← BioTransfer GEO Dataset Finder
GEO series

Integrative metaprogram analysis reveals transcriptional dysregulation of oxidative stress response in granulosa cells from polycystic ovary syndrome

GSE293353 Homo sapiens (human) Single-cell RNA-seq 18 samples Submitted 2025/04/05 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 18 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
18 samples: 9 × Follicular granulosa cells, PCOS vs 9 × Follicular granulosa cells, ControlGroups 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
Integrative metaprogram analysis reveals transcriptional dysregulation of oxidative stress response in granulosa cells from polycystic ovary syndromeJournal of ovarian research · 2025
Summary (written by the submitters)
Objective: The molecular mechanisms underlying polycystic ovary syndrome (PCOS) pathogenesis were investigated using an integrative metaprogram analysis framework, with specific focus on oxidative stress-related pathways through combined single-cell and bulk RNA sequencing approaches. Methods: Three datasets were integrated: a single-cell RNA-seq dataset (GSE240688), a laboratory-generated bulk RNA-seq dataset, and a validation microarray dataset (GSE34526).
Read the full summary ↓
Transcriptional programs in granulosa cells were identified by non-negative matrix factorization, while dysregulated genes were characterized by differential expression and weighted gene co-expression network analyses. An integrative multi-omics approach was employed to identify key regulatory genes at the intersection of these complementary analytical methods. Results: Ten distinct transcriptional metaprograms in granulosa cells were identified, with metaprogram 4 (MP4) significantly enriched in PCOS samples and associated with oxidative stress response pathways. 199 consistently dysregulated genes across independent patient cohorts were revealed by differential expression analysis. Through integrative analysis, glutathione peroxidase 3 (GPX3) was identified as the only gene present across all three analytical approaches. GPX3 was significantly upregulated in PCOS samples with robust discriminatory power (AUC>0.8) and was functionally associated with insulin signaling, glucose metabolism, and mitochondrial pathways, suggesting its role in connecting oxidative stress and metabolic dysfunction. Conclusions: Oxidative stress responses were revealed as central to PCOS pathophysiology by our comprehensive multi-omics approach, with GPX3 identified as a key regulatory node connecting metabolic and reproductive dysfunction. A molecular basis for the oxidative stress-mediated pathology in PCOS is established by these findings.
Published in
Integrative metaprogram analysis reveals transcriptional dysregulation of oxidative stress response in granulosa cells from polycystic ovary syndrome
Li Y, Li L, Zheng H et al. · Journal of ovarian research 2025 · PMID 41146316 · doi:10.1186/s13048-025-01811-2
This dataset
Open GSE293353 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 GSE293353_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1243573 and SRA study SRP574358. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41146316) ↗
Study design
9 × Follicular granulosa cells, PCOS vs 9 × Follicular granulosa cells, Control

Supports a between-group comparison across 18 samples.

How we read this: 2 replicated groups read from 18 sample titles; they account for 18 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

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.