1. Examining risk factors by tumor subtype. One broad research goal of the OC3 is to examine whether associations of putative ovarian cancer risk factors differ by ovarian cancer subtype. Thus far, we have defined subtypes by tumor histology/grade, dominance (as a surrogate for cell of origin), aggressiveness (tumors fatal within three years vs. all others), and anatomic location of the tumor. Future research in the OC3 will continue to explore multi-faceted approaches to characterizing tumor heterogeneity and the associations of tumor subtypes with known and suspected risk factors.

 

2. Risk prediction. Although there are several known ovarian cancer risk factors, the ability to identify women at high risk remains limited. Thus, a major goal of the OC3 is to improve ovarian cancer risk prediction. Given the unique risk factor profiles of different ovarian cancer subtypes observed in previous OC3 research, and the poor performance of the model in predicting serous cancer (the most deadly subtype), the OC3 is focused on determining whether risk prediction models for ovarian cancer can be improved by accounting for differential associations by cancer phenotype.

 

3. Identifying factors associated with survival. Outside of surgery and chemotherapy, few factors have been associated with improved survival after diagnosis with ovarian cancer. An important goal of the OC3 is to conduct research to improve understanding of the impact of pre- and post-diagnosis exposures, and their interactions with tumor subtype, on survival.

 

4. Data repository expansion for future research aims. An important goal of the OC3 is to create an infrastructure with a core dataset of important variables for ovarian cancer epidemiology that will be available for future efforts to study ovarian cancer risk. Therefore, the OC3 plans to expand its data repository by obtaining funding to include dietary factors, updated exposure data from follow-up questionnaires, and biomarker information (both plasma/serum markers, including high-throughput omics data, and genetics) that can be used to identify new risk factors as well as early detection markers.