ABSTRACT
BACKGROUND: Despite improvements in diagnostics and treatment, the clinical outcome of epithelial ovarian cancer remains poor over the last three decades. Recent high-throughput genomic studies have demonstrated ovarian cancer as a highly heterogeneous entity with distinctive molecular signatures among different or even within the same histotype. In this article, we review the molecular genetics of epithelial ovarian cancer and how they have been translated into modern clinical trials, as well as their implications in patient stratification for more targeted and personalized approaches. PATIENTS AND METHODS: Multiple genomic studies were collected to summarize the major advances in understanding ovarian cancer-associated molecular abnormalities with emphasis on their potential clinical applicability to rationalize the design of recent clinical trials. RESULTS: The clinical management of ovarian cancer can significantly benefit from comprehensive molecular profiling studies, which have uncovered the distinctiveness of ovarian cancer subsets bearing characteristic genomic aberrance and consequentially dysregulated genes and pathways underlying the tumor progression and chemoresistance. Genomics studies have demonstrated a powerful tool to delineate the molecular basis responsible for diverse clinical behaviors associated with tumor histology and grade. In addition, molecular signatures obtained by integrated 'omics' analyses have promised opportunities for novel therapeutic or stratification biomarkers to tailor current clinical management as well as novel predictive tools of clinical end points including patient prognosis and therapeutic efficacy. CONCLUSIONS: Recent progress in understanding the molecular landscape of ovarian cancer has profoundly shifted the design of clinical trials from empirical, unitary paradigms to more rationalized and personalized regimes. Correspondingly, a promising prospective has emerged for ovarian cancer patients to have considerably improved outcome upon careful alignment of patient characteristics, therapeutic biomarkers and targeting approaches. Nevertheless, extensive validation and inference of potential biomarkers are pressing demands on both bioinformatic and biological levels to warrant sufficient clinical relevance for potential translation, so that the performance of related clinical trial can be well predicted and achieved.
