Matching Items (123)
Description
We propose a novel solution to prevent cancer by developing a prophylactic cancer. Several sources of antigens for cancer vaccines have been published. Among these, antigens that contain a frame-shift (FS) peptide or viral peptide are quite attractive for a variety of reasons. FS sequences, from either mistake in RNA processing or in genomic DNA, may lead to generation of neo-peptides that are foreign to the immune system. Viral peptides presumably would originate from exogenous but integrated viral nucleic acid sequences. Both are non-self, therefore lessen concerns about development of autoimmunity. I have developed a bioinformatical approach to identify these aberrant transcripts in the cancer transcriptome. Their suitability for use in a vaccine is evaluated by establishing their frequencies and predicting possible epitopes along with their population coverage according to the prevalence of major histocompatibility complex (MHC) types. Viral transcripts and transcripts with FS mutations from gene fusion, insertion/deletion at coding microsatellite DNA, and alternative splicing were identified in NCBI Expressed Sequence Tag (EST) database. 48 FS chimeric transcripts were validated in 50 breast cell lines and 68 primary breast tumor samples with their frequencies from 4% to 98% by RT-PCR and sequencing confirmation. These 48 FS peptides, if translated and presented, could be used to protect more than 90% of the population in Northern America based on the prediction of epitopes derived from them. Furthermore, we synthesized 150 peptides that correspond to FS and viral peptides that we predicted would exist in tumor patients and we tested over 200 different cancer patient sera. We found a number of serological reactive peptide sequences in cancer patients that had little to no reactivity in healthy controls; strong support for the strength of our bioinformatic approach. This study describes a process used to identify aberrant transcripts that lead to a new source of antigens that can be tested and used in a prophylactic cancer vaccine. The vast amount of transcriptome data of various cancers from the Cancer Genome Atlas (TCGA) project will enhance our ability to further select better cancer antigen candidates.
ContributorsLee, HoJoon (Author) / Johnston, Stephen A. (Thesis advisor) / Kumar, Sudhir (Committee member) / Miller, Laurence (Committee member) / Stafford, Phillip (Committee member) / Sykes, Kathryn (Committee member) / Arizona State University (Publisher)
Created2012
Description
Immunosignaturing is a technology that allows the humoral immune response to be observed through the binding of antibodies to random sequence peptides. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides in a multiplexed fashion. There are computational and statistical challenges to the analysis of immunosignaturing data. The overall aim of my dissertation is to develop novel computational and statistical methods for immunosignaturing data to access its potential for diagnostics and drug discovery. Firstly, I discovered that a classification algorithm Naive Bayes which leverages the biological independence of the probes on our array in such a way as to gather more information outperforms other classification algorithms due to speed and accuracy. Secondly, using this classifier, I then tested the specificity and sensitivity of immunosignaturing platform for its ability to resolve four different diseases (pancreatic cancer, pancreatitis, type 2 diabetes and panIN) that target the same organ (pancreas). These diseases were separated with >90% specificity from controls and from each other. Thirdly, I observed that the immunosignature of type 2 diabetes and cardiovascular complications are unique, consistent, and reproducible and can be separated by 100% accuracy from controls. But when these two complications arise in the same person, the resultant immunosignature is quite different in that of individuals with only one disease. I developed a method to trace back from informative random peptides in disease signatures to the potential antigen(s). Hence, I built a decipher system to trace random peptides in type 1 diabetes immunosignature to known antigens. Immunosignaturing, unlike the ELISA, has the ability to not only detect the presence of response but also absence of response during a disease. I observed, not only higher but also lower peptides intensities can be mapped to antigens in type 1 diabetes. To study immunosignaturing potential for population diagnostics, I studied effect of age, gender and geographical location on immunosignaturing data. For its potential to be a health monitoring technology, I proposed a single metric Coefficient of Variation that has shown potential to change significantly when a person enters a disease state.
ContributorsKukreja, Muskan (Author) / Johnston, Stephen Albert (Thesis advisor) / Stafford, Phillip (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2012
Description
A system for illuminating a sample in situ with visible and UV light inside a transmission electron microscope was devised to study photocatalysts. There are many factors which must be considered when designing and building such a system. These include both mechanical, optical, and electron optical considerations. Some of the restrictions posed by the electron microscope column are significant, and care must be taken not to degrade the microscope's electron optical performance, or to unduly restrict the other current capabilities of the microscope. The nature of these various design considerations is discussed in detail. A description of the system that has been added to the microscope at ASU, an FEI Tecnai F20 environmental transmission electron microscope is also given. The system includes a high brightness broadband light source with optical filters, a fiber to guide the light to the sample, and a system for precisely aligning the fiber tip. The spatial distribution and spectrum of the light reaching the sample has been characterized, and is described in detail.
ContributorsMiller, Benjamin (Author) / Crozier, Peter A. (Thesis advisor) / McCartney, Martha (Committee member) / Rez, Peter (Committee member) / Arizona State University (Publisher)
Created2012
Description
It has been well established that mitochondria play a critical role in the pathology of Friedreich's Ataxia. This disease is believed to be caused by a deficiency of frataxin, which research suggests is responsible for iron sulfur cluster assembly. This incomplete assembly of iron sulfur clusters is believed to be linked with dysfunctional complexes in the mitochondrial respiratory chain, increased oxidative stress, and potential cell death. Increased understanding of the pathophysiology of this disease has enabled the development of various therapeutic strategies aimed at restoring mitochondrial respiration. This thesis contains an analysis of the biological activity of several classes of antioxidants against oxidative stress induced by diethyl maleate in Friedreich's Ataxia lymphocytes and CEM leukemia cells. Analogues of vitamin E α-tocopherol have been shown to protect cells under oxidative stress. However, these same analogues show various levels of inhibition towards the electron transport chain complex I. Bicyclic pyridinols containing a ten carbon substituent provided favorable cytoprotection. N-hydroxy-4-pyridone compounds were observed to provide little protection. Similarly, analogues of CoQ10 in the form of pyridinol and pyrimidinol compounds also preserved cell viability at low concentrations.
ContributorsJaruvangsanti, Jennifer (Author) / Hecht, Sidney (Thesis advisor) / Woodbury, Neal (Committee member) / Skibo, Edward (Committee member) / Arizona State University (Publisher)
Created2012
Description
The field of biomedical research relies on the knowledge of binding interactions between various proteins of interest to create novel molecular targets for therapeutic purposes. While many of these interactions remain a mystery, knowledge of these properties and interactions could have significant medical applications in terms of understanding cell signaling and immunological defenses. Furthermore, there is evidence that machine learning and peptide microarrays can be used to make reliable predictions of where proteins could interact with each other without the definitive knowledge of the interactions. In this case, a neural network was used to predict the unknown binding interactions of TNFR2 onto LT-ɑ and TRAF2, and PD-L1 onto CD80, based off of the binding data from a sampling of protein-peptide interactions on a microarray. The accuracy and reliability of these predictions would rely on future research to confirm the interactions of these proteins, but the knowledge from these methods and predictions could have a future impact with regards to rational and structure-based drug design.
ContributorsPoweleit, Andrew Michael (Author) / Woodbury, Neal (Thesis director) / Diehnelt, Chris (Committee member) / Chiu, Po-Lin (Committee member) / School of Molecular Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Students across the United States lack the necessary skills to be successful college students in Science, Technology and Math (STEM) majors and as a result post-secondary institutions are developing summer bridge programs to aid in their transition. As they develop these programs, effective theory and approach are critical to developing successful programs. Though there are a multitude of theories on successful student development, a focus on self-efficacy is critical. Summer Bridge programs across the country as well as the Bio Bridge summer program at Arizona State University were studied alone and through the lens of Cognitive Self-Efficacy Theory as mentioned in Albert Bandura's "Perceived Self-Efficacy in Cognitive Development and Functioning." Cognitive Self-Efficacy Theory provides a framework for self-efficacy development in academic settings. An analysis of fifteen bridge programs found that a large majority focused on developing academic capabilities and often overlooked development of community and social efficacy. An even larger number failed to focus on personal psychology in managing self-debilitating thought patterns based on published goals. Further, Arizona State University's Bio Bridge program could not be considered successful at developing cognitive self-efficacy or increasing retention as data was inconclusive. However, Bio Bridge was tremendously successful at developing social efficacy and community among participants and faculty. Further research and better evaluative techniques need to be developed to understand the program's effectiveness in cognitive self-efficacy development and retention.
ContributorsTummala, Sailesh Vardhan (Author) / Orchinik, Miles (Thesis director) / Brownell, Sara (Committee member) / Shortlidge, Erin (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2015-05
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 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
Description
Cancer remains one of the leading killers throughout the world. Death and disability due to lung cancer in particular accounts for one of the largest global economic burdens a disease presents. The burden on third-world countries is especially large due to the unusually large financial stress that comes from late tumor detection and expensive treatment options. Early detection using inexpensive techniques may relieve much of the burden throughout the world, not just in more developed countries. I examined the immune responses of lung cancer patients using immunosignatures – patterns of reactivity between host serum antibodies and random peptides. Immunosignatures reveal disease-specific patterns that are very reproducible. Immunosignaturing is a chip-based method that has the ability to display the antibody diversity from individual sera sample with low cost. Immunosignaturing is a medical diagnostic test that has many applications in current medical research and in diagnosis. From a previous clinical study, patients diagnosed for lung cancer were tested for their immunosignature vs. healthy non-cancer volunteers. The pattern of reactivity against the random peptides (the ‘immunosignature’) revealed common signals in cancer patients, absent from healthy controls. My study involved the search for common amino acid motifs in the cancer-specific peptides. My search through the hundreds of ‘hits’ revealed certain motifs that were repeated more times than expected by random chance. The amino acids that were the most conserved in each set include tryptophan, aspartic acid, glutamic acid, proline, alanine, serine, and lysine. The most overall conserved amino acid observed between each set was D - aspartic acid. The motifs were short (no more than 5-6 amino acids in a row), but the total number of motifs I identified was large enough to assure significance. I utilized Excel to organize the large peptide sequence libraries, then CLUSTALW to cluster similar-sequence peptides, then GLAM2 to find common themes in groups of peptides. In so doing, I found sequences that were also present in translated cancer expression libraries (RNA) that matched my motifs, suggesting that immunosignatures can find cancer-specific antigens that can be both diagnostic and potentially therapeutic.
ContributorsShiehzadegan, Shima (Author) / Johnston, Stephen (Thesis director) / Stafford, Phillip (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
With a quantum efficiency of nearly 100%, the electron transfer process that occurs within the reaction center protein of the photosynthetic bacteria Rhodobacter (Rh.) sphaeroides is a paragon for understanding the complexities, intricacies, and overall systemization of energy conversion and storage in natural systems. To better understand the way in which photons of light are captured, converted into chemically useful forms, and stored for biological use, an investigation into the reaction center protein, specifically into its cascade of cofactors, was undertaken. The purpose of this experimentation was to advance our knowledge and understanding of how differing protein environments and variant cofactors affect the spectroscopic aspects of and electron transfer kinetics within the reaction of Rh. sphaeroides. The native quinone, ubiquinone, was extracted from its pocket within the reaction center protein and replaced by non-native quinones having different reduction/oxidation potentials. It was determined that, of the two non-native quinones tested—1,2-naphthaquinone and 9,10- anthraquinone—the substitution of the anthraquinone (lower redox potential) resulted in an increased rate of recombination from the P+QA- charge-separated state, while the substitution of the napthaquinone (higher redox potential) resulted in a decreased rate of recombination.
ContributorsSussman, Hallie Rebecca (Author) / Woodbury, Neal (Thesis director) / Redding, Kevin (Committee member) / Lin, Su (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
Advances in peptide microarray technology have allowed for the creation of fast-paced and modular experiments within affinity ligand discovery. Previously, low density peptide arrays of 10,000 peptides were used to identify low affinity peptide ligands for a target protein; an approach that can be subsequently improved upon with a number of techniques. VDAP[a] offers more information about the relative affinity of protein-peptide interactions via signal intensity in contrast to high throughput screening (HTS) and display technologies which offer binary data. Now, high density peptide arrays with 130,000 to 330,000 peptides are available that allow screening across peptide libraries of greater diversity. With this increase in scale and diversity, faster analytical tools are needed to adequately characterize array data. Using the statistical power available in the R programming language, we have created a flexible analysis package that efficiently processes high density peptide array data from a variety of layouts, rank existing peptide hits, and utilize signal intensity data to generate new hits. This analysis provides a user-friendly method to efficiently analyze high density peptide array data, generate peptide leads for targeted therapeutic development, and further improve peptide array technologies.
ContributorsMoore, Cody Allen (Author) / Woodbury, Neal (Thesis director) / Diehnelt, Chris (Committee member) / Barrett, The Honors College (Contributor)
Created2015-12