In vivo modeling of metastatic human high-grade serous ovarian cancer in mice

Metastasis is responsible for 90% of human cancer mortality, yet it remains a challenge to model human cancer metastasis in vivo. Here we describe mouse models of high-grade serous ovarian cancer, also known as high-grade serous carcinoma (HGSC), the most common and deadliest human ovarian cancer type. Mice genetically engineered to harbor Dicer1 and Pten inactivation and mutant p53 robustly replicate the peritoneal metastases of human HGSC with complete penetrance. Arising from the fallopian tube, tumors spread to the ovary and metastasize throughout the pelvic and peritoneal cavities, invariably inducing hemorrhagic ascites. Widespread and abundant peritoneal metastases ultimately cause mouse deaths (100%). Besides the phenotypic and histopathological similarities, mouse HGSCs also display marked chromosomal instability, impaired DNA repair, and chemosensitivity. Faithfully recapitulating the clinical metastases as well as molecular and genomic features of human HGSC, this murine model will be valuable for elucidating the mechanisms underlying the development and progression of metastatic ovarian cancer and also for evaluating potential therapies. Author summary Rarely does an experimental model fully replicate the clinical metastases of a human malignancy. Faithfully representing the clinical metastases of human high-grade serous ovarian cancer with complete penetrance, coupled with histopathological, molecular, and genomic similarities, these mouse models, particularly one harboring mutant p53, will be vital to elucidating the underlying pathogenesis of human ovarian cancer. In-depth understanding of the development and progression of ovarian cancer is crucial to medical advances in the early detection, effective treatment, and prevention of ovarian cancer. Also, these robust mouse models, as well as cell lines established from the mouse primary and metastatic tumors, will serve as useful preclinical tools to evaluate therapeutic target genes and new therapies in ovarian cancer.