Predictive factors in epithelial ovarian cancer: Towards individualized patient care

Ovarian cancer is a disease with a high mortality. Most patients with epithelial ovarian cancer (EOC) present with advanced stage disease with multiple tumour deposits in the peritoneal cavity. Survival of early stages is high, yet, survival of advanced stage disease is low with a five year survival of 30%. The major problem in treatment of ovarian cancer is late detection of disease. However, still no methods have been identified to diagnose ovarian cancer in an early stage, therefore effort should be made to optimize current treatment protocols. It is known that ovarian cancer is a heterogeneous disease and response to therapy varies greatly. Yet, all patients receive the same treatment. In order to improve outcome, treatment protocols should be targeted to subgroups, selected based on predicted prognosis and response to specific therapies. In this thesis we tried to define prognostic markers and find methods to improve surgical treatment results of patients with EOC. In the first chapters we describe how subgroups can be defined based on genetic, immunological as well as clinical factors. The last chapters of this thesis focus on diagnostic methods to optimize surgery result. In summary, the studies described in this thesis shows that seemingly similar patients not only respond different to treatment, but that also molecular differences are present. We provided evidence that distinct risk groups can be defined using clinical biomarkers. This thesis emphasizes that development of new treatment modalities should focus on specific risk groups based on molecular and clinical biomarkers