Date of Award

Summer 8-3-2021

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Chemistry

First Advisor

Jenny J Yang

Second Advisor

Ming Luo

Third Advisor

Zhi-ren Liu

Fourth Advisor

Hans E Grossniklaus

Abstract

Chronic diseases are leading cause of death in US and globally. About 60 % of adults in the US have at least one form of chronic disease while 40 % suffer from 2 or more chronic diseases. Noninvasive, early detection, quantitative diagnosis, and staging of these diseases with high-resolution imaging remain a pressing unmet medical need. Type I collagen a major constituent of extracellular matrix is highly expressed in the microenvironment of various chronic and acute human diseases such as hepatocellular carcinoma and liver and lung fibrosis. Its expression level and spatial crosslink pattern are stage-dependent and is an attractive diagnostic and therapeutic target for many chronic diseases via pathological analysis. This dissertation reports the design and optimization of a human collagen-targeted protein-based MRI contrast agent (hProCA32.collagen) to extend MRI analysis for diagnosis and staging of liver and lung diseases via detection of overexpressed collagen biomarker using several mouse models. hProCA32.collagen exhibits strong collagen type I binding affinity and specificity over types III and IV. hProCA32.collagen has 104 to 1011 metal selectivity for Gd3+ over Ca2+ and Zn2+, respectively. It exhibits much stronger resistance against transmetallation than linear contrast agents. Importantly, hProCA32.collagen exhibits the high relaxivity values for both r1 (32 ± 0.3 mM-1.s-1) and r2 (51 ± 0.2 mM-1.s-1) per Gd3+ at 1.4 T and r1 (18.5 ± 1.5 mM-1.s-1) and r2 (105.6 ± 2 mM-1.s-1) at 7.0 T that is 8 to 11-fold greater than clinically approved contrast agents Eovist and Gadovist. hProCA32.collagen enabled the early detection of idiopathic lung fibrosis (Ashcroft 2 of 8) as well as heterogeneously expressed UIP patterns validated by histology analysis and correlation. In addition, collagen mapping in a nicotine-induced COPD mouse model was achieved with hProCA32.collagen. hProCA32.collagen enabled the progressive and heterogeneous detection of liver diseases from an early-stage diabetes mice model (Ishak 1 of 6) and late-stage (Ishak 5 of 6) mouse model to hepatocellular carcinoma. The developed hProCA32.collagen is expected to overcome the major clinical barriers in early disease detection and staging with strong translational potential.

DOI

https://doi.org/10.57709/24161345

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