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Pathway analysis helps researchers gain insight into the biology behind gene expression-based data. By applying this data to known biological pathways, we can learn about mutations or other changes in cellular function, such as those seen in cancer. There are many tools that can be used to analyze pathways; however,

Pathway analysis helps researchers gain insight into the biology behind gene expression-based data. By applying this data to known biological pathways, we can learn about mutations or other changes in cellular function, such as those seen in cancer. There are many tools that can be used to analyze pathways; however, it can be difficult to find and learn about the which tool is optimal for use in a certain experiment. This thesis aims to comprehensively review four tools, Cytoscape, PaxtoolsR, PathOlogist, and Reactome, and their role in pathway analysis. This is done by applying a known microarray data set to each tool and testing their different functions. The functions of these programs will then be analyzed to determine their roles in learning about biology and assisting new researchers with their experiments. It was found that each tools holds a very unique and important role in pathway analysis. Visualization pathways have the role of exploring individual pathways and interpreting genomic results. Quantification pathways use statistical tests to determine pathway significance. Together one can find pathways of interest and then explore areas of interest.
ContributorsRehling, Thomas Evan (Author) / Buetow, Kenneth (Thesis director) / Wilson, Melissa (Committee member) / School of Life Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Description
Immunotherapy is an effective treatment for cancer which enables the patient's immune system to recognize tumor cells as pathogens. In order to design an individualized treatment, the t cell receptors (TCR) which bind to a tumor's unique antigens need to be determined. We created a convolutional neural network to predict

Immunotherapy is an effective treatment for cancer which enables the patient's immune system to recognize tumor cells as pathogens. In order to design an individualized treatment, the t cell receptors (TCR) which bind to a tumor's unique antigens need to be determined. We created a convolutional neural network to predict the binding affinity between a given TCR and antigen to enable this.
ContributorsCai, Michael Ray (Author) / Lee, Heewook (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-12
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Description

The purpose of this project is to analyze the current state of cancer nanomedicine and its challenges. Cancer is the second most deadly illness in the United States after heart disease. Nanomedicine, the use of materials between 1 and 100 nm to for the purpose of addressing healthcare-related problems, is

The purpose of this project is to analyze the current state of cancer nanomedicine and its challenges. Cancer is the second most deadly illness in the United States after heart disease. Nanomedicine, the use of materials between 1 and 100 nm to for the purpose of addressing healthcare-related problems, is particularly suited for treating it since nanoparticles have properties such as high surface area-to-volume ratios and favorable drug release profiles that make them more suitable for tasks such as consistent drug delivery to tumor tissue. The questions posed are: What are the current nanomedical treatments for cancer? What are the technical, social, and legal challenges related to nanomedical treatments and how can they be overcome? To answer the questions mentioned above, information from several scientific papers on nanomedical treatments for cancer as well as from social science journals was synthesized. Based on the findings, nanomedicine has a wide range of applications for cancer drug delivery, detection, and immunotherapy. The main technical challenge related to nanomedical treatments is navigating through biological barriers such as the mononuclear phagocyte system, the kidney, the blood-brain barrier, and the tumor microenvironment. Current approaches to meeting this challenge include altering the size, shape, and charge of nanoparticles for easier passage. The main social and legal challenge related to nanomedical treatments is the difficulty of regulating them due to factors such as the near impossibility of detecting nanowaste. Current approaches to meeting this challenge include the use of techniques such as scanning tunneling microscopy and atomic force microscopy to help distinguish nanowaste from the surroundings. More research will have to be done in these and other areas to enhance a major cancer-fighting tool.

ContributorsAbraham, Alfred Francy (Author) / Brian, Jennifer (Thesis director) / Liu, Yan (Committee member) / Materials Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Glioblastoma (GBM) is the most lethal primary brain tumor in adults with a less than 5% chance of survival beyond 5 years. With few effective therapies beyond the standard of care, there are often treatment resistant recurrences seen in most patients. STAT5 is a protein that has shown to be

Glioblastoma (GBM) is the most lethal primary brain tumor in adults with a less than 5% chance of survival beyond 5 years. With few effective therapies beyond the standard of care, there are often treatment resistant recurrences seen in most patients. STAT5 is a protein that has shown to be upregulated in highly invasive and treatment resistant GBM. Elucidating the role of STAT5 in GBM could reveal a node of therapeutic vulnerability in primary and recurrent GBM.

ContributorsInforzato, Hannah (Author) / Plaisier, Christopher (Thesis director) / Tran, Nhan (Committee member) / Blomquist, Mylan (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Department of Psychology (Contributor)
Created2022-05
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Description

Cancer is an ever-relevant disease with many genetic, social, environmental, and behavioral risk factors. One factor which has been garnering interest is the impact of nutrition on cancer. As a disease process, cancer is primarily driven by an accumulation of genetic aberrations. Recent epidemiological, pre-clinical, and clinical studies have demonstrated

Cancer is an ever-relevant disease with many genetic, social, environmental, and behavioral risk factors. One factor which has been garnering interest is the impact of nutrition on cancer. As a disease process, cancer is primarily driven by an accumulation of genetic aberrations. Recent epidemiological, pre-clinical, and clinical studies have demonstrated various impacts of bioactive food molecules on the promotion or prevention of these oncogenic mutations. This work explores several of these molecules and their relation to cancer prevention and provides a sample meal plan, which highlights many additional molecules that are currently being studied.

ContributorsCurtin, Elise (Author) / Don, Rachael (Thesis director) / Compton, Carolyn (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2022-05
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Description

Cancer is an ever-relevant disease with many genetic, social, environmental, and behavioral risk factors. One factor which has been garnering interest is the impact of nutrition on cancer. As a disease process, cancer is primarily driven by an accumulation of genetic aberrations. Recent epidemiological, pre-clinical, and clinical studies have demonstrated

Cancer is an ever-relevant disease with many genetic, social, environmental, and behavioral risk factors. One factor which has been garnering interest is the impact of nutrition on cancer. As a disease process, cancer is primarily driven by an accumulation of genetic aberrations. Recent epidemiological, pre-clinical, and clinical studies have demonstrated various impacts of bioactive food molecules on the promotion or prevention of these oncogenic mutations. This work explores several of these molecules and their relation to cancer prevention and provides a sample meal plan, which highlights many additional molecules that are currently being studied.

ContributorsCurtin, Elise (Author) / Don, Rachael (Thesis director) / Compton, Carolyn (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2022-05
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Description

Cancer treatments such as chemotherapy and radiation are expensive, painful, and often ineffective, as they compromise the patient’s immune system. Genetically-modified Salmonella Typhimurium (GMS) strains, however, have been proven to target tumors and suppress tumor growth. The GMS then undergo programmed lysis, optimally leaving no trace of Salmonella in the

Cancer treatments such as chemotherapy and radiation are expensive, painful, and often ineffective, as they compromise the patient’s immune system. Genetically-modified Salmonella Typhimurium (GMS) strains, however, have been proven to target tumors and suppress tumor growth. The GMS then undergo programmed lysis, optimally leaving no trace of Salmonella in the body. Additionally, constant culturing of S. Typhimurium changes the pH of the culture medium. The objective of this research is to investigate using Salmonella to induce changes in the typically acidic tumor microenvironment (TME) pH, ideally hindering tumor growth. Future studies involve utilizing Salmonella to treat a multitude of cancers.

ContributorsFleck, Kiera (Author) / Kong, Wei (Thesis director) / Fu, Lingchen (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Harrington Bioengineering Program (Contributor)
Created2022-05
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Description
Glioblastoma brain tumors are among the most lethal human cancers. Treatment efforts typically involve both surgical tumor removal, as well as ongoing therapy. In this work, we propose the use of deuterium magnetic resonance imaging (MRI) to delineate tumor boundaries based on spatial distributions of deuterated leucine, as well as

Glioblastoma brain tumors are among the most lethal human cancers. Treatment efforts typically involve both surgical tumor removal, as well as ongoing therapy. In this work, we propose the use of deuterium magnetic resonance imaging (MRI) to delineate tumor boundaries based on spatial distributions of deuterated leucine, as well as resolve the metabolism of leucine within the tumor. Accurate boundary identification contributes to effectiveness of tumor removal efforts, while amino acid metabolism information may help characterize tumor malignancy and guide ongoing treatment. So, we first examine the fundamental mechanisms of deuterium MRI. We then discuss the use of spin-echo and gradient recall echo sequences for mapping spatial distributions of deuterated leucine, and the use of single-voxel spectroscopy for imaging metabolites within a tumor.
ContributorsCostelle, Anna (Author) / Beeman, Scott (Thesis director) / Kodibagkar, Vikram (Committee member) / Barrett, The Honors College (Contributor) / Department of Physics (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05
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Description

Molecular pathology makes use of estimates of tumor content (tumor percentage) for pre-analytic and analytic purposes, such as molecular oncology testing, massive parallel sequencing, or next-generation sequencing (NGS), assessment of sample acceptability, accurate quantitation of variants, assessment of copy number changes (among other applications), determination of specimen viability for testing

Molecular pathology makes use of estimates of tumor content (tumor percentage) for pre-analytic and analytic purposes, such as molecular oncology testing, massive parallel sequencing, or next-generation sequencing (NGS), assessment of sample acceptability, accurate quantitation of variants, assessment of copy number changes (among other applications), determination of specimen viability for testing (since many assays require a minimum tumor content to report variants at the limit of detection) may all be improved with more accurate and reproducible estimates of tumor content. Currently, tumor percentages of samples submitted for molecular testing are estimated by visual examination of Hematoxylin and Eosin (H&E) stained tissue slides under the microscope by pathologists. These estimations can be automated, expedited, and rendered more accurate by applying machine learning methods on digital whole slide images (WSI).

ContributorsCirelli, Claire (Author) / Yang, Yezhou (Thesis director) / Yalim, Jason (Committee member) / Velu, Priya (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05
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Description

Age is the most significant risk factor for cancer development in humans. The somatic mutation theory postulates that the accumulation of genomic mutations over time results in cellular function degradation which plays an important role in understanding aging and cancer development. Specifically, degradation of the mechanisms that underlie somatic maintenance

Age is the most significant risk factor for cancer development in humans. The somatic mutation theory postulates that the accumulation of genomic mutations over time results in cellular function degradation which plays an important role in understanding aging and cancer development. Specifically, degradation of the mechanisms that underlie somatic maintenance can occur due to decreased immune cell function and genomic responses to DNA damage. Research has shown that this degradation can lead to the accumulation of mutations that can cause cancer in humans. Despite recent advances in our understanding of cancer in non-human species, how this risk factor translates across species is poorly characterized. Here, we analyze a veterinarian cancer dataset of 4,178 animals to investigate if age related cancer prevalence is similar in non-human animals. We intend for this work to be used as a primary step towards understanding the potential overlap and/or uniqueness between human and non-human cancer risk factors. This study can be used to better understand cancer development and how evolutionary processes have shaped somatic maintenance across species.

ContributorsAksoy, Selin (Author) / Maley, Carlo (Thesis director) / Boddy, Amy (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Department of Psychology (Contributor)
Created2022-05