Single-cell profiling and machine learning identify cuproptosis-related fibroblast subpopulations and fibrogenesis modulator AEBP1 in endometriosis

Clinical Snapshot

Key Findings

• P Value: Not reported

• Effect Size: Not quantified in abstract

• Primary Outcome: Identification of cuproptosis-related fibroblast subpopulation with profibrotic features and AEBP1 as hub gene

• Nnt Or Sensitivity: TTM treatment reduced lesion burden and fibrotic markers in mouse model

• Confidence Interval: Not reported

Clinical Application

Early-stage research requiring significant further development before clinical application Relevant to Australian practice given endometriosis prevalence; would require TGA approval for any therapeutic applications targeting copper metabolism Women with endometriosis, particularly those with fibrotic disease progression

Abstract

Endometriosis is characterized by progressive fibrosis and limited therapeutic options. Cuproptosis, a copper-dependent form of regulated cell death, has been implicated in multiple pathological conditions, but its relevance to fibroblast-mediated fibrotic progression in endometriosis remains unclear. Single-cell RNA sequencing data from normal, eutopic, and ectopic endometrial tissues were analyzed to assess cuproptosis-related gene (CRG) activity and fibroblast heterogeneity. Pseudotime analysis, cell-cell communication analysis and high-dimensional weighted gene co-expression network analysis were performed to identify disease-associated fibroblast states and candidate fibrosis-related genes. Machine learning approaches were applied to prioritize candidate hub genes. Functional validation was conducted in endometrial stromal cells, and a mouse model of endometriosis was used to assess the effects of tetrathiomolybdate (TTM), a copper chelator. Elevated CRG activity was enriched in a distinct fibroblast subpopulation with profibrotic transcriptional features. Network and machine learning analyses consistently prioritized AEBP1 as a candidate fibroblast-associated hub gene linked to cuproptosis-related signatures. In vitro, CuCl2 plus elesclomol treatment was associated with increased AEBP1 and fibrosis-related marker expression, accompanied by changes in β-catenin pathway-related proteins, whereas FDX1 or AEBP1 knockdown attenuated these effects. In vivo, TTM treatment reduced lesion burden, fibrotic marker expression and collagen deposition in ectopic lesions. Cuproptosis-related molecular alterations are associated with fibroblast activation and fibrotic progression in endometriosis. Targeting copper metabolism may have therapeutic potential in limiting lesion fibrosis.

References

1. 1.Huang, E., Li, J. T., Zuo, D., Li, R., Wu, Q., Lin, N., Zhao, J., Wang, H., Liu, Y., & Zhang, L. (2026). Single-cell profiling and machine learning identify cuproptosis-related fibroblast subpopulations and fibrogenesis modulator AEBP1 in endometriosis. Apoptosis, Article 0219764. https://doi.org/10.1371/journal.pone.0219764