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Cancer is one of the most serious global diseases. We have focused on cancer immunoprevention. My thesis projects include developing a prophylactic primary and metastatic cancer vaccines, early cancer detection and investigation of genes involved in tumor development. These studies were focused on frame-shift (FS) antigens. The FS antigens are generated by genomic mutations or abnormal RNA processing, which cause a portion of a normal protein to be translated out of frame. The concept of the prophylactic cancer vaccine is to develop a general cancer vaccine that could prevent healthy people from developing different types of cancer. We have discovered a set of cancer specific FS antigens. One of the FS candidates, structural maintenance of chromosomes protein 1A (SMC1A) FS, could start to accumulate at early stages of tumor and be specifically exposed to the immune system by tumor cells. Prophylactic immunization with SMC1A-FS could significantly inhibit primary tumor development in different murine tumor models and also has the potential to inhibit tumor metastasis. The SMC1A-FS transcript was detected in the plasma of the 4T1/BALB/c mouse tumor model. The tumor size was correlated with the transcript ratio of the SMC1A-FS verses the WT in plasma, which could be measured by regular RT-PCR. This unique cancer biomarker has a practical potential for a large population cancer screen, as well as clinical tumor monitoring. With a set of mimotope peptides, antibodies against SMC1A-FS peptide were detected in different cancer patients, including breast cancer, pancreas cancer and lung cancer with a 53.8%, 56.5% and 12.5% positive rate respectively. This suggested that the FS antibody could be a biomarker for early cancer detection. The characterization of SMC1A suggested that: First, the deficiency of the SMC1A is common in different tumors and able to promote tumor initiation and development; second, the FS truncated protein may have nucleolus function in normal cells. Mis-control of this protein may promote tumor development. In summary, we developed a systematic general cancer prevention strategy through the variety immunological and molecular methods. The results gathered suggest the SMC1A-FS may be useful for the detection and prevention of cancer.
ContributorsShen, Luhui (Author) / Johnston, Stephen Albert (Thesis advisor) / Chang, Yung (Committee member) / Miller, Laurence (Committee member) / Sykes, Kathryn (Committee member) / Jacobs, Bertram (Committee member) / Arizona State University (Publisher)
Created2012
Description
The advent of new high throughput technology allows for increasingly detailed characterization of the immune system in healthy, disease, and age states. The immune system is composed of two main branches: the innate and adaptive immune system, though the border between these two states is appearing less distinct. The adaptive immune system is further split into two main categories: humoral and cellular immunity. The humoral immune response produces antibodies against specific targets, and these antibodies can be used to learn about disease and normal states. In this document, I use antibodies to characterize the immune system in two ways: 1. I determine the Antibody Status (AbStat) from the data collected from applying sera to an array of non-natural sequence peptides, and demonstrate that this AbStat measure can distinguish between disease, normal, and aged samples as well as produce a single AbStat number for each sample; 2. I search for antigens for use in a cancer vaccine, and this search results in several candidates as well as a new hypothesis. Antibodies provide us with a powerful tool for characterizing the immune system, and this natural tool combined with emerging technologies allows us to learn more about healthy and disease states.
ContributorsWhittemore, Kurt (Author) / Sykes, Kathryn (Thesis advisor) / Johnston, Stephen A. (Committee member) / Jacobs, Bertram (Committee member) / Stafford, Phillip (Committee member) / Stout, Valerie (Committee member) / Arizona State University (Publisher)
Created2014
Description
Peptide microarrays are to proteomics as sequencing is to genomics. As microarrays become more content-rich, higher resolution proteomic studies will parallel deep sequencing of nucleic acids. Antigen-antibody interactions can be studied at a much higher resolution using microarrays than was possible only a decade ago. My dissertation focuses on testing the feasibility of using either the Immunosignature platform, based on non-natural peptide sequences, or a pathogen peptide microarray, which uses bioinformatically-selected peptides from pathogens for creating sensitive diagnostics. Both diagnostic applications use relatively little serum from infected individuals, but each approaches diagnosis of disease differently. The first project compares pathogen epitope peptide (life-space) and non-natural (random-space) peptide microarrays while using them for the early detection of Coccidioidomycosis (Valley Fever). The second project uses NIAID category A, B and C priority pathogen epitope peptides in a multiplexed microarray platform to assess the feasibility of using epitope peptides to simultaneously diagnose multiple exposures using a single assay. Cross-reactivity is a consistent feature of several antigen-antibody based immunodiagnostics. This work utilizes microarray optimization and bioinformatic approaches to distill the underlying disease specific antibody signature pattern. Circumventing inherent cross-reactivity observed in antibody binding to peptides was crucial to achieve the goal of this work to accurately distinguishing multiple exposures simultaneously.
ContributorsNavalkar, Krupa Arun (Author) / Johnston, Stephen A. (Thesis advisor) / Stafford, Phillip (Thesis advisor) / Sykes, Kathryn (Committee member) / Jacobs, Bertram (Committee member) / Arizona State University (Publisher)
Created2014
Description
This study aims to unearth monological and monocultural discourses buried under the power of the dominant biomedical model governing the HIV/AIDS debate. The study responds to an apparent consensus, rooted in Western biomedicine and its "standardizations of knowledge," in the production of the current HIV/AIDS discourse, especially in Sub-Saharan Africa. As a result, biomedicine has become the dominant actor (in) writing and rewriting discourse for the masses while marginalizing other forms of medical knowledge. Specifically, in its development, the Western biomedical model has arguably isolated the disease from its human host and the social experiences that facilitate the disease's transmission, placing it in the realm of laboratories and scientific experts and giving full ownership to Western medical discourse. Coupled with Western assumptions about African culture that reproduce a one-sided discourse informing the social construction of HIV/AIDS in Africa, this Western monopoly thus constrained the extent and efficacy of international prevention efforts. In this context, the goal for this study is not to demonize the West and biomedicine in general. Rather, this study seeks an alternative and less monolithic understanding currently absent in scientific discourses of HIV/AIDS that frequently elevates Western biomedicine over indigenous medicine; the Western expert over the local. The study takes into account the local voices of Sub-Saharan Africa and how the system has affected them, this study utilizes a Foucauldian approach to analyze discourse as a way to explore how certain ways of knowledge are formed in relation to power. This study also examines how certain knowlege is maintaned and reinforced within specific discourses.
ContributorsAbdalla, Mohamed (Author) / Jacobs, Bertram (Thesis advisor) / Robert, Jason (Committee member) / Klimek, Barbara (Committee member) / Arizona State University (Publisher)
Created2014
Description
The healthcare system in this country is currently unacceptable. New technologies may contribute to reducing cost and improving outcomes. Early diagnosis and treatment represents the least risky option for addressing this issue. Such a technology needs to be inexpensive, highly sensitive, highly specific, and amenable to adoption in a clinic. This thesis explores an immunodiagnostic technology based on highly scalable, non-natural sequence peptide microarrays designed to profile the humoral immune response and address the healthcare problem. The primary aim of this thesis is to explore the ability of these arrays to map continuous (linear) epitopes. I discovered that using a technique termed subsequence analysis where epitopes could be decisively mapped to an eliciting protein with high success rate. This led to the discovery of novel linear epitopes from Plasmodium falciparum (Malaria) and Treponema palladium (Syphilis), as well as validation of previously discovered epitopes in Dengue and monoclonal antibodies. Next, I developed and tested a classification scheme based on Support Vector Machines for development of a Dengue Fever diagnostic, achieving higher sensitivity and specificity than current FDA approved techniques. The software underlying this method is available for download under the BSD license. Following this, I developed a kinetic model for immunosignatures and tested it against existing data driven by previously unexplained phenomena. This model provides a framework and informs ways to optimize the platform for maximum stability and efficiency. I also explored the role of sequence composition in explaining an immunosignature binding profile, determining a strong role for charged residues that seems to have some predictive ability for disease. Finally, I developed a database, software and indexing strategy based on Apache Lucene for searching motif patterns (regular expressions) in large biological databases. These projects as a whole have advanced knowledge of how to approach high throughput immunodiagnostics and provide an example of how technology can be fused with biology in order to affect scientific and health outcomes.
ContributorsRicher, Joshua Amos (Author) / Johnston, Stephen A. (Thesis advisor) / Woodbury, Neal (Committee member) / Stafford, Phillip (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2014
Description
Vaccination remains one of the most effective means for preventing infectious diseases. During viral infection, activated CD8 T cells differentiate into cytotoxic effector cells that directly kill infected cells and produce anti-viral cytokines. Further T cell differentiation results in a population of memory CD8 T cells that have the ability to self-renew and rapidly proliferate into effector cells during secondary infections. However during persistent viral infection, T cell differentiation is disrupted due to sustained antigen stimulation resulting in a loss of T cell effector function. Despite the development of vaccines for a wide range of viral diseases, efficacious vaccines for persistent viral infections have been challenging to design. Immunization against virus T cell epitopes has been proposed as an alternative vaccination strategy for persistent viral infections, such as HIV. However, vaccines that selectively engage T cell responses can result in inappropriate immune responses that increase, rather than prevent, disease. Quantitative models of virus infection and immune response were used to investigate how virus and immune system variables influence pathogenic versus protective T cell responses generated during persistent viral infection. It was determined that an intermediate precursor frequency of virus-specific memory CD8 T cells prior to LCMV infection resulted in maximum T cell mediated pathology. Increased pathology was independent of antigen sensitivity or the diversity of TCR in the CD8 T cell response, but was dependent on CD8 T cell production of TNF and the magnitude of initial virus exposure. The threshold for exhaustion of responding CD8 T cells ultimately influences the precursor frequency that causes enhanced disease.In addition, viral infection can occur in the context of co-infection by heterologous pathogens that modulate immune responses and/or disease. Co-infection of two unrelated viruses in their natural host, Ectromelia virus (ECTV) and Lymphocytic Choriomeningitis virus (LCMV) infection in mice, were studied. ECTV infection can be a lethal infection in mice due in part to the blockade of antiviral cytokines, including Type I Interferons (IFN-I). It was determined that ECTV/LCMV co-infection results in decreased ECTV viral load and amelioration of ECTV-induced disease, presumably due to IFN-I induction by LCMV. However, immune responses to LCMV in ECTV co-infected mice were also lower compared to mice infected with LCMV alone and biased toward effector-memory cell generation. Thus, providing evidence for bi-directional effects of viral co-infection that modulate disease and immunity. Together the results suggest heterogeneity in T cell responses during vaccination with viral vectors may be in part due to heterologous virus infection or vaccine usage and that TNF-blockade may be useful for minimizing pathology while maintaining protection during virus infection. Lastly, quantitative mathematical models of virus and T cell immunity can be useful to generate predictions regarding which molecular and cellular pathways mediate T cell protection versus pathology.
ContributorsMcAfee, Megan (Author) / Blattman, Joseph N (Thesis advisor) / Anderson, Karen (Committee member) / Jacobs, Bertram (Committee member) / Hogue, Brenda (Committee member) / Arizona State University (Publisher)
Created2015
Description
Peptide microarrays have been used in molecular biology to profile immune responses and develop diagnostic tools. When the microarrays are printed with random peptide sequences, they can be used to identify antigen antibody binding patterns or immunosignatures. In this thesis, an advanced signal processing method is proposed to estimate epitope antigen subsequences as well as identify mimotope antigen subsequences that mimic the structure of epitopes from random-sequence peptide microarrays. The method first maps peptide sequences to linear expansions of highly-localized one-dimensional (1-D) time-varying signals and uses a time-frequency processing technique to detect recurring patterns in subsequences. This technique is matched to the aforementioned mapping scheme, and it allows for an inherent analysis on how substitutions in the subsequences can affect antibody binding strength. The performance of the proposed method is demonstrated by estimating epitopes and identifying potential mimotopes for eight monoclonal antibody samples.
The proposed mapping is generalized to express information on a protein's sequence location, structure and function onto a highly localized three-dimensional (3-D) Gaussian waveform. In particular, as analysis of protein homology has shown that incorporating different kinds of information into an alignment process can yield more robust alignment results, a pairwise protein structure alignment method is proposed based on a joint similarity measure of multiple mapped protein attributes. The 3-D mapping allocates protein properties into distinct regions in the time-frequency plane in order to simplify the alignment process by including all relevant information into a single, highly customizable waveform. Simulations demonstrate the improved performance of the joint alignment approach to infer relationships between proteins, and they provide information on mutations that cause changes to both the sequence and structure of a protein.
In addition to the biology-based signal processing methods, a statistical method is considered that uses a physics-based model to improve processing performance. In particular, an externally developed physics-based model for sea clutter is examined when detecting a low radar cross-section target in heavy sea clutter. This novel model includes a process that generates random dynamic sea clutter based on the governing physics of water gravity and capillary waves and a finite-difference time-domain electromagnetics simulation process based on Maxwell's equations propagating the radar signal. A subspace clutter suppression detector is applied to remove dominant clutter eigenmodes, and its improved performance over matched filtering is demonstrated using simulations.
The proposed mapping is generalized to express information on a protein's sequence location, structure and function onto a highly localized three-dimensional (3-D) Gaussian waveform. In particular, as analysis of protein homology has shown that incorporating different kinds of information into an alignment process can yield more robust alignment results, a pairwise protein structure alignment method is proposed based on a joint similarity measure of multiple mapped protein attributes. The 3-D mapping allocates protein properties into distinct regions in the time-frequency plane in order to simplify the alignment process by including all relevant information into a single, highly customizable waveform. Simulations demonstrate the improved performance of the joint alignment approach to infer relationships between proteins, and they provide information on mutations that cause changes to both the sequence and structure of a protein.
In addition to the biology-based signal processing methods, a statistical method is considered that uses a physics-based model to improve processing performance. In particular, an externally developed physics-based model for sea clutter is examined when detecting a low radar cross-section target in heavy sea clutter. This novel model includes a process that generates random dynamic sea clutter based on the governing physics of water gravity and capillary waves and a finite-difference time-domain electromagnetics simulation process based on Maxwell's equations propagating the radar signal. A subspace clutter suppression detector is applied to remove dominant clutter eigenmodes, and its improved performance over matched filtering is demonstrated using simulations.
ContributorsO'Donnell, Brian (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Bliss, Daniel (Committee member) / Johnston, Stephen A. (Committee member) / Kovvali, Narayan (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Arizona State University (Publisher)
Created2014
Description
Immunosignaturing is a new immunodiagnostic technology that uses random-sequence peptide microarrays to profile the humoral immune response. Though the peptides have little sequence homology to any known protein, binding of serum antibodies may be detected, and the pattern correlated to disease states. The aim of my dissertation is to analyze the factors affecting the binding patterns using monoclonal antibodies and determine how much information may be extracted from the sequences. Specifically, I examined the effects of antibody concentration, competition, peptide density, and antibody valence. Peptide binding could be detected at the low concentrations relevant to immunosignaturing, and a monoclonal's signature could even be detected in the presences of 100 fold excess naive IgG. I also found that peptide density was important, but this effect was not due to bivalent binding. Next, I examined in more detail how a polyreactive antibody binds to the random sequence peptides compared to protein sequence derived peptides, and found that it bound to many peptides from both sets, but with low apparent affinity. An in depth look at how the peptide physicochemical properties and sequence complexity revealed that there were some correlations with properties, but they were generally small and varied greatly between antibodies. However, on a limited diversity but larger peptide library, I found that sequence complexity was important for antibody binding. The redundancy on that library did enable the identification of specific sub-sequences recognized by an antibody. The current immunosignaturing platform has little repetition of sub-sequences, so I evaluated several methods to infer antibody epitopes. I found two methods that had modest prediction accuracy, and I developed a software application called GuiTope to facilitate the epitope prediction analysis. None of the methods had sufficient accuracy to identify an unknown antigen from a database. In conclusion, the characteristics of the immunosignaturing platform observed through monoclonal antibody experiments demonstrate its promise as a new diagnostic technology. However, a major limitation is the difficulty in connecting the signature back to the original antigen, though larger peptide libraries could facilitate these predictions.
ContributorsHalperin, Rebecca (Author) / Johnston, Stephen A. (Thesis advisor) / Bordner, Andrew (Committee member) / Taylor, Thomas (Committee member) / Stafford, Phillip (Committee member) / Arizona State University (Publisher)
Created2011
Description
The majority of chronic myeloid leukemia (CML) and some of acute lymphocytic leukemia (ALL) cases are associated with possessing the BCR-Abl fusion protein from an oncogenic translocation, resulting in a constantly active form of Abl and rapid proliferation. CML and ALL cells that possess the BCR-Abl fusion protein are known as Philadelphia chromosome positive (Ph+). Currently, Imatinib (selective Abl inhibitor) is used as therapy against CML and ALL. However, some patients may have malignancies which show resistance to Imatinib. Previous work displays that the transformation of progenitor B cells with the v-Abl oncogene of Abelson murine leukemia virus results in cell cycle progression, rapid proliferation, and potentially malignant transformation while preventing any further differentiation. Progenitor B cells transformed with the temperature-sensitive form of the v-Abl oncogene have served as a model to study cellular response to Imatinib treatment. After some manipulation, very few cells were forced to progress to malignancy, forming tumor in vivo. These cells were no long sensitive to v-Abl inactivation, resembling the Imatinib resistant ALL. Autophagy is the process by which proteins and organelles are broken-down and recycled within the eukaryotic cell and has been hypothesized to play a part in cancer cell survival and drug-resistance. LC3 processing is a widely accepted marker of autophagy induction and progression. It has also been shown that Imatinib treatment of Ph+ leukemia can induce autophagy. In this study, we examined the autophagy induction in response to v-Abl inactivation in a Ph+-B-ALL cell model that shows resistance to Imatinib. In particular, we wonder whether the tumor cell line resistant to v-Abl inactivation may acquire a high level of autophagy to become resistant to apoptosis induced by v-Abl inactivation, and thus become addicted to autophagy. Indeed, this tumor cell line displays a high basal levels of LC3 I and II expression, regardless of v-Abl activity. We further demonstrated that inhibition of the autophagy pathway enhances the tumor line's sensitivity to Imatinib, resulting in cell cycle arrest and massive apoptosis. The combination of autophagy and Abl inhibitions may serve as an effective therapy for BCR-Abl positive CML.
ContributorsArkus, Nohea (Author) / Chang, Yung (Thesis advisor) / Kusumi, Kenro (Committee member) / Lake, Douglas (Committee member) / Jacobs, Bertram (Committee member) / Arizona State University (Publisher)
Created2011
Description
Recombinant protein expression is essential to biotechnology and molecular medicine, but facile methods for obtaining significant quantities of folded and functional protein in mammalian cell culture have been lacking. Here I describe a novel 37-nucleotide in vitro selected sequence that promotes unusually high transgene expression in a vaccinia driven cytoplasmic expression system. Vectors carrying this sequence in a monocistronic reporter plasmid produce >1,000-fold more protein than equivalent vectors with conventional vaccinia promoters. Initial mechanistic studies indicate that high protein expression results from dual activity that impacts both transcription and translation. I suggest that this motif represents a powerful new tool in vaccinia-based protein expression and vaccine development technology.
ContributorsFlores, Julia Anne (Author) / Chaput, John C (Thesis advisor) / Jacobs, Bertram (Committee member) / LaBaer, Joshua (Committee member) / Arizona State University (Publisher)
Created2012