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Bexarotene is a commercially produced drug commonly known as Targetin presecribed to treat cutaneous T-cell lymphoma (CTCL). Bex mimics the actions of natural 9-cis retinoic acid in the body, which are derived from Vitamin A in the diet and boost the immune system. Bex has been shown to be effective

Bexarotene is a commercially produced drug commonly known as Targetin presecribed to treat cutaneous T-cell lymphoma (CTCL). Bex mimics the actions of natural 9-cis retinoic acid in the body, which are derived from Vitamin A in the diet and boost the immune system. Bex has been shown to be effective in the treatment of multiple types of cancer, including lung cancer. However, the disadvantages of using Bex include increased instances of hypothyroidism and excessive concentrations of blood triglycerides. If an analog of Bex can be developed which retains high affinity RXR binding similar to the 9-cis retinoic acid while exhibiting less interference for heterodimerization pathways, it would be of great clinical significance in improving the quality of life for patients with CTCL. This thesis will detail the biological profiling of additional novel (Generation Two) analogs, which are currently in submission for publication, as well as that of Generation Three analogs. The results from these studies reveal that specific alterations in the core structure of the Bex "parent" compound structure can have dramatic effects in modifying the biological activity of RXR agonists.
ContributorsYang, Joanna (Author) / Jurutka, Peter (Thesis director) / Wagner, Carl (Committee member) / Hibler, Elizabeth (Committee member) / Barrett, The Honors College (Contributor)
Created2012-05
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Glioblastoma Multiforme (GBM) is an aggressive and deadly form of brain cancer with a median survival time of about a year with treatment. Due to the aggressive nature of these tumors and the tendency of gliomas to follow white matter tracks in the brain, each tumor mass has a unique

Glioblastoma Multiforme (GBM) is an aggressive and deadly form of brain cancer with a median survival time of about a year with treatment. Due to the aggressive nature of these tumors and the tendency of gliomas to follow white matter tracks in the brain, each tumor mass has a unique growth pattern. Consequently it is difficult for neurosurgeons to anticipate where the tumor will spread in the brain, making treatment planning difficult. Archival patient data including MRI scans depicting the progress of tumors have been helpful in developing a model to predict Glioblastoma proliferation, but limited scans per patient make the tumor growth rate difficult to determine. Furthermore, patient treatment between scan points can significantly compound the challenge of accurately predicting the tumor growth. A partnership with Barrow Neurological Institute has allowed murine studies to be conducted in order to closely observe tumor growth and potentially improve the current model to more closely resemble intermittent stages of GBM growth without treatment effects.
ContributorsSnyder, Lena Haley (Author) / Kostelich, Eric (Thesis director) / Frakes, David (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
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Description
Bexarotene (Bex) is a FDA-approved drug used to treat cutaneous T-cell lymphoma (CTCL). It binds with high affinity to the retinoid-X-receptor (RXR), a nuclear receptor implicated in numerous biological pathways. Bex may have the potential to attenuate estrogenic activity by acting as an estrogen receptor alpha (ERα) signaling antagonist, and

Bexarotene (Bex) is a FDA-approved drug used to treat cutaneous T-cell lymphoma (CTCL). It binds with high affinity to the retinoid-X-receptor (RXR), a nuclear receptor implicated in numerous biological pathways. Bex may have the potential to attenuate estrogenic activity by acting as an estrogen receptor alpha (ERα) signaling antagonist, and can therefore be used to treat ERα-positive cancers, such as breast cancer. Using dual luciferase reporter assays, real-time qRT-PCR, and metabolic proliferation assays, the anti-estrogenic properties of Bex were ascertained. However, since Bex produces numerous contraindications, select novel RXR drug analogs were also evaluated. Results revealed that, in luciferase assays, Bex could significantly (P < 0.01) inhibit the transcriptional activity of ERα, so much so that it rivaled ER pan-antagonist ZK164015 in potency. Bex was also able to suppress the proliferation of two breast cancer cell models, MCF-7 and T-47D, and downregulate the expression of an estrogen receptor target gene (A-myb), which is responsible for cell proliferation. In addition, novel analogs A30, A33, A35, and A38 were evaluated as being more potent at inhibiting ERE-mediated transcription than Bex at lower concentrations. Analogs A34 and A35 were able to suppress MCF-7 cell proliferation to a degree comparable to that of Bex. Inhibition of T-47D cell proliferation, by contrast, was best achieved by analogs A34 and A36. For those with ERα – positive breast cancer who are refractory to current chemotherapeutics used to treat breast cancer, Bex and its analogs may prove to be useful alternative options.
ContributorsBains, Supreet (Author) / Jurutka, Peter (Thesis director) / Hackney Price, Jennifer (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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Description
Cancer is a major health problem in the world today and is expected to become an even larger one in the future. Although cancer therapy has improved for many cancers in the last several decades, there is much room for further improvement. Mathematical modeling has the advantage of being able

Cancer is a major health problem in the world today and is expected to become an even larger one in the future. Although cancer therapy has improved for many cancers in the last several decades, there is much room for further improvement. Mathematical modeling has the advantage of being able to test many theoretical therapies without having to perform clinical trials and experiments. Mathematical oncology will continue to be an important tool in the future regarding cancer therapies and management.

This dissertation is structured as a growing tumor. Chapters 2 and 3 consider spheroid models. These models are adept at describing 'early-time' tumors, before the tumor needs to co-opt blood vessels to continue sustained growth. I consider two partial differential equation (PDE) models for spheroid growth of glioblastoma. I compare these models to in vitro experimental data for glioblastoma tumor cell lines and other proposed models. Further, I investigate the conditions under which traveling wave solutions exist and confirm numerically.

As a tumor grows, it can no longer be approximated by a spheroid, and it becomes necessary to use in vivo data and more sophisticated modeling to model the growth and diffusion. In Chapter 4, I explore experimental data and computational models for describing growth and diffusion of glioblastoma in murine brains. I discuss not only how the data was obtained, but how the 3D brain geometry is created from Magnetic Resonance (MR) images. A 3D finite-difference code is used to model tumor growth using a basic reaction-diffusion equation. I formulate and test hypotheses as to why there are large differences between the final tumor sizes between the mice.

Once a tumor has reached a detectable size, it is diagnosed, and treatment begins. Chapter 5 considers modeling the treatment of prostate cancer. I consider a joint model with hormonal therapy as well as immunotherapy. I consider a timing study to determine whether changing the vaccine timing has any effect on the outcome of the patient. In addition, I perform basic analysis on the six-dimensional ordinary differential equation (ODE). I also consider the limiting case, and perform a full global analysis.
ContributorsRutter, Erica Marie (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric J (Thesis advisor) / Frakes, David (Committee member) / Gardner, Carl (Committee member) / Jackiewicz, Zdzislaw (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Since its isolation from a rhesus monkey in the Zika forest of Uganda in 1947, Zika virus (ZIKV) has spread into many parts of the world, causing major epidemics, notably in the Americas and some parts of Europe and Asia. The flavivirus ZIKV is primarily transmitted to humans via the

Since its isolation from a rhesus monkey in the Zika forest of Uganda in 1947, Zika virus (ZIKV) has spread into many parts of the world, causing major epidemics, notably in the Americas and some parts of Europe and Asia. The flavivirus ZIKV is primarily transmitted to humans via the bite of infectious adult female Aedes mosquitoes. In the absence of effective treatment or a safe and effective vaccine against the disease, control efforts are focused on effective vector management to reduce the mosquito population and limit human exposure to mosquito bites. The work in this thesis is based on the use of a mathematical model for gaining insight into the transmission dynamics of ZIKV in a population. The model, which takes the form of a deterministic system of nonlinear differential equations, is rigorously analyzed to gain insight into its basic qualitative features. In particular, it is shown that the disease-free equilibrium of the model is locally-asymptotically stable whenever a certain epidemiological quantity (known as the reproduction number, denoted by R0) is less than unity. The epidemiological implication of this result is that a small influx of ZIKV-infected individuals or vectors into the community will not generate a large outbreak if the anti-ZIKV control strategy (or strategies) adopted by the community can reduce and maintain R0 to a value less than unity. Numerical simulations of the model, using data relevant to ZIKV transmission dynamics in Puerto Rico, shows that a control strategy that solely focuses on killing immature mosquitoes (using highly efficacious larvicides) can lead to the elimination of ZIKV if the larvicide coverage (i.e., proportion of breeding sites treated with larvicides) is high enough (over 90%). Such elimination is also feasible using a control strategy that solely focuses on the use of insect repellents (as a means of personal protection against mosquito bites) if the coverage level of the insect repellent usage in the community is high enough (at least 70%). However, it is also shown that although the use of adulticides (i.e., using insecticides to kill adult mosquitoes) can reduce the reproduction number (hence, disease burden), it fails to reduce it to a value less than unity, regardless of coverage level. Thus, unlike with the use of larvicide-only or repellent-only strategies, the population-wide implementation of an adulticide-only strategy is unable to lead to ZIKV elimination. Finally, it is shown that the combined (integrated pest management) strategy, based on using all three aforementioned strategies, is the most effective approach for combatting ZIKV in the population. In particular, it is shown that even a moderately-effective level of this strategy, which entails using only 50% coverage of both larvicides and adulticides, together with about 45% coverage for a repellent strategy, will lead to ZIKV elimination. This moderately-effective combined strategy seems attainable in Puerto Rico.
ContributorsUrcuyo, Javier (Author) / Gumel, Abba (Thesis director) / Hackney Price, Jennifer (Committee member) / School of Mathematical and Natural Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05