Matching Items (197)
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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
The processes of a human somatic cell are very complex with various genetic mechanisms governing its fate. Such cells undergo various genetic mutations, which translate to the genetic aberrations that we see in cancer. There are more than 100 types of cancer, each having many more subtypes with aberrations being

The processes of a human somatic cell are very complex with various genetic mechanisms governing its fate. Such cells undergo various genetic mutations, which translate to the genetic aberrations that we see in cancer. There are more than 100 types of cancer, each having many more subtypes with aberrations being unique to each. In the past two decades, the widespread application of high-throughput genomic technologies, such as micro-arrays and next-generation sequencing, has led to the revelation of many such aberrations. Known types and subtypes can be readily identified using gene-expression profiling and more importantly, high-throughput genomic datasets have helped identify novel sub-types with distinct signatures. Recent studies showing usage of gene-expression profiling in clinical decision making in breast cancer patients underscore the utility of high-throughput datasets. Beyond prognosis, understanding the underlying cellular processes is essential for effective cancer treatment. Various high-throughput techniques are now available to look at a particular aspect of a genetic mechanism in cancer tissue. To look at these mechanisms individually is akin to looking at a broken watch; taking apart each of its parts, looking at them individually and finally making a list of all the faulty ones. Integrative approaches are needed to transform one-dimensional cancer signatures into multi-dimensional interaction and regulatory networks, consequently bettering our understanding of cellular processes in cancer. Here, I attempt to (i) address ways to effectively identify high quality variants when multiple assays on the same sample samples are available through two novel tools, snpSniffer and NGSPE; (ii) glean new biological insight into multiple myeloma through two novel integrative analysis approaches making use of disparate high-throughput datasets. While these methods focus on multiple myeloma datasets, the informatics approaches are applicable to all cancer datasets and will thus help advance cancer genomics.
ContributorsYellapantula, Venkata (Author) / Dinu, Valentin (Thesis advisor) / Scotch, Matthew (Committee member) / Wallstrom, Garrick (Committee member) / Keats, Jonathan (Committee member) / Arizona State University (Publisher)
Created2014
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Description
No two cancers are alike. Cancer is a dynamic and heterogeneous disease, such heterogeneity arise among patients with the same cancer type, among cancer cells within the same individual’s tumor and even among cells within the same sub-clone over time. The recent application of next-generation sequencing and precision medicine techniques

No two cancers are alike. Cancer is a dynamic and heterogeneous disease, such heterogeneity arise among patients with the same cancer type, among cancer cells within the same individual’s tumor and even among cells within the same sub-clone over time. The recent application of next-generation sequencing and precision medicine techniques is the driving force to uncover the complexity of cancer and the best clinical practice. The core concept of precision medicine is to move away from crowd-based, best-for-most treatment and take individual variability into account when optimizing the prevention and treatment strategies. Next-generation sequencing is the method to sift through the entire 3 billion letters of each patient’s DNA genetic code in a massively parallel fashion.

The deluge of next-generation sequencing data nowadays has shifted the bottleneck of cancer research from multiple “-omics” data collection to integrative analysis and data interpretation. In this dissertation, I attempt to address two distinct, but dependent, challenges. The first is to design specific computational algorithms and tools that can process and extract useful information from the raw data in an efficient, robust, and reproducible manner. The second challenge is to develop high-level computational methods and data frameworks for integrating and interpreting these data. Specifically, Chapter 2 presents a tool called Snipea (SNv Integration, Prioritization, Ensemble, and Annotation) to further identify, prioritize and annotate somatic SNVs (Single Nucleotide Variant) called from multiple variant callers. Chapter 3 describes a novel alignment-based algorithm to accurately and losslessly classify sequencing reads from xenograft models. Chapter 4 describes a direct and biologically motivated framework and associated methods for identification of putative aberrations causing survival difference in GBM patients by integrating whole-genome sequencing, exome sequencing, RNA-Sequencing, methylation array and clinical data. Lastly, chapter 5 explores longitudinal and intratumor heterogeneity studies to reveal the temporal and spatial context of tumor evolution. The long-term goal is to help patients with cancer, particularly those who are in front of us today. Genome-based analysis of the patient tumor can identify genomic alterations unique to each patient’s tumor that are candidate therapeutic targets to decrease therapy resistance and improve clinical outcome.
ContributorsPeng, Sen (Author) / Dinu, Valentin (Thesis advisor) / Scotch, Matthew (Committee member) / Wallstrom, Garrick (Committee member) / Arizona State University (Publisher)
Created2015
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Description
A series of mitochondria targeting probes was synthesized for the purpose of exploring the feasibility of a mitochondria targeting fluorescent sensor. Of the probes, the probe with a two carbon spacer showed the best co-localization from staining with the established MitoTracker Red® FM, indicating a potential development of the probe

A series of mitochondria targeting probes was synthesized for the purpose of exploring the feasibility of a mitochondria targeting fluorescent sensor. Of the probes, the probe with a two carbon spacer showed the best co-localization from staining with the established MitoTracker Red® FM, indicating a potential development of the probe into mitochondria targeting sensor. However, cytotoxicity was observed for the probe with a six carbon spacer. Three additional mitochondria targeting fluorescent probes of longer spacer groups were synthesized, but the cytotoxicity was not observed to be as high as that of the probe with a two carbon spacer. The cytotoxicity was characterized to be that of caspase dependent cell death. To screen for a possible effect on apoptosis due to the mitochondrial probe, three fluorescent fusion proteins binding the anti-apoptotic proteins were designed and expressed. Each purified fusion protein was then incubated with the cytotoxic mitochondrial probe, and the mixture was isolated by running an affinity column. The fluorescence analysis of eluted fractions showed preliminary data of possible interaction between the protein and the mitochondrial probe.
ContributorsLee, Fred (Author) / Meldrum, Deirdre R. (Thesis director) / Tian, Yanqing (Committee member) / Zhang, Liqiang (Committee member) / Barrett, The Honors College (Contributor) / Chemical Engineering Program (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2014-12
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Description
An in-depth analysis of Homeview Realty and Homeview Financial was conducted. A marketing plan for both companies was prepared for this project. Homeview Realty and Homeview Financial are in the midst of dynamic industries. The landscape of doing business in the real estate and mortgage industries are constantly changing and

An in-depth analysis of Homeview Realty and Homeview Financial was conducted. A marketing plan for both companies was prepared for this project. Homeview Realty and Homeview Financial are in the midst of dynamic industries. The landscape of doing business in the real estate and mortgage industries are constantly changing and evolving. Thus, it is vital for Homeview Realty and Homeview Financial to constantly be knowledgeable in these fields. With this dynamic aspect, the landscape for marketing has also changed; it became digital in nature. Thus, it is important to analyze Homeview Realty and Homeview Financial currently and create a live marketing plan that can be updated when needed. With a marketing plan in hand, Homeview will be able understand its business model, mission, goals, and objectives and in turn be able to create marketing campaigns compatible with the companies objectives and strategic directions.
ContributorsCrowley, Rachel Victoria (Author) / Ostrom, Lonnie (Thesis director) / Montoya, Detra (Committee member) / Mirshak, Paul (Committee member) / Barrett, The Honors College (Contributor) / Department of Marketing (Contributor) / Department of Supply Chain Management (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Department of Finance (Contributor) / School of Accountancy (Contributor)
Created2014-05
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Description
Repeating tiles made of DNA were used to try to form an indefinitely large structure. Both the tiles and structure were 2D. Two different patterns were tested, one corrugated and one not. Corrugation means that the tiles alternated between facing up and facing down, canceling out any curvature to the

Repeating tiles made of DNA were used to try to form an indefinitely large structure. Both the tiles and structure were 2D. Two different patterns were tested, one corrugated and one not. Corrugation means that the tiles alternated between facing up and facing down, canceling out any curvature to the tile and creating a slightly corrugated but largely 2D pattern. Annealing methods were also experimented with. Annealing the structure in two, separate steps as opposed to one was tested. Another experiment was comparing cyclic versus linear annealing. A linear decrease in temperatures defines the linear annealing, and a cyclic method involved a linear drop to a certain temperature, followed by a slight increase in temperature and cooling back down again. This cycle is done several times before it continues linear cool down. It was seen that both corrugated and non-corrugated structures could be made. In both cases tiles that make up a larger section of the overall pattern were more successful. This is especially important for the non-corrugated pattern. Linear and 2step annealing methods seem to yield the best results.
ContributorsHunt, Ashley Elizabeth (Author) / Yan, Liu (Thesis director) / Yan, Hao (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
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Description
Introduction: Human papillomavirus (HPV) infection is seen in up to 90% of cases of cervical cancer, the third leading cancer cause of death in women. Current HPV screening focuses on only two HPV types and covers roughly 75% of HPV-associated cervical cancers. A protein based assay to test for antibody

Introduction: Human papillomavirus (HPV) infection is seen in up to 90% of cases of cervical cancer, the third leading cancer cause of death in women. Current HPV screening focuses on only two HPV types and covers roughly 75% of HPV-associated cervical cancers. A protein based assay to test for antibody biomarkers against 98 HPV antigens from both high and low risk types could provide an inexpensive and reliable method to screen for patients at risk of developing invasive cervical cancer. Methods: 98 codon optimized, commercially produced HPV genes were cloned into the pANT7_cGST vector, amplified in a bacterial host, and purified for mammalian expression using in vitro transcription/translation (IVTT) in a luminescence-based RAPID ELISA (RELISA) assay. Monoclonal antibodies were used to determine immune cross-reactivity between phylogenetically similar antigens. Lastly, several protein characteristics were examined to determine if they correlated with protein expression. Results: All genes were successfully moved into the destination vector and 86 of the 98 genes (88%) expressed protein at an adequate level. A difference was noted in expression by gene across HPV types but no correlation was found between protein size, pI, or aliphatic index and expression. Discussion: Further testing is needed to express the remaining 12 HPV genes. Once all genes have been successfully expressed and purified at high concentrations, DNA will be printed on microscope slides to create a protein microarray. This microarray will be used to screen HPV-positive patient sera for antibody biomarkers that may be indicative of cervical cancer and precancerous cervical neoplasias.
ContributorsMeshay, Ian Matthew (Author) / Anderson, Karen (Thesis director) / Magee, Mitch (Committee member) / Katchman, Benjamin (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2015-05
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Description
Lung cancer is the leading cause of cancer-related deaths in the US. Low-dose computed tomography (LDCT) scans are speculated to reduce lung cancer mortality. However LDCT scans impose multiple risks including false-negative results, false- positive results, overdiagnosis, and cancer due to repeated exposure to radiation. Immunosignaturing is a new method

Lung cancer is the leading cause of cancer-related deaths in the US. Low-dose computed tomography (LDCT) scans are speculated to reduce lung cancer mortality. However LDCT scans impose multiple risks including false-negative results, false- positive results, overdiagnosis, and cancer due to repeated exposure to radiation. Immunosignaturing is a new method proposed to screen and detect lung cancer, eliminating the risks associated with LDCT scans. Known and blinded primary blood sera from participants with lung cancer and no cancer were run on peptide microarrays and analyzed. Immunosignatures for each known sample collectively indicated 120 peptides unique to lung cancer and non-cancer participants. These 120 peptides were used to determine the status of the blinded samples. Verification of the results from Vanderbilt is pending.
ContributorsNguyen, Geneva Trieu (Author) / Woodbury, Neal (Thesis director) / Zhao, Zhan-Gong (Committee member) / Stafford, Phillip (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Department of Psychology (Contributor)
Created2015-05
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Description
The purpose of this project was to identify proteins associated with the migration and invasion of non-transformed MCF10A mammary epithelial cells with ectopically expressed missense mutations in p53. Because of the prevalence of TP53 missense mutations in basal-like and triple-negative breast cancer tumors, understanding the effect of TP53 mutations on

The purpose of this project was to identify proteins associated with the migration and invasion of non-transformed MCF10A mammary epithelial cells with ectopically expressed missense mutations in p53. Because of the prevalence of TP53 missense mutations in basal-like and triple-negative breast cancer tumors, understanding the effect of TP53 mutations on the phenotypic expression of human mammary epithelial cells may offer new therapeutic targets for those currently lacking in treatment options. As such, MCF10A mammary epithelial cells ectopically overexpressing structural mutations (G245S, H179R, R175H, Y163C, Y220C, and Y234C) and DNA-binding mutations (R248Q, R248W, R273C, and R273H) in the DNA-binding domain were selected for use in this project. Overexpression of p53 in the mutant cell lines was confirmed by western blot and q-PCR analysis targeting the V5 epitope tag present in the pLenti4 vector used to transduce TP53 into the mutant cell lines. Characterization of the invasion and migration phenotypes resulting from the overexpression of p53 in the mutant cell lines was achieved using transwell invasion and migration assays with Boyden chambers. Statistical analysis showed that three cell lines—DNA-contact mutants R248W and R273C and structural mutant Y220C—were consistently more migratory and invasive and demonstrated a relationship between the migration and invasion properties of the mutant cell lines. Two families of proteins were then explored: those involved in the Epithelial-Mesenchymal Transition (EMT) and matrix metalloproteinases (MMPs). Results of q-PCR and immunofluorescence analysis of epithelial marker E-cadherin and mesenchymal proteins Slug and Vimentin did not show a clear relationship between mRNA and protein expression levels with the migration and invasiveness phenotypes observed in the transwell studies. Results of western blotting, q-PCR, and zymography of MMP-2 and MMP-9 also did not show any consistent results indicating a definite relationship between MMPs and the overall invasiveness of the cells. Finally, two drugs were tested as possible treatments inhibiting invasiveness: ebselen and SBI-183. These drugs were tested on only the most invasive of the MCF10A p53 mutant cell lines (R248W, R273C, and Y220C). Results of invasion assay following 30 μM treatment with ebselen and SBI-183 showed that ebselen does not inhibit invasiveness; SBI-183, however, did inhibit invasiveness in all three cell lines tested. As such, SBI-183 will be an important compound to study in the future as a treatment that could potentially serve to benefit triple-negative or basal-like breast cancer patients who currently lack therapeutic treatment options.
ContributorsZhang, Kathie Q (Author) / LaBaer, Joshua (Thesis director) / Anderson, Karen (Committee member) / Gonzalez, Laura (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
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Description
This study assessed the effects of running an eating prevention program on body image satisfaction/behavior and the leadership skills of collegiate women. The sample included a group of 43 undergraduate women who voluntarily chose to become peer-educators in the eating prevention program called the Body Project. Self-report questionnaires evaluating both

This study assessed the effects of running an eating prevention program on body image satisfaction/behavior and the leadership skills of collegiate women. The sample included a group of 43 undergraduate women who voluntarily chose to become peer-educators in the eating prevention program called the Body Project. Self-report questionnaires evaluating both the preoccupation with personal body image and general leadership skills were distributed and collected electronically. The results were analyzed to determine that being a peer leader in the Body project did not increase eating disorder symptoms but actually decreased the symptoms. It was also determined that being a peer educator had no effect on leadership skills. Therefore, being a peer leader is beneficial for reducing eating disorder symptoms, but not for advancing leadership skills.
ContributorsCamiliere, Taylor Marie (Author) / Perez, Marisol (Thesis director) / Cavanaugh Toft, Carolyn (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Department of Psychology (Contributor)
Created2015-05