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Hydroxychloroquine Alleviates Cyclophosphamide-Induced Premature Ovarian Failure by Attenuating Granulosa Cell Senescence and Modulating the mtDNA-cGAS Pathway

GSE320421 Mus musculus (mouse) RNA-seq (gene expression) 9 samples Submitted 2026/05/15 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 9 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
9 samples: 3 × Control mouse granulosa cells, vs 3 × CTX mouse granulosa cells, vs 3 × CTX+HCQ mouse granulosa cells,Groups 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
Hydroxychloroquine alleviates cyclophosphamide-induced premature ovarian failure by attenuating granulosa cell senescence and modulating the mtDNA-cGAS pathwaynpj aging · 2026
Summary (written by the submitters)
Cyclophosphamide (CTX) is a first-line chemotherapeutic agent for various cancers but is associated with a significant risk of ovarian dysfunction, which may even progress to premature ovarian failure (POF). Granulosa cell senescence is a key phenotypic manifestation of this process. Hydroxychloroquine (HCQ) exerts anti-senescence effects in age-related diseases; however, its efficacy in preventing CTX-induced ovarian damage remains elusive. We aimed to verify the protective effect of HCQ using a CTX-induced POF mouse model.
Published in
Hydroxychloroquine alleviates cyclophosphamide-induced premature ovarian failure by attenuating granulosa cell senescence and modulating the mtDNA-cGAS pathway
Su D, Ma R, Su H et al. · npj aging 2026 · PMID 41839900 · doi:10.1038/s41514-026-00359-9
This dataset
Open GSE320421 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 GSE320421_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 PRJNA1428170 and SRA study SRP679226. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41839900) ↗
Study design
3 × Control mouse granulosa cells, vs 3 × CTX mouse granulosa cells, vs 3 × CTX+HCQ mouse granulosa cells,

Supports a between-group comparison across 9 samples.

How we read this: 3 replicated groups read from 9 sample titles; they account for 9 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 mouse RNA-seq datasets in GEO →

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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.