Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Doctor of Philosophy

Program

Medical Biophysics

Collaborative Specialization

Molecular Imaging

Supervisor

Scholl, Timothy J.

2nd Supervisor

Ronald, John A.

Joint Supervisor

Abstract

Introduction: Molecular imaging allows for non-invasive longitudinal visualization of cellular functions in vivo. This area of research has provided better understanding of fundamental molecular and biochemical processes, enabled optimization of pre-clinical and clinical assessments for new treatments, and allowed for more accurate and early detection of many pathologies. Extensive research for novel imaging techniques and emerging technologies have rapidly advanced the field. However, an ideal single imaging modality or approach does not exist. Alternatively, multi-modal imaging approaches are commonly applied to overcome limitations of individual technologies. In this thesis, we design, develop, validate, and image various cell types using multi-modal complementary tracking systems including bioluminescence imaging (BLI), magnetic resonance imaging (MRI), magnetic particle imaging (MPI), and positron emission tomography (PET) to maximize the strengths of each technology. Methods and Results: First, we develop a multi-modal imaging approach to track breast cancer cells in a safe, sensitive, and quantitative manner in vivo. We have subsequently optimized and applied our multi-modal system further to visualize mesenchymal stem cells (MSCs), a clinically-relevant cell type, with high sensitivity. Furthermore, we have validated this imaging approach in an emerging cellular immunotherapy for the treatment of a rodent model of ovarian cancer. Specifically, using a safe dual human reporter-gene imaging approach, breast cancer cells were detectable in mice with PET and MRI - two clinical imaging modalities. Next, MSCs were genetically modified with a PET reporter gene and labelled with iron oxide nanoparticles for longitudinal imaging with clinical PET and sensitive MPI. Finally, we demonstrate chimeric antigen receptor natural killer (CAR-NK) cells slowed tumor progression in an ovarian cancer model using BLI, and were able to track the CAR-NK cells using reporter-based BLI and PET. Conclusion: The studies reported in this thesis contribute new multi-modal non-invasive molecular imaging tools to track various cell types in preclinical models to reveal complementary information on cell localization, proliferation, viability, and therapeutic response. Continued development of the clinically-relevant imaging tools we have built for tracking MSCs and CAR-NK cells may one day provide valuable information on cell therapy response/non-response or side effects in individual patients – important goals in the era of precision medicine.

Summary for Lay Audience

Traditional imaging primarily focuses on imaging structural changes in the body. Molecular imaging (MI) allows one to visualize particular molecules and cells in the body in a non-invasive and sensitive manner and works by labeling of cells of interest with imaging labels to enable their visualization with various imaging scanners. There are many applications of these approaches, ranging from better understanding of basic cellular-cellular interactions and functions, to providing more knowledge on new medicine, as well as extending to earlier diagnosis of many diseases. In this thesis, we use MI approaches to non-invasively track cancer cells, stem cells, and immune cells in a safe, sensitive, and quantitative approach using numerous imaging technologies: positron emission tomography (PET), magnetic resonance imaging (MRI), bioluminescence imaging (BLI) and magnetic particle imaging (MPI). The first cell system we describe uses safe genetic modifications of breast cancer cells to enable their detection with MRI and PET longitudinally. Next, we combined MPI and PET to track stem cells, a therapeutic cell type, to allow for sensitive cell tracking for a long time after their implantation into mice. Finally, we combined BLI and PET to track a novel cellular immunotherapy that was able to successfully treat ovarian cancer in mice. This thesis adds to the rapidly growing field of non-invasive detection of cells in the body to better understand where they localize, if they persist, expand, die, or how they interact in preclinical models.

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