Identification of Dysregulated Mirnas-Genes Network in Ovarian Cancer: An Integrative Approach to Uncover the Molecular Interactions and Oncomechanisms Publisher Pubmed



Kadkhoda S¹ ; Darbeheshti F^{1, 2} ; Tavakkolybazzaz J¹ Show Affiliations
Source: Cancer Reports Published:2020

Abstract

Background: Ovarian (OV) cancer is considered as one of the most deadly malignancies in women, since it is unfortunately diagnosed in advanced stages. Nowadays, the importance of bioinformatics tools and their frequent usage in tracking dysregulated cancer-related genes and pathways have been highlighted in researches. Aim: The aim of this study is to investigate dysregulated miRNAs-genes network and its function in OV tumors based on the integration of microarray data through a system biology approach. Methods: Two microarray data (GSE119056 and GSE4122) were analyzed to explore the differentially expressed miRNAs (DEmiRs) and genes among OV tumors and normal tissues. Then, through the help of TargetScan, miRmap, and miRTarBase databases, the dysregulated miRNA-gene network in OV tumors was constructed by Cytoscape. In the next step, co-expression and protein-protein interaction networks were made using GEPIA and STRING databases. Moreover, the functional analysis of the hub genes was done by DAVID, KEGG, and Enrichr databases. Eventually, the regulatory network of TF-miRNA-gene was constructed. Results: The potential dysregulated miRNAs-genes network in OV tumors has been constructed, including 109 differentially expressed genes (DEGs), 25 DEmiRs, and 213 interactions. Two down-regulated microRNAs, miR-660-3p and hsa-miR-4510, have the most interactions with up-expressed oncogenic DEGs. CDK1, PLK1, CCNB1, CCNA2, and EZH2 are involved in protein module, which show significant overexpression in OV tumors according to The Cancer Genome Atlas (TCGA) data. EZH2 shows amplification in OV tumors with remarkable percentage. The transcription factors TFAP2C and GATA4 have the pivotal regulatory functions in oncotranscriptomic profile of OV tumors. Conclusion: In current study, we have collected and integrated different data to uncover the complex molecular interactions and oncomechanisms in OV tumors. The DEmiRs-DEGs and TF-miRNA-gene networks reveal the potential interactions that could be a significant piece of the OV onco-puzzle. © 2020 The Authors. Cancer Reports published by Wiley Periodicals LLC.