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dc.contributor.advisorWang, Michael Z
dc.contributor.authorDoyle, Laura Michelle
dc.date.accessioned2019-09-06T19:25:48Z
dc.date.available2019-09-06T19:25:48Z
dc.date.issued2019-05-31
dc.date.submitted2019
dc.identifier.otherhttp://dissertations.umi.com/ku:16433
dc.identifier.urihttp://hdl.handle.net/1808/29545
dc.description.abstractTwo main routes of drug elimination include renal excretion via the kidney and metabolic degradation via metabolizing enzymes (DMEs) in the liver, followed by renal excretion or biliary elimination of the now more polar molecule. Unlike renal excretion, liver metabolism tends to be highly variable between individuals due to various intrinsic and extrinsic factors such as age, genetics, smoking, and diet. The variability in liver DME activity among individuals creates a challenge in drug development and pharmacotherapy, especially for drugs that are required to be metabolized and have narrow therapeutic windows. If the liver DME activity of an individual could be predicted and each patient dosed according to their unique liver DME activity, the adverse effects or lack of effectiveness associated with these drugs may be prevented. Currently, two methods available for predicting an individual’s liver DME activity are genotyping and phenotyping. For genotyping, RT-PCR is used to determine the DNA sequence of the expressed enzyme. This reveals the specific polymorphism of the enzyme and the “typical activity” of the expressed polymorph is used to dose the patient accordingly. The issue with this however, is that it fails to account for other intrinsic or extrinsic factors that can affect the expression level of the given DME polymorph. On the other hand, phenotyping is done by administering a cocktail of drugs to a patient and monitoring the activity of the expressed enzyme(s). Because this reveals the true activity of the liver DMEs, it is more clinically relevant and used more often than genotyping. However, phenotyping is expensive and requires consistent monitoring by medical professionals in the hospital, thus is inconvenient. Accurate prediction of liver DME activity at the individual level in the clinical setting remains challenging, however if a more clinically friendly method were to be developed, it could lead to a broader range of potential drug candidates in drug development and lower risk of adverse drug responses. In this dissertation, the use of exosomes to act as biomarkers for liver DMEs is investigated. Exosomes are vesicles, typically 50 – 150 nm in diameter, secreted by cells into the extracellular space. In the human body, exosomal vesicles have been found in blood, saliva, urine, breast milk, and other bodily fluids. What makes exosomes unique from other vesicles secreted by cells, is that exosomes are formed by an endosomal route, thus contain cargo that reflecting the cell from which they are being secreted, in the extracellular space. This allows for the development of minimally invasive “liquid biopsies” to probe for markers of different diseases and cancers. While exosomes have been demonstrated as useful tools for diagnosis and monitoring patient response to treatment, they are yet to be used in the clinical setting. This is due to the lack of standardization in exosomal isolation and analysis. These challenges were also addressed in this dissertation. In summary, this dissertation describes the development of a liquid chromatography multiple-reaction-monitoring mass spectrometry (LC-MRM-MS) method for exosomal analysis and its benefits over more traditional assays. Following the method development, the presence of DMEs in exosomes were explored along with the ability of exosomal DME levels to be altered to reflect a change occurring in the secreting cell. Finally, the ability to isolate liver derived exosomes based on the expression of a liver specific marker protein, ASGR1, is explored. Further efforts of this project could lead to the development of a blood-based biopsy to evaluate the DME content of liver derived exosomes, which may correlate to liver DME activity, providing a new-found basis of personalized medicine.
dc.format.extent167 pages
dc.language.isoen
dc.publisherUniversity of Kansas
dc.rightsCopyright held by the author.
dc.subjectPharmaceutical sciences
dc.subjectASGR-1
dc.subjectDrug Metabolizing Enzymes
dc.subjectExosomes
dc.subjectLC-MRM-MS
dc.subjectLiver
dc.titleTargeted Proteomics for Exosome Analysis and Its Application to Develop Blood Markers of Liver Drug-Metabolizing Enzymes
dc.typeDissertation
dc.contributor.cmtememberSchoeneich, Christian
dc.contributor.cmtememberStobaugh, John
dc.contributor.cmtememberKrise, Jeff
dc.contributor.cmtememberZeng, Yong
dc.thesis.degreeDisciplinePharmaceutical Chemistry
dc.thesis.degreeLevelPh.D.
dc.identifier.orcid
dc.rights.accessrightsembargoedAccess


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