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- All Subjects: Oncology
- Creators: Kostelich, Eric
Description
The majority of chronic myeloid leukemia (CML) and some of acute lymphocytic leukemia (ALL) cases are associated with possessing the BCR-Abl fusion protein from an oncogenic translocation, resulting in a constantly active form of Abl and rapid proliferation. CML and ALL cells that possess the BCR-Abl fusion protein are known as Philadelphia chromosome positive (Ph+). Currently, Imatinib (selective Abl inhibitor) is used as therapy against CML and ALL. However, some patients may have malignancies which show resistance to Imatinib. Previous work displays that the transformation of progenitor B cells with the v-Abl oncogene of Abelson murine leukemia virus results in cell cycle progression, rapid proliferation, and potentially malignant transformation while preventing any further differentiation. Progenitor B cells transformed with the temperature-sensitive form of the v-Abl oncogene have served as a model to study cellular response to Imatinib treatment. After some manipulation, very few cells were forced to progress to malignancy, forming tumor in vivo. These cells were no long sensitive to v-Abl inactivation, resembling the Imatinib resistant ALL. Autophagy is the process by which proteins and organelles are broken-down and recycled within the eukaryotic cell and has been hypothesized to play a part in cancer cell survival and drug-resistance. LC3 processing is a widely accepted marker of autophagy induction and progression. It has also been shown that Imatinib treatment of Ph+ leukemia can induce autophagy. In this study, we examined the autophagy induction in response to v-Abl inactivation in a Ph+-B-ALL cell model that shows resistance to Imatinib. In particular, we wonder whether the tumor cell line resistant to v-Abl inactivation may acquire a high level of autophagy to become resistant to apoptosis induced by v-Abl inactivation, and thus become addicted to autophagy. Indeed, this tumor cell line displays a high basal levels of LC3 I and II expression, regardless of v-Abl activity. We further demonstrated that inhibition of the autophagy pathway enhances the tumor line's sensitivity to Imatinib, resulting in cell cycle arrest and massive apoptosis. The combination of autophagy and Abl inhibitions may serve as an effective therapy for BCR-Abl positive CML.
ContributorsArkus, Nohea (Author) / Chang, Yung (Thesis advisor) / Kusumi, Kenro (Committee member) / Lake, Douglas (Committee member) / Jacobs, Bertram (Committee member) / Arizona State University (Publisher)
Created2011
Description
High-dimensional systems are difficult to model and predict. The underlying mechanisms of such systems are too complex to be fully understood with limited theoretical knowledge and/or physical measurements. Nevertheless, redcued-order models have been widely used to study high-dimensional systems, because they are practical and efficient to develop and implement. Although model errors (biases) are inevitable for reduced-order models, these models can still be proven useful to develop real-world applications. Evaluation and validation for idealized models are indispensable to serve the mission of developing useful applications. Data assimilation and uncertainty quantification can provide a way to assess the performance of a reduced-order model. Real data and a dynamical model are combined together in a data assimilation framework to generate corrected model forecasts of a system. Uncertainties in model forecasts and observations are also quantified in a data assimilation cycle to provide optimal updates that are representative of the real dynamics. In this research, data assimilation is applied to assess the performance of two reduced-order models. The first model is developed for predicting prostate cancer treatment response under intermittent androgen suppression therapy. A sequential data assimilation scheme, the ensemble Kalman filter (EnKF), is used to quantify uncertainties in model predictions using clinical data of individual patients provided by Vancouver Prostate Center. The second model is developed to study what causes the changes of the state of stratospheric polar vortex. Two data assimilation schemes: EnKF and ES-MDA (ensemble smoother with multiple data assimilation), are used to validate the qualitative properties of the model using ECMWF (European Center for Medium-Range Weather Forecasts) reanalysis data. In both studies, the reduced-order model is able to reproduce the data patterns and provide insights to understand the underlying mechanism. However, significant model errors are also diagnosed for both models from the results of data assimilation schemes, which suggests specific improvements of the reduced-order models.
ContributorsWu, Zhimin (Author) / Kostelich, Eric (Thesis advisor) / Moustaoui, Mohamed (Thesis advisor) / Jones, Chris (Committee member) / Espanol, Malena (Committee member) / Platte, Rodrigo (Committee member) / Arizona State University (Publisher)
Created2021
Description
Glioblastoma Multiforme is a prevalent and aggressive brain tumor. It has an average 5-year survival rate of 6% and average survival time of 14 months. Using patient-specific MRI data from the Barrow Neurological Institute, this thesis investigates the impact of parameter manipulation on reaction-diffusion models for predicting and simulating glioblastoma growth. The study aims to explore key factors influencing tumor morphology and to contribute to enhancing prediction techniques for treatment.
ContributorsShayegan, Tara (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution & Social Change (Contributor)
Created2024-05
Description
The analysis focuses on a two-population, three-dimensional model that attempts to accurately model the growth and diffusion of glioblastoma multiforme (GBM), a highly invasive brain cancer, throughout the brain. Analysis into the sensitivity of the model to
changes in the diffusion, growth, and death parameters was performed, in order to find a set of parameter values that accurately model observed tumor growth for a given patient. Additional changes were made to the diffusion parameters to account for the arrangement of nerve tracts in the brain, resulting in varying rates of diffusion. In general, small changes in the growth rates had a large impact on the outcome of the simulations, and for each patient there exists a set of parameters that allow the model to simulate a tumor that matches observed tumor growth in the patient over a period of two or three months. Furthermore, these results are more accurate with anisotropic diffusion, rather than isotropic diffusion. However, these parameters lead to inaccurate results for patients with tumors that undergo no observable growth over the given time interval. While it is possible to simulate long-term tumor growth, the simulation requires multiple comparisons to available MRI scans in order to find a set of parameters that provide an accurate prognosis.
changes in the diffusion, growth, and death parameters was performed, in order to find a set of parameter values that accurately model observed tumor growth for a given patient. Additional changes were made to the diffusion parameters to account for the arrangement of nerve tracts in the brain, resulting in varying rates of diffusion. In general, small changes in the growth rates had a large impact on the outcome of the simulations, and for each patient there exists a set of parameters that allow the model to simulate a tumor that matches observed tumor growth in the patient over a period of two or three months. Furthermore, these results are more accurate with anisotropic diffusion, rather than isotropic diffusion. However, these parameters lead to inaccurate results for patients with tumors that undergo no observable growth over the given time interval. While it is possible to simulate long-term tumor growth, the simulation requires multiple comparisons to available MRI scans in order to find a set of parameters that provide an accurate prognosis.
ContributorsTrent, Austin Lee (Author) / Kostelich, Eric (Thesis advisor) / Gumel, Abba (Committee member) / Kuang, Yang (Committee member) / Arizona State University (Publisher)
Created2020