GEO series

Upregulation of MMP3 promotes cisplatin resistance in ovarian cancer

GSE275051 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2025/04/24 Platform GPL16791

At a glance

RNA-seq (gene expression) · human · 24 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)
Topic: Ovarian cancerThis series is part of our curated briefing on it.
Samples: 24 samples
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: Upregulation of MMP3 Promotes Cisplatin Resistance in Ovarian CancerInternational journal of molecular sciences · 2025

Summary (written by the submitters)

Seventy percent of women with ovarian cancer develop resistance to cisplatin, contributing to persistently high mortality rates. Understanding the mechanisms behind this resistance is crucial for developing improved therapies. Matrix metalloproteinase 3 (MMP3) is elevated in ovarian cancer patients, but its role in cisplatin resistance remains underexplored.

Read the full summary ↓

We observed significantly higher MMP3 protein and mRNA levels in cisplatin-resistant high-grade serous ovarian cancer (HGSOC) cells compared to cisplatin-sensitive cells, with further increases following cisplatin treatment. Kaplan‒Meier analysis indicated that patients with lower MMP3 levels have better survival outcomes. MMP3 knockdown via siRNA reduced cell viability, proliferation, and invasion, effects enhanced by cisplatin; however, a chemical MMP3 inhibitor did not replicate these effects. To better understand MMP3’s role, we conducted RNA sequencing to analyze gene expression changes and used immunoprecipitation with mass spectrometry to identify MMP3-interacting proteins, making this the first study to explore this in cisplatin-resistant ovarian cancer. Surprisingly, multiple injections of liposomal MMP3-siRNA increased tumor size in a mouse model, while combining MMP3-siRNA with cisplatin reduced tumor growth. These findings highlight MMP3’s complex role in cisplatin resistance and raise concerns about its targeting in vivo.

Published in

Upregulation of MMP3 Promotes Cisplatin Resistance in Ovarian Cancer

Rivera-Serrano M, Flores-Colón M, Valiyeva F et al. · International journal of molecular sciences 2025 · PMID 40362252 · doi:10.3390/ijms26094012

This dataset

Open GSE275051 in finder → Find more human RNA-seq datasets → Ovarian cancer landscape →

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 GSE275051_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 PRJNA1149018 and SRA study SRP529110. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40362252) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 24 more — browse all 24 samples with per-sample file links →

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GSE128098 TET1 reprograms the epithelial ovarian cancer epigenome and reveals casein kinase 2α as a therapeutic target 4 samples same disease briefing · shares ovarian
GSE154600 Multi-omic analysis of subtype evolution and heterogeneity in high-grade serous ovarian carcinoma 5 samples same disease briefing · shares ovarian
GSE57477 Molecular subtyping of serous ovarian tumors reveals multiple connections to intrinsic breast cancer subtypes 72 samples same disease briefing · shares ovarian
GSE314300 Rb CUT&RUN profiling in ovarian cancer cell lines following CDK2 inhibitor treatment 10 samples same disease briefing · shares ovarian
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Search all human 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.