Stochastic Models of Epithelial Cancer Initiation and Glioblastoma Recurrence
2018-06
Loading...
View/Download File
Persistent link to this item
Statistics
View StatisticsJournal Title
Journal ISSN
Volume Title
Title
Stochastic Models of Epithelial Cancer Initiation and Glioblastoma Recurrence
Authors
Published Date
2018-06
Publisher
Type
Thesis or Dissertation
Abstract
Cancer development involves the inherently stochastic accumulation of genetic mutations, conferring growth advantages to the cells affected by these mutations. Thus, stochastic modeling provides useful insight when studying the evolutionary processes of cancer initiation and tumor progression. This thesis consists of three projects within the field of stochastic modeling of cancer evolution. First we explore the temporal dynamics of spatial heterogeneity during the process of carcinogenesis from healthy tissue. We utilize a spatial stochastic model of mutation accumulation and clonal expansion to describe this process. Under a two-step carcinogenesis model, we analyze two new measures of spatial population heterogeneity. In particular, we study the typical length-scale of genetic heterogeneity during carcinogenesis and estimate the size of the clone surrounding a sampled premalignant cell. Next we study the propagation speed of a premalignant clone during carcinogenesis. We approximate a premalignant clone in epithelial tissue containing w layers of proliferating cells (referred to as a ``basal zone'') with a biased voter model on a set of w stacked integer lattices. Using the dual process of the biased voter model, we determine the asymptotic propagation speed of the premalignant clone in this setting and compare it to the previously determined speed in epithelial tissue with a single layer of proliferating cells. We then use this speed to investigate clinical implications for primary tumors detected in various types of epithelial tissue. Finally we develop a multi-type branching process model of the tumor progression and treatment response in glioblastoma multiforme (GBM). GBM recurrence is often attributed to acquired resistance to the standard chemotherapeutic agent temozolomide (TMZ). Promoter methylation of the DNA repair gene MGMT is frequently linked to TMZ sensitivity. We develop and parameterize a model using clinical and experimental data, to investigate the interplay between TMZ and MGMT methylation during GBM treatment. Our model suggests that TMZ may have an inhibitory effect on maintenance methylation of MGMT after cell division. Incorporating this effect, we study the optimal TMZ dosing regimen for GBM patients with high and low levels of MGMT methylation at diagnosis.
Description
University of Minnesota Ph.D. dissertation June 2018. Major: Mathematics. Advisor: Jasmine Foo. 1 computer file (PDF); vii, 152 pages.
Related to
Replaces
License
Collections
Series/Report Number
Funding information
Isbn identifier
Doi identifier
Previously Published Citation
Suggested citation
Storey, Kathleen. (2018). Stochastic Models of Epithelial Cancer Initiation and Glioblastoma Recurrence. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/200252.
Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.