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IL-17 links the tumor suppressor LKB1 to gastrointestinal inflammation and polyposis

GSE266416 Mus musculus (mouse) RNA-seq (gene expression) 33 samples Submitted 2025/04/28 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 33 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
33 samples: 5 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)
Loss-of-function mutations in the tumor suppressor liver kinase B1 (LKB1) promote the development of Peutz-Jeghers Syndrome (PJS), a chronic disease characterized by the development of gastrointestinal (GI) polyps. Treatment options for patients are extremely limited due to a poor understanding of how LKB1 mutations lead to the development of GI polyps.
Read the full summary ↓
Here, we reveal a role for CREB-regulated transcription coactivator 2 (CRTC2) signaling in the regulation of inflammatory potential in LKB1 mutant T cells. We also demonstrate that targeting CRTC2 and pathogenic T helper 17 (Th17) cells reduces GI polyp growth in LKB1 mutant mice. Our data reveal a critical role for CRTC2 in LKB1-mediated T cell inflammatory responses that we hypothesize predisposes PJS patients harboring LKB1 mutations to GI polyp development.
This dataset
Open GSE266416 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 GSE266416_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 PRJNA1107138 and SRA study SRP505417. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 conditions, mostly in triplicate
Stomach, Lkb1+/+, ×12 Polyp, Lkb1+/-, ×12 Th17, Lkb1+/-, ctrl, ×3 Th17, Lkb1+/-/Crtc2-/-, ctrl, ×3 Th17, Lkb1+/-, A485, ×3

Supports a between-group comparison across 33 samples.

How we read this: 5 replicated groups read from 33 sample titles; they account for 33 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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