OBJECTIVES: Ovarian cancer remains a major health problem for women. Although there is considerable clinico-pathological heterogeneity, the molecular genetic basis of ovarian cancer remains poorly understood. Recently, high-resolution genomic maps generated by genome-wide SNP analyses and novel sequencing technologies, have started to dissect the genetic basis of ovarian cancer. METHODS: Here, we will describe our first insights on how somatic mutations may contribute to the diagnostic re-classification of ovarian cancer. We will discuss how copy number alterations and epigenetic changes represent promising biomarkers to predict resistance to treatment in ovarian cancer, and will also highlight how some of the recently-discovered microRNAs might represent interesting therapeutic targets for ovarian cancer. RESULTS AND CONCLUSIONS: Future studies, such as the Cancer Genome Atlas Project, involving a large number of ovarian tumors and combining various high-throughput genetic technologies with sophisticated integrative bioinformatic analyses, will be required and are expected to fine-map the full genetic spectrum of ovarian cancer. It is hoped, however, that once the molecular genetic basis of ovarian cancer is understood, this will lead to better and personalized treatments for ovarian cancer.