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Inhibition of oogenic JNK prevents primary ovarian insufficiency and infertility induced by DNA-damaging anti-cancer agents

GSE314244 Mus musculus (mouse) RNA-seq (gene expression) 61 samples Submitted 2026/04/28 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 61 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
61 samples: 61 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.
Summary (written by the submitters)
Primary ovarian insufficiency (POI) and related infertility, early menopause, and endocrine disorders are major side effects in young female cancer patients undergoing cancer treatment. Current strategies preserving ovarian functions and fertility can be suboptimal due to concerns of feasibility, efficacy, or safety. Herein, we identify c-Jun N-terminal kinase (JNK) as a pivotal factor regulating the DNA damage response (DDR) signaling in oocytes of primordial follicles in response to DNA-damaging chemotherapy.
Read the full summary ↓
Using pharmacological inhibition of JNK and a mouse model with oocyte-specific deletion of JNK, together with bioinformatic, molecular, and computational approaches, we show that inhibition of oogenic JNK prevents chemotherapy-induced oocyte apoptosis and POI as well as preserve long-term reproductive cycles and fertility. Mechanistically, JNK is activated upon chemotherapy-induced DNA damage in oocytes of primordial follicles, which further activates the transcription factor TAp63α and triggers oocyte apoptosis. we further used a breast cancer mouse model to demonstrate that JNK inhibition preserves the ovarian reserve without interfering with the anti-cancer efficacy of chemotherapy. Together, our research establishes JNK as a crucial determinant of oocyte apoptosis and POI following DNA-damaging cancer therapy, highlighting JNK as a promising target for developing ovarian protectant and preserving the ovarian reserve, fertility, and ovarian endocrine functions in young female cancer patients.
This dataset
Open GSE314244 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 GSE314244_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 PRJNA1390593 and SRA study SRP656322. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
61 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 61 sample titles: 61 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

+ 21 more — browse all 61 samples with per-sample file links →

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.