Exploratory miRNA Profiling and Network Analysis of Endometrioma Fluid: Identifying a Candidate Microenvironmental miRNA Signature and Putative In Silico Regulatory Networks

Karolina Frankowska, Paulina Gil-Kulik, Wiktor Babiuch, Petniak A, Izabela Dymanowska, Grzegorz Polak, Kocki J
In: Genes · 2026 · vol. 17(11) , pp. 1402 · doi:10.3390/genes17111402 · W7225618124
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This study profiled miRNAs in endometrioma fluid to identify a distinct molecular signature and regulatory networks involving metabolic processes, cell division, and stress responses relevant to the endometriotic microenvironment.

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Abstract

Background: Benign ovarian cysts encompass various lesions, including functional cysts and endometriomas. Given the complex pathogenesis of endometriosis, this study aimed to perform the first exploratory, high-throughput microarray profiling of microRNAs (miRNAs) directly from endometrioma fluid, comparing it with functional ovarian cyst fluid to establish a novel molecular baseline and map putative regulatory networks. Methods: Total RNA was isolated from uncentrifuged cyst fluid (n = 7). Profiling was performed using Affymetrix GeneChip miRNA 4.0 Arrays. Following differential expression analysis (FDR 2.0), candidate target genes for the directly measured mature miRNAs were retrieved from miRTarBase. Standardized HGNC targets regulated by ≥4 distinct miRNAs were analyzed using Cytoscape v3.10.4 for network topology, g:Profiler (version e114_eg62_p19_27110d83) for Gene Ontology (GO) enrichment, and Metascape v3.5.20260701 for protein–protein interaction (PPI) modules. Results: Principal Component Analysis demonstrated robust separation between cohorts (PC1: 93.5% variance). We identified 37 FDR-significant microarray features, including 35 mature miRNAs. The primary mature miRNA network comprised 234 unique target genes and 1072 interactions. Functional enrichment highlighted the regulation of primary metabolic processes (padj = 1.43 × 10−16), cell division (padj = 9.97 × 10−4), and nucleocytoplasmic transport. PPI clustering identified densely connected modules driving cellular stress responses, cell cycle progression, and AGE-RAGE signaling. Conclusions: The identified whole-fluid miRNA profile predominantly reflects the distinct cellular, inflammatory, and hemorrhagic composition of the endometriotic microenvironment. These highly filtered, database-curated networks provide a robust in silico reference framework for future targeted functional validation and biomarker discovery in endometriosis.

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