ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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First, prostate cancer is modeled, where androgen is considered the limiting nutrient since most tumors depend on androgen for proliferation and survival. The model's accuracy for predicting the biomarker for patients on intermittent androgen deprivation therapy is tested by comparing the simulation results to clinical data as well as to an existing simpler model. The results suggest that a simpler model may be more beneficial for a predictive use, although further research is needed in this field prior to implementing mathematical models as a predictive method in a clinical setting.
Next, two chronic myeloid leukemia models are compared that consider Imatinib treatment, a drug that inhibits the constitutively active tyrosine kinase BCR-ABL. Both models describe the competition of leukemic and normal cells, however the first model also describes intracellular dynamics by considering BCR-ABL as the limiting nutrient. Using clinical data, the differences in estimated parameters between the models and the capacity for each model to predict drug resistance are analyzed.
Last, a simple model is presented that considers ovarian tumor growth and tumor induced angiogenesis, subject to on and off anti-angiogenesis treatment. In this environment, the cell quota represents the intracellular concentration of necessary nutrients provided through blood supply. Mathematical analysis of the model is presented and model simulation results are compared to pre-clinical data. This simple model is able to fit both on- and off-treatment data using the same biologically relevant parameters.
Three approaches were used for the characterization of these suppressors. The first approach focused on side chain specificity. The results showed that certain suppressor sites prefer a particular side chain property, such as size, to overcome the F610A defect. The second approach focused on the effects of efflux pump inhibitors. The results showed that though the suppressor residues were able to overcome the intrinsic defect of F610A, they were unable to overcome the extrinsic defect caused by the efflux pump inhibitors. This showed that the mechanism by which F610A imposes its effect on AcrB function is different than that of the efflux pump inhibitors. The final approach was to determine whether suppressors mapping in the periplasmic and trans-membrane domains act by the same or different mechanisms. The results showed both overlapping and distinct mechanisms of suppression.
To conclude, these approaches have provided a deeper understanding of the mechanisms by which novel suppressor residues of AcrB overcome the functional defect of the drug binding domain alteration, F610A.