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Changes of Molecular, Cellular and Biological Activities According to microRNA-mRNA Interactions in Ovarian Cancer | DOGAN 1 | Computational Molecular Biology

Changes of Molecular, Cellular and Biological Activities According to microRNA-mRNA Interactions in Ovarian Cancer  

Senol DOGAN1 , Kurtovic -Kozaric A.1,2
1 International Burch University, Genetics and Bioengineering Department, Francuske Revolucije bb, Ilidža, 71000 Sarajevo, Bosnia and Herzegovina
2 Department of Clinical Pathology, Clinical Center of the University of Sarajevo, Bolnicka 25, 71000 Sarajevo, Bosnia and Herzegovina
Author    Correspondence author
Computational Molecular Biology, 2015, Vol. 5, No. 4   doi: 10.5376/cmb.2015.05.0004
Received: 14 Apr., 2015    Accepted: 25 May, 2015    Published: 30 Jun., 2015
© 2015 BioPublisher Publishing Platform
This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Preferred citation for this article:

DOGAN S., and Kurtovic-Kozaric A., 2015, Changes of Molecular, Cellular and Biological Activities According to microRNA-mRNA Interactions in Ovarian Cancer, Computational Molecular Biology, 5(4): 1-8

Abstract

microRNA is a noncoding RNA sequence, 20-22 nucleotides long, which functions in silencing gene expression. Changes in normal microRNA expression lead to cancer progression. The following study has been done to elucidate the changes in the expression of microRNAs in ovarian cancer compared to the normal expression because such comparison may lead to better understanding of ovarian carcinogenesis. In the tumor samples, out of 680 microRNA types, 230 show high expression, 295 show low expression and 155 are non-expressed. When we categorized microRNAs based on fold increase >50, we found 31 high and 89 low expressed microRNAs. The huge differences in aberrant expression show the extent of changes in microRNA activities. Using Cancerminer tool, we found the corresponding mRNA targets of these abberantly expressed microRNAs. We found that the most target genes which are captured by the data process are related to cellular proliferation and carcinogenesis.

Keywords
Ovarian cancer microRNA; TCGA, REC Score; Cancerminer
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