Matching Items (11)
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- All Subjects: Cancer
- Creators: Blattman, Joseph
- Creators: Kostelich, Eric
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Resource Type: Text
Description
Since Metastatic Osteosarcoma is unresponsive to most of the current standards of care currently available, and yields a survival rate of 20%, it is pertinent that novel approaches to treating it be undertaken in scientific research. Past studies in our lab have used a The Immune Blockade Therapy, utilizing α-CTLA-4 and α-PD-L1 to treat mice with metastatic osteosarcoma; this resulted in 60% of mice achieving disease-free survival and protective immunity against metastatic osteosarcoma. 12 We originally wanted to see if the survival rate could be boosted by pairing the immune blockade therapy with another current, standard of care, radiation. We had found that there were certain, key features to experimental design that had to be maintained and explored further in order to raise survival rates, ultimately with the goal of reestablishing the 60% survival rate seen in mice treated with the immune blockade therapy. Our results show that mice with mature immune systems, which develop by 6-8 weeks, should be used in experiments testing an immune blockade, or other forms of immunotherapy, as they are capable of properly responding to treatment. Treatment as early as one day after should be maintained in future experiments looking at the immune blockade therapy for the treatment of metastatic osteosarcoma in mice. The immune blockade therapy, using α-PD-L1 and α-CTLA-4, seems to work synergistically with radiation, a current standard of care. The combination of these therapies could potentially boost the 60% survival rate, as previously seen in mice treated with α-PD-L1 and α-CTLA-4, to a higher percent by means of reducing tumor burden and prolonging length of life in metastatic osteosarcoma.
ContributorsLabban, Nicole (Author) / Blattman, Joseph (Thesis director) / Appel, Nicole (Committee member) / Barrett, The Honors College (Contributor)
Created2017-05
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
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
Glioblastoma multiforme (GBM) is an aggressive malignant brain tumor with a median prognosis of 14 months. Human hairless protein (HR) is a 130 kDa nuclear transcription factor that plays a critical role in skin and hair function but was found to be highly expressed in neural tissue as well. The expression of HR in GBM tumor cells is significantly decreased compared to the normal brain tissue and low levels of HR expression is associated with shortened patient survival. We have recently reported that HR is a DNA binding phosphoprotein, which binds to p53 protein and p53 responsive element (p53RE) in vitro and in intact cells. We hypothesized that HR can regulate p53 downstream target genes, and consequently affects cellular function and activity. To test the hypothesis, we overexpressed HR in normal human embryonic kidney HEK293 and GBM U87MG cell lines and characterized these cells by analyzing p53 target gene expression, viability, cell-cycle arrest, and apoptosis. The results revealed that the overexpressed HR not only regulates p53-mediated target gene expression, but also significantly inhibit cell viability, induced early apoptosis, and G2/M cell cycle arrest in U87MG cells, compared to mock groups. Translating the knowledge gained from this research on the connections between HR and GBM could aid in identifying novel therapies to circumvent GBM progression or improve clinical outcome.
ContributorsBrook, Lemlem Addis (Author) / Blattman, Joseph (Thesis director) / Hsieh, Jui-Cheng (Committee member) / Goldstein, Elliott (Committee member) / Harrington Bioengineering Program (Contributor) / School of Social Transformation (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
Through a standpoint feminist perspective (Harding 2009) I conducted a situational analysis (Clarke, 2015) that examined academic literature and cancer support discussion boards (DBs) to identify how Western biomedicine, specifically oncology, can integrate complementary and alternative medicine (CAM) to improve cancer treatment in children. The aims of this project were: 1) to identify the CAM treatments that are being used to alleviate the side effects from oncological treatments and/or treat pediatric cancers; 2) to compare the subjective experience of CAM to Western biomedicine of cancer patients who leave comments on Group Loop, Cancer Compass and Cancer Forums, which are online support groups (N=20). I used grounded theory and situational mapping to analyze discussion threads. The participants identified using the following CAM treatments: herbs, imagery, prayer, stinging nettle, meditation, mind-body therapies and supplements. The participants turned to CAM treatments when their cancer was late-stage or terminal, often as an integrative and not exclusively to treat their cancer. CAM was more "effective" than biomedical oncology treatment at improving their overall quality of life and functionality. We found that youth on discussion boards did not discuss CAM treatments like the adult participants, but all participants visited these sites for support and verification of their cancer treatments. My main integration recommendation is to combine mind-body CAM therapies with biomedical treatment. This project fills the gap in literature that ignores the ideas of vulnerable populations by providing the experiences of adult and pediatric cancer patients, and that of their families. It is applicable to areas of the social studies of medicine, patient care, and families suffering from cancer. KEYWORDS: Cancer; Complementary and Alternative Medicine; Situational Analysis; Standpoint Feminism
ContributorsEsposito, Sydney Maria (Author) / Martinez, AirÃÂn (Thesis director) / Hruschka, Daniel (Committee member) / School of Human Evolution and Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
The p53 gene functions as a tumor suppressor that inhibits proliferation, regulates apoptosis, DNA repair, and normal cell cycle arrest. Mutation of the p53 gene is linked to be prevalent in 50% of all human cancers. In this paper, we are exploring triple negative breast cancer and the effects of simvastatin on tumor growth and survival. Simvastatin is a drug that is primarily used to treat high cholesterol and heart disease. Simvastatin is unique because it is able to inhibit protein prenylation through regulation of the mevalonate pathway. This makes it a potential targeted drug for therapy against p53 mutant cancer. The mechanism behind this is hypothesized to be correlated to aberrant activation of the Ras pathway. The Ras subfamily functions to transcriptionally regulate cell growth and survival, and will therefore allow for a tumor to thrive if the pathway is continually and abnormally activated. The Ras protein has to be prenylated in order for activation of this pathway to occur, making statin drug treatment a viable option as a cancer treatment. This is because it acts as a regulator of the mevalonate pathway which is upstream of protein prenylation. It is thus vital to understand these pathways at both the gene and protein level in different p53 mutants to further understand if simvastatin is indeed a drug with anti-cancer properties and can be used to target cancers with p53 mutation. The goal of this project is to study the biochemistry behind the mutation of p53's sensitivity to statin. With this information we can create a possible signature for those who could benefit from Simvastatin drug treatment as a possible targeted treatment for p53 mutant cancers.
ContributorsGrewal, Harneet (Co-author) / Loo, Yi Jia Valerie (Co-author) / Anderson, Karen (Thesis director) / Blattman, Joseph (Committee member) / Ferdosi, Shayesteh (Committee member) / Department of Psychology (Contributor) / School of Life Sciences (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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
PD-L1 blockade has shown recent success in cancer therapy and cancer vaccine regimens. One approach for anti-PD-L1 antibodies has been their application as adjuvants for cancer vaccines. Given the disadvantages of such antibodies, including long half-life and adverse events related to their use, a novel strategy using synbodies in place of antibodies can be tested. Synbodies offer a variety of advantages, including shorter half-life, smaller size, and cheaper cost. Peptides that could bind PD-L1 were identified via peptide arrays and used to construct synbodies. These synbodies were tested with inhibition ELISA assays, SPR, and pull down assays. Additional flow cytometry analysis was done to determine the binding specificity of the synbodies to PD-L1 and the ability of those synbodies to inhibit the PD-L1/PD-1 interaction. Although analysis of permeabilized cells expressing PD-L1 indicated that the synbodies could successfully bind PD-L1, those results were not replicated in non-permeabilized cells. Further assays suggested that the binding of the synbodies was non-specific. Other tests were done to see if the synbodies could inhibit the PD-1/PD-L1 interaction. This assay did not yield any conclusive results and further experimentation is needed to determine the efficacy of the synbodies in inhibiting this interaction.
ContributorsMujahed, Tala (Author) / Johnston, Stephen (Thesis director) / Blattman, Joseph (Committee member) / Diehnelt, Chris (Committee member) / School of Molecular Sciences (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