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Role of the TRIF-IFN-I pathway in Helicobacter-induced gastric cancer progression in an accelerated murine disease model

GSE250438 Mus musculus (mouse) RNA-seq (gene expression) 19 samples Submitted 2024/04/17 Platform GPL17021
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: 8 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
TRIF-IFN-I pathway in Helicobacter-induced gastric cancer in an accelerated murine disease model and patient biopsiesiScience · 2024
Summary (written by the submitters)
Background: Helicobacter pylori (H. pylori) infection is a known cause of many digestive diseases, including gastritis, peptic ulcers, and gastric cancer. However, the underlying mechanism(s)by which H. pylori infection triggers these disorders are still not clearly understood. Methods: We have developed an accelerated disease progression mouse model, which leverages mice deficient in the myeloid differentiation primary response 88 gene (Myd88-/-) infected with Helicobacter felis (H.
Read the full summary ↓
felis) Findings: In this study, we found that H. felis-induced inflammation in Myd88-/- mice progressed to high-grade dysplasia, driven by activation of the type I interferon (IFN-I) signaling pathway and upregulation of its downstream targets, IFN-stimulated genes (ISGs). We also observed enrichment of IFN stimulated-response element (ISRE) motifs in the promoters of upregulated genes, further supporting the involvement of this pathway. In contrast, mice deficient in Toll/interleukin-1 receptor (TIR)-domain-containing adaptor inducing interferon-β (TRIF, TrifLps2) did not progress to severe gastric pathology after H. felis infection, implicating the TRIF signaling pathway in disease pathogenesis and progression. Additionally, analysis of gastric biopsy samples from human gastric cancer patients illustrated that low expression of Myd88 and high expression of Trif were both significantly correlated with poor survival. Interpretation: Our study using an accelerated animal model for gastric cancer and gastric biopsy samples from patients demonstrated that activation of the TRIF-IFN-I signaling pathway promotes Helicobacter-induced disease progression toward severe gastric pathology and gastric cancer development. This represents a potential target for therapeutic intervention, and further exploration may lead to the identification of novel treatment strategies.
Published in
TRIF-IFN-I pathway in Helicobacter-induced gastric cancer in an accelerated murine disease model and patient biopsies
Bali P, Lozano-Pope I, Hernandez J et al. · iScience 2024 · PMID 38558931 · doi:10.1016/j.isci.2024.109457
This dataset
Open GSE250438 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 GSE250438_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 PRJNA1054071 and SRA study SRP478608. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38558931) ↗
Study design
8 conditions, mostly in duplicate
inf-BL ×3 inf-DK ×3 inf-LP ×3 ctrl-BL ×2 ctrl-DK ×2 ctrl-LP ×2 ctrl-MD ×2 inf-MD ×2

Supports a between-group comparison across 19 samples.

How we read this: 8 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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