Volume 5, Issue 4 (Winter 2019)                   jhbmi 2019, 5(4): 495-506 | Back to browse issues page

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Khorasani M, Shahbazi S, Mahdian R. Bioinformatics Study of the miR-200 Family and the Target Genes in Prostate Cancer. jhbmi 2019; 5 (4) :495-506
URL: http://jhbmi.ir/article-1-313-en.html
Ph.D. in Medical Biotechnology, Associate Professor in Medical Biotechnology Dept., Pasteur Institute of Iran, Tehran, Iran
Abstract:   (5969 Views)
Introduction: Considering the limitations of the common diagnostic test for prostate cancer prostate cancer, the introduction of higher-specific biomarkers for a more accurate and timely diagnosis of prostate cancer is desired. In this study, we aimed to investigate the miR-200 family (miR-200a, miR-200b, miR-200c, miR-141, and miR-429) and their target genes using bioinformatics prediction tools in order to propose potential diagnostic biomarkers for prostate cancer.
Method: In this theoretical study, based on bioinformatics study of micro RNA, the DIANA TOLLS-mirPath v.3 database was used to search the target genes of the miR-200 family in the signaling pathways known in prostate cancer pathogenesis. Then, we confirmed the suggested genes by the online predictive tools such as MiRWalk, Targetscan and RNAhybrid. Finally, the functional role of target genes was investigated on the DAIVID bioinformatics database.
Results: According to the results of this study, the E2F3 gene is the target of all family members of miR-200, BCL2 is the common target of miR-200b / miR-200c / miR-429 and CCNE2 is the common target of miR-200a / miR-141 subsets. Also, miR-200c and miR-429 can modulate the pathogenesis of prostate cancer by targeting CDKN1B and KRAS genes, respectively.
Conclusion: The results of this study showed that members of the miR-200 family targeting the genes involved in important biological processes and molecular pathways of prostate cancer pathogenesis are likely to be effective diagnostic biomarkers in future experimental studies.
 
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Type of Study: Original Article | Subject: Bioinformatics
Received: 2018/05/20 | Accepted: 2018/11/10

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