Work

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

Year: 2026

Type: article

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 < 0.05, FC > 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.

Source: Genes

DOI: 10.3390/genes17111402