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Resumen de Expression of serum miR-200a, miR-200b, and miR-200c as candidate biomarkers in epithelial ovarian cancer and their association with clinicopathological features

M. Zuberi, R. Mir, J. Das, I. Ahmad, J. Javid, P. Yadav, M. Masroor, S. Ahmad, P. C. Ray, A. Saxena

  • Background MicroRNAs (miRs) have been implicated in the etiology of various human cancers. The aim of this study was to investigate the association of the expression of three members—miR 200a, miR 200b, and miR 200c belonging to the miR-200 family with clinicopathological characteristics and their impact on the progression of epithelial ovarian cancer (EOC).

    Materials and methods Total RNA from serum was isolated by Trizol method, polyadenylated, and reverse transcribed into cDNA. Expression levels of miR-200a, miR-200b, and miR-200c were detected by using miRNA qRT-PCR. We measured miR expression in 70 serum samples of EOC patients with matched controls using U6 snRNA as a reference. Levels of miR expression was compared with distinct clinicopathological features.

    Results Expression of miR-200a was found to be greater than six-fold (p = 0.01), miR-200b and miR-200c greater than three-fold (p = 0.01) in comparison with matched normal controls. Association of miRNA expression with clinicopathological factors and progression was statistically evaluated. The expression levels of miR-200a and miR-200c were found to be significantly associated with disease progression (p = 0.04 and p < 0.001, respectively). miR-200a overexpression was found be associated with tumor histology and stage. Patients with lymph node metastasis showed significant elevation of miR-200c (p = 0.006). The AUC in ROC curve also indicated that serum levels of miR-200a and miR-200c might be worthwhile as a diagnostic tool in the near future.

    Conclusion Our findings suggest that miR-200a, miR-200b, and miR-200c overexpressions are associated with the aggressive tumor progression and be recognized as reliable markers to predict the prognosis and survival in EOC patients.


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