Despite advances in treatment strategies, ovarian cancer remains the deadliest gynecological malignancy and the 5th largest cancer killer in women. Located deep in the body, with few early symptoms and no effective screening technique, ovarian cancer has remained stubbornly difficult to understand, much less effectively combat. Ovarian cancer is almost always discovered at an advanced stage. Therefore, women at high risk for ovarian cancer are usually counseled to have a prophylactic oophorectomy, which can reduce risk of death from cancer but comes with associated morbidity and may reduce life span. The key to reducing the mortality from ovarian cancer is to develop an effective early detection technique. The investigators have shown that high resolution optical imaging, including optical coherence tomography (OCT) fluorescence imaging (FI), and multiphoton microscopy (MPM) can differentiate normal from advanced stage cancer in humans and mouse models. However, imaging biomarkers of early stage cancer are not yet known. Developing imaging markers is highly impractical in women due to the low number of early stage cancers detected, and the inability to follow cancer development over time. A relevant, validated mouse model of early stage high grade serous carcinoma (HGSC) is needed to develop imaging biomarkers that could be translated to an early detection system for women.
Specific Aim 1 : Validate a model for early stage ovarian cancer. The MISIIR-TAg mouse develops spontaneous bilateral HGSC. Because most women who develop ovarian cancer are post-menopausal, we will augment this transgenic model with administration of 4-vinylcyclohexene diepoxide (VCD), which induces selective follicular atresia and mimics menopause. At very early time points in cancer development, we will examine ovarian/fallopian tube morphology, gene expression, and cell surface marker expression, creating a roadmap of changes that occur during early OC. We will compare our findings on gene expression to those seen in women by comparison to published gene atlases and curated data sets, as well as validating select cell surface markers in mouse and human tissue microarrays.
Specific Aim 2. Develop imaging biomarkers of early stage ovarian cancer. Using the validated mouse model, we will obtain in vivo optical images and develop qualitative and quantitative optical image features of ovaries and fallopian tubes that identify cancer at the earliest time points. We will follow mice over time, and test sensitivity and specificity of these in vivo image markers for single and multiple modalities to determine the earliest time point that cancer can reliably be detected. Additionally, we will develop contrast agents targeted to overexpressed cell surface markers, for potential increase in sensitivity. At the end of this project, we will have the information necessary to develop a viable optical imaging method for early detection of HGSC, which has the potential to dramatically reduce mortality from this disease.
There is currently no acceptable screening method for ovarian cancer, and most cases are detected when the disease is widespread and likely to be deadly. We propose to develop and validate a novel, post-menopausal mouse model of ovarian cancer, and to use this model to discover image markers of early disease. These markers can be translated into an imaging system that enables early detection of ovarian cancer and saves lives.
