Morphologic Changes of Mammary Carcinomas in Mice over Time as Monitored by Flat-Panel Detector Volume Computed Tomography1

Noninvasive methods are strongly needed to detect and quantify not only tumor growth in murine tumor models but also the development of vascularization and necrosis within tumors. This study investigates the use of a new imaging technique, flat-panel detector volume computed tomography (fpVCT), to monitor in vivo tumor progression and structural changes within tumors of two murine carcinoma models. After tumor cell inoculation, single fpVCT scans of the entire mice were performed at different time points. The acquired isotropic, high-resolution volume data sets enable an accurate real-time assessment and precise measurements of tumor volumes. Spreading of contrast agent-containing blood vessels around and within the tumors was clearly visible over time. Furthermore, fpVCT permits the identification of differences in the uptake of contrast media within tumors, thus delineating necrosis, tumor tissues, and blood vessels. Classification of tumor tissues based on the decomposition of the underlying mixture distribution of tissue-related Hounsfield units allowed the quantitative acquisition of necrotic tissues at each time point. Morphologic alterations of the tumor depicted by fpVCT were confirmed by histopathologic examination. Concluding, our data show that fpVCT may be highly suitable for the noninvasive evaluation of tumor responses to anticancer therapies during the course of the disease

Flat-Panel Detector-Based Volume Computed Tomography: A Novel 3D Imaging Technique to Monitor Osteolytic Bone Lesions in a Mouse Tumor Metastasis Model1

Skeletal metastasis is an important cause of mortality in patients with breast cancer. Hence, animal models, in combination with various imaging techniques, are in high demand for preclinical assessment of novel therapies. We evaluated the applicability of flat-panel volume computed tomography (fpVCT) to noninvasive detection of osteolytic bone metastases that develop in severe immunodeficient mice after intracardial injection of MDA-MB-231 breast cancer cells. A single fpVCT scan at 200-µm isotropic resolution was employed to detect osteolysis within the entire skeleton. Osteolytic lesions identified by fpVCT correlated with Faxitron X-ray analysis and were subsequently confirmed by histopathological examination. Isotropic three-dimensional image data sets obtained by fpVCT were the basis for the precise visualization of the extent of the lesion within the cortical bone and for the measurement of bone loss. Furthermore, fpVCT imaging allows continuous monitoring of growth kinetics for each metastatic site and visualization of lesions in more complex regions of the skeleton, such as the skull. Our findings suggest that fpVCT is a powerful tool that can be used to monitor the occurrence and progression of osteolytic lesions in vivo and can be further developed to monitor responses to antimetastatic therapies over the course of the disease

NeuCode Proteomics Reveals Bap1 Regulation of Metabolism

We introduce neutron-encoded (NeuCode) amino acid labeling of mice as a strategy for multiplexed proteomic analysis in vivo. Using NeuCode, we characterize an inducible knockout mouse model of Bap1, a tumor suppressor and deubiquitinase whose in vivo roles outside of cancer are not well established. NeuCode proteomics revealed altered metabolic pathways following Bap1 deletion, including profound elevation of cholesterol biosynthetic machinery coincident with reduced expression of gluconeogenic and lipid homeostasis proteins in liver. Bap1 loss increased pancreatitis biomarkers and reduced expression of mitochondrial proteins. These alterations accompany a metabolic remodeling with hypoglycemia, hypercholesterolemia, hepatic lipid loss, and acinar cell degeneration. Liver-specific Bap1 null mice present with fully penetrant perinatal lethality, severe hypoglycemia, and hepatic lipid deficiency. This work reveals Bap1 as a metabolic regulator in liver and pancreas, and it establishes NeuCode as a reliable proteomic method for deciphering in vivo biology