Novel targets and clinically relevant models for ovarian cancer

Ovarian cancer, with high-grade serous ovarian cancer (HGSOC) as the most common histological subtype, has the highest mortality among all gynaecological cancers. HGSOC is generally diagnosed in an advanced stage with the majority of cases showing platinum resistant relapses. Therefore, 5-year survival rates for advanced stage disease remained low over the last decades. Genomic interrogation of large numbers of patient samples has improved our understanding about the complexity of HGSOCs in terms of genetic aberrations and intra-tumoural heterogeneity and underscored their lack of targetable mutations. Clearly, experimental models are required in which resistance to platinum therapy and the use of novel therapeutics can be studied. Several novel genetically engineered mouse models (GEMMs) have recently emerged, in which pathogenic mutations are introduced that mimic human pathogenesis. With patient-tailored therapy as a new treatment modality in multiple cancer types, also more personalised models for HGSOC are arising. DNA repair status of the tumour can be obtained using ex vivo tumour tissue slices and novel therapeutic strategies can be tested using patient-derived xenografts (PDXs). Previously, tracking changes in tumours during treatment and after relapse was hardly possible because of the invasiveness of serial sampling without contributing to personal care of patients. This problem might be solved in the near future by profiling tumours and analysing circulating cell-free tumour DNA or circulating tumour cells. This review will focus on recently developed models and platforms suitable for investigating responses to platinum-based chemotherapy, with BRCA1/2 - mutation carriers and BRCAness ovarian cancer patients as an example. We will discuss how various models can be combined to study resistance mechanisms, to predict responses by measuring DNA repair capacity of tumours and to use synthetic lethality as a way to improve therapy outcomes in specific subgroups among ovarian cancer patients.