Integrative gene ontology-driven analysis of the eutopic endometrium reveals key dysregulated functionomes and pathways in endometriosis

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Abstract

BACKGROUND: Endometriosis is a chronic estrogen-dependent inflammatory disorder associated with pelvic pain, infertility, and an increased risk of endometriosis-associated ovarian cancer. Despite extensive research, its molecular mechanisms remain incompletely understood. This study aimed to identify dysregulated biological functions and potential molecular signatures in the eutopic endometrium of women with endometriosis using an integrative functionome-based approach. METHODS: An integrative gene ontology-driven functionome analysis was conducted using publicly available transcriptomic datasets. A modified Differential Rank Conservation algorithm was applied to reconstruct sample-specific Gene Set Regularity (GSR) indices across 10,192 Gene Ontology (GO)-defined gene sets. Statistical analyses, exploratory factor analysis, and support vector machine (SVM)-based machine learning were used to identify dysregulated functionomes, dysfunctional pathways, and key differentially expressed genes (DEGs). RESULTS: The analysis included 196 patients with endometriosis and 246 healthy controls. Functionome profiling revealed widespread dysregulation of immune, metabolic, angiogenic, and extracellular matrix-related pathways. Among the top 50 dysregulated functionomes, eight were related to copper ion transport and homeostasis. Integrative analysis identified a recurrent four-gene copper-regulatory signature consisting of ATP7A, ATP7B, ATOX1, and SLC31A1 (p <0.05), suggesting coordinated disruption of copper homeostasis in endometriosis. CONCLUSION: Dysregulation of copper ion homeostasis and cuproptosis-related pathways may represent a previously underappreciated molecular feature of endometriosis. Although causal relationships cannot be established from this comparative analysis, the identified copper-regulatory signature provides a reproducible transcriptomic framework for future mechanistic and translational studies.
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Background

Endometriosis is a chronic estrogen-dependent inflammatory disorder associated with pelvic pain, infertility, and an increased risk of endometriosis-associated ovarian cancer. Despite extensive research, its molecular mechanisms remain incompletely understood. This study aimed to identify dysregulated biological functions and potential molecular signatures in the eutopic endometrium of women with endometriosis using an integrative functionome-based approach.

Methods

An integrative gene ontology–driven functionome analysis was conducted using publicly available transcriptomic datasets. A modified Differential Rank Conservation algorithm was applied to reconstruct sample-specific Gene Set Regularity (GSR) indices across 10,192 Gene Ontology (GO)–defined gene sets. Statistical analyses, exploratory factor analysis, and support vector machine (SVM)–based machine learning were used to identify dysregulated functionomes, dysfunctional pathways, and key differentially expressed genes (DEGs).

Results

The analysis included 196 patients with endometriosis and 246 healthy controls. Functionome profiling revealed widespread dysregulation of immune, metabolic, angiogenic, and extracellular matrix–related pathways. Among the top 50 dysregulated functionomes, eight were related to copper ion transport and homeostasis. Integrative analysis identified a recurrent four-gene copper-regulatory signature consisting of ATP7A, ATP7B, ATOX1, and SLC31A1 (p <0.05), suggesting coordinated disruption of copper homeostasis in endometriosis.

Conclusion

Dysregulation of copper ion homeostasis and cuproptosis-related pathways may represent a previously underappreciated molecular feature of endometriosis. Although causal relationships cannot be established from this comparative analysis, the identified copper-regulatory signature provides a reproducible transcriptomic framework for future mechanistic and translational studies.

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endometriosisinfertility

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europepmc
last seen: 2026-06-11T06:19:48.454388+00:00
pubmed
last seen: 2026-06-11T06:15:06.289189+00:00
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last seen: 2026-05-11T08:34:28.763810+00:00
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