One of the principal impediments to the broad success of conventional chemotherapy is poor delivery to and transport within the tumor microenvironment (TME), caused by irregular and leaky vasculature, the lack of functional lymphatics, and underscored by the overproduction of extracellular matrix (ECM) proteins such as collagen. Coupled with limited specificity, the high chemotherapeutic doses needed to effectively treat tumors often lead to unacceptable levels of damage to healthy tissues. Bacteria-based cancer therapy (BBCT) is an innovative alternative. Attenuated strains of species such as Salmonella Typhimurium have been shown to preferentially replicate in the TME, competing for cellular resources and imparting intrinsic and immune-mediated cytotoxic effects on cancer cells. Nevertheless, the immense successes observed in in vitro and immunocompromised murine models have not translated to the clinic, attributable to the lack of sufficient tumor colonization. Synthetic biology today enables the precision engineering of microbes with traits for improved survival, penetration, and replication in the TME, rationally optimizable through computational modeling. In this dissertation, we explore several facets of rationally engineering of bacteria toward augmenting bacterial penetration and retention in the TME. Namely, we (1) develop a novel assay to interrogate the neutrophil migratory response to pathogens and characterize the effects of modifying the molecular structure of the outer membrane (OM) of S. Typhimurium, (2) develop a mathematical model of bacterial intratumoral transport and growth and explore the effects of nutrient availability and the tumor ECM on colonization, (3) engineer bacteria that constitutively secrete collagenase and show significantly augmented transport in collagen hydrogels and collagen-rich tumor spheroids, and (4) develop computational models to explore control schemes for the programmed behavior of bacteria-based biohybrid systems, which will leverage the engineered bacteria to deliver therapeutics to the TME. Our work serves as the foundation for the logical and efficient design of the next generation of BBCTs. / Doctor of Philosophy / Cancer is one of the deadliest diseases facing our world today not because of a lack of effective medications in most cases, but because of our inability to target the diseased sites with those treatments. Many tumors lie in deep and sensitive regions that render them untouchable by direct physical means. Poor vascularization leads to only small fractions of toxic, systemically injected drugs being deposited in tumors. State-of-the-art treatments such as so-called "nano-medicines" that can target features of the diseased tissues and immunotherapies that train the immune system to attack tumor cells have made tremendous strides, but for many types of cancer, the underlying challenge of reaching cells far from blood vessels and targeting immunologically cold tumors remains. Bacteria-based cancer therapy (BBCT) presents an exciting opportunity to address these challenges. Based on microorganisms that can self-propel, proliferate, and display a preference for diseased tissues, their potential not only to carry chemotherapeutic payloads but also to elicit directly toxic or immunotherapeutic effects on cancer cells is clear from experimental work. Nevertheless, the same delivery and transport barriers facing other treatments, as well as immune-mediated clearance, have limited BBCTs' clinical success. Advances in synthetic biology and computational modeling today make the precision engineering of BBCT for traits that favor targeted cancer therapy a reality. The central hypothesis of this dissertation is that endowing tumor-targeting bacteria with a tissue-degrading enzyme has the potential to enhance tumor penetration and colonization. This dissertation work has led to development of computational and experimental frameworks for the design, testing, and optimization of BBCTs through direct quantitative assessment of the immune response, simulations to both optimize nutrient consumption for optimal growth and for programming genetic control strategies, and characterization of transport in tissue. Our work serves as a foundation for engineering "intelligent" BBCT.
Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/113671 |
Date | 13 August 2021 |
Creators | Leaman, Eric Joshua |
Contributors | Mechanical Engineering, Behkam, Bahareh, Paul, Mark R., Davalos, Rafael V., Senger, Ryan S., Tafti, Danesh K. |
Publisher | Virginia Tech |
Source Sets | Virginia Tech Theses and Dissertation |
Detected Language | English |
Type | Dissertation |
Format | ETD, application/pdf, application/x-zip-compressed |
Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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