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TNFR2 loss prevents TOX upregulation in CD8+TIM3+ T cells and affords improved responses to tumor and chronic LCMV

GSE297330 Mus musculus (mouse) RNA-seq (gene expression) 19 samples Submitted 2025/05/19 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 19 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
19 samples: 10 × TNFR2_WT vs 9 × TNFR2_MUTGroups 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)
Preview PDF Abstract Exhaustion represents a collection of programmed T cell differentiation states and an important mode of T cell dysfunction. T cell progression from progenitor to terminal exhaustion is associated with upregulation of the transcription factor TOX and expression of TIM3. Our understanding of factors regulating TOX expression and the transition from progenitor to terminal exhaustion, however, remains incomplete.
Read the full summary ↓
We reveal here that T cell upregulation of tumor necrosis factor receptor type II (TNFR2) coincides with the gain of phenotypic markers and functions reflective of terminal exhaustion. Meanwhile, knocking out TNFR2 affords a novel population of T cells that express TIM3 but possess diminished TOX levels and functional characteristics of both progenitor and terminally exhausted cells. TIM3+ TNFR2 KO T cells exhibit reduced exhaustion transcriptional programs and enhanced AP1 pathway signatures. Finally, TNFR2 KO mice demonstrate improved T cell-dependent control of tumor and chronic lymphocytic choriomeningitis viral (cLCMV) infection, while pharmacologic antagonism of TNFR2 licenses responses to checkpoint blockade in multiple tumor models.
This dataset
Open GSE297330 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 GSE297330_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1263524 and SRA study SRP585641. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
10 × TNFR2_WT vs 9 × TNFR2_MUT

Supports a between-group comparison across 19 samples.

How we read this: 2 replicated groups read from 19 sample titles; they account for 19 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
Datasets on a similar topic

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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.