← BioTransfer GEO Dataset Finder
GEO series

TET3 Promotes Tumor Immune Evasion Through Negative Regulation of Type I Interferon Signaling [RNA-Seq]

GSE300460 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2026/06/26 Platform GPL24676Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 20 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
20 samples: 10 conditions, mostly in duplicateGroups 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)
The Ten-eleven translocation (TET) family genes, which encode 5-methylcytosine (5mC) dioxygenases, have been described as tumor suppressors or oncogenes in various cancers. However, the functional role of TET3 in cancer immunity and the underlying molecular mechanisms remain incompletely understood. Here, we reported that TET3 restrains the innate immune response in MCF7 and B16F10 cells.
Read the full summary ↓
Mechanistically, TET3 does not influence the generation of endogenous dsRNA but represses the expression of major dsRNA sensor genes (i.e., MDA5 and RIG-I) as well as the activation of JAK-STAT1 pathway. Importantly, depletion of Tet3 in B16F10 melanoma cells significantly curbed the synergistic tumor growth, accompanied with increased proportion of tumor-infiltrating CD4+ T cells, CD8+ T cells and dendritic cells. Analysis of the TCGA data also revealed elevated expression of TET3 in most types of cancer. Notably, elevated TET3 expression levels were inversely associated with overall survival rate and exhibited a negative correlation with tumor-infiltrating cytotoxic CD8+ T cells. Taken together, our findings identify TET3 as a negative regulator of type I interferon signaling, suggesting that TET3 may be a new target of anti-tumor immunity and immunotherapy.
This dataset
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.

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 GSE300460_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1281004 and SRA study SRP594078. Searching any of these in the dataset finder brings you back here.

Study design
10 conditions, mostly in duplicate
MCF7_WT_mRNAseq ×2 MCF7_TET3KO_mRNAseq ×2 MCF7_shscramble_mRNAseq ×2 MCF7_shTET3-1_mRNAseq ×2 MCF7_shTET3-2_mRNAseq ×2 B16F10_WT_mRNAseq ×2 B16F10_Tet3KO_mRNAseq ×2 B16F10_siNC_RiboZero ×2 +2 more

Supports a between-group comparison across 20 samples.

How we read this: 10 replicated groups read from 20 sample titles; they account for 20 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

Search all RNA-seq datasets in GEO →

Share this dataset

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.