Open Access
Regulatory network involving miRNAs and genes in serous ovarian carcinoma
Author(s) -
Hang Zhao,
Hao Xu,
Luchen Xue
Publication year - 2017
Publication title -
oncology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.766
H-Index - 54
eISSN - 1792-1082
pISSN - 1792-1074
DOI - 10.3892/ol.2017.6927
Subject(s) - microrna , biology , gene , gene regulatory network , oncogene , computational biology , transcription factor , gene expression profiling , genetics , gene expression , cell cycle
Serous ovarian carcinoma (SOC) is one of the most life-threatening types of gynecological malignancy, but the pathogenesis of SOC remains unknown. Previous studies have indicated that differentially expressed genes and microRNAs (miRNAs) serve important functions in SOC. However, genes and miRNAs are identified in a disperse form, and limited information is known about the regulatory association between miRNAs and genes in SOC. In the present study, three regulatory networks were hierarchically constructed, including a differentially-expressed network, a related network and a global network to reveal associations between each factor. In each network, there were three types of factors, which were genes, miRNAs and transcription factors that interact with each other. Focus was placed on the differentially-expressed network, in which all genes and miRNAs were differentially expressed and therefore may have affected the development of SOC. Following the comparison and analysis between the three networks, a number of signaling pathways which demonstrated differentially expressed elements were highlighted. Subsequently, the upstream and downstream elements of differentially expressed miRNAs and genes were listed, and a number of key elements (differentially expressed miRNAs, genes and TFs predicted using the P-match method) were analyzed. The differentially expressed network partially illuminated the pathogenesis of SOC. It was hypothesized that if there was no differential expression of miRNAs and genes, SOC may be prevented and treatment may be identified. The present study provided a theoretical foundation for gene therapy for SOC.