JOURNAL ARTICLE

Multiple target-specific molecular agents for detection and image analysis of breast cancer characteristics in mice

S Ke, W Wang, X Qiu, F Zhang, J T Yustein, A G Cameron, S Zhang, D Yu, C Zou, X Gao, J Lin, S Yallampalli, M Li
Current Molecular Medicine 2013, 13 (3): 446-58
23331017
Breast cancer is a heterogenetic tumor at the cellular level with multiple factors and components. The inconsistent expression of molecular markers during disease progression reduces the accuracy of diagnosis and efficacy of target-specific therapy. Single target-specific imaging agents can only provide limited tumor information at one time point. In contrast, multiple target-specific imaging agents can increase the accuracy of diagnosis. The aim of this study was to demonstrate the ability of multi-agent imaging to discriminate such differences in single tumor. Mice bearing human cancer cell xenografts were tested to determine individual differences under optimal experimental conditions. Neovasculature agent (RGD peptide), tumor stromal agent (matrix metalloproteinase), and tumor cell markers (epidermal growth factor, Her-2, interleukin 11) imaging agents were labeled with reporters. 18F-Fluorodeoxyglucose was used to evaluate the tumor glucose status. Optical, X-ray, positron emission tomography, and computer tomography imaging modalities were used to determine tumor characteristics. Tumor size and imaging data demonstrated that individual differences exist under optimal experimental conditions. The target-specific agents used in the study bind to human breast cancer cell lines in vitro and xenografts in vivo. The pattern of binding corresponds to that of tumor markers. Multi-agent imaging had complementary effects in tumor detection. Multiple noninvasive imaging agents and modalities are complementary in the interrogation of unique biological information from each individual tumor. Such multi-agent approaches provide methods to study several disease components simultaneously. In addition, the imaging results provide information on disease status at the molecular level.

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