B7-H3 Targeted Ultrasound Molecular Imaging System for Early Breast Cancer and Metastatic Detection

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ABSTRACT Breast cancer is the second leading cause of cancer-related deaths in women in the United States, and its incidence is expected to grow by more than 50% by 2030. If detected early, the survival of women can be substantially increased compared to late-stage detection. Ultrasound molecular imaging, using molecularly- targeted contrast microbubbles, is a promising technique for the early detection of breast cancer, particularly in women with radiographically dense breast. In ultrasound molecular imaging, a molecularly-targeted ligand attached to a microbubble can bind to proteins expressed on the tumor neovasculature and produce contrast that can identify cancer early. This approach has large potential for improving the diagnostic accuracy of ultrasound and noninvasive characterization of focal breast lesions. The keys to successful ultrasound molecular imaging in this regard are: (1) having a molecular target that is highly specific to breast cancer, and (2) having a sensitive imaging system that can correctly visualize the microbubbles bound to breast cancer and differentiate those bubbles from background tissue. In addition, the system must integrate well with existing ultrasound imaging technology so as to be practically distributable to existing breast imaging clinics. In this application, we propose to build a real-time ultrasound molecular imaging platform that consisting of a novel ultrasound contrast imaging technology that is targeted to a newly identified biomarker of breast cancer. We propose to utilize targeted microbubbles to enhance the contrast signal and improve the sensitivity of the imaging system and propose to conjugate these microbubbles with a high-affinity affibody targeted to the B7-H3 biomarker, which is a vascular biomarker highly specific to breast cancer, and is not expressed in benign disease processes. In addition, our preliminary results demonstrate that this biomarker may potentially allow for the detection of metastatic disease at the time of imaging, potentially enabling the ability to image the extent of metastatic disease prior to treatment decisions. The real-time imaging technology in this proposal is based on a neural network design for contrast imaging that requires low computational resources and avoids destruction of bubbles, and enable real-time imaging of the targeted contrast agent. During this project, we will optimize the ultrasound parameters of these B7-H3 targeted microbubbles for breast ultrasound imaging frequencies and will utilize conjugation chemistry for the microbubbles to permit the potential for future clinical translation of the B7- H3-targeted microbubbles. We will design and construct this ultrasound molecular imaging platform (non- destructive imaging system plus monodisperse B7-H3-targeted microbubbles) and thoroughly test it in phantoms, in vitro flow chambers, and several preclinical animal models of primary and metastatic breast cancer.