GEO series

Multinucleated giant cells are hallmarks of ovarian aging with unique immune and degradation-associated molecular signatures

GSE283393 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2024/12/03 Platform GPL34290

At a glance

Single-cell RNA-seq · mouse · 12 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: Mus musculus (mouse)
Samples: 12 samples: 4 × Macrophage, vs 4 × MNGC, vs 4 × Stroma,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: Multinucleated giant cells are hallmarks of ovarian aging with unique immune and degradation-associated molecular signaturesPLoS biology · 2025

Summary (written by the submitters)

The ovary is one of the first organs to exhibit signs of aging, characterized by reduced tissue function, chronic inflammation, and fibrosis. Multinucleated giant cells (MNGCs), formed by macrophage fusion, typically occur in chronic immune pathologies, including infectious and non-infectious granulomas and the foreign body response, but are also observed in the aging ovary.

Read the full summary ↓

The function and consequence of ovarian MNGCs remain unknown as their biological activity is highly context-dependent, and their large size has limited their isolation and analysis through technologies such as single-cell RNA sequencing. In this study, we define ovarian MNGCs through a deep analysis of their presence across age and species using advanced imaging technologies as well as their unique transcriptome using laser capture microdissection. MNGCs form complex interconnected networks that increase with age in both mouse and nonhuman primate ovaries. MNGCs are characterized by high Gpnmb expression, a putative marker of ovarian and non-ovarian MNGCs. Pathway analysis highlighted functions in apoptotic cell clearance, lipid metabolism, proteolysis, immune processes, and increased oxidative phosphorylation and antioxidant activity. Thus, MNGCs have signatures related to degradative processes, immune function, and high metabolic activity. These processes were enriched in MNGCs compared to primary ovarian macrophages, suggesting discrete functionality. MNGCs express CD4 and colocalize with T-cells, which were enriched in regions of MNGCs, indicative of a close interaction between these immune cell types. These findings implicate MNGCs in modulation of the ovarian immune landscape during aging given their high penetrance and unique molecular signature that supports degradative and immune functions.

Published in

Multinucleated giant cells are hallmarks of ovarian aging with unique immune and degradation-associated molecular signatures

Converse A, Perry MJ, Dipali SS et al. · PLoS biology 2025 · PMID 40550000 · doi:10.1371/journal.pbio.3003204

This dataset

Open GSE283393 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 GSE283393_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 PRJNA1193574 and SRA study SRP549060. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40550000) ↗

Study design

4 × Macrophage, vs 4 × MNGC, vs 4 × Stroma,

Supports a between-group comparison across 12 samples.

How we read this: 3 replicated groups read from 12 sample titles; they account for 12 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

GSM8661341 Macrophage, replicate 1 Macrophage,
GSM8661342 Macrophage, replicate 2 Macrophage,
GSM8661343 Macrophage, replicate 3 Macrophage,
GSM8661344 Macrophage, replicate 4 Macrophage,
GSM8661345 MNGC, replicate 1 MNGC,
GSM8661346 MNGC, replicate 2 MNGC,
GSM8661347 MNGC, replicate 3 MNGC,
GSM8661348 MNGC, replicate 4 MNGC,
GSM8661349 Stroma, replicate 1 Stroma,
GSM8661350 Stroma, replicate 2 Stroma,
GSM8661351 Stroma, replicate 3 Stroma,
GSM8661352 Stroma, replicate 4 Stroma,

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