Cancer is among the leading causes of death worldwide. Incidence of cancer is rising at a rate that is almost completely nullifying... Show moreCancer is among the leading causes of death worldwide. Incidence of cancer is rising at a rate that is almost completely nullifying improvements in cancer treatment and the heterogeneity of advanced disease poses significant complications for the development of effective therapies. With more aggressive cancers tending to display abnormally high expression of signaling receptors associated cell proliferation - receptors that tend to be expressed at very low levels by healthy cells in adulthood - many new cancer-specific “molecular therapies” have been developed to target and block these pathways. However, not all cancers overexpress the same proliferation pathways, so many have proposed molecular imaging as a non-invasive means of identifying on a patient-by-patient basis, which specific targets may be overexpressed to tailor therapies to the individual (“precision medicine”). The primary goal of this thesis was to develop and validate some of the first non-invasive means of measuring drug-target concentrations prior to therapy and the first measures of drug-target occupancy during therapy to ultimately predict and monitor the efficacy of cancer molecular therapy. All work was founded on paired-agent molecular imaging protocols that employ co-administration of two imaging agents: one agent that is targeted to the biomolecule of interest (e.g. a cell surface signaling receptor that may be overexpressed by a cancer), and a second, “control” (“untargeted”) agent that is as chemically similar to the targeted agent as possible, but that does not bind to the biomolecule of interest. In all paired-agent imaging strategies, the signal from the control agent is used to account for delivery and nonspecific retention effects that can confound the relationship between the targeted imaging agent concentration in a region-of-interest (ROI) and the targeted biomolecule concentration in that ROI. Show less
