Breast cancer is the most frequently diagnosed form of cancer and the second leading cause of death in women. Death and most of the complications associated with breast cancer are due to the metastasis of the primary tumor to the lung, as well as other tissues. To visualize the metastatic process in real time, the genetically engineered mouse mammary tumor virus-polyoma middle T (MMTV-PyMT) mouse model was employed along with in vivo µCT (computed tomography) imaging to evaluate and characterize the size and incidence of lung nodules. µCT images are able to detect lung nodules as small as approximately 0.5mm3. The MMTV-PyMT model is widely used to evaluate metastatic breast cancer; the model produces lung metastases (80-90% incidence rate) in a more clinically relevant manner in a syngeneic mouse with intact immune system. In this study female MMTV-PyMT mice were allowed to develop primary mammary fat pad tumors (>3grams) which were then excised and processed into single cell suspension. Syngeneic female mice (FVB/J) were implanted with the cell suspension into mammary fat pad #4 and the resulting tumors were resected once the primary tumor burden surpassed 750mg (late stage). Standard twice weekly intravenous therapy with eribulin at 1mg/kg was initiated following resection and continued the duration of the experiment. µCT images were used to assess the presence and size of lung metastases in vivo starting at 3 weeks post-primary tumor resection. Mice were monitored daily via cage side observations and imaged a second time once labored breathing was apparent. Treatment with eribulin (1mg/kg, IV) not only decreased the incidence of lung metastases by 75% compared to the vehicle control group but also inhibited the ability of the primary tumor to regrow. Coupling the MMTV-PyMT model with µCT imaging allowed for the longitudinal evaluation of therapeutic efficacy on progressive lung metastases. Visualizing lung metastases in real time with in vivo imaging is advantageous since traditional pharmacology endpoints of the MMTV-PyMT model can be extremely long (20-40 weeks).
Citation Information: Mol Cancer Ther 2013;12(11 Suppl):B145.
Citation Format: Mary Anne Meade, Deepa Balagurunathan, Chris Bull, Deanne Lister, Erin Trachet, Bryan Smith, Daniel Flynn, Scott C. Wise. Use of μCT imaging in the PyMT breast cancer model to monitor lung metastasis development and determine therapeutic benefit in real time. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr B145.