GEO series

Novel Placental Biomarker Shows Predictive Potential for Spontaneous Preterm Labor

GSE255051 Homo sapiens (human) Single-cell RNA-seq 2 samples Submitted 2025/02/04 Platform GPL20795

At a glance

Single-cell RNA-seq · human · 2 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: 2 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: Novel Placental Biomarker Shows Predictive Potential for Spontaneous Preterm LaborAmerican journal of perinatology · 2025

Summary (written by the submitters)

Objective: Human parturition involves many events among mother, fetus, and placenta, and the initiation of these events is the consequence of activation of a series of endocrine and immune responses. Multiple underlying pathways account for the cascade of events that culminate in spontaneous preterm labor. In this study, we aimed to characterize these signaling pathways of placental origin at molecular levels.

Read the full summary ↓

Study design: We used single-cell RNA-sequencing (sc-RNA-seq) analysis to probe transcriptional heterogeneity in human placenta delivered at preterm or term and then used RNA in situ hybridization (RNA-ISH) assay on formalin-fixed paraffin-embedded (FFPE) placental tissues to validate these results. Results: By using sc-RNA-seq on villous cytotrophoblast (CTB) isolated from a preterm placenta, we found that signaling pathways implicated in the initiation of term or preterm labor including ferroptosis, kisspeptin (KISS1), and senescence were constitutively activated in distinct cellular clusters of these trophoblastic stem cells. RNA-ISH-based spatial gene expression profiling in FFPE tissues revealed that pregnancy-specific beta-1-glycoprotein 4 (PSG4), a potent molecular driver for cellular aging, was significantly increased in preterm placentas (N = 30) compared to their full-term counterparts (N = 9). Furthermore, PSG4 mRNA signals were predominantly detected in the villous syncytiotrophoblast and the discontinuous monolayer of CTB as well as the intervillous space where maternal blood circulates. Conclusion: Our study provides strong support for PSG4 overexpression serving as a biomarker for pregnant women at risk for preterm delivery, which can allow for the development of timely and clinical preventive strategies.

Published in

Novel Placental Biomarker Shows Predictive Potential for Spontaneous Preterm Labor

Wang B, Seif K, Lei J et al. · American journal of perinatology 2025 · PMID 39613308 · doi:10.1055/a-2491-4391

This dataset

Open GSE255051 in finder → Find more human 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 GSE255051_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 PRJNA1073437 and SRA study SRP488144. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39613308) ↗

Samples in this study

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+ 2 more — browse all 2 samples with per-sample file links →

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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.