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Abstract. NEK2 [NIMA (never in mitosis gene A)-related expressed kinase 2] is associated with various biological behaviors in the development of cancer, while research concerning its association with drug resistance is limited. The association of NEK2 with drug resistance in ovarian cancer has not yet been reported. In the present study, on the basis of microarray results from Oncomine and the GEO Profiles online database, we revealed that NEK2 mRNA expression in ovarian cancer tissues is upregulated. In addition, its expression in drugresistant ovarian cancer cells was upregulated when compared with expression with their sensitive or parental counterparts. Finally, we performed a comprehensive bioinformatic analysis consisting of protein/gene-protein/gene interaction network, annotation of biological processes and microRNA-mRNA interaction analysis. We observed that NEK2 directly or indirectly interacts with a number of genes, proteins, microRNAs and biological processes associated with drug resistance in ovarian and other types of cancer. These results indicate that NEK2 contributes to drug resistance in ovarian cancer and it may be an important therapeutic target.

Ovarian cancer is a fatal gynecological cancer and a major cause of cancer-related mortality worldwide. The main limitation to a successful treatment for ovarian cancer is the development of drug resistance to combined chemotherapy. Tumor suppressor genes (TSGs) are wild-type alleles of genes which play regulatory roles in diverse cellular activities, and whose loss of function contributes to the development of cancer. It has been demonstrated that TSGs contribute to drug resistance in several types of solid tumors. However, an overview of the contribution of TSGs to drug resistance in ovarian cancer has not previously been reported. In this study, 15 TSGs responding to drug resistance in ovarian cancer were reviewed to determine the relationship of TSGs with ovarian cancer drug resistance. Furthermore, gene/protein-interaction and bio-association analysis were performed to demonstrate the associations of these TSGs and to mine the potential drug resistance-related genes in ovarian cancer. We observed that the 15 TSGs had close interactions with each other, suggesting that they may contribute to drug resistance in ovarian cancer as a group. Five pathways/processes consisting of DNA damage, apoptosis, cell cycle, DNA binding and methylation may be the key ways with which TSGs participate in the regulation of drug resistance. In addition, ubiquitin C (UBC) and six additional TSGs including the adenomatous polyposis coli gene (APC), death associated protein kinase gene (DAPK), pleiomorphic adenoma gene-like 1 (PLAGL1), retinoblastoma susceptibility gene (RB1), a gene encoding an apoptosis-associated speck-like protein (PYCARD/ASC) and tumor protein 63 (TP63), which had close interactions with the 15 TSGs, are potential drug resistance-related genes in ovarian cancer.

Total of 25 oncogenes contributing to drug resistance in ovarian cancer was integrated and further analyzed. An oncogene-mediated drug resistance pathway that explains the associations of 21 of these oncogenes in drug resistance was drafted on the basis of previously published papers. The downstream location of v-akt murine thymoma viral oncogene (AKT) and B-cell CLL/lymphoma 2-associated X protein (BAX) with respect to many other oncogenes was determined, indicating that the two genes may play a central role, and the AKT- and BAX-mediated signaling are the main pathways accounting for the involvement of oncogenes in drug resistance in ovarian cancer. Besides, the annotation of biological process indicated that the apoptosis (cell death) and phosphorylation (phosphate metabolic process) might be the two major biological routes through which oncogenes contribute to drug resistance in ovarian cancer. In addition, on the basis of the comprehensive analysis of microRNA-mRNA interactions, 11 microRNAs were identified to be targeted at least 7 of the 25 oncogenes, indicating that those microRNAs could be an important regulator of the 25 oncogenes. Collectively, by integrating and further analyzing the available data on these oncogenes, this study contributes to improving our understanding of the mechanisms by which their expression leads to drug resistance in this ovarian cancer.

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Ovarian cancer is the leading cause of death among malignancies of the female reproductive system. The 5-year survival rates of ovarian cancer (OC) patients are very poor as a result of recurrent disease and emergence of drug resistance; thus, studies to find predictive markers and factors for drug resistance are ongoing. In the present study, based on the microarrays from The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) profiles covering 1648 OC patients, 11 out of 136 genes that were found to be significantly dysregulated in OC were associated with overall survival (OS) in 489 OC patients of the TCGA cohort. Of these genes, CRISP3, LYVE1, OVGP1 and BCHE were identified as independent prognostic factors, with decreased expression of the first three genes predicting shorter OS, and decreased BCHE predicting longer OS. OVGP1, BCHE and further two genes, CKAP2 and CLDN10, were consistently and remarkably associated with OS when the number of patients increased from 489 to 1583, with increased CKAP2 and decreased CLDN10 predicted shorter OS; combining the four genes provided better predictions. Associations among the four genes with OS in subgroups of OC were further verified. Downregulation of OVGP1 was significantly associated with shorter OS in all subgroups of OC patients, including subgroups of 752 patients treated with chemotherapy regimens containing taxol, 763 with both platin and taxol, 1364 with platin, 371 patients with grade 1-2 disease, 968 with grade 3 disease, 1148 with stage III-IV disease, and 439 with TP53 mutations. In addition, CKAP2 expression was significantly associated with shorter OS in 515 OC patients who had low CA125 levels. Furthermore, comprehensive analyses that including RT-qPCR, bioinformatics analysis and clinical data revealed an association of CKAP2, BCHE, CLDN10 and OVGP1 with drug resistance in OC. The genes identified in the present study might be prognostic factors as well as potential therapeutic targets in the treatment of OC.

BackgroundHepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths. The average survival and 5-year survival rates of HCC patients still remains poor. Thus, there is an urgent need to better understand the mechanisms of cancer progression in HCC and to identify useful biomarkers to predict prognosis.MethodsPublic data portals including Oncomine, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) profiles were used to retrieve the HCC-related microarrays and to identify potential genes contributed to cancer progression. Bioinformatics analyses including pathway enrichment, protein/gene interaction and text mining were used to explain the potential roles of the identified genes in HCC. Quantitative real-time polymerase chain reaction analysis and Western blotting were used to measure the expression of the targets. The data were analysed by SPSS 20.0 software.ResultsWe identified 80 genes that were significantly dysregulated in HCC according to four independent microarrays covering 386 cases of HCC and 327 normal liver tissues. Twenty genes were consistently and stably dysregulated in the four microarrays by at least 2-fold and detection of gene expression by RT-qPCR and western blotting showed consistent expression profiles in 11 HCC tissues compared with corresponding paracancerous tissues. Eleven of these 20 genes were associated with disease-free survival (DFS) or overall survival (OS) in a cohort of 157 HCC patients, and eight genes were associated with tumour pathologic PT, tumour stage or vital status. Potential roles of those 20 genes in regulation of HCC progression were predicted, primarily in association with metastasis. INTS8 was specifically correlated with most clinical characteristics including DFS, OS, stage, metastasis, invasiveness, diagnosis, and age.ConclusionThe significantly dysregulated genes identified in this study were associated with cancer progression and prognosis in HCC, and might be potential therapeutic targets for HCC treatment or potential biomarkers for diagnosis and prognosis.Electronic supplementary materialThe online version of this article (doi:10.1186/s13046-016-0403-2) contains supplementary material, which is available to authorized users.

Abstract. Emerging drug resistance in epithelial ovarian cancer (EOC) thwarted progress in platinum-based chemotherapy, resulting in increased mortality, morbidity and healthcare costs. The aim of this study was to detect the responses induced by chemotherapy at protein and metabolite levels, and to search for new plasma markers that can predict resistance to platinum-based chemotherapy in EOC patients, leading to improved clinical response rates. Serum samples were collected and subjected to proteomic relative quantitation analysis and metabolomic analysis. Differentially expressed proteins and metabolites were subjected to bioinformatics and statistical analysis. Proteins that played a key role in platinum resistance were validated by western blotting and enzyme-linked immunosorbent assay (ELISA). Metabolites that were the main contributors to the groups and closely with clinical characteristics were identified based on the database using nuclear magnetic resonance (NMR). In total, 248 proteins from two independent experiments were identified using isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomic approach. Among them, FN1, SERPINA1, GPX3 and ORM1 were chosen for western blotting and ELISA validation. Platinum resistance likely associated with differentially expressed proteins and FN1, SERPINA1 and ORM1 may play a positive role in chemotherapy. HPLC-MS analysis of four groups revealed a total of 25,800 metabolic features, of which six compounds were chosen for candidate biomarkers and identified based on the database using NMR. The metabolic signatures of normal control (NC), platinum-sensitive (PTS) and platinum-resistant (PTR) groups were clearly separated from each other.Those findings may provide theoretical clues for the prediction of chemotherapeutic response and reverse of drug resistance, even lead to novel targets for therapeutic intervention.