Our laboratory developed a transgenic mouse model of spontaneous epithelial ovarian cancer (EOC) in which tumors are initiated by expression of the early region of the Simian Virus 40 (SV40) under transcriptional control of the 5' upstream regulatory region of the Müllerian inhibiting substance type II receptor (MISIIR) gene. Female TgMISIIR-Tag-DR26 transgenic mice develop bilateral ovarian tumors with variable latency and survive an average of 152 days. In the absence of reliable methods for disease detection and evaluation of therapeutic response, preclinical studies of this transgenic mouse model of EOC would be limited to longitudinal experiments involving large numbers of animals with euthanasia as the endpoint. Therefore, a non-invasive method for detecting tumors, measuring tumor volume and calculating parameters relevant to the evaluation of therapeutic or preventive interventions (i.e., tumor growth rates, tumor initiation, tumor regression and the time for tumors to reach a given size) is required. We developed and optimized a non-invasive Magnetic Resonance Imaging (MRI) scanning protocol to obtain high resolution abdominal images that is well tolerated by mice. Superior contrast and contrast to noise ratio (CNR) was found with Gd-DTPA contrast enhanced T(1)-weighted sequences. Image sets in both the axial and coronal orientations for redundant measurements of normal ovary and ovarian tumor volume can be acquired in approximately 20 minutes. Accuracy of MRI-based ovary and tumor volume determinations was verified by standard volume measurements at necropsy. Serial imaging studies were performed on 41 ovarian cancer bearing TgMISIIR-Tag-DR26 transgenic mice to quantitate tumor progression over time in this model. A chemotherapy study was conducted on TgMISIIR-Tag-DR26 transgenic mice using a standard combination therapy consisting of cisplatin and paclitaxel. Our results demonstrate that MRI is well tolerated and can be repeated in serial imaging studies, permitting quantitative analysis of tumor growth and progression and response to therapeutic interventions.
SciCrunch is a data sharing and display platform. Anyone can create a custom portal where they can select searchable subsets of hundreds of data sources, brand their web pages and create their community. SciCrunch will push data updates automatically to all portals on a weekly basis. User communities can also add their own data to scicrunch, however this is not currently a free service.