Predictive modeling of gene mutations for the survival outcomes of epithelial ovarian cancer patients.

Epithelial ovarian cancer (EOC) has a low overall survival rate, largely due to frequent recurrence and acquiring resistance to platinum-based chemotherapy. EOC with homologous recombination (HR) deficiency has increased sensitivity to platinum-based chemotherapy because platinum-induced DNA damage cannot be repaired. Mutations in genes involved in the HR pathway are thought to be strongly correlated with favorable response to treatment. Patients with these mutations have better prognosis and an improved survival rate. On the other hand, mutations in non-HR genes in EOC are associated with increased chemoresistance and poorer prognosis. For this reason, accurate predictions in response to treatment and overall survival remain challenging. Thus, analyses of 360 EOC cases on NCI's The Cancer Genome Atlas (TCGA) program were conducted to identify novel gene mutation signatures that were strongly correlated with overall survival. We found that a considerable portion of EOC cases exhibited multiple and overlapping mutations in a panel of 31 genes. Using logistical regression modeling on mutational profiles and patient survival data from TCGA, we determined whether specific sets of deleterious gene mutations in EOC patients had impacts on patient survival. Our results showed that six genes that were strongly correlated with an increased survival time are BRCA1, NBN, BRIP1, RAD50, PTEN, and PMS2. In addition, our analysis shows that six genes that were strongly correlated with a decreased survival time are FANCE, FOXM1, KRAS, FANCD2, TTN, and CSMD3. Furthermore, Kaplan-Meier survival analysis of 360 patients stratified by these positive and negative gene mutation signatures corroborated that our regression model outperformed the conventional HR genes-based classification and prediction of survival outcomes. Collectively, our findings suggest that EOC exhibits unique mutation signatures beyond HR gene mutations. Our approach can identify a novel panel of gene mutations that helps improve the prediction of treatment outcomes and overall survival for EOC patients.

Gene expression of non-homologous end-joining pathways in the prognosis of ovarian cancer.

Ovarian cancer is the deadliest gynecologic malignancy in women, with a 46% five-year overall survival rate. The objective of the study was to investigate the effects of non-homologous end-joining (NHEJ) genes on clinical outcomes of ovarian cancer patients. To determine if these genes act as prognostic biomarkers of mortality and disease progression, the expression profiles of 48 NHEJ-associated genes were analyzed using an array of statistical and machine learning techniques: logistic regression models, decision trees, naive-Bayes, two sample t-tests, support vector machines, hierarchical clustering, principal component analysis, and neural networks. In this process, the correlation of genes with patient survival and disease progression and recurrence was noted. Also, multiple features from the gene set were found to have significant predictive capabilities. APTX, BRCA1, PAXX, LIG1, and TP53 were identified as most important out of all the candidate genes for predicting clinical outcomes of ovarian cancer patients.

In silico screening identifies a novel small molecule inhibitor that counteracts PARP inhibitor resistance in ovarian cancer.

Poly ADP-ribose polymerase (PARP) inhibitors are promising targeted therapy for epithelial ovarian cancer (EOC) with BRCA mutations or defective homologous recombination (HR) repair. However, reversion of BRCA mutation and restoration of HR repair in EOC lead to PARP inhibitor resistance and reduced clinical efficacy of PARP inhibitors. We have previously shown that triapine, a small molecule inhibitor of ribonucleotide reductase (RNR), impaired HR repair and sensitized HR repair-proficient EOC to PARP inhibitors. In this study, we performed in silico screening of small molecule libraries to identify novel compounds that bind to the triapine-binding pocket on the R2 subunit of RNR and inhibit RNR in EOC cells. Following experimental validation of selected top-ranking in silico hits for inhibition of dNTP and DNA synthesis, we identified, DB4, a putative RNR pocket-binding inhibitor markedly abrogated HR repair and sensitized BRCA-wild-type EOC cells to the PARP inhibitor olaparib. Furthermore, we demonstrated that the combination of DB4 and olaparib deterred the progression of BRCA-wild type EOC xenografts and significantly prolonged the survival time of tumor-bearing mice. Herein we report the discovery of a putative small molecule inhibitor of RNR and HR repair for combination with PARP inhibitors to treat PARP inhibitor-resistant and HR repair-proficient EOC.