From Gene Networks to Repurposed Drugs: A Systems Biomedicine Approach to Endometriosis Management

Fadime Dilşad Taş, Büşra Aydın
In: Genel Tıp Dergisi · 2026 · vol. 36(2026) , pp. 1–13 · doi:10.54005/geneltip.1812858 · W7143401165
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⚙ AI-generated summary by claude@2026-06, 2026-06-06 ⓘ

This study identified 25 hub molecules and promising drug candidates including fluticasone propionate for endometriosis by analyzing gene expression data and constructing multi-layered biological networks.

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⚙ AI-generated deep summary by claude@2026-06, 2026-06-06 ⓘ

This paper used publicly available gene expression data from six endometrial tissue GEO datasets to identify differentially expressed genes between endometriosis and healthy groups, then built a three-layer systems biology network (transcription factor–gene, protein–protein, and microRNA–gene interactions) to extract 25 hub molecules. Using PCA to evaluate how well hub genes separated diseased from healthy samples, and KM-plotter survival analysis to assess diagnostic and prognostic associations, the authors reported moderate specificity (~50%) and higher sensitivity (≥80%), while docking supported stronger binding of three repurposed drugs (fluticasone propionate, pyrimethamine, and manumycin A) to their target proteins than known inhibitors. A stated limitation is that the work relies on in silico analyses and repurposing predictions rather than experimental validation. This paper is centrally about endometriosis — it applies systems-biology transcriptomic networks to identify hub genes and propose repurposed drugs, highlighting fluticasone propionate as a candidate for endometriosis management.

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Abstract

Aim: Endometriosis is a widespread gynecological condition with no definitive cure, often managed through hormonal therapies, NSAIDs, and laparoscopy, which remains the gold standard for both diagnosisand treatment. Its underlying pathogenesis remains unclear. The absence of effective treatment options for endometriosis underscores the urgent need for innovative approaches to alleviate patient pain andimprove quality of life. This study explores an alternative therapeutic strategy for endometriosis utilizing systems biomedicine approaches.Materials and Methods: Gene expression data from six endometrial tissue datasets (GSE135485, GSE153740, GSE232713, GSE51981, GSE23339, and GSE25628) were retrieved from the publicly available database Gene Expression Omnibus (GEO) and analyzed via GEO2R to identify differentially expressed genes (DEGs). To assess the statistical significance, p-value ≤ 0.05, log2FC > 1, and log2FC <-1 cut-offs were applied. A three-layered biological network comprising transcription factor-gene interaction, protein– protein interactions, and microRNA-gene interactions was constructed using Cytoscape to identify keyhub genes. To assess the discriminatory capacity of the hub genes between healthy and diseased groups, principal component analysis (PCA) was conducted independently for each dataset. Key genes as theprimary contributors to group differentiation were further evaluated by survival analysis.Results: The construction of a multi-layered network analysis revealed 25 hub molecules that were used for in silico drug repositioning, and among 50 candidate compounds, fluticasone propionate, pyrimethamine, and manumycin A emerged as promising therapies. Molecular docking analysis confirmed that candidate repurposed drugs exhibited stronger binding to their respective proteins compared with known inhibitors. Additionally, PCA analysis demonstrated good sensitivity (≥80%) and moderate specificity (≈50%) in distinguishing endometriosis patients from healthy controls. Survival analysis via KM-plotter revealed the diagnostic and prognostic power of the hub genes (CXADR, RELA, STXBP6, ANK3, and PDGFR), further supporting their therapeutic potential in endometriosis.Conclusion: Fluticasone propionate has emerged as a promising candidate for the management of endometriosis based on systems biomedicine approaches.

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Outcome instruments

rASRM Enzian

Condition tags

endometriosis

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Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

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