UC Irvine

Cancer metastases are driven by complex interactions among tumor cells, immune cells, and other cell types. Dissecting the roles of these cells is complicated by the inherent heterogeneity of the tumor environment. Currently we lack the models needed to profile cancer metastasis and monitor disease progression. Improved cancer models can be used in conjunction with noninvasive imaging probes to further visualize specific cell types and cellular interactions that are important to cancer progression in vivo. Bioluminescence is well suited for sensitive, noninvasive imaging in disease models. Bioluminescence relies on enzymes (luciferases) that generate light via the chemical oxidation of small molecule substrates (luciferins). No external excitation source is required, and enough tissue-penetrant light is released, enabling sensitive detection of cells and other biological features. Despite its broad applicability, bioluminescence has historically been limited to monitoring one cell population at a time and lacks the spatial resolution necessary to “see” cellular interactions relevant to cancer progression. This dissertation bridges the need for better methods to study metastatic progression by developing platforms that (1) enable multicomponent bioluminescence imaging in vivo, (2) recapitulate disease progression with new metastatic cancer models, (3) profile comprehensive transcriptome analyses of metastatic disease, and (4) facilitate tumor-immune cell monitoring through engineered imaging probes. Collectively, the imaging methods and models developed in this dissertation enable a more detailed examination of tumor heterogeneity and metastatic disease progression in vivo.