ArticleInternational journal of molecular sciences2026
Comparative Analysis of Serum and Tissue miRNA Expression Profiles and Regulatory Pathways in Early-Stage Ovarian Cancer Using Public Databases.
Article in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
To characterize the distinct expression profiles of microRNAs (miRNAs) in serum and tissue and to delineate the heterogeneity of their regulatory mechanisms in early-stage ovarian cancer (EOC), thereby identifying candidate biomarkers for non-invasive early diagnosis. Differentially expressed miRNAs were identified by integrating publicly available datasets of EOC tissues and serum samples from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Core miRNAs were subsequently screened through integrated differential expression analysis, weighted gene co-expression network analysis (WGCNA), and feature importance ranking derived from optimized machine learning models. Protein-protein interaction (PPI) networks and functional enrichment analyses (GO and KEGG) were performed on predicted target genes to systematically compare the functional discrepancies between serum- and tissue-derived miRNAs. No overlapping core miRNAs were observed between the two compartments. Serum miRNAs exhibited an overall up-regulated trend, whereas tissue miRNAs were predominantly down-regulated. Although the regulatory pathways demonstrated significant heterogeneity, they ultimately converged on the cell cycle and the PI3K-Akt signaling pathway, indicating high functional homology. Furthermore, serum miRNAs are not merely passive leakage products from tissues; current evidence suggests they may be selectively packaged into exosomes to participate in tumor regulation. Despite divergent expression profiles, serum and tissue miRNAs share homologous regulatory functions in EOC. These findings suggest that serum miRNAs accurately reflect the core molecular status of tumor tissues, providing a robust molecular foundation for liquid biopsy-based early detection strategies.
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