GEO series

Human single cell RNA-sequencing reveals a targetable CD8+ exhausted T cell population that maintains murine low-grade glioma growth

GSE244433 Mus musculus (mouse) Single-cell RNA-seq 16 samples Submitted 2024/10/23 Platform GPL24247Platform GPL24676

At a glance

Single-cell RNA-seq · mouse · 16 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Topic: Lower-grade gliomaThis series is part of our curated briefing on it.
Samples: 16 samples
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: Human single cell RNA-sequencing reveals a targetable CD8(+) exhausted T cell population that maintains mouse low-grade glioma growthNature communications · 2024

Summary (written by the submitters)

Immune cell infiltration is a common feature of solid cancers, where T cells typically function as cytotoxic effectors to limit tumor growth, prompting therapies that activate this antineoplastic property (immune checkpoint inhibition; ICI). Unfortunately, ICI treatments have been largely ineffective for high-grade brain tumors (gliomas; HGGs).

Read the full summary ↓

Leveraging several single-cell RNA sequencing datasets, we report greater CD8+ exhausted T cells in human pediatric low-grade gliomas (LGGs) relative to adult and pediatric HGGs. Using several preclinical mouse LGG models (Nf1-OPG mice), we showed that these PD1+/TIGIT+ CD8+ terminally exhausted T cells are restricted to the tumor tissue, where they express paracrine factors necessary for OPG growth. Importantly, ICI treatments with anti-PD1 and anti-TIGIT antibodies attenuate Nf1-OPG tumor proliferation through suppression of cytokine-mediated immune axis support, rather than by T cell-mediated cytotoxicity. Collectively, these findings establish a previously unrecognized function for CD8+ exhausted T cells as specialized regulators of LGG maintenance.

Published in

Human single cell RNA-sequencing reveals a targetable CD8(+) exhausted T cell population that maintains mouse low-grade glioma growth

Barakat R, Chatterjee J, Mu R et al. · Nature communications 2024 · PMID 39609412 · doi:10.1038/s41467-024-54569-4

This dataset

Open GSE244433 in finder → Find more RNA-seq datasets → Lower-grade glioma 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 GSE244433_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 PRJNA1023164 and SRA study SRP464147. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39609412) ↗

Samples in this study

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+ 16 more — browse all 16 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.