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TET2-mutant clonal hematopoiesis prevents T-cell exhaustion and suppresses cancer metastasis [RNA-seq]

GSE327454 Mus musculus (mouse) RNA-seq (gene expression) 19 samples Submitted 2026/04/17 Platform GPL21273
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: 6 conditions, mostly in triplicateGroups 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)
TET2-mutant clonal hematopoiesis (CH) is associated with reduced cancer metastasis in human cohorts. Using mouse models of colorectal cancer liver metastasis, we demonstrate that Tet2-deficient hematopoietic cells suppress metastatic tumor burden by preventing CD8+ T-cell exhaustion. Bulk RNA-seq of sorted CD4+ and CD8+ tumor-infiltrating lymphocytes (TILs) from Vav1CreTet2KO, Cd4CreTet2KO, and Tet2fl/fl control mice was performed to characterize transcriptional changes associated with Tet2 loss in tumor-infiltrating T cells.
This dataset
Open GSE327454 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 GSE327454_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 PRJNA1450958 and SRA study SRP690451. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
Cd4CreTet2KO CD8+ TILs, biol ×4 Tet2fl/fl CD8+ TILs, biol ×3 Tet2fl/fl CD4+ TILs, biol ×3 Vav1CreTet2KO CD8+ TILs, biol ×3 Vav1CreTet2KO CD4+ TILs, biol ×3 Cd4CreTet2KO CD4+ TILs, biol ×3

Supports a between-group comparison across 19 samples.

How we read this: 6 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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