Identification of Novel Drugs Targeting Cell Cycle Regulators for the Treatment of High-Grade Serous Ovarian Cancer via Integrated Bioinformatics Analysis

High-grade serous ovarian carcinoma (HGSC), the most common and aggressive histological type of cancer, remains leading cause cancer-related deaths among females. It is important to develop novel drugs improve therapeutic outcomes HGSC patients, thereby reducing their mortality. Symmetry one properties biological network, which determines stability a system. As aberrant gene expression critical symmetry-breaking event that perturbs networks triggers tumor progression, we aim in this study discover new candidate predict targets for therapy based on differentially expressed genes involved pathogenesis. Firstly, 98 up-regulated 108 down-regulated were identified from three independent transcriptome datasets. Then, small-molecule compounds PHA-793887, pidorubicine lestaurtinib, target cell-cycle-related processes, as treatment by adopting connectivity map (CMap)-based drug repositioning approach. Furthermore, through topological analysis protein–protein interaction cell cycle regulators CDK1, TOP2A AURKA bottleneck nodes, patterns validated at mRNA protein levels. Moreover, results molecular docking showed lestaurtinib had strong binding affinity AURKA, respectively. Therefore, our repositioned can inhibit regulators, agents treatment, helping optimize strategy HGSC.