Ovarian cancer is the first leading cause of mortality in gynecological malignancies. To identify key genes and microRNAs in ovarian cancer, mRNA microarray dataset GSE36668, GSE18520, GSE14407 and microRNA dataset GSE47841 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and microRNAs (DEMs) were obtained using GEO2R. Functional and pathway enrichment analysis were performed for DEGs using DAVID database. Protein-protein interaction (PPI) network was established by STRING and visualized by Cytoscape. Following, overall survival (OS) analysis of hub genes was performed by the Kaplan-Meier plotter online tool. Module analysis of the PPI network was performed using MCODE. Moreover, miRecords was applied to predict the targets of the DEMs. A total of 345 DEGs were obtained, which were mainly enriched in the terms related to cell cycle, mitosis, and ovulation cycle process. A PPI network was constructed, consisting of 141 nodes and 296 edges. Sixteen genes had high degrees in the network. High expression of four genes of the 16 genes was associated with worse OS of patients with ovarian cancer, including CCNB1, CENPF, KIF11, and ZWINT. A significant module was detected from the PPI network. The enriched functions and pathways included cell cycle, nuclear division, and oocyte meiosis. Additionally, a total of 36 DEMs were identified. The expression of KIF11 was negatively correlated with that of has-miR-424 and has-miR-381, and it was also the potential target of two microRNAs. In conclusion, these results identified key genes, which could provide potential targets for ovarian cancer diagnosis and treatment.

The tumor suppressor protein 53BP1 plays key roles in response to DNA double-strand breaks (DSBs) by serving as a master scaffold at the damaged chromatin. Current evidence indicates that 53BP1 assembles a cohort of DNA damage response (DDR) factors to distinctly execute its repertoire of DSB responses, including checkpoint activation and non-homologous end joining (NHEJ) repair. Here, we have uncovered LC8 (a.k.a. DYNLL1) as an important 53BP1 effector. We found that LC8 accumulates at laser-induced DNA damage tracks in a 53BP1-dependent manner and requires the canonical H2AX-MDC1-RNF8-RNF168 signal transduction cascade. Accordingly, genetic inactivation of LC8 or its interaction with 53BP1 resulted in checkpoint defects. Importantly, loss of LC8 alleviated the hypersensitivity of BRCA1-depleted cells to ionizing radiation and PARP inhibition, highlighting the 53BP1-LC8 module in counteracting BRCA1-dependent functions in the DDR. Together, these data establish LC8 as an important mediator of a subset of 53BP1-dependent DSB responses.

Abstract. Cervical cancer is one of the most common types of cancer among women worldwide. In order to identify the microRNAs (miRNAs/miRs) and mRNAs associated with the carcinogenesis of cervical cancer, and to investigate the molecular mechanisms of cervical cancer, an miRNA microarray, GSE30656, and 3 mRNA microarrays, GSE63514, GSE39001 and GSE9750, for cervical cancer were retrieved from Gene Expression Omnibus. These datasets were analyzed in order to obtain differentially-expressed genes (DEGs) and miRNAs using the GEO2R tool. Gene Ontology (GO) and pathway enrichment analysis for DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery. Protein-protein interaction (PPI) analysis for DEGs was conducted using The Search Tool for the Retrieval of Interacting Genes software and visualized using Cytoscape, followed by hub gene identification, and biological process and pathway enrichment analysis of the module selected from the PPI network using the Molecular Complex Detection plugin. In addition, miRecords was applied to predict the targets of differentially-expressed miRNAs. A total of 44 DEGs and 15 differentially-expressed miRNAs were identified. These DEGs were mainly enriched in GO terms associated with the cell cycle. In the PPI network, cyclin-dependent kinase 1, topoisomerase DNA IIα, aurora kinase A (AURKA) and minichromosome maintenance complex component 2 (MCM2) had higher degrees of connectivity. A significant module was detected from the PPI network. AURKA, MCM2 and kinesin family member 20A exhibited higher degrees in this module, while the genes in the module were mainly involved in the cell cycle and the DNA replication pathway. In addition, estrogen receptor 1 was predicted as the potential target of 13 miRNAs. A total of 10 DEGs were identified as potential targets of miR-203. In conclusion, the results indicated that microarray dataset analysis may provide a useful method for the identification of key genes and patterns to successfully identify determinants of the carcinogenesis of cervical cancer. The functional studies of candidate genes and miRNAs from these databases may lead to an increased understanding of the development of cervical cancer.

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Eukaryotic initiation factor 4E (eIF4E) plays an important role in cap-dependent translation. The overexpression of eIF4E gene has been found in a variety of human malignancies. In this study, we attempted to identify the potential effects of eIF4E and explore the possibility of eIF4E as a therapeutic target for the treatment of human ovarian cancer. First the activation of eIF4E protein was detected with m7-GTP cap binding assays in ovarian cancer and control cells. Next, the eIF4E-shRNA expression plasmids were used to specifically inhibit eIF4E activity in ovarian cancer cells line A2780 and C200. The effects of knockdown eIF4E gene on cell proliferation, migration and invasion were investigated in vitro. Moreover, the changes of cell cycle and apoptosis of ovarian cancer cells were detected by flow cytometry. Finally, we investigated the effect of knockdown of eIF4E on the chemosensitivity of ovarian cancer cells to cisplatin in vitro. Our results show there is elevated activation of eIF4E in ovarian cancer cells compared with normal human ovarian epithelial cell line. The results of BrdU incorporation and FCM assay indicate that knockdown of eIF4E efficiently suppressed cell growth and induce cell cycle arrest in G1 phase and subsequent apoptosis in ovarian cancer cells. From Transwell assay analysis, knockdown eIF4E significantly decrease cellular migration and invasion of ovarian cancer cells. We also confirmed that knockdown eIF4E could synergistically enhance the cytotoxicity effects of cisplatin to cancer cells and sensitized cisplatin-resistant C200 cells in vitro. This study demonstrates that the activation of eIF4E gene is an essential component of the malignant phenotype in ovarian cancer, and aberration of eIF4E expression is associated with proliferation, migration, invasion and chemosensitivity to cisplatin in ovarian cancer cells. Knockdown eIF4E gene can be used as a potential therapeutic target for the treatment of human ovarian cancer.