Matching Items (78)
Filtering by
- Creators: Arizona State University
Description
Cancer is the second leading cause of death in the United States and novel methods of treating advanced malignancies are of high importance. Of these deaths, prostate cancer and breast cancer are the second most fatal carcinomas in men and women respectively, while pancreatic cancer is the fourth most fatal in both men and women. Developing new drugs for the treatment of cancer is both a slow and expensive process. It is estimated that it takes an average of 15 years and an expense of $800 million to bring a single new drug to the market. However, it is also estimated that nearly 40% of that cost could be avoided by finding alternative uses for drugs that have already been approved by the Food and Drug Administration (FDA). The research presented in this document describes the testing, identification, and mechanistic evaluation of novel methods for treating many human carcinomas using drugs previously approved by the FDA. A tissue culture plate-based screening of FDA approved drugs will identify compounds that can be used in combination with the protein TRAIL to induce apoptosis selectively in cancer cells. Identified leads will next be optimized using high-throughput microfluidic devices to determine the most effective treatment conditions. Finally, a rigorous mechanistic analysis will be conducted to understand how the FDA-approved drug mitoxantrone, sensitizes cancer cells to TRAIL-mediated apoptosis.
ContributorsTaylor, David (Author) / Rege, Kaushal (Thesis advisor) / Jayaraman, Arul (Committee member) / Nielsen, David (Committee member) / Kodibagkar, Vikram (Committee member) / Dai, Lenore (Committee member) / Arizona State University (Publisher)
Created2013
Description
ABSTRACT The phenomenon of cyberbullying has captured the attention of educators and researchers alike as it has been associated with multiple aversive outcomes including suicide. Young people today have easy access to computer mediated communication (CMC) and frequently use it to harass one another -- a practice that many researchers have equated to cyberbullying. However, there is great disagreement among researchers whether intentional harmful actions carried out by way of CMC constitute cyberbullying, and some authors have argued that "cyber-aggression" is a more accurate term to describe this phenomenon. Disagreement in terms of cyberbullying's definition and methodological inconsistencies including choice of questionnaire items has resulted in highly variable results across cyberbullying studies. Researchers are in agreement however, that cyber and traditional forms of aggression are closely related phenomena, and have suggested that they may be extensions of one another. This research developed a comprehensive set of items to span cyber-aggression's content domain in order to 1) fully address all types of cyber-aggression, and 2) assess the interrelated nature of cyber and traditional aggression. These items were administered to 553 middle school students located in a central Illinois school district. Results from confirmatory factor analyses suggested that cyber-aggression is best conceptualized as integrated with traditional aggression, and that cyber and traditional aggression share two dimensions: direct-verbal and relational aggression. Additionally, results indicated that all forms of aggression are a function of general aggressive tendencies. This research identified two synthesized models combining cyber and traditional aggression into a shared framework that demonstrated excellent fit to the item data.
ContributorsLerner, David (Author) / Green, Samuel B (Thesis advisor) / Caterino, Linda (Committee member) / Atkinson, Robert (Committee member) / Nakagawa, Kathryn (Committee member) / Arizona State University (Publisher)
Created2013
Description
Time adolescents spend in organized or informal skill based activities after school is associated with a variety of positive developmental outcomes. Little is known about how siblings might shape adolescents' motivation to participate in after-school activities. The current study applied the expectancy value model and ecological theory to understand if sibling behaviors were related to adolescents' after-school activities for 34 Mexican origin families. Qualitative and quantitative results suggested siblings engaged in five promoting behaviors (i.e., support, provider of information, role modeling, comparison, co-participation) and three inhibiting behaviors (i.e., babysitting, transportation, and negativity) towards adolescent activity participation. Furthermore, sibling behaviors differed by adolescent characteristics (i.e., cultural orientation, familism, and neighborhood) and sibling characteristics (i.e., gender, age). The results provide evidence of the various promoting and inhibiting socialization behaviors sibling might use to influence adolescents' activity motivation.
ContributorsPrice, Chara Dale (Author) / Simpkins, Sandra (Thesis advisor) / Updegraff, Kimberly (Committee member) / Menjivar, Cecilia (Committee member) / Arizona State University (Publisher)
Created2012
Description
The bleomycins are a family of glycopeptide-derived antibiotics isolated from various Streptomyces species and have been the subject of much attention from the scientific community as a consequence of their antitumor activity. Bleomycin clinically and is an integral part of a number of combination chemotherapy regimens. It has previously been shown that bleomycin has the ability to selectively target tumor cells over their non-malignant counterparts. Pyrimidoblamic acid, the N-terminal metal ion binding domain of bleomycin is known to be the moiety that is responsible for O2 activation and the subsequent chemistry leading to DNA strand scission and overall antitumor activity. Chapter 1 describes bleomycin and related DNA targeting antitumor agents as well as the specific structural domains of bleomycin. Various structural analogues of pyrimidoblamic acid were synthesized and subsequently incorporated into their corresponding full deglycoBLM A6 derivatives by utilizing a solid support. Their activity was measured using a pSP64 DNA plasmid relaxation assay and is summarized in Chapter 2. The specifics of bleomycin—DNA interaction and kinetics were studied via surface plasmon resonance and are presented in Chapter 3. By utilizing carefully selected 64-nucleotide DNA hairpins with variable 16-mer regions whose sequences showed strong binding in past selection studies, a kinetic profile was obtained for several BLMs for the first time since bleomycin was discovered in 1966. The disaccharide moiety of bleomycin has been previously shown to be a specific tumor cell targeting element comprised of L-gulose-D-mannose, especially between MCF-7 (breast cancer cells) and MCF-10A ("normal" breast cells). This phenomenon was further investigated via fluorescence microscopy using multiple cancerous cell lines with matched "normal" counterparts and is fully described in Chapter 4.
ContributorsBozeman, Trevor C (Author) / Hecht, Sidney M. (Thesis advisor) / Chaput, John (Committee member) / Gould, Ian (Committee member) / Arizona State University (Publisher)
Created2013
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 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
Description
In a 2004 paper, John Nagy raised the possibility of the existence of a hypertumor \emph{i.e.}, a focus of aggressively reproducing parenchyma cells that invade part or all of a tumor. His model used a system of nonlinear ordinary differential equations to find a suitable set of conditions for which these hypertumors exist. Here that model is expanded by transforming it into a system of nonlinear partial differential equations with diffusion, advection, and a free boundary condition to represent a radially symmetric tumor growth. Two strains of parenchymal cells are incorporated; one forming almost the entirety of the tumor while the much more aggressive strain
appears in a smaller region inside of the tumor. Simulations show that if the aggressive strain focuses its efforts on proliferating and does not contribute to angiogenesis signaling when in a hypoxic state, a hypertumor will form. More importantly, this resultant aggressive tumor is paradoxically prone to extinction and hypothesize is the cause of necrosis in many vascularized tumors.
appears in a smaller region inside of the tumor. Simulations show that if the aggressive strain focuses its efforts on proliferating and does not contribute to angiogenesis signaling when in a hypoxic state, a hypertumor will form. More importantly, this resultant aggressive tumor is paradoxically prone to extinction and hypothesize is the cause of necrosis in many vascularized tumors.
ContributorsAlvarez, Roberto L (Author) / Milner, Fabio A (Thesis advisor) / Nagy, John D. (Committee member) / Kuang, Yang (Committee member) / Thieme, Horst (Committee member) / Mahalov, Alex (Committee member) / Smith, Hal (Committee member) / Arizona State University (Publisher)
Created2014
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 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
Description
The phycologist, M. R. Droop, studied vitamin B12 limitation in the flagellate Monochrysis lutheri and concluded that its specific growth rate depended on the concentration of the vitamin within the cell; i.e. the cell quota of the vitamin B12. The Droop model provides a mathematical expression to link growth rate to the intracellular concentration of a limiting nutrient. Although the Droop model has been an important modeling tool in ecology, it has only recently been applied to study cancer biology. Cancer cells live in an ecological setting, interacting and competing with normal and other cancerous cells for nutrients and space, and evolving and adapting to their environment. Here, the Droop equation is used to model three cancers.
First, prostate cancer is modeled, where androgen is considered the limiting nutrient since most tumors depend on androgen for proliferation and survival. The model's accuracy for predicting the biomarker for patients on intermittent androgen deprivation therapy is tested by comparing the simulation results to clinical data as well as to an existing simpler model. The results suggest that a simpler model may be more beneficial for a predictive use, although further research is needed in this field prior to implementing mathematical models as a predictive method in a clinical setting.
Next, two chronic myeloid leukemia models are compared that consider Imatinib treatment, a drug that inhibits the constitutively active tyrosine kinase BCR-ABL. Both models describe the competition of leukemic and normal cells, however the first model also describes intracellular dynamics by considering BCR-ABL as the limiting nutrient. Using clinical data, the differences in estimated parameters between the models and the capacity for each model to predict drug resistance are analyzed.
Last, a simple model is presented that considers ovarian tumor growth and tumor induced angiogenesis, subject to on and off anti-angiogenesis treatment. In this environment, the cell quota represents the intracellular concentration of necessary nutrients provided through blood supply. Mathematical analysis of the model is presented and model simulation results are compared to pre-clinical data. This simple model is able to fit both on- and off-treatment data using the same biologically relevant parameters.
First, prostate cancer is modeled, where androgen is considered the limiting nutrient since most tumors depend on androgen for proliferation and survival. The model's accuracy for predicting the biomarker for patients on intermittent androgen deprivation therapy is tested by comparing the simulation results to clinical data as well as to an existing simpler model. The results suggest that a simpler model may be more beneficial for a predictive use, although further research is needed in this field prior to implementing mathematical models as a predictive method in a clinical setting.
Next, two chronic myeloid leukemia models are compared that consider Imatinib treatment, a drug that inhibits the constitutively active tyrosine kinase BCR-ABL. Both models describe the competition of leukemic and normal cells, however the first model also describes intracellular dynamics by considering BCR-ABL as the limiting nutrient. Using clinical data, the differences in estimated parameters between the models and the capacity for each model to predict drug resistance are analyzed.
Last, a simple model is presented that considers ovarian tumor growth and tumor induced angiogenesis, subject to on and off anti-angiogenesis treatment. In this environment, the cell quota represents the intracellular concentration of necessary nutrients provided through blood supply. Mathematical analysis of the model is presented and model simulation results are compared to pre-clinical data. This simple model is able to fit both on- and off-treatment data using the same biologically relevant parameters.
ContributorsEverett, Rebecca Anne (Author) / Kuang, Yang (Thesis advisor) / Nagy, John (Committee member) / Milner, Fabio (Committee member) / Crook, Sharon (Committee member) / Jackiewicz, Zdzislaw (Committee member) / Arizona State University (Publisher)
Created2015
Description
The communication of genetic material with biomolecules has been a major interest in cancer biology research for decades. Among its different levels of involvement, DNA is known to be a target of several antitumor agents. Additionally, tissue specific interaction between macromolecules such as proteins and structurally important regions of DNA has been reported to define the onset of certain types of cancers.
Illustrated in Chapter 1 is the general history of research on the interaction of DNA and anticancer drugs, most importantly different congener of bleomycin (BLM). Additionally, several synthetic analogues of bleomycin, including the structural components and functionalities, are discussed.
Chapter 2 describes a new approach to study the double-strand DNA lesion caused by antitumor drug bleomycin. The hairpin DNA library used in this study displays numerous cleavage sites demonstrating the versatility of bleomycin interaction with DNA. Interestingly, some of those cleavage sites suggest a novel mechanism of bleomycin interaction, which has not been reported before.
Cytidine methylation has generally been found to decrease site-specific cleavage of DNA by BLM, possibly due to structural change and subsequent reduced bleomycin-mediated recognition of DNA. As illustrated in Chapter 3, three hairpin DNAs known to be strongly bound by bleomycin, and their methylated counterparts, were used to study the dynamics of bleomycin-induced degradation of DNAs in cancer cells. Interestingly, cytidine methylation on one of the DNAs has also shown a major shift in the intensity of bleomycin induced double-strand DNA cleavage pattern, which is known to be a more potent form of bleomycin induced cleavages.
DNA secondary structures are known to play important roles in gene regulation. Chapter 4 demonstrates a structural change of the BCL2 promoter element as a result of its dynamic interaction with the individual domains of hnRNP LL, which is essential to facilitate the transcription of BCL2. Furthermore, an in vitro protein synthesis technique has been employed to study the dynamic interaction between protein domains and the i-motif DNA within the promoter element. Several constructs were made involving replacement of a single amino acid with a fluorescent analogue, and these were used to study FRET between domain 1 and the i-motif, the later of which harbored a fluorescent acceptor nucleotide analogue.
Illustrated in Chapter 1 is the general history of research on the interaction of DNA and anticancer drugs, most importantly different congener of bleomycin (BLM). Additionally, several synthetic analogues of bleomycin, including the structural components and functionalities, are discussed.
Chapter 2 describes a new approach to study the double-strand DNA lesion caused by antitumor drug bleomycin. The hairpin DNA library used in this study displays numerous cleavage sites demonstrating the versatility of bleomycin interaction with DNA. Interestingly, some of those cleavage sites suggest a novel mechanism of bleomycin interaction, which has not been reported before.
Cytidine methylation has generally been found to decrease site-specific cleavage of DNA by BLM, possibly due to structural change and subsequent reduced bleomycin-mediated recognition of DNA. As illustrated in Chapter 3, three hairpin DNAs known to be strongly bound by bleomycin, and their methylated counterparts, were used to study the dynamics of bleomycin-induced degradation of DNAs in cancer cells. Interestingly, cytidine methylation on one of the DNAs has also shown a major shift in the intensity of bleomycin induced double-strand DNA cleavage pattern, which is known to be a more potent form of bleomycin induced cleavages.
DNA secondary structures are known to play important roles in gene regulation. Chapter 4 demonstrates a structural change of the BCL2 promoter element as a result of its dynamic interaction with the individual domains of hnRNP LL, which is essential to facilitate the transcription of BCL2. Furthermore, an in vitro protein synthesis technique has been employed to study the dynamic interaction between protein domains and the i-motif DNA within the promoter element. Several constructs were made involving replacement of a single amino acid with a fluorescent analogue, and these were used to study FRET between domain 1 and the i-motif, the later of which harbored a fluorescent acceptor nucleotide analogue.
ContributorsRoy, Basab (Author) / Hecht, Sidney M. (Thesis advisor) / Jones, Anne (Committee member) / Levitus, Marcia (Committee member) / Chaput, John (Committee member) / Arizona State University (Publisher)
Created2014
Description
Daily life stressors and negative emotional experiences predict poor physical and psychological health. The stress response of the hypothalamic-pituitary-adrenal axis is a primary biological system through which stressful experiences impact health and well-being across development. Individuals differ in their capacity for self-regulation and utilize various coping strategies in response to stress. Everyday experiences and emotions are highly variable during adolescence, a time during which self-regulatory abilities may become particularly important for adapting to shifting social contexts. Many adolescents in the U.S. enter college after high school, a context characterized by new opportunities and challenges for self-regulation. Guided by biopsychosocial and daily process approaches, the current study explored everyday stress and negative affect (NA), cortisol reactivity, and self-regulation assessed at the momentary, daily, and trait level among a racially/ethnically and socioeconomically diverse sample of first-year college students (N = 71; Mage = 18.85; 23% male; 52% non-Hispanic White) who completed a modified ecological momentary assessment. It was expected that within-person increases in momentary stress level or NA would be associated with cortisol reactivity assessed in college students' naturalistic settings. It was predicted that these within-person associations would differ based on engagement coping responses assessed via momentary diary reports, by the range of engagement coping responses assessed via diary reports at the end of the day, and by higher trait levels of self-regulation assessed via standard self-report questionnaire. Within-person increases in momentary stress level were significantly associated with momentary elevations in cortisol only during moments characterized by greater than usual engagement coping efforts (i.e., within-person
increases). At a different level of analysis, within-person increases in momentary stress level were significantly associated with increases in cortisol only for those with low trait levels of coping efficacy and engagement coping. On average, within-person increases in momentary NA were significantly associated with cortisol reactivity. Tests of moderation revealed this momentary association was only significant for those with low trait levels of support-seeking coping.
increases). At a different level of analysis, within-person increases in momentary stress level were significantly associated with increases in cortisol only for those with low trait levels of coping efficacy and engagement coping. On average, within-person increases in momentary NA were significantly associated with cortisol reactivity. Tests of moderation revealed this momentary association was only significant for those with low trait levels of support-seeking coping.
ContributorsSladek, Michael Ronald (Author) / Doane, Leah D (Thesis advisor) / Eisenberg, Nancy (Committee member) / Luecken, Linda J. (Committee member) / Arizona State University (Publisher)
Created2015