per-sample file links →

More Glioblastoma datasets

Search all RNA-seq datasets in GEO →

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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.