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All -trans retinoic acid suppresses CD8+ T cell terminal exhaustion which enhances anti–PD-1 efficacy against glioblastoma [RNA-Seq]

GSE320177 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2026/05/21 Platform GPL24247
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: 3 × OT-I, CTRL, exhaustion, vs 3 × OT-I, ATRA, exhaustion, vs 3 × OT-I, CTRL, exhaustion_stim, vs 3 × OT-I, ATRA, exhaustion_stim,Groups 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.
Summary (written by the submitters)
Terminal exhaustion of CD8⁺ T cells limits the efficacy of immune checkpoint blockade (ICB), particularly in glioblastoma, which is characterized by an immunosuppressive tumor microenvironment. Therefore, better understanding of the regulators of terminal exhaustion could overcome intrinsic resistance to ICB and thereby improve the efficacy of immunotherapy.
Read the full summary ↓
In this study, we find that all-trans retinoic acid (ATRA) suppresses CD8⁺ T cell terminal exhaustion. Administration of ATRA during CD8⁺ T cell activation in vitro conferred resistance to terminal exhaustion and preserved effector cytokine production and effector function. Mechanistically, ATRA selectively induced the expression of the long isoform of T cell factor 1 (TCF-1βBD), through activation of the canonical WNT/β-catenin pathway. In a mouse glioma model, adoptively transferred ATRA-conditioned CD8⁺ T cells exhibited exhaustion resistance, which led to superior tumor-infiltrating CD8+ T cell polyfunctionality and enhanced glioma suppression. Oral administration of ATRA also suppressed terminal exhaustion of tumor-infiltrating CD8+ T cells and synergized with anti-PD-1 therapy, overcoming resistance in mouse models of glioma. Synergistic ATRA administration and anti-PD-1 treatment displayed significant therapeutic potential in mouse recurrent glioma model. Single-cell transcriptomic analysis of glioblastoma patients receiving anti-PD-1 therapy revealed that CD8⁺ T cells from responders were enriched for retinoic acid responsive and WNT-associated gene signatures, which correlated with improved survival. These findings establish ATRA as a modulator of CD8⁺ T cell exhaustion by inducing WNT/β-catenin dependent TCF-1βBD expression. This pathway offers therapeutic potential to overcome resistance to ICB in glioma.
This dataset
Open GSE320177 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 GSE320177_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 PRJNA1427090 and SRA study SRP678705. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × OT-I, CTRL, exhaustion, vs 3 × OT-I, ATRA, exhaustion, vs 3 × OT-I, CTRL, exhaustion_stim, vs 3 × OT-I, ATRA, exhaustion_stim,

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
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