Gene Expression Signatures in Endometriosis: Molecular Insights and Potential Clinical Applications

Marek Murawski, Julia Bania, Izabela Łaczmańska
In: International Journal of Molecular Sciences · 2026 · vol. 27(22) , pp. 10088 · doi:10.3390/ijms272210088 · W7225832260
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This narrative review evaluates gene expression signatures in endometriosis, identifying promising individual biomarkers like AEBP1 and HOXB6 and highlighting the potential of multigene diagnostic models for distinguishing disease stages and infertility while noting current limitations in clinical translation.

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Abstract

Endometriosis (EM) is a chronic disease affecting approximately 190 million women worldwide. Despite its high prevalence and substantial impact on quality of life and fertility, diagnosis remains challenging because of heterogeneous clinical presentation and the lack of validated molecular biomarkers. Altered gene expression provides valuable insights into the molecular mechanisms and biological heterogeneity of EM and may facilitate the identification of candidate biomarkers. However, molecular signatures derived from surgically collected lesions must be distinguished from markers measurable in minimally invasive specimens, as their potential clinical applications differ substantially. This narrative review summarizes current evidence on gene-expression alterations with potential diagnostic and clinical relevance in EM, including differentially expressed genes (DEGs), transcription factors (TFs), genes involved in major pathogenic pathways, and multigene diagnostic models. Among individual candidates, AEBP1, KLF2, HOXB6, and RORB have demonstrated promising discriminatory performance, while HOXB6 may also contribute to distinguishing stages of disease. Distinct expression profiles have also been associated with EM-related infertility. Multigene approaches appear particularly promising, as integrated expression signatures may provide more robust discriminatory performance than individual markers. However, most proposed biomarkers remain at the candidate stage, and methodological and clinical heterogeneity limits comparability across studies. Future research should prioritize independent validation in large, well-characterized cohorts, standardized analytical procedures, and evaluation of multigene signatures in minimally invasive samples to support their clinical translation.

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