A recent advance in translational oncology research has been the demonstration that the mutational status of a solid tumor can predict the therapeutic efficacy of a specific drug in a molecularly defined subset of patients. An impactful example of the study of the genomic prediction of therapeutic efficacy that has transformed ovarian cancer treatment is that of poly (ADP-ribose) polymerase inhibitors (PARPi). PARPi have emerged as a novel class of drugs to treat advanced ovarian cancer, specifically, cancers that are deficient in homologous recombination (HR) repair. Unfortunately, genetic testing does not identify a significant proportion of HR deficient tumors, and it does not accurately predict the response to PARPi treatment for all patients with high-grade serous ovarian cancer. Additionally, there is considerable inter-patient heterogeneity in the response to PARPi treatment, and significantly positive responses have been observed in patients with intact HR repair functions. Determining protein-level mechanisms of PARPi sensitivity could enhance our ability to select the high-grade serous ovarian cancer patient population that would benefit the most from PARPi therapy, consequently improving survival and overall treatment response.