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Medroxyprogesterone acetate inhibits tumorigenesis in mouse models of oviductal high-grade serous carcinoma

GSE309487 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2025/12/04 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 20 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
20 samples: 6 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.
Paper
Medroxyprogesterone Acetate Inhibits Tumorigenesis in Mouse Models of Oviductal High-Grade Serous CarcinomaCancers · 2025
Summary (written by the submitters)
Background/Objectives: Tubo-ovarian high-grade serous carcinoma (HGSC) is a highly lethal malignancy, usually diagnosed at an advanced stage due to the lack of early symptoms and biomarkers. Contraceptive hormone use is associated with reduced risk of HGSC, but the relative contributions of natural versus synthetic progestins, and their interaction with estrogens, are poorly characterized.
Read the full summary ↓
Methods: We evaluated the chemopreventive efficacy of a synthetic progestin medroxyprogesterone acetate (MPA), progesterone (P4), and combined 17β-estradiol-progesterone (E2+P4) in a well-characterized genetically engineered mouse model (GEMM) of oviductal HGSC based on conditional inactivation of one or both alleles of the Brca1, Trp53, Rb1, and Nf1 tumor suppressor genes (BPRN-het and BPRN-homo mice, respectively). Mice received hormones or placebo via slow-release pellets implanted subcutaneously, and after induction of tumor formation, mice were monitored for tumor development, progression, and survival. Tumor incidence was assessed histologically, and hormone effects were further explored via RNA-seq analysis of oviductal tissues. Results: MPA significantly reduced HGSC incidence and delayed tumor progression compared to placebo, P4, and P4 + E2, in both BPRN-homo and BPRN-het mice, with up to 78% tumor-free survival in the MPA-treated BPRN-het cohort. P4 monotherapy did not provide significant protection vs. placebo, while the E2+P4 combination accelerated tumorigenesis and reduced survival (p < 0.0001 in BPRN-homo and p = 0.0004 in BPRN-het mice). MPA did not affect tumorigenesis in a colon cancer GEMM, or the growth of mouse HGSC-derived cells in vivo, suggesting a role for MPA in the early stages of HGSC development. Gene expression analyses showed that P4 and MPA downregulated cholesterol homeostasis, early and late estrogen response, and epithelial-mesenchymal transition pathways, though only MPA translated this into substantial tumor protection. Conclusions: These findings demonstrate that a synthetic progestin, specifically MPA, confers robust protection against HGSC development, while P4 is not effective and a combination including E2 increases risk. This work also illustrates how HGSC GEMMs can be used to compare the chemopreventive effects of various synthetic progestins on HGSC development in order to prioritize the most effective ones for use in preventing HGSC in high-risk populations.
Published in
Medroxyprogesterone Acetate Inhibits Tumorigenesis in Mouse Models of Oviductal High-Grade Serous Carcinoma
Zhai Y, Bedi K, Wu R et al. · Cancers 2025 · PMID 41228249 · doi:10.3390/cancers17213456
This dataset
Open GSE309487 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 GSE309487_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 PRJNA1336159 and SRA study SRP629535. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41228249) ↗
Study design
6 conditions, mostly in triplicate
GEMM_noPnoTAM ×4 GEMM_noPwithTAM ×4 GEMM_E2P4 ×3 GEMM_MPA ×3 GEMM_P4 ×3 GEMM_Placebo ×3

Supports a between-group comparison across 20 samples.

How we read this: 6 replicated groups read from 20 sample titles; they account for 20 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
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