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Therapeutic bacteria-trained NK cells confer long-term protection against cancer metastasis

GSE333350 Mus musculus (mouse) RNA-seq (gene expression) 9 samples Submitted 2026/05/28 Platform GPL23479
At a glance

RNA-seq (gene expression) · mouse · 9 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
9 samples: 8 distinct titles, 1 of them repeatedGroups 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)
We report that a single dose of therapeutic Salmonella, a prominent anti-tumor bacterial therapy, provides long-lasting protection against metastasis in mice by inducing trained NK cells. Integrated functional and multi-omics analyses revealed that Salmonella-trained NK (stNK) cells establish an enduring reprogrammed epigenome characterized by enhanced pro-survival signaling and immune effector functions, resulting in more potent IFN-gamma release and cytotoxicity upon secondary stimulation.
Read the full summary ↓
We further showed that this training requires a transient pulse of IL-12 combined with sustained IL-18 signaling. Crucially, stNK cells significantly outperform conventional immune checkpoint therapies, including PD-1 and TIGIT blockade, in preventing metastasis, underscoring the unique immunological mechanisms in combating metastasis.
This dataset
Open GSE333350 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 GSE333350_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 PRJNA1446262 and SRA study SRP702854. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 distinct titles, 1 of them repeated
Immune cells for scRNAseq from lung after PBS… ×2

How we read this: Read from 9 sample titles: 8 distinct titles with little repetition. 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.