Abstract
Background/Aims: This study aimed to investigate the expression and prognostic value of kinesin family member 2A (KIF2A) and the suppression effects of microRNA-206 (miR-206) on KIF2A in ovarian cancer. Methods: Ovarian cancer tissues from patients and ovarian cancer cell lines (A2780 and SKOV3) were used in this study. miR-206 mimics and control were transiently transfected into cells. RT-qPCR was performed to detect KIF2A mRNA and miR-206 expression levels, Western blot was performed to detect KIF2A protein levels, Dual-Luciferase Reporter Assay was used to examine the inhibition effects of miR-206 on KIF2A mRNA, immunohistochemical staining was used to examine the expression of KIF2A in tissue sections. CCK-8, transwell and Annexin-V-FITC/Propidium Iodide staining with flow cytometry were used to detect the cell proliferation, migration/invasion, and apoptosis respectively. Results: Our study explored the expression profiles of KIF2A and miR-206 in the patients with ovarian cancer. We found that overexpression of KIF2A was associated with a poor prognosis in ovarian cancer. We also found that KIF2A mRNA contains two target sites for miR-206 binding and confirmed that miR-206 directly suppresses KIF2A; inhibits ovarian cancer cell proliferation, migration, and invasion; and induces apoptosis. Conclusion: The results suggest KIF2A could serve a valuable prognostic indicator in ovarian cancer and provide a rationale for treatment of ovarian cancer by targeting KIF2A via miR-206.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.