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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Description
Anti-retroviral drugs and AIDS prevention programs have helped to decrease the rate of new HIV-1 infections in some communities, however, a prophylactic vaccine is still needed to control the epidemic world-wide. Despite over two decades of research, a vaccine against HIV-1 remains elusive, although recent clinical trials have shown promising

Anti-retroviral drugs and AIDS prevention programs have helped to decrease the rate of new HIV-1 infections in some communities, however, a prophylactic vaccine is still needed to control the epidemic world-wide. Despite over two decades of research, a vaccine against HIV-1 remains elusive, although recent clinical trials have shown promising results. Recent successes have focused on highly conserved, mucosally-targeted antigens within HIV-1 such as the membrane proximal external region (MPER) of the envelope protein, gp41. MPER has been shown to play critical roles in the viral mucosal transmission, though this peptide is not immunogenic on its own. Gag is a structural protein configuring the enveloped virus particles, and has been suggested to constitute a target of the cellular immunity potentially controlling the viral load. It was hypothesized that HIV-1 enveloped virus-like particles (VLPs) consisting of Gag and a deconstructed form of gp41 comprising the MPER, transmembrane, and cytoplasmic domains (dgp41) could be expressed in plants. Plant-optimized HIV-1 genes were constructed and expressed in Nicotiana benthamiana by stable transformation, or transiently using a tobacco mosaic virus-based expression system or a combination of both. Results of biophysical, biochemical and electron microscopy characterization demonstrated that plant cells could support not only the formation of HIV-1 Gag VLPs, but also the accumulation of VLPs that incorporated dgp41. These particles were purified and utilized in mice immunization experiments. Prime-boost strategies combining systemic and mucosal priming with systemic boosting using two different vaccine candidates (VLPs and CTB-MPR - a fusion of MPER and the B-subunit of cholera toxin) were administered to BALB/c mice. Serum antibody responses against both the Gag and gp41 antigens could be elicited in mice systemically primed with VLPs and these responses could be recalled following systemic boosting with VLPs. In addition, mucosal priming with VLPs allowed for a robust boosting response against Gag and gp41 when boosted with either candidate. Functional assays of these antibodies are in progress to test the antibodies' effectiveness in neutralizing and preventing mucosal transmission of HIV-1. This immunogenicity of plant-based Gag/dgp41 VLPs represents an important milestone on the road towards a broadly-efficacious and inexpensive subunit vaccine against HIV-1.
ContributorsKessans, Sarah (Author) / Mor, Tsafrir S (Thesis advisor) / Matoba, Nobuyuki (Committee member) / Mason, Hugh (Committee member) / Hogue, Brenda (Committee member) / Fromme, Petra (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Resistance to existing anti-cancer drugs poses a key challenge in the field of medical oncology, in that it results in the tumor not responding to treatment using the same medications to which it responded previously, leading to treatment failure. Adaptive therapy utilizes evolutionary principles of competitive suppression, leveraging competition between

Resistance to existing anti-cancer drugs poses a key challenge in the field of medical oncology, in that it results in the tumor not responding to treatment using the same medications to which it responded previously, leading to treatment failure. Adaptive therapy utilizes evolutionary principles of competitive suppression, leveraging competition between drug resistant and drug sensitive cells, to keep the population of drug resistant cells under control, thereby extending time to progression (TTP), relative to standard treatment using maximum tolerated dose (MTD). Development of adaptive therapy protocols is challenging, as it involves many parameters, and the number of parameters increase exponentially for each additional drug. Furthermore, the drugs could have a cytotoxic (killing cells directly), or a cytostatic (inhibiting cell division) mechanism of action, which could affect treatment outcome in important ways. I have implemented hybrid agent-based computational models to investigate adaptive therapy, using either a single drug (cytotoxic or cytostatic), or two drugs (cytotoxic or cytostatic), simulating three different adaptive therapy protocols for treatment using a single drug (dose modulation, intermittent, dose-skipping), and seven different treatment protocols for treatment using two drugs: three dose modulation (DM) protocols (DM Cocktail Tandem, DM Ping-Pong Alternate Every Cycle, DM Ping-Pong on Progression), and four fixed-dose (FD) protocols (FD Cocktail Intermittent, FD Ping-Pong Intermittent, FD Cocktail Dose-Skipping, FD Ping-Pong Dose-Skipping). The results indicate a Goldilocks level of drug exposure to be optimum, with both too little and too much drug having adverse effects. Adaptive therapy works best under conditions of strong cellular competition, such as high fitness costs, high replacement rates, or high turnover. Clonal competition is an important determinant of treatment outcome, and as such treatment using two drugs leads to more favorable outcome than treatment using a single drug. Switching drugs every treatment cycle (ping-pong) protocols work particularly well, as well as cocktail dose modulation, particularly when it is feasible to have a highly sensitive measurement of tumor burden. In general, overtreating seems to have adverse survival outcome, and triggering a treatment vacation, or stopping treatment sooner when the tumor is shrinking seems to work well.
ContributorsSaha, Kaushik (Author) / Maley, Carlo C (Thesis advisor) / Forrest, Stephanie (Committee member) / Anderson, Karen S (Committee member) / Cisneros, Luis H (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Adoptive transfer of T cells engineered to express synthetic antigen-specific T cell receptors (TCRs) has provocative therapeutic applications for treating cancer. However, expressing these synthetic TCRs in a CD4+ T cell line is a challenge. The CD4+ Jurkat T cell line expresses endogenous TCRs that compete for space, accessory proteins,

Adoptive transfer of T cells engineered to express synthetic antigen-specific T cell receptors (TCRs) has provocative therapeutic applications for treating cancer. However, expressing these synthetic TCRs in a CD4+ T cell line is a challenge. The CD4+ Jurkat T cell line expresses endogenous TCRs that compete for space, accessory proteins, and proliferative signaling, and there is the potential for mixed dimer formation between the α and β chains of the endogenous receptor and that of the synthetic cancer-specific TCRs. To prevent hybridization between the receptors and to ensure the binding affinity measured with flow cytometry analysis is between the tetramer and the TCR construct, a CRISPR-Cas9 gene editing pipeline was developed. The guide RNAs (gRNAs) within the complex were designed to target the constant region of the α and β chains, as they are conserved between TCR clonotypes. To minimize further interference and confer cytotoxic capabilities, gRNAs were designed to target the CD4 coreceptor, and the CD8 coreceptor was delivered in a mammalian expression vector. Further, Golden Gate cloning methods were validated in integrating the gRNAs into a CRISPR-compatible mammalian expression vector. These constructs were transfected via electroporation into CD4+ Jurkat T cells to create a CD8+ knockout TCR Jurkat cell line for broadly applicable uses in T cell immunotherapies.
ContributorsHirneise, Gabrielle Rachel (Author) / Anderson, Karen (Thesis advisor) / Mason, Hugh (Committee member) / Lake, Douglas (Committee member) / Arizona State University (Publisher)
Created2020
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Description
In contrast to traditional chemotherapy for cancer which fails to address tumor heterogeneity, raises patients’ levels of toxicity, and selects for drug-resistant cells, adaptive therapy applies ideas from cancer ecology in employing low-dose drugs to encourage competition between cancerous cells, reducing toxicity and potentially prolonging disease progression. Despite promising results

In contrast to traditional chemotherapy for cancer which fails to address tumor heterogeneity, raises patients’ levels of toxicity, and selects for drug-resistant cells, adaptive therapy applies ideas from cancer ecology in employing low-dose drugs to encourage competition between cancerous cells, reducing toxicity and potentially prolonging disease progression. Despite promising results in some clinical trials, optimizing adaptive therapy routines involves navigating a vast space of combina- torial possibilities, including the number of drugs, drug holiday duration, and drug dosages. Computational models can serve as precursors to efficiently explore this space, narrowing the scope of possibilities for in-vivo and in-vitro experiments which are time-consuming, expensive, and specific to tumor types. Among the existing modeling techniques, agent-based models are particularly suited for studying the spatial inter- actions critical to successful adaptive therapy. In this thesis, I introduce CancerSim, a three-dimensional agent-based model fully implemented in C++ that is designed to simulate tumorigenesis, angiogenesis, drug resistance, and resource competition within a tissue. Additionally, the model is equipped to assess the effectiveness of various adaptive therapy regimens. The thesis provides detailed insights into the biological motivation and calibration of different model parameters. Lastly, I propose a series of research questions and experiments for adaptive therapy that CancerSim can address in the pursuit of advancing cancer treatment strategies.
ContributorsShah, Sanjana Saurin (Author) / Daymude, Joshua J (Thesis advisor) / Forrest, Stephanie (Committee member) / Maley, Carlo C (Committee member) / Arizona State University (Publisher)
Created2023