# Fibroblast heterogeneity and FN1-mediated signaling in endometriosis revealed by single-cell and spatial transcriptomics

## TL;DR

This study uses single-cell and spatial transcriptomics to uncover fibroblast diversity and signaling in endometriosis, identifying a key fibroblast subtype linked to fibrosis and immune responses.

## Contribution

The study reveals a novel fibroblast subpopulation (C2 CXCR4+), associated with fibrosis and immune signaling, using integrated single-cell and spatial transcriptomic data.

## Key findings

- Fibroblasts in endometriosis lesions are divided into five distinct subtypes with roles in matrix remodeling, immune signaling, and metabolism.
- The C2 CXCR4+ fibroblast subtype shows high stemness and proliferative capacity, and mediates fibrotic and immune signaling via FN1.
- Spatial transcriptomics confirms the localized enrichment of C2 CXCR4+ fibroblasts in ectopic lesions with active signaling.

## Abstract

Endometriosis (EM) is a chronic gynecological disorder that affects 5% to 10% of women of childbearing age, often causing pelvic pain and infertility. Fibrosis is a hallmark of EM progression, yet its underlying molecular drivers remain poorly understood. Emerging progress in single-cell and spatial transcriptomic technologies offer new opportunities to unravel the cellular heterogeneity and intercellular interactions driving fibrotic and immune remodeling in EM lesions.

We performed an integrative multi-omics analysis combining single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics to dissect fibroblast heterogeneity and cell–cell communication networks in EM. ScRNA-seq data from 15 EM patients (GSE213216) were processed to identify transcriptionally distinct fibroblast subpopulations. Functional enrichment (GO, GSEA), stemness estimation (CytoTRACE), and trajectory inference were applied to reveal lineage plasticity. CellChat was used to infer intercellular signaling networks, and spatial transcriptomic data from two ectopic lesions (GSM6690475, GSM6690476) were analyzed to validate the spatial distribution of key ligand–receptor interactions.

We identified 35 cell clusters across EM lesions, with Fibroblast and T/NK cells as dominant populations. Fibroblast were divided into five subtypes, which were associated with extracellular matrix remodeling, immune interactions, and metabolic regulation. Notably, the C2 CXCR4
+ Fibroblast subpopulation exhibited high proliferative capacity and stemness characteristics, and mediated signaling pathways involved in immune and fibrotic responses through FN1. Spatial transcriptomic analysis confirmed the local enrichment of these Fibroblast in ectopic lesions, where they were associated with regions of active signaling.

This study revealed the transcriptional and spatial heterogeneity of Fibroblast in EM syndrome, and identified the C2 CXCR4
+ Fibroblast subpopulation as a may represent key driver of fibrosis and immune regulation. Our integrated omics approach provided new mechanistic insights into the pathogenesis of EM and pointed out new targets for therapeutic intervention.

Diagram illustrating fibroblast subpopulations in endometriosis using scRNA-seq data. It includes charts and graphs on cell differentiation, metabolism-related pathways, and cell stemness. Key methods and analyses shown are DEG analysis, Slingshot trajectory, Monocle 2, TF-regulatory submodules, CellChat interactions, and spatial transcriptomic mapping. Different fibroblast clusters are identified and compared, highlighting transcription factor activity and signaling pathways.