A Holistic View to Cisplatin-Resistant Ovarian Can-cer Determined Proteins and Signaling Pathways Related to Cancer Cell Polyploidy

Background: Ovarian carcinoma is the fifth cause of death from cancer in women with a high proportion of chemotherapy resistance and recurrence in patients . A survey on the reasons for tumor recurrence demonstrates that cancer therapeutic ap-proaches are one of the suspects. Cisplatin is the first line of treatment in ovarian cancer but various clinical reports show a high rate of recurrence post-cancer treatment with this drug. It is supposed that cisplatin with its microtubule-destabilizing role leads to the formation of polyploid cells that are capable of producing malignant cancer stem cells. With a focus on the main regulatory pathways of cell polyploidy and depolyploidy, we re-analyzed a microarray dataset of cisplatin treatment on ovarian cancer cell line to investigate the main accelerators of tumor relapse.Materials and Methods: GSE58470 mRNA microarray data-set deposited by Arrighetti et al was downloaded from the gene expression omnibus (GEO) database. The quality of microarray data was measured by principal component analysis using the ggplot2 package of R. Using GEO2R tool of GEO, genes with adjusted P-value≤0.05 were assumed as differentially expressed (DE). Using CluePedia plugin version 3.7.1 of Cytoscape, a protein-protein interaction network was constructed and topol-ogy of network analyzed by Cytoscape Network Analyzer tool and nodes with the highest degree centrality parameters were identified. Pathway enrichment analysis was performed using ingenuity pathway analysis (IPA) and signaling pathways with P-value≤0.05 were determined.Results: In this study, we re-analyzed the GSE58470 micro-array dataset which measured the effect of cisplatin treatment on the expression profile of a cisplatin-sensitive ovarian can-cer cell line(IGROV-1) and a cisplatin-resistant cell line (IG-ROV-1/Pt1). In quality check, the samples were segregated based on their state (sensitive or resistant), indicating the satis-factory quality of this dataset. Comparison of cisplatin-resistant with cisplatin-sensitive samples demonstrated 1931 genes with adjusted P-value < 0.05. ontology (GO) enrichment analysis of DEGs underscored cell cycle, hypoxia pathway, Hippo signal-ing and 14-3-3 which their role on polyploidy state of cancer cells is determined. On the other hand, analysis of the protein-protein interaction network of DEGs demonstrated key ele-ments of cell cycle regulation like PLK1 as top genes with most degree centrality.Conclusion: In this study, we followed a systematic approach to exploring the underlying molecular mechanisms of cisplatin resistance in ovarian cancer. PLK1 as a key regulator of the cell cycle was determined as a hub node in our analysis and in accordance with previous studies its down-regulation would be correlated with a cell cycle arrest in G2/M and polyploidy induction. Future studies should be performed to determine the role of PLK1 in ovarian cancer relapse and polyploidy

Keywords:

Bioinformatics , Cisplatin , Microarray , Ovarian Can-cer , Polyploidy