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Gastric epithelial cells infected with Helicobacter pylori for 24 hours

GSE295523 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2025/04/29 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 24 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
Homo sapiens (human)
Samples
24 samples: 8 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)
Helicobacter pylori (H. pylori) infects nearly half of the global population. H. pylori infection is associated with various gastric diseases and is a recognized causative factor for gastric cancer. The mechanisms underlying the persistent colonization of H. pylori and its role in the development and progression of gastritis-associated carcinogenesis remain unclear.
Read the full summary ↓
To investigate the pathogenic mechanisms of H. pylori infection, we performed RNA sequencing (RNA-seq) on H. pylori-infected gastric epithelial cells and analyzed the gene expression patterns induced by H. pylori infection, aiming to provide critical insights for understanding its disease-driving pathways.
This dataset
Open GSE295523 in finder → Find more human 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 GSE295523_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 PRJNA1255114 and SRA study SRP580995. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in triplicate
HGC27 cells, Control, ×3 HGC27 cells, H. pylori, ×3 AGS cells, Control, ×3 AGS cells, H. pylori, ×3 MKN45 cells, Control, ×3 MKN45 cells, H. pylori, ×3 GES-1 cells, Control, ×3 GES-1 cells, H. pylori, ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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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