Application of Protein-Protein interaction network analysis in order to identify Cervical cancer mRNA and miRNA biomarkers

Abstract

Background: Cervical cancer (CC) is one of the most common and serious cancers in the world. This cancer includes two histological types including Squamous cell carcinoma (SCC) and adenocarcinoma (ADC). In this project SCC have been studied. The current study aimed to identify novel potential candidate mRNA and miRNA biomarkers for CC based on a Protein-Protein Interaction (PPI) and miRNA-mRNA networks analysis.Results: In the current project, transcriptome profile for normal and CC samples was utilized. First, the PPI network was constructed for the 1335 DEGs, and then a significant gene module was extracted from the PPI network. Next, a list of miRNAs which are targeting module's genes are collected from the miRTarBase online database and a miRNA-mRNA regulatory network was formed. Afterward, CC driver genes were selected from the module's genes (MCM2, MCM10, POLA1, and TONSL) and introduced as potential candidate biomarkers for CC. As well as, two hub miRNAs including miR-193b-3p and miR-615-3p were selected from the miRNA-mRNA regulatory network and reported as potential candidate biomarkers for CC. Conclusion: In summary, six potential candidate RNA-based biomarkers consist of four genes containing MCM2, MCM10, POLA1, and TONSL and two miRNAs containing miR-193b-3p and miR-615-3p are opposed as potential candidate biomarker for CC.