Matching Items (7)
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- All Subjects: Cancer
- Creators: Kuang, Yang
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
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
In a dormant state, cancer cells survive chemotherapy leaving the opportunity for cancer cell relapse and metastasis ultimately leading to patient death. A novel aminoglycoside-based hydrogel ‘Amikagel’ developed in Dr. Rege’s lab serves as a platform for a 3D tumor microenvironment (3DTM) mimicking cancer cell dormancy and relapse. Six Amikagels of varying mechanical stiffness and adhesivities were synthesized and evaluated as platforms for 3DTM formation through cell viability and cell cycle arrest analyses. The impact of fetal bovine serum concentration and bovine serum albumin concentration in the media were studied for their impact on 3DTM formation. These experiments allow us to identify the best possible Amikagel formulation for 3DTM.
ContributorsGjertsen, Haley Nicole (Author) / Rege, Kaushal (Thesis director) / Grandhi, Taraka Sai Pavan (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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
Abstract Molecular Engineering of Novel Polymeric Agents for Targeted Cancer Gene Therapy Dana Matthews Cancer gene cell therapy is a strategy that involves the administration of genes for correcting the effect of mutated cancer cells in order to induce tumor cell death. In particular, genes that encode for pro-apoptotic proteins can result in death of tumor cells. Prostate cancer is a very common cancer among males in America, and as highly destructive chemotherapy and radiation are generally the only treatments available once the cancer has metastasized, there is a need for the development of treatments that can specifically target and kill prostate cancer cells, while demonstrating low toxicity to other tissue. This experiment will attempt to create such a treatment through gene therapy techniques. The parallel synthesis and DNA binding affinity assay utilized in these experiments have produced a polymer that surpasses pEI-25, a gene delivery polymer standard, in both transfection efficacy and low cytotoxicity and trafficking of polyplexes in the cell, and finding methods to increase the transfection efficacy and specificity of polyplexes for PC3-PSMA cells.
ContributorsMatthews, Dana (Author) / Rege, Kaushal (Thesis director) / Linton, Rebecca (Committee member) / Huang, Huang-Chial (Committee member) / Barrett, The Honors College (Contributor)
Created2008-12
Description
This research addresses the need for improvement in radiation sensors for applications of ionizing radiation such as radiotherapy. The current sensors involved are polymer gel dosimeters, MOSFETs, radio-chromic films, etc. Most of the sensors involved require expensive equipment's and processing facilities for readout. There is still a need to develop better sensors that can be clinically applied. There are numerous groups around the world trying to conceive a better dosimeter. One of the radiation sensors that was developed recently was based on fluorescence signal emitted from the sensor. To advance the field of radiation sensors, a visual indicator has been developed in-lab as a method of detect ionizing radiation. The intensity of change in color is directly dependent on the amount of incident ionizing radiation. An aqueous gold nanoparticle sensor can be used to accurately determine the incident amount of ionizing radiation1. A gold nanoparticle sensor has been developed in lab with the use of hexadecyltrimethylammonium bromide (C16TAB) as the templating molecule. In the presence of ionizing radiation, the colorless gold salt is reduced and templated, creating a dispersion within the fluid1. The formation of suspended nanoparticles leads to a color change that can be visually detected and accurately analyzed through the employment of a spectrometer. Unfortunately, the toxicity of C16TAB is high. It is expected the toxicity can be reduced by replacing C16TAB with an amino acid, as amino acids can act as templating molecules in the solution and many are naturally occuring2. The experiments included a screening of 20 natural amino acids and 12 unnatural amino acids with the gold salt solution in the presence of ionizing radiation. Stability and absorbance testing was conducted on the amino acid sensors. Additional screening of lead amino acid sensors at various concentrations of irradiation was conducted.
ContributorsGupta, Saumya (Co-author) / Rege, Kaushal (Co-author, Thesis director) / Pushpavanam, Karthik (Co-author, Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Prostate cancer is the second most common kind of cancer in men. Fortunately, it has a 99% survival rate. To achieve such a survival rate, a variety of aggressive therapies are used to treat prostate cancers that are caught early. Androgen deprivation therapy (ADT) is a therapy that is given in cycles to patients. This study attempted to analyze what factors in a group of 79 patients caused them to stick with or discontinue the treatment. This was done using naïve Bayes classification, a machine-learning algorithm. The usage of this algorithm identified high testosterone as an indicator of a patient persevering with the treatment, but failed to produce statistically significant high rates of prediction.
ContributorsMillea, Timothy Michael (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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