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Epithelial ovarian cancer (EOC) is an infrequent but highly lethal disease, almost invariably treated with platinum‐based therapies. Improving the response to platinum represents a great challenge, since it could significantly impact on patient survival. Here, we report that silencing or pharmacological inhibition of CDK6 increases EOC cell sensitivity to platinum. We observed that, upon platinum treatment, CDK6 phosphorylated and stabilized the transcription factor FOXO3, eventually inducing ATR transcription. Blockage of this pathway resulted in EOC cell death, due to altered DNA damage response accompanied by increased apoptosis. These observations were recapitulated in EOC cell lines in vitro , in xenografts in vivo , and in primary tumor cells derived from platinum‐treated patients. Consistently, high CDK6 and FOXO3 expression levels in primary EOC predict poor patient survival. Our data suggest that CDK6 represents an actionable target that can be exploited to improve platinum efficacy in EOC patients. As CDK4/6 inhibitors are successfully used in cancer patients, our findings can be immediately transferred to the clinic to improve the outcome of EOC patients.

Next-generation sequencing (NGS) technology has advanced knowledge of the genomic landscape of ovarian cancer, leading to an innovative molecular classification of the disease. However, patient survival and response to platinum-based treatments are still not predictable based on the tumor genetic profile. This retrospective study characterized the repertoire of somatic mutations in advanced ovarian cancer to identify tumor genetic markers predictive of platinum chemo-resistance and prognosis. Using targeted NGS, 79 primary advanced (III&ndash, IV stage, tumor grade G2-3) ovarian cancer tumors, including 64 high-grade serous ovarian cancers (HGSOCs), were screened with a 26 cancer-genes panel. Patients, enrolled between 1995 and 2011, underwent primary debulking surgery (PDS) with optimal residual disease (RD &lt, 1 cm) and platinum-based chemotherapy as first-line treatment. We found a heterogeneous mutational landscape in some uncommon ovarian histotypes and in HGSOC tumor samples with relevance in predicting platinum sensitivity. In particular, we identified a poor prognostic signature in patients with HGSOC harboring concurrent mutations in two driver actionable genes of the panel. The tumor heterogeneity described, sheds light on the translational potential of targeted NGS approach for the identification of subgroups of patients with distinct therapeutic vulnerabilities, that are modulated by the specific mutational profile expressed by the ovarian tumor.

Background Risk of relapse or progression remains high in the treatment of most patients with epithelial ovarian cancer, and development of a molecular predictor could be a valuable tool for stratification of patients by risk. We aimed to develop a microRNA (miRNA)-based molecular classifier that can predict risk of progression or relapse in patients with epithelial ovarian cancer.Methods We analysed miRNA expression profiles in three cohorts of samples collected at diagnosis. We used 179 samples from a Multicenter Italian Trial in Ovarian cancer trial (cohort OC179) to develop the model and 263 samples from two cancer centres (cohort OC263) and 452 samples from The Cancer Genome Atlas epithelial ovarian cancer series (cohort OC452) to validate the model. The primary clinical endpoint was progression-free survival, and we adapted a semi-supervised prediction method to the miRNA expression profile of OC179 to identify miRNAs that predict risk of progression. We assessed the independent prognostic role of the model using multivariable analysis with a Cox regression model.Findings We identified 35 miRNAs that predicted risk of progression or relapse and used them to create a prognostic model, the 35-miRNA-based predictor of Risk of Ovarian Cancer Relapse or progression (MiROvaR). MiROvaR was able to classify patients in OC179 into a high-risk group (89 patients; median progression-free survival 18 months [95% CI 15-22]) and a low-risk group (90 patients; median progression-free survival 38 months [24-not estimable]; hazard ratio [HR] 1.85 [1.29-2.64], p=0.00082). MiROvaR was a significant predictor of progression in the two validation sets (OC263 HR 3.16, 95% CI 2.33-4.29, p