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Esomeprazole Inhibits Proliferation of Scleroderma Fibroblasts via Cell Cycle Regulation

GSE314222 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2025/12/17 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 10 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
10 samples: 10 samples, each with a distinct title — no replicated groupsGroups 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
Esomeprazole inhibits proliferation of scleroderma fibroblasts via cell cycle regulationFrontiers in pharmacology · 2025
Summary (written by the submitters)
Scleroderma is a complex autoimmune disease characterized by abnormal fibroblast proliferation and excessive collagen deposits in the skin and internal organs. We previously showed that esomeprazole, an FDA-approved drug for gastric disorders, may prevent dermal fibrosis. Here, we demonstrate that esomeprazole exerts anti-proliferative effects on scleroderma fibroblasts by interfering with cell cycle regulation.
Read the full summary ↓
To test this, we evaluated the antiproliferative effect of esomeprazole and the underlying molecular mechanisms using primary fibroblasts derived from patients with scleroderma. BrdU incorporation, flow cytometry, immunofluorescence, Western blot analysis, RNA sequencing, and functional enrichment analysis all showed a decrease in fibroblast proliferation. In addition, esomeprazole inhibited the proliferation of scleroderma fibroblasts in a dose-dependent manner, as measured by the Ki-67 marker. Intriguingly, esomeprazole arrested fibroblasts in the G1 phase of the cell cycle, resulting in a reduction of cells in the S phase. Expression of p21, a known inhibitor of cyclin-dependent kinases (CDKs), was elevated, while CDK1 and CDK2 levels decreased following esomeprazole treatment. These data provide important insights into how esomeprazole regulates fibroblast proliferation in scleroderma and suggest that it may represent a potential therapeutic intervention for scleroderma.
Published in
Esomeprazole inhibits proliferation of scleroderma fibroblasts via cell cycle regulation
Khan MA, Koniyan S, Ahir M et al. · Frontiers in pharmacology 2025 · PMID 41567630 · doi:10.3389/fphar.2025.1703115
This dataset
Open GSE314222 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 GSE314222_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 PRJNA1390281 and SRA study SRP656176. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41567630) ↗
Study design
10 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 10 sample titles: 10 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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