The promise and challenge of ovarian cancer models

The complexity and heterogeneity of ovarian cancer cases are difficult to reproduce in in vitro studies, which cannot adequately elucidate the molecular events involved in tumor initiation and disease metastasis. It has now become clear that, although the multiple histological subtypes of ovarian cancer are being treated with similar surgical and therapeutic approaches, they are in fact characterized by distinct phenotypes, cell of origin, and underlying key genetic and genomic alterations. Consequently, the development of more personalized treatment methodologies, which are aimed at improving patient care and prognosis, will greatly benefit from a better understanding of the key differences between various subtypes. To accomplish this, animal models of all histotypes need to be generated in order to provide accurate in vivo platforms for research and the testing of targeted treatments and immune therapies. Both genetically engineered mouse models (GEMMs) and xenograft models have the ability to further our understanding of key mechanisms facilitating tumorigenesis, and at the same time offer insight into enhanced imaging and treatment modalities. While genetic models may be better suited to examine oncogenic functions and interactions during tumorigenesis, patient-derived xenografts (PDXs) are likely a superior model to assess drug efficacy, especially in concurrent clinical trials, due to their similarity to the tumors from which they are derived. Genetic and avatar models possess great clinical utility and have both benefits and limitations. Additionally, the laying hen model, which spontaneously develops ovarian tumors, has inherent advantages for the study of epithelial ovarian cancer (EOC) and recent work champions this model especially when assessing chemoprevention strategies. While high-grade ovarian serous tumors are the most prevalent form of EOC, rarer ovarian cancer variants, such as small cell ovarian carcinoma of the hypercalcemic type and transitional cell carcinoma, or non-epithelial tumors, including germ cell tumors, will also benefit from the generation of improved models to advance our understanding of tumorigenic mechanisms and the development of selective therapeutic options.