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Genomic instability and mutations are fundamental aspects of human malignancies, leading to progressive accumulation of the hallmarks of cancer. For some time, it has been clear that key mutations may be used both as prognostic and predictive biomarkers, the best-known examples being the presence of germline BRCA1 or BRCA2 mutations, which are not only associated with improved prognosis in ovarian cancer, but are also predictive of response to poly(ADP-ribose) polymerase (PARP) inhibitors. Although biomarkers as specific and powerful as these are rare in human malignancies, next generation sequencing and improved bioinformatic analyses are revealing mutational signatures, broader patterns of alterations in the cancer genome that have the power to reveal information about underlying driver mutational processes. Thus, the cancer genome can act as a stratification factor in clinical trials and, ultimately, will be used to drive personalised treatment decisions. In this review, we will use ovarian high grade serous carcinoma (HGSC) as an example of a disease of extreme genomic complexity that is marked by widespread copy number alterations, but which lacks powerful driver oncogene mutations. Understanding of the genomics of HGSC has led to the routine introduction of germline and somatic BRCA1/2 testing, as well as testing of mutations in other homologous recombination genes, widening the range of patients who may benefit from PARP inhibitors. We will discuss how whole genome-wide analyses, including loss of heterozygosity quantification and whole genome sequencing, may extend this paradigm to allow all patients to benefit from effective targeted therapies.