Integrated miRNA-mRNA Analysis Reveals Potential Biomarkers of Chemoresistance in Ovarian Cancer

Abstract

The current study aimed to determine potential biomarkers related to chemoresistance in ovarian cancer and the involved signaling pathways through bioinformatics analysis. This was followed by an exploration of the related indices on the occurrence and development of chemoresistance in ovarian cancer (OC). Five miRNA/mRNA expression datasets on chemoresistance OC were obtained from the Geodatabase. The significantly different expressed miRNAs (DEMs) and differently expressed genes (DEGs) between chemoresistant OC tissues and control tissues were screened using the GEO2R online tool. Afterwards, pathway analysis was utilized to analyze the DEGs and Cytoscape with STRING 11.0 was used to visualize the protein-protein interaction (PPI) network of DEGs. Afterwards, TFmiR webserver was performed to predict the TF-miRNA-mRNA network. Finally, KM-Plotter was utilized to determine the effects of hub genes and key miRNAs on survival time. A total of 24 DEMs and 548 DEGs were screened from four different datasets on chemoresistance in OC. Seven mRNA-miRNA pairs were found. Survival analysis based on the Kaplan-Meier plotter revealed that 11 biomarkers, including hsa-miR-363, hsa-miR-125b, CDKN1N, JUN, KFL4, IGFBP3, TGFBR2, CCR5, SPP1, LOX, and MMP1, which were associated with TF-miRNA-mRNA network, were closely associated with overall survival (OS) in patients with OC (P< 0.05). The integrated genomic analysis method was successful in screening novel and important genes for the occurrence and progression of chemoresistance in OC. Moreover, this method provided valuable information for investigating chemoresistance in OC and also forms the basis for further functional research.