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GFI1-FOXO1 axis regulate NK cell maturation and function [RNA-seq]

GSE278867 Mus musculus (mouse) RNA-seq (gene expression) 74 samples Submitted 2026/03/13 Platform GPL30172Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 74 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
74 samples: 30 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.
Paper
The GFI1-FOXO1 axis regulates NK cell maturation and functionNature communications · 2026
Summary (written by the submitters)
Natural killer cells protect against malignant and virally-infected cells through a tightly regulated differentiation, maturation, and homeostatic program. The signals guiding differentiation of NK cells has not yet been fully elucidated. GFI1 is a transcriptional repressor broadly expressed in bone marrow progenitors and adaptive immune cells and acts to shape differentiation but has not been defined in NK cells.
Read the full summary ↓
We show that GFI1 is differentially expressed across NK cell subsets but is not required for the development of immature (Imm) NK cell. Instead, GFI1 regulates the checkpoints that control the transition from Imm to mature NK stages (M1 and M2). Using multiomics approaches, we show that GFI1 regulates FOXO1 and EOMES signalling in mature NK cells and is critical for NK cell division and maturation. Furthermore, we show that the GFI1-FOXO1 axis is essential for protection against tumor metastasis through NK cell activation and effector functions, highlighting the important role of GFI1 in innate immune regulation.
Published in
The GFI1-FOXO1 axis regulates NK cell maturation and function
Huang Q, Chaudhry MZ, Dight J et al. · Nature communications 2026 · PMID 42020400 · doi:10.1038/s41467-026-72022-6
This dataset
Open GSE278867 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 GSE278867_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 PRJNA1169327 and SRA study SRP536775. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42020400) ↗
Study design
30 conditions, mostly in duplicate
NCR-cre M2 NK cells, Exp2, ×4 NCR-cre M1 NK cells, Exp2, ×4 NCR-cre Imm NK cells, Exp1, ×3 GF1-KO Imm NK cells, Exp1, ×3 NCR-cre M1 NK cells, Exp1, ×3 GF1-KO M1 NK cells, Exp1, ×3 NCR-cre M2 NK cells, Exp1, ×3 GF1-KO M2 NK cells, Exp1, ×3 +22 more

Supports a between-group comparison across 74 samples.

How we read this: 30 replicated groups read from 74 sample titles; they account for 74 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

+ 34 more — browse all 74 samples with per-sample file links →

Datasets on a similar topic

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