More and more, researchers are learning that ovarian cancer is not one disease but, rather, a number of distinct diseases with different genetic, and likely different environmental, risk factors. However, we still treat ovarian cancer as if it were a single disease, and, sadly, many women simply do not respond to current treatment options. Treatment improvements rely on understanding how tumors differ from each other and targeting treatment accordingly. This proposal explores a newly recognized and important aspect of tumor difference in women with high-grade serous cancer, the most common and deadly form of ovarian cancer.

Ovarian tumors are diagnosed by pathologists based on how the cells look under a microscope, with serous, endometrioid, mucinous, and clear cell cancers being regarded as the most common cell types or histotypes. Tumors are, additionally, grouped by their grade, which measures how different a tumor cell looks compared to a healthy cell. High-grade serous cancers (HGSC) are the largest group of tumors and account for around 65% of ovarian cancer deaths.

We have found that HGSC can be divided into four distinct groups or molecular subtypes, based on gene expression patterns. This observation is strong -- we have observed it in many groups of patients from Australia, North America, and Europe, including a very large study recently reported in the journal Nature, by The Cancer Genome Atlas (TCGA) consortium. Importantly, there is a consistent pattern of clinical outcome linked with the different subtypes. For example, median survival of women with "C2" subtype tumors is 78 months compared to 45 months in women with "C1" tumors. The consistency of these observations and the fact that subtypes are linked with different survival patterns means that the molecular subtypes need to be recognized for their different biology if we expect to treat these patients better. Molecular subtypes of breast cancer were recognized a decade ago and the research resulting from that observation has had a profound impact on understanding and treating the disease.

Our application has three parts:

1. To develop more affordable laboratory tests that can identify the four molecular subtypes of HGSC using a wide range of samples collected for research -- freshly frozen, fixed, and those embedded in paraffin.

2. To use the validated tests to group HGSC into the four molecular subtypes from thousands of patients, collected through an international collaborative network, and to link the subtypes to clinical outcome.

3. To find risk factors for the four molecular subtypes of HGSC including newly discovered genetic variants as well as environmental and lifestyle factors.

Our work will have several important outcomes. We will develop laboratory tests for the molecular subtypes that are accessible to the larger ovarian cancer research community, so that the unique biology of the HGSC subtypes can be studied by a wider group of researchers. We believe that genetic and environmental risk factors may link differently with the specific molecular subtypes, which will help us identify groups of women at higher risk of developing ovarian cancer, as well as identify cancer prevention strategies for these high-risk women. Defining risk factors and the molecular "circuitry" of HGSC should impact on screening, prevention, and identification of new therapies.

The work can progress rapidly and accordingly we have requested funding over 2 rather than 3 years. We have substantial preliminary data that demonstrates proof-of-principle for two tests in development and we will be taking advantage of large numbers of previously collected samples and data through a large and well-organized research collaborative that, together, provides high statistical power for the proposed study. The work leverages millions of dollars of past and current research effort and is uniquely placed, given our access to previously molecularly subtyped HGSC samples, experience in the biology of HGSC, and integration in key research networks that have a proven track record of working together efficiently.