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Enhancing Proteasome Activity in T Cells Alleviates Exhaustion and Improves Antitumor Immunity

GSE279430 Homo sapiens (human) Single-cell RNA-seq 12 samples Submitted 2026/02/12 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 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
Homo sapiens (human)
Samples
12 samples: 4 × CD8 T cells, 1 stimultation, vs 4 × CD8 T cells, 4 stimulations normoxia, vs 4 × CD8 T cells, 4 stimulations hypoxia,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.
Paper
Enhancing Proteasome Activity in T Cells Alleviates Exhaustion and Improves Antitumor ImmunityCancer research · 2026
Summary (written by the submitters)
Chronic T cell receptor (TCR) stimulation combined with adverse conditions in the tumor microenvironment (TME), such as hypoxia and nutrient deprivation, frequently results in T cell exhaustion. Exhausted T cells (TEX) experience oxidative stress, which causes an accumulation of oxidized proteins within the cells. We hypothesized that oxidized protein formation might exceed proteasomal degradation capacity, leading to their accumulation and impairing T cell fitness.
Read the full summary ↓
Single-cell transcriptomics analysis across 16 tumor types revealed increased expression of proteasome genes in TEX compared to non-exhausted T cells. In a robust in vitro model for the generation of human TEX, the cells exhibited hallmarks of exhaustion, with higher levels of reactive oxygen species (ROS)-induced protein oxidation and increased expression of proteasome genes. Pharmacological and genetic enhancement of proteasome activity delayed the onset of T cell exhaustion, improved T cell fitness, and translated into superior antitumor immunity and tumor control. These findings identify proteasome modulation as a promising strategy to counteract TME-driven T cell dysfunction, potentially overcoming a major obstacle to the efficacy of cell-based immunotherapies in solid tumors.
Published in
Enhancing Proteasome Activity in T Cells Alleviates Exhaustion and Improves Antitumor Immunity
de Blas A, Andreatta M, Antoñana-Vildosola A et al. · Cancer research 2026 · PMID 41886620 · doi:10.1158/0008-5472.CAN-25-1246
This dataset
Open GSE279430 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 GSE279430_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 PRJNA1172688 and SRA study SRP538471. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41886620) ↗
Study design
4 × CD8 T cells, 1 stimultation, vs 4 × CD8 T cells, 4 stimulations normoxia, vs 4 × CD8 T cells, 4 stimulations hypoxia,

Supports a between-group comparison across 12 samples.

How we read this: 3 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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