Matching Items (19)
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- All Subjects: Cancer
- Creators: Lake, Douglas
- Creators: School of Mathematical and Statistical Sciences
- Member of: Theses and Dissertations
Description
Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and includes chemotherapy, radiation therapy, and surgical removal if the tumor is surgically accessible. Treatment seldom results in a significant increase in longevity, partly due to the lack of precise information regarding tumor size and location. This lack of information arises from the physical limitations of MR and CT imaging coupled with the diffusive nature of glioblastoma tumors. GBM tumor cells can migrate far beyond the visible boundaries of the tumor and will result in a recurring tumor if not killed or removed. Since medical images are the only readily available information about the tumor, we aim to improve mathematical models of tumor growth to better estimate the missing information. Particularly, we investigate the effect of random variation in tumor cell behavior (anisotropy) using stochastic parameterizations of an established proliferation-diffusion model of tumor growth. To evaluate the performance of our mathematical model, we use MR images from an animal model consisting of Murine GL261 tumors implanted in immunocompetent mice, which provides consistency in tumor initiation and location, immune response, genetic variation, and treatment. Compared to non-stochastic simulations, stochastic simulations showed improved volume accuracy when proliferation variability was high, but diffusion variability was found to only marginally affect tumor volume estimates. Neither proliferation nor diffusion variability significantly affected the spatial distribution accuracy of the simulations. While certain cases of stochastic parameterizations improved volume accuracy, they failed to significantly improve simulation accuracy overall. Both the non-stochastic and stochastic simulations failed to achieve over 75% spatial distribution accuracy, suggesting that the underlying structure of the model fails to capture one or more biological processes that affect tumor growth. Two biological features that are candidates for further investigation are angiogenesis and anisotropy resulting from differences between white and gray matter. Time-dependent proliferation and diffusion terms could be introduced to model angiogenesis, and diffusion weighed imaging (DTI) could be used to differentiate between white and gray matter, which might allow for improved estimates brain anisotropy.
ContributorsAnderies, Barrett James (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Stepien, Tracy (Committee member) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The purpose of this project is to explore the benefit of using prodrugs in chemotherapy, as well as to explain the concept of angiogenesis and the importance of this process to tumor development. Angiogenesis is the formation of new blood capillaries that are necessary for the survival of a tumor, as a tumor cannot grow larger than 1-2 mm3 without developing its own blood supply. Vascular disrupting agents, such as iodocombstatin, a derivative of combretastatin, can be used to effectively cut off the blood supply to a growing neoplasm, effectively inhibiting the supply of oxygen and nutrients needed for cell division Thus, VDAs have a very important implication in terms of the future of chemotherapy. A prodrug, defined as an agent that is inactive in the body until metabolized to yield the drug itself, was synthesized by combining iodocombstatin with a β-glucuronide linker. The prodrug is theoretically hydrolyzed in the body to afford the active drug by β-glucuronidase, an enzyme that is produced five times as much by cancer cells as by normal cells. This effectively creates a “magic-bullet” form of chemotherapy, known as Direct Enzyme Prodrug Therapy (DEPT).
ContributorsClark, Caroline Marie (Author) / Pettit, George Robert (Thesis director) / Melody, Noeleen (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
Description
Despite the 40-year war on cancer, very limited progress has been made in developing a cure for the disease. This failure has prompted the reevaluation of the causes and development of cancer. One resulting model, coined the atavistic model of cancer, posits that cancer is a default phenotype of the cells of multicellular organisms which arises when the cell is subjected to an unusual amount of stress. Since this default phenotype is similar across cell types and even organisms, it seems it must be an evolutionarily ancestral phenotype. We take a phylostratigraphical approach, but systematically add species divergence time data to estimate gene ages numerically and use these ages to investigate the ages of genes involved in cancer. We find that ancient disease-recessive cancer genes are significantly enriched for DNA repair and SOS activity, which seems to imply that a core component of cancer development is not the regulation of growth, but the regulation of mutation. Verification of this finding could drastically improve cancer treatment and prevention.
ContributorsOrr, Adam James (Author) / Davies, Paul (Thesis director) / Bussey, Kimberly (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
Magnetic resonance imaging (MRI) data of metastatic brain cancer patients at the Barrow Neurological Institute sparked interest in the radiology department due to the possibility that tumor size distributions might mimic a power law or an exponential distribution. In order to consider the question regarding the growth trends of metastatic brain tumors, this thesis analyzes the volume measurements of the tumor sizes from the BNI data and attempts to explain such size distributions through mathematical models. More specifically, a basic stochastic cellular automaton model is used and has three-dimensional results that show similar size distributions of those of the BNI data. Results of the models are investigated using the likelihood ratio test suggesting that, when the tumor volumes are measured based on assuming tumor sphericity, the tumor size distributions significantly mimic the power law over an exponential distribution.
ContributorsFreed, Rebecca (Co-author) / Snopko, Morgan (Co-author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
Programmed cell death ligand-1 (PD-L1) is an overexpressed protein on many tumor cell types. PD-L1 is involved in normal immune regulation, playing an important role in self-tolerance and controlling autoimmunity. However, ligation of PD-L1 to PD-1 on activated T cells leads to tumor-mediated T cell suppression. Inhibiting the PD-1/PD-L1 pathway has emerged as an effective target for anti-tumor immunotherapies. Monoclonal antibodies (mAbs) targeting tumor-associated antigens such as PD-L1 have proven to be effective checkpoint blockades, improving therapeutic outcomes for cancer patients and receiving FDA approval as first line therapies for some cancers. A single chain variable fragment (scFv) is composed of the variable heavy and light chain regions of a mAb, connected by a flexible linker. We hypothesized that scFv proteins based on the published anti-PD-L1 monoclonal antibody sequences of atezolizumab and avelumab would bind to cell surface PD-L1. Four single chain variable fragments (scFvs) were constructed based on the sequences of these mAbs. PCR was used to assemble, construct, and amplify DNA fragments encoding the scFvs which were subsequently ligated into a eukaryotic expression vector. Mammalian cells were transfected with the scFv and scFv-IgG plasmids. The scFvs were tested for binding to PD-L1 on tumor cell lysates by western blot and to whole tumor cells by staining and flow cytometry analysis. DNA sequence analysis demonstrated that the scFv constructs were successfully amplified and cloned into the expression vectors and recombinant scFvs were produced. The binding capabilities of the scFvs constucts to PD-L1 protein were confirmed by western blot and flow cytometry analysis. This lead to the idea of constructing a CAR T cell engineered to target PD-L1, providing a possible adoptive T cell immunotherapy.
ContributorsPfeffer, Kirsten M. (Author) / Lake, Douglas (Thesis director) / Ho, Thai (Committee member) / Hastings, Karen (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
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
Description
Exosomes have been known to secrete an increased amount of miRNA and noncoding genes that are abnormally expressed in various cancer subtypes. Thus, they may be an early marker for pediatric cancer types that are more difficult to diagnosis without invasive techniques, and may also help identify progression of the disease. In the project, six types of pediatric cancer cell lines, along with their extracted exosomes, were analyzed and tested for different monoclonal antibodies through western blot analysis. The genes EWS-FLI1 and FGFR4 were also identified in some cancer cell lines through Reverse-Transcriptase Polymerase Chain Reaction analysis (RT-PCR). The results were indicative of similar protein markers being found in both the originating cells and their corresponding exosomes.
ContributorsKaur Bhinder, Harsimran (Author) / Lake, Douglas (Thesis director) / Azorsa, David (Committee member) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Cancer is one of the leading causes of death in the world and represents a tremendous burden on patients, families and societies. S. Typhimurium strains are specifically attracted to compounds produced by cancer cells and could overcome the traditional therapeutic barrier. However, a major problem with using live attenuated Salmonella as anti-cancer agents is their toxicity at the dose required for therapeutic efficacy, but reducing the dose results in diminished efficacy. In this project, we explored novel means to reduce the toxicity of the recombinant attenuated Salmonella by genetically engineering those virulence factors to facilitate maximal colonization of tumor tissues and reduced fitness in normal tissues. We have constructed two sets of Salmonella strains. In the first set, each targeted gene was knocked out by deletion of the gene. In the second set, the predicted promoter region of each gene was replaced with a rhamnose-regulated promoter, which will cease the synthesis of these genes in vivo, a rhamnose-free environment.
ContributorsBenson, Lee Samuel (Author) / Kong, Wei (Thesis director) / Martin, Thomas (Committee member) / Lake, Douglas (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor) / Center for Infectious Diseases and Vaccinology (Contributor) / School of Life Sciences (Contributor)
Created2013-05
Description
The long-term survival of patients with glioblastoma multiforme is compromised by the tumor's proclivity for local invasion into the surrounding normal brain. These invasive cells escape surgery and display resistance to chemotherapeutic- and radiation-induced apoptosis. We have previously shown that tumor necrosis factor-like weak inducer of apoptosis (TWEAK), a member of the tumor necrosis factor superfamily, can stimulate glioma cell invasion and survival via binding to the fibroblast growth factor-inducible 14 (Fn14) receptor and subsequent activation of the Rac1/NF-kappaB pathway. In addition, we have reported previously that Fn14 is expressed at high levels in migrating glioma cells in vitro and invading glioma cells in vivo. Here we demonstrate that TWEAK can act as a chemotactic factor for glioma cells, a potential process to drive cell invasion into the surrounding brain tissue. Specifically, we detected a chemotactic migration of glioma cells to the concentration gradient of TWEAK. Since Src family kinases (SFK) have been implicated in chemotaxis, we next determined whether TWEAK:Fn14 engagement activated these cytoplasmic tyrosine kinases. Our data shows that TWEAK stimulation of glioma cells results in a rapid phosphorylation of the SFK member Lyn as determined by multiplex Luminex assay and verified by immunoprecipitation. Immunodepletion of Lyn by siRNA oligonucleotides suppressed the chemoattractive effect of TWEAK on glioma cells. We hypothesize that TWEAK secretion by cells present in the glioma microenvironment induce invasion of glioma cells into the brain parenchyma. Understanding the function and signaling of the TWEAK-Fn14 ligand-receptor system may lead to development of novel therapies to therapeutically target invasive glioma cells.
ContributorsJameson, Nathan Meade (Author) / Anderson, Karen (Thesis director) / Lake, Douglas (Committee member) / Tran, Nhan (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2013-05
Description
Over time, tumor treatment resistance inadvertently develops when androgen de-privation therapy (ADT) is applied to metastasized prostate cancer (PCa). To combat tumor resistance, while reducing the harsh side effects of hormone therapy, the clinician may opt to cyclically alternates the patient’s treatment on and off. This method,known as intermittent ADT, is an alternative to continuous ADT that improves the patient’s quality of life while testosterone levels recover between cycles. In this paper,we explore the response of intermittent ADT to metastasized prostate cancer by employing a previously clinical data validated mathematical model to new clinical data from patients undergoing Abiraterone therapy. This cell quota model, a system of ordinary differential equations constructed using Droop’s nutrient limiting theory, assumes the tumor comprises of castration-sensitive (CS) and castration-resistant (CR)cancer sub-populations. The two sub-populations rely on varying levels of intracellular androgen for growth, death and transformation. Due to the complexity of the model,we carry out sensitivity analyses to study the effect of certain parameters on their outputs, and to increase the identifiability of each patient’s unique parameter set. The model’s forecasting results show consistent accuracy for patients with sufficient data,which means the model could give useful information in practice, especially to decide whether an additional round of treatment would be effective.
ContributorsBennett, Justin Klark (Author) / Kuang, Yang (Thesis director) / Kostelich, Eric (Committee member) / Phan, Tin (Committee member) / School of Mathematical and Statistical Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05