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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

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

Stress is a necessary and functional part of human physiology. From responding to life-threatening situations to getting people out of bed in the morning, stress serves a major purpose in human survival. However, when consistent and high levels of stress are experienced, it can pose a threat to human health.

Stress is a necessary and functional part of human physiology. From responding to life-threatening situations to getting people out of bed in the morning, stress serves a major purpose in human survival. However, when consistent and high levels of stress are experienced, it can pose a threat to human health. One of the major mediators of physiological stress is a hormone called cortisol. Cortisol is a well-defined substance and its function in normal physiology is well understood. Scientific research indicates that consistent and high levels of this hormone may be an aid in cancer’s ability to evade the human immune response. Despite this, there is not much known about its relationship with cancer. I used immunofluorescence to determine cell-to-cell variability of vimentin expression and DNA content for cells that were exposed to cortisol at consistent and frequent doses overtime and those not exposed to cortisol to determine if cortisol altered the variability of vimentin expression and DNA content. I observed no change in the variability in vimentin expression across both cell conditions. I did observe variability in DNA content across both cell conditions, with more variability in the population affected by cortisol. These results suggest that there might be a relationship between the stress induced by cortisol, taking place at the genomic level but may have no impact on specific protein expression. Potential implications of the research conducted are looks to preventative medicine in the context of stress experienced by members of marginalized groups as a way of preventing cancer development.

ContributorsWarthen, Alexander (Author) / Quaranta, Kimberly (Thesis director) / Bussey, Kimberly (Thesis director) / Cunningham, Anna (Committee member) / Barrett, The Honors College (Contributor) / College of Health Solutions (Contributor)
Created2023-05
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Description
Genomic structural variation (SV) is defined as gross alterations in the genome broadly classified as insertions/duplications, deletions inversions and translocations. DNA sequencing ushered structural variant discovery beyond laboratory detection techniques to high resolution informatics approaches. Bioinformatics tools for computational discovery of SVs however are still missing variants in the complex

Genomic structural variation (SV) is defined as gross alterations in the genome broadly classified as insertions/duplications, deletions inversions and translocations. DNA sequencing ushered structural variant discovery beyond laboratory detection techniques to high resolution informatics approaches. Bioinformatics tools for computational discovery of SVs however are still missing variants in the complex cancer genome. This study aimed to define genomic context leading to tool failure and design novel algorithm addressing this context. Methods: The study tested the widely held but unproven hypothesis that tools fail to detect variants which lie in repeat regions. Publicly available 1000-Genomes dataset with experimentally validated variants was tested with SVDetect-tool for presence of true positives (TP) SVs versus false negative (FN) SVs, expecting that FNs would be overrepresented in repeat regions. Further, the novel algorithm designed to informatically capture the biological etiology of translocations (non-allelic homologous recombination and 3&ndashD; placement of chromosomes in cells –context) was tested using simulated dataset. Translocations were created in known translocation hotspots and the novel&ndashalgorithm; tool compared with SVDetect and BreakDancer. Results: 53% of false negative (FN) deletions were within repeat structure compared to 81% true positive (TP) deletions. Similarly, 33% FN insertions versus 42% TP, 26% FN duplication versus 57% TP and 54% FN novel sequences versus 62% TP were within repeats. Repeat structure was not driving the tool's inability to detect variants and could not be used as context. The novel algorithm with a redefined context, when tested against SVDetect and BreakDancer was able to detect 10/10 simulated translocations with 30X coverage dataset and 100% allele frequency, while SVDetect captured 4/10 and BreakDancer detected 6/10. For 15X coverage dataset with 100% allele frequency, novel algorithm was able to detect all ten translocations albeit with fewer reads supporting the same. BreakDancer detected 4/10 and SVDetect detected 2/10 Conclusion: This study showed that presence of repetitive elements in general within a structural variant did not influence the tool's ability to capture it. This context-based algorithm proved better than current tools even with half the genome coverage than accepted protocol and provides an important first step for novel translocation discovery in cancer genome.
ContributorsShetty, Sheetal (Author) / Dinu, Valentin (Thesis advisor) / Bussey, Kimberly (Committee member) / Scotch, Matthew (Committee member) / Wallstrom, Garrick (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Glioblastoma multiforme is associated with a very low survival rate and is recognized as the most vicious form of intracranial cancer. The Akt gene pathway has three different isoforms, each of which has a different role in the tumors of GBM. Preliminary data suggests that Akt3 may work to decrease

Glioblastoma multiforme is associated with a very low survival rate and is recognized as the most vicious form of intracranial cancer. The Akt gene pathway has three different isoforms, each of which has a different role in the tumors of GBM. Preliminary data suggests that Akt3 may work to decrease tumorigenicity. A produced image that visualizes the subcellular localization of Akt3 led the author to believe that Akt3 may reduce tumorigenicity by decreasing genomic instability caused by the cancer. To explore this, flow cytometry was performed on GBM cell lines with Akt3v1 over-expression, Akt3v2 over-expression, and a control glioma cell line.
ContributorsGhorayeb, Antoine (Author) / Neisewander, Janet (Thesis director) / Diehnelt, Chris (Committee member) / Moussallem, Suzan (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2012-12