Ovarian carcinoma is the most deadly gynecologic cancer, causing almost 15,000 deaths annually in the U.S. Most women with ovarian cancer are treated with a combination of surgery and platinum chemotherapy. Even though the majority of women respond well to this treatment initially, eventually their cancers recur and develop resistance to platinum and other types of chemotherapy. Accordingly, new treatment modalities are urgently needed for both primary and recurrent disease.
PARP inhibitors are relatively new therapeutic agents that have demonstrated substantial promise in early phase clinical trials, particularly in hereditary ovarian carcinoma that occurs in women with inherited BRCA1 and BRCA2 mutations. PARP inhibitors are also likely to be effective in a subset of nonhereditary (sporadic) ovarian carcinomas, but which subset of cancers will respond is not certain. Because the addition of biologic therapies like PARP inhibitors to standard chemotherapy has the potential to not only improve outcomes, but also increase cost and toxicity, it is important to develop tests or biomarkers that help identify women most likely to benefit from the therapy. It is also useful to predict which cancers are resistant to platinum and should be treated with other drugs. Currently, such tests or biomarkers have not been identified.
We propose to apply modern sequencing and molecular technologies to existing samples at two institutions to develop a biomarker of response and resistance to DNA damaging agents. We will then test the validity of this biomarker in a mouse model of ovarian cancer. These experiments are designed to lead to a clinically useful test that can identify the subset of women with ovarian carcinoma most likely to benefit from PARP inhibitor treatment and those unlikely to respond to PARP inhibitors or to platinum chemotherapy. Such a predictive test will allow personalized treatments for women with ovarian cancer, which is likely to improve survival and quality of life. This strategy will also allow women with ovarian cancer to avoid treatments unlikely to work, thereby avoiding unnecessary cost and toxicity.
- Paul Haluska MD, PhD – Mayo Clinic
- Scott H. Kaufmann, MD, PhD – Mayo Clinic