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Comparison of FOLR2-negative and FOLR2-positive human decidual macrophages at term

GSE337384 Homo sapiens (human) Single-cell RNA-seq 12 samples Submitted 2026/07/02 Platform GPL30173
At a glance

Single-cell RNA-seq · human · 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
Homo sapiens (human)
Samples
12 samples: 6 × FOLR2_pos_dono vs 6 × FOLR2_neg_donoGroups 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)
The initiation of human labour is associated with inflammatory activation at the maternal-fetal interface; however, the cellular mechanisms driving this process remain incompletely understood. Decidual macrophages are abundant leukocytes within the decidua and are thought to play important roles in maintaining pregnancy and promoting labour-associated inflammation.
Read the full summary ↓
Despite this, macrophage heterogeneity within the decidua remains poorly defined, with multiple classification systems proposed but no consensus regarding their biological relevance or application across gestation and labour. This thesis investigates decidual macrophage heterogeneity and function in decidua parietalis using flow cytometry, bulk RNA sequencing, RT-qPCR, ELISA, and functional tissue culture assays. Initial studies sought to validate a labour-associated macrophage population identified by single-cell RNA sequencing. Although a population with a similar phenotype was identified by flow cytometry, its extremely low abundance suggested it was unlikely to be a major driver of labour-associated immune adaptation. This prompted a broader investigation of decidual macrophage phenotyping strategies. Current and historical macrophage classification systems, including M1/M2 and several CD11c-based frameworks, failed to reliably distinguish macrophage subsets within this dataset. In contrast, a phenotyping strategy incorporating CD14, pan macrophage marker CD68, and tissue residency marker FOLR2 consistently identified monocytes, FOLR2- macrophages, and FOLR2+ macrophages across first trimester and term decidua, within both decidua parietalis and decidua basalis, and across term not in labour (TNL), term early labour (TeaL), and term in labour (TIL) samples. Bulk RNA sequencing validated FOLR2- and FOLR2+ macrophages as transcriptionally distinct populations. FOLR2- macrophages were enriched for pathways associated with neutrophil chemotaxis, antimicrobial responses, and inflammation, whereas FOLR2+ macrophages were enriched for antigen presentation, MHC class II assembly, and tissue-resident functions. Labour was associated with selective remodelling of the decidual myeloid compartment rather than global leukocyte infiltration. Monocyte abundance increased significantly during early labour, while the proportion of FOLR2- macrophages decreased before increasing again in established labour. Functional analyses demonstrated distinct cytokine profiles between macrophage subsets. FOLR2- macrophages preferentially expressed IL-8 and increased CCL5 expression during early labour, consistent with a chemotactic and inflammatory phenotype. In contrast, FOLR2+ macrophages exhibited high expression of IL-6, CCL2, MMP-9, and MMP-19, supporting roles in tissue homeostasis, leukocyte recruitment, and extracellular matrix remodelling. Furthermore, co-culture experiments demonstrated that FOLR2+ macrophages promoted degradation of chorionic collagen in vitro. Together, these findings support a model in which labour-associated immune adaptation is mediated by functionally specialised decidual macrophage populations rather than a single labour-specific macrophage subset. Functional analysis of FOLR2- macrophages suggests they contribute predominantly to inflammatory signalling and leukocyte recruitment, whereas FOLR2+ macrophages contribute to antigen presentation and tissue remodelling. This work establishes a simple and robust framework for decidual macrophage phenotyping that is applicable across gestation, decidual compartment, and labour status, providing a foundation for future studies investigating macrophage function at the maternal-fetal interface.
This dataset
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.

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 GSE337384_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1484994 and SRA study SRP714699. Searching any of these in the dataset finder brings you back here.

Study design
6 × FOLR2_pos_dono vs 6 × FOLR2_neg_dono

Supports a between-group comparison across 12 samples.

How we read this: 2 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
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