Serum Exosomal MicroRNAs as Potential Circulating Biomarkers for Endometriosis.
Ontology highlight
ABSTRACT: Background:A reliable noninvasive biomarker is not yet available for endometriosis diagnosis. Novel biomarkers for the diagnosis of endometriosis are urgently needed. The molecular constituents of exosomes, especially exosomal microRNAs (miRNAs), have considerable potential as novel biomarkers for clinical diagnosis. This study is aimed at exploring aberrant exosomal miRNA profiles by using miRNA microarray and at providing more accurate molecular biomarkers of endometriosis. Methods:Exosomes were isolated from the serum of patients with endometriosis and negative controls and identified by electron microscopy, nanoparticle tracking analysis, and Western blot. Exosomal miRNAs were profiled by miRNA microarrays. The expression of selective serum exosomal miRNA was validated by qRT-PCR. Receiver operating characteristic (ROC) curves were established to explore the diagnostic value of selective miRNAs. Finally, GO annotation and KEGG pathway enrichment analyses were used to display possible functions associated with the two miRNAs. Results:A total of 24 miRNAs showed differential levels of enrichment with P < 0.05 and |log2?fold?change| > 1 by miRNA microarrays. Among the six selective miRNAs (i.e., miR-134-5p, miR-197-5p, miR-22-3p, miR-320a, miR-494-3p, and miR-939-5p), qRT-PCR analysis revealed that miR-22-3p and miR-320a were significantly upregulated in serum exosomes from patients with endometriosis compared with negative individuals. ROC curve revealed that the serum exosomal miR-22-3p and miR-320a yielded the area under the curve values of 0.855 and 0.827, respectively. Conclusion:Our results demonstrated that exosomal miR-22-3p and miR-320a were significantly increased in the sera of patients with endometriosis. The two miRNAs may be useful potential biomarkers for endometriosis diagnosis.
SUBMITTER: Zhang L
PROVIDER: S-EPMC7008302 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
ACCESS DATA