MicroRNA-based signatures impacting clinical course and biology of ovarian cancer: a miRNOmics study

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Abstract

Background: In Western countries, ovarian cancer (OC) still represents the leading cause of gynecological cancer-related deaths, despite the remarkable gains in therapeutical options. Novel biomarkers of early diagnosis, prognosis definition and prediction of treatment outcomes are of pivotal importance. Prior studies have shown the potentials of micro-ribonucleic acids (miRNAs) as biomarkers for OC and other cancers. Methods: We focused on the prognostic and/or predictive potential of miRNAs in OC by conducting a comprehensive array profiling of miRNA expression levels in ovarian tissue samples from 17 non-neoplastic controls, and 60 tumor samples from OC patients treated at the Regina Elena National Cancer Institute (IRE). A set of 54 miRNAs with differential expression in tumor versus normal samples (T/N-deregulated) was identified in the IRE cohort and validated against data from the Cancer Genoma Atlas (TCGA) related to 563 OC patients and 8 non-neoplastic controls. The prognostic/predictive role of the selected 54 biomarkers was tested in reference to survival endpoints and platinum resistance (P-res). Results: In the IRE cohort, downregulation of the 2 miRNA-signature including miR-99a-5p and miR-320a held a negative prognostic relevance, while upregulation of miR-224-5p was predictive of less favorable event free survival (EFS) and P-res. Data from the TCGA showed that downregulation of 5 miRNAs, i.e., miR-150, miR-30d, miR-342, miR-424, and miR-502, was associated with more favorable EFS and overall survival outcomes, while miR-200a upregulation was predictive of P-res. The 9 miRNAs globally identified were all included into a single biologic signature, which was tested in enrichment analysis using predicted/validated miRNA target genes, followed by network representation of the miRNA-mRNA interactions. Conclusions: Specific dysregulated microRNA sets in tumor tissue showed predictive/prognostic value in OC, and resulted in a promising biological signature for this disease.

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Krasniqi, E., Sacconi, A., Marinelli, D., Pizzuti, L., Mazzotta, M., Sergi, D., … Vici, P. (2021). MicroRNA-based signatures impacting clinical course and biology of ovarian cancer: a miRNOmics study. Biomarker Research, 9(1). https://doi.org/10.1186/s40364-021-00289-6

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