In silico analyses identify gene-sets, associated with clinical outcome in ovarian cancer: role of mitotic kinases.

INTRODUCTION: Accurate assessment of prognosis in early stage ovarian cancer is challenging resulting in suboptimal selection of patients for adjuvant therapy. The identification of predictive markers for cytotoxic chemotherapy is therefore highly desirable. Protein kinases are important components in oncogenic transformation and those relating to cell cycle and mitosis control may allow for identification of high-risk early stage ovarian tumors. METHODS: Genes with differential expression in ovarian surface epithelia (OSE) and ovarian cancer epithelial cells (CEPIs) were identified from public datasets and analyzed with dChip software. Progression-free (PFS) and overall survival (OS) associated with these genes in stage I/II and late stage ovarian cancer was explored using the Kaplan Meier Plotter online tool. RESULTS: Of 2925 transcripts associated with modified expression in CEPIs compared to OSE, 66 genes coded for upregulated protein kinases. Expression of 9 of these genes (CDC28, CHK1, NIMA, Aurora kinase A, Aurora kinase B, BUB1, BUB1ßB, CDKN2A and TTK) was associated with worse PFS (HR:3.40, log rank p<0.001). The combined analyses of CHK1, CDKN2A, AURKA, AURKB, TTK and NEK2 showed the highest magnitude of association with PFS (HR:4.62, log rank p<0.001). Expression of AURKB predicted detrimental OS in stage I/II ovarian cancer better than all other combinations Conclusion: Genes linked to cell cycle control are associated with worse outcome in early stage ovarian cancer. Incorporation of these biomarkers in clinical studies may help in the identification of patients at high risk of relapse for whom optimizing adjuvant therapeutic strategies is needed.

Transcriptomic analyses identify association between mitotic kinases, PDZ-binding kinase and BUB1, and clinical outcome in breast cancer.

Protein kinases are important components in oncogenic transformation of breast cancer. Evaluation of upregulated genes that codify for protein kinases could be used as biomarkers to predict clinical outcome. Gene expression and functional analyses using public datasets were performed to identify differential gene expression and functions in basal-like tumors compared with normal breast tissue. Overall survival (OS) associated with upregulated genes was explored using the KM Plotter online tool. The prognostic influence of these genes in luminal tumors and systemically untreated patients was also assessed. Of the 426 transcripts identified in basal-like tumors, 11 genes that coded for components of protein kinases were upregulated with more than a fourfold change. Regulation of cell cycle was an enriched function containing 10 of these 11 identified genes. Among them, expression of four genes, BUB1ß, CDC28, NIMA, and PDZ binding kinase, were all associated with improved OS when using at least one probe in the basal-like subtype. Two genes, BUB1ß and PDZ binding kinase, showed consistent association with improved OS irrespective of the gene probe used for the analysis. No association was observed for these genes with relapse-free survival. In contrast, both BUB1ß and PDZ binding kinase showed worse OS in luminal tumors and in a cohort of systemically untreated patients. BUB1ß and PDZ binding kinase are associated with improved OS in basal-like tumors and worse OS in luminal and untreated patients. The association with a better outcome in basal-like tumors could be due to a more favorable response to chemotherapy.