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Mouse Models of Ovarian Cancer
The study of ovarian carcinogenesis has been limited by the lack of appropriate tumor models. Presently, there are no developed experimental systems that recapitulate genetic changes that occur during ovarian carcinoma initiation or simulate the complex interactions between ovarian surface epithelial and stromal cells. The focus of our current research involves developing mouse models for early and metastatic ovarian cancer. We are developing mouse models in which defined multiple genetic lesions can be introduced into mouse ovarian stromal and/or surface epithelial cells in culture or in mouse ovaries. This system is based on avian RCAS virus delivery to the cells that are programmed to express the avian TVA receptor under the control of a tissue-specific promoter. The expression of the TVA receptor in mouse ovarian cells renders the cells susceptible to infection with RCAS viruses. RCAS vectors can be designed to carry oncogenes, marker genes, Cre recombinase, or activators of inducible systems into the TVA receptor-expressing cells. Various candidate genes that are thought to play a role in ovarian cancer can be introduced simultaneously or sequentially into mouse ovarian cells. Since multiple genes can be delivered to the same cell, it is possible to study the collaboration of biochemical pathways in ovarian cancer induction and progression.
Ovulatory Wound Repair in a Mouse Model
Epidemiologic studies show a direct correlation between the number of ovulatory cycles and the risk of ovarian cancer, suggesting that ovulation may play a role in ovarian carcinogenesis. It is thought that the repair of the ovulatory wound results in rapid proliferation of the ovarian surface epithelial (OSE) cells, which may increase the frequency and accumulation of spontaneous mutations. Additionally, ovulation may lead to structural disorganization or entrapment of OSE cells in the underlying stroma with subsequent formation of inclusion cysts. In order to elucidate the sequence of events involved in the pathogenesis of ovarian cancer, we conducted a thorough analysis of morphologic changes in the OSE and underlying stroma during the process of ovulation. This was accomplished using traditional immunohistochemistry (IHC) and whole-ovary IHC, a method that was devised in our laboratory. We determined that cells on the ovarian surface proliferate most extensively during antral follicle growth. Cell proliferation is less extensive during ovulatory wound repair and corpus luteum formation, and is almost nonexistent in the areas distant from follicular activity. Rather than inducing a wave of new cell proliferation, we showed that ovulatory wound repair primarily involves a highly organized migration of epithelial and stromal cells at the wound edge.
Functional Characterization of BRCA1-Associated Ovarian Cancer Genes
Understanding the underlying genetic changes that drive ovarian cancer progression could have a major impact on the diagnosis and treatment of the disease. One of the pathways known to play a role in ovarian cancer development is the BRCA pathway. Using comparative oncogenomics in BRCA1-associated human tumors and mouse models, we identified several BRCA1-associated candidate cancer genes. We are currently testing the roles of these genes in the pathophysiology of BRCA-associated ovarian cancers. These genes have the potential to serve as biomarkers of clinical response to therapies that target the BRCA pathway and thus could have a major impact on the clinical management of hereditary ovarian cancers as well as sporadic ovarian cancers that have defective components of the BRCA pathway.
Ovarian Cancer Biomarkers
Survival rates for advanced stage ovarian cancer have not changed significantly in the past 40 years, and ovarian cancer remains the most lethal gynecologic cancer in women. Our goal is to change the status quo by developing new paradigms in the laboratory and efficiently translating them into the clinic. The most common type of ovarian cancer, and the one that accounts for the majority of deaths from ovarian cancer, is serous papillary carcinoma. Approximately 20 percent of patients with this ovarian cancer subtype are intrinsically resistant to chemotherapy or develop chemoresistant disease within one year from initial treatment. A reliable method to identify these poor prognosis patients would facilitate their inclusion into clinical trials or personalized treatment strategies at an earlier point. The lack of reliable biomarkers and curative treatment strategies for ovarian cancer inspired our work aimed at identifying biomarkers for early detection, prognostication and personalization of therapy. Our laboratory identified a gene signature that is strongly correlated with poor prognosis in ovarian cancer patients. We are currently optimizing the gene signature and developing a quantitative assay for use in the clinical setting.
Epithelial-Stromal Interactions in Tumor Progression
Stroma is universally found in malignant tumors, and pathologists use the abundance and density of stroma to predict poor prognosis. Despite its universal presence and wide clinical use as a prognostic marker, the origin of cancer-associated stroma is still the subject of extensive debate. The dynamic bi-directional interaction between the cancer cells and stroma is also not well understood, although it is becoming increasingly apparent that the stroma can modify the aggressiveness of tumor cells and that tumor cells re-program the stroma to generate a nurturing microenvironment that is crucial for tumor survival, progression, and metastasis. Because of the prominent role of stroma in most aspects of tumor progression, it is believed that rational anticancer therapy design should not only target the cancer cells but also the stroma. Our lab is studying the interaction between cancer cells and stroma with the goal of identifying molecular events whose disruption may undermine tumor progression.
Succinate dehydrogenase (SDH) is a mitochondrial metabolic enzyme complex involved in both the electron transport chain and the citric acid cycle. We identified that dysregulation of SDH components also occurs in serous ovarian cancer, particularly the SDH subunit SDHB. Targeted-knockdown of Sdhb in mouse ovarian cancer cells resulted in enhanced proliferation and an epithelial-to-mesenchymal transition (EMT). Bioinformatics analysis revealed that decreased SDHB expression leads to a transcriptional upregulation of genes involved in metabolic networks affecting histone methylation. We confirmed that Sdhb knockdown leads to a hypermethylated epigenome that is sufficient to promote EMT. Metabolically, the loss of Sdhb resulted in reprogrammed carbon source utilization and mitochondrial dysfunction. This altered metabolic state of Sdhb knockdown cells rendered them hypersensitive to energy stress. These data illustrate how SDH dysfunction alters the epigenetic and metabolic landscape in ovarian cancer. By analyzing the involvement of this enzyme in transcriptional and metabolic networks, we found a metabolic Achilles’ heel that can be exploited therapeutically. Analyses of this type provide an understanding how specific perturbations in cancer metabolism may lead to novel anti-cancer strategies.