Date of Award
Doctor of Philosophy (PhD)
Michael J. Therien
Noninvasive imaging technologies, capable of visualizing early carcinoma or dormant or latent metastatic tumor cells and evaluating the efficacy of cancer therapies are becoming increasingly important. In this thesis, NIR-emissive polymersomes are engineered for optimal cellular uptake to enable fluorescence-based tumor targeting. A series of benzothiadiazole conjugated porphyrin oligomers with high emission dipole strength and exceptional large quantum yields in the NIR region are synthesized for optimized emissive output would be greatly enhanced. Furthermore, this thesis established for the first time a class of universal chemistry modification methods to directly attach antibody to polymersomes surface with very high antibody coupling efficiency and precise control of antibody density on polymersomes. These antibody conjugated NIR-emissive polymersomes exhibit ideal cell-surface adhesion dynamics and enables future in vivo tracking of labeled tumor cells by NIR fluorescence based imaging. Ultimately, tracking residual disease in vivo requires biodegradable polymersomes. Towards this goal, we fabricated analogous nanoscale NIR-emissive, soft-matter-based vesicles based on already FDA-approved materials poly(caprolactone) (PCL) and poly(trimethylene carbonate ) (PTMC) blocks, and involves copolymer synthesis, evaluation of vesicle physical properties, and polymersome functionalization. Finally, a new emissive polymersomes platform is designed by quantitative incorporation of quantum dots into the polymersomes bilayer membranes, featuring a wide range of applications for in vivo diagnostic and drug-delivery applications. In summary, this synthesis developed functionalized nanoscale NIR-emissive polymersomes with optimal fluorescence output and ability to detect limited target cell numbers under clinically relevant diagnostic conditions, and define new tools for the study of metastatic disease.
Qi, Wei, "NIR-Emissive Polymersomal Markers for Molecular-Level Detection of Metastasis" (2011). Publicly accessible Penn Dissertations. Paper 369.