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. 2024 Oct 19;12(10):2393.
doi: 10.3390/biomedicines12102393.

Circulating Serum Micro-RNA as Non-Invasive Diagnostic Biomarkers of Endometriosis

Antonella Ravaggi  1   2   3 , Cosetta Bergamaschi  1   3   4 , Chiara Galbiati  5 , Laura Zanotti  1   3 , Aline S C Fabricio  6 , Massimo Gion  7 , Elia Cappelletto  6 , Antonette E Leon  7 , Massimo Gennarelli  8 , Cesare Romagnolo  9 , Giuseppe Ciravolo  1 , Stefano Calza  10 , Eliana Bignotti  1   3 , Franco Odicino  1   2
Affiliations

Circulating Serum Micro-RNA as Non-Invasive Diagnostic Biomarkers of Endometriosis

Antonella Ravaggi et al. Biomedicines. .

Abstract

Background/objectives: Endometriosis (END) is a painful gynecological condition. Clinical examination, imaging, and laparoscopy can provide a definitive diagnosis of END. Nonetheless, non-invasive biomarkers could help enhance and streamline the diagnostic process. Micro-RNAs (miRNAs), a family of small non-coding RNAs, could serve as useful non-invasive biomarkers for END. The aim of this study was to perform serum miRNA profiling in a retrospective cohort of women to identify miRNAs that are differentially expressed in END compared to control patients.

Methods: RNA was isolated from serum samples of 67 END patients and 60 control women. The expression profile of a 754-miRNA panel was studied with RT-qPCR performed on a QuantStudio 12K Flex with the TaqMan OpenArray miRNA panel. A Censored Regression Model was used for miRNA differential expression analysis. Several gene-enrichment algorithms were employed to identify pathways related to the target genes of differentially expressed miRNAs.

Results: One hundred and thirty miRNAs were detected in at least 75% of samples from either the END or the control group. Sixteen miRNAs were significantly modulated between the END and control groups. Enrichment analysis identified targets significantly overrepresented in numerous pathways involved in biological processes related to END, including inflammation, angiogenesis, cellular invasion, cell-cycle/cell proliferation, and estrogen and progesterone hormonal signaling.

Conclusions: Our study indicates that differentially expressed miRNAs between END patients and controls can be identified through liquid biopsy. Our findings also suggest a potential role for serum miRNAs in the pathophysiology of END, warranting further investigations for their use as non-invasive biomarkers.

Keywords: endometriosis; expression profile; liquid biopsy; microRNA.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Gene-concept networks for selected Gene Ontology Biological Processes (GO-BP) linked to differentially expressed miRNA between endometriosis patients and controls. Pathways were grouped based on their involvement in the main biological processes associated with endometriosis: inflammation (a), angiogenesis (b), cellular invasion/metastatization (c), cell cycle and cell proliferation (d), and hormonal signaling (e). Dot size represents the number of genes involved in the different pathways.
Figure 2
Figure 2
Barplots represent the number of selected target genes of differentially expressed miRNAs, derived from Gene Ontology Biological Processes (GO-BP), in the comparison between endometriosis patients and controls. Pathways were grouped based on their involvement in the main biological processes associated with endometriosis: inflammation (a), angiogenesis (b), cellular invasion/metastatization (c), cell cycle and cell proliferation (d), and hormonal signaling (e). False Discovery Rate (FDR) is also shown in each barplot.
See this image and copyright information in PMC

References

    1. Anastasiu C.V., Moga M.A., Neculau A.E., Bălan A., Scârneciu I., Dragomir R.M., Dull A.M., Chicea L.M. Biomarkers for the Noninvasive Diagnosis of Endometriosis: State of the Art and Future Perspectives. Int. J. Mol. Sci. 2020;21:1750. doi: 10.3390/ijms21051750. - DOI - PMC - PubMed
    1. Chapron C., Marcellin L., Borghese B., Santulli P. Rethinking Mechanisms, Diagnosis and Management of Endometriosis. Nat. Rev. Endocrinol. 2019;15:666–682. doi: 10.1038/s41574-019-0245-z. - DOI - PubMed
    1. Giudice L.C., Kao L.C. Endometriosis. Lancet. 2004;364:1789–1799. doi: 10.1016/S0140-6736(04)17403-5. - DOI - PubMed
    1. Taylor H.S., Kotlyar A.M., Flores V.A. Endometriosis Is a Chronic Systemic Disease: Clinical Challenges and Novel Innovations. Lancet. 2021;397:839–852. doi: 10.1016/S0140-6736(21)00389-5. - DOI - PubMed
    1. Dunselman G.A.J., Vermeulen N., Becker C., Calhaz-Jorge C., D’Hooghe T., De Bie B., Heikinheimo O., Horne A.W., Kiesel L., Nap A., et al. ESHRE Guideline: Management of Women with Endometriosis. Hum. Reprod. 2014;29:400–412. doi: 10.1093/humrep/det457. - DOI - PubMed

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