Researchers at the USC Norris Comprehensive Cancer Center have been awarded nearly $4 million for two ovarian cancer research project grants from the National Institutes of Health. Both projects utilize the multicenter Ovarian Cancer Association Consortium (OCAC) to perform a large population-based analysis of ovarian cancer patients and their tissues.
The first project, led by Simon Gayther, professor of preventive medicine at the Keck School of Medicine of USC, and Susan Ramus, associate professor of preventive medicine, is aimed at finding moderate risk genes for ovarian cancer, with the goal of improving clinical risk prediction and prevention.
The project, which will receive $2 million over five years, is a high-throughput sequencing study of ovarian cancer patients, using data from the ovarian cancer families and from ovarian cancer populations through OCAC.
The project has the potential to be rapidly translated into the clinical setting to reduce mortality caused by ovarian cancer.
“We expect to identify, in the population, ovarian cancer susceptibility genes that confer substantial risks of ovarian cancer,” Gayther said. “We will calculate these risks by comparing the frequency of gene mutations in ovarian cancer cases compared to unaffected controls.
“We expect the size of disease risks caused by these genes to be quite substantial, and anticipate this information could soon be used to screen unaffected women in the population to identify those individuals at greatest risk,” he explained. “Preventive surgery could then be used to remove the ovarian cancer risks in these women.”
The second project, led by Ramus, will identify and confirm molecular markers for ovarian cancer to stratify subtypes and locate potential targets for treatment. The research program received nearly $1.9 million in funding and represents the world’s largest ovarian cancer tumor tissue study.
“Although successful in other cancers, there is currently no treatment for ovarian cancer based on tumor profiling,” said Gayther, who is also involved in the second project. “Five main histological types of ovarian cancer have been described and recently, expression profiling has been used to divide the most common and aggressive type — high-grade serous ovarian cancer — into four different groups.
“We hope that better defining groups of patients with similar pathways of tumor progression will lead to the development of much needed new, effective personalized treatments for ovarian cancer.”