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- Creators: Arizona State University
Description
In an effort to begin validating the large number of discovered candidate biomarkers, proteomics is beginning to shift from shotgun proteomic experiments towards targeted proteomic approaches that provide solutions to automation and economic concerns. Such approaches to validate biomarkers necessitate the mass spectrometric analysis of hundreds to thousands of human samples. As this takes place, a serendipitous opportunity has become evident. By the virtue that as one narrows the focus towards "single" protein targets (instead of entire proteomes) using pan-antibody-based enrichment techniques, a discovery science has emerged, so to speak. This is due to the largely unknown context in which "single" proteins exist in blood (i.e. polymorphisms, transcript variants, and posttranslational modifications) and hence, targeted proteomics has applications for established biomarkers. Furthermore, besides protein heterogeneity accounting for interferences with conventional immunometric platforms, it is becoming evident that this formerly hidden dimension of structural information also contains rich-pathobiological information. Consequently, targeted proteomics studies that aim to ascertain a protein's genuine presentation within disease- stratified populations and serve as a stepping-stone within a biomarker translational pipeline are of clinical interest. Roughly 128 million Americans are pre-diabetic, diabetic, and/or have kidney disease and public and private spending for treating these diseases is in the hundreds of billions of dollars. In an effort to create new solutions for the early detection and management of these conditions, described herein is the design, development, and translation of mass spectrometric immunoassays targeted towards diabetes and kidney disease. Population proteomics experiments were performed for the following clinically relevant proteins: insulin, C-peptide, RANTES, and parathyroid hormone. At least thirty-eight protein isoforms were detected. Besides the numerous disease correlations confronted within the disease-stratified cohorts, certain isoforms also appeared to be causally related to the underlying pathophysiology and/or have therapeutic implications. Technical advancements include multiplexed isoform quantification as well a "dual- extraction" methodology for eliminating non-specific proteins while simultaneously validating isoforms. Industrial efforts towards widespread clinical adoption are also described. Consequently, this work lays a foundation for the translation of mass spectrometric immunoassays into the clinical arena and simultaneously presents the most recent advancements concerning the mass spectrometric immunoassay approach.
ContributorsOran, Paul (Author) / Nelson, Randall (Thesis advisor) / Hayes, Mark (Thesis advisor) / Ros, Alexandra (Committee member) / Williams, Peter (Committee member) / Arizona State University (Publisher)
Created2011
Description
Cancer claims hundreds of thousands of lives every year in US alone. Finding ways for early detection of cancer onset is crucial for better management and treatment of cancer. Thus, biomarkers especially protein biomarkers, being the functional units which reflect dynamic physiological changes, need to be discovered. Though important, there are only a few approved protein cancer biomarkers till date. To accelerate this process, fast, comprehensive and affordable assays are required which can be applied to large population studies. For this, these assays should be able to comprehensively characterize and explore the molecular diversity of nominally "single" proteins across populations. This information is usually unavailable with commonly used immunoassays such as ELISA (enzyme linked immunosorbent assay) which either ignore protein microheterogeneity, or are confounded by it. To this end, mass spectrometric immuno assays (MSIA) for three different human plasma proteins have been developed. These proteins viz. IGF-1, hemopexin and tetranectin have been found in reported literature to show correlations with many diseases along with several carcinomas. Developed assays were used to extract entire proteins from plasma samples and subsequently analyzed on mass spectrometric platforms. Matrix assisted laser desorption ionization (MALDI) and electrospray ionization (ESI) mass spectrometric techniques where used due to their availability and suitability for the analysis. This resulted in visibility of different structural forms of these proteins showing their structural micro-heterogeneity which is invisible to commonly used immunoassays. These assays are fast, comprehensive and can be applied in large sample studies to analyze proteins for biomarker discovery.
ContributorsRai, Samita (Author) / Nelson, Randall (Thesis advisor) / Hayes, Mark (Thesis advisor) / Borges, Chad (Committee member) / Ros, Alexandra (Committee member) / Arizona State University (Publisher)
Created2012
Description
Biomarkers find a wide variety of applications in oncology from risk assessment to diagnosis and predicting and monitoring recurrence and response to therapy. Developing clinically useful biomarkers for cancer is faced with several challenges, including cancer heterogeneity and factors related to assay development and biomarker performance. Circulating biomarkers offer a rapid, cost-effective, and minimally-invasive window to disease and are ideal for population-based screening. Circulating immune biomarkers are stable, measurable, and can betray the underlying antigen when present below detection levels or even no longer present. This dissertation aims to investigate potential circulating immune biomarkers with applications in cancer detection and novel therapies. Over 600,000 cancers each year are attributed to the human papillomavirus (HPV), including cervical, anogenital and oropharyngeal cancers. A key challenge in understanding HPV immunobiology and developing immune biomarkers is the diversity of HPV types and the need for multiplexed display of HPV antigens. In Project 1, nucleic acid programmable protein arrays displaying the proteomes of 12 HPV types were developed and used for serum immunoprofiling of women with cervical lesions or invasive cervical cancer. These arrays provide a valuable high-throughput tool for measuring the breadth, specificity, heterogeneity, and cross-reactivity of the serologic response to HPV. Project 2 investigates potential biomarkers of immunity to the bacterial CRISPR/Cas9 system that is currently in clinical trials for cancer. Pre-existing B cell and T cell immune responses to Cas9 were detected in humans and Cas9 was modified to eliminate immunodominant epitopes while preserving its function and specificity. This dissertation broadens our understanding of the immunobiology of cervical cancer and provides insights into the immune profiles that could serve as biomarkers of various applications in cancer.
ContributorsEwaisha, Radwa Mohamed Emadeldin Mahmoud (Author) / Anderson, Karen S (Thesis advisor) / LaBaer, Joshua (Committee member) / Lake, Douglas F (Committee member) / Stout, Valerie (Committee member) / Arizona State University (Publisher)
Created2018
Description
Coccidioidomycosis, or Valley fever, is an endemic pneumonia of the arid and semi-arid regions of North and South America and is responsible for up to 30% of community-acquired pneumonias in endemic and highly populated areas of the United States southwest. The causative agents of Valley fever are the dimorphic fungi Coccidioides immitis and Coccidioides posadasii, which grow as mycelia in the environment and spherules within the lungs of vulnerable hosts. The current diagnostics for Valley fever are severely lacking due to poor sensitivity and invasiveness, strongly contributing to a 23-day median time-to-diagnosis. There is a critical need for sensitive and non-invasive diagnostics for identifying Valley fever lung infections. The long-term goal of my work is to substantially shorten the time-to-diagnosis for Valley fever through the development of sensitive and specific breath-based diagnostics for coccidioidomycosis lung infections. Herein, I characterized the volatile organic compounds (VOCs) produced by C. immitis and C. posadasii in vitro and evaluated the relationship of the volatile metabolomes to lifecycle. I explored the VOC profiles of bronchoalveolar lavage fluid (BALF) samples from mouse model lung infections of Valley fever. Finally, I investigated the VOC profiles of BALF from persons with community-acquired pneumonia. All VOCs were analyzed by headspace solid-phase microextraction and comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry (HS-SPME-GC×GC-TOFMS). The volatile metabolomes were compared using a variety of statistical analyses. For the in vitro samples, I detected a total of 353 VOCs that were at least two-fold more abundant in a Coccidioides culture versus medium controls and found the volatile metabolome of Coccidioides is more dependent on lifecycle than species. The mouse BALF samples indicate that lung infection VOCs are correlated to cytokine production and classify mice based on their individual level of infection. From the human BALF samples, I identified VOCs that were able to differentiate between Coccidioides and bacterial pneumonia. Combined, these studies suggest that Coccidioides spp. and the host produce volatile metabolites that may yield biomarkers for a Valley fever breath test.
ContributorsHiggins Keppler, Emily (Author) / Bean, Heather D (Thesis advisor) / Barker, Bridget M (Committee member) / Borges, Chad R (Committee member) / Lake, Douglas F (Committee member) / Arizona State University (Publisher)
Created2023
Description
Traumatic brain injury (TBI) affects an estimated 1.7 million people in the United States each year and is a leading cause of death and disability for children and young adults in industrialized countries. Unfortunately, the molecular and cellular mechanisms of injury progression have yet to be fully elucidated. Consequently, this complexity impacts the development of accurate diagnosis and treatment options. Biomarkers, objective signatures of injury, can inform and facilitate development of sensitive and specific theranostic devices. Discovery techniques that take advantage of mining the temporal complexity of TBI are critical for the identification of high specificity biomarkers.
Domain antibody fragment (dAb) phage display, a powerful screening technique to uncover protein-protein interactions, has been applied to biomarker discovery in various cancers and more recently, neurological conditions such as Alzheimer’s Disease and stroke. The small size of dAbs (12-15 kDa) and ability to screen against brain vasculature make them ideal for interacting with the neural milieu in vivo. Despite these characteristics, implementation of dAb phage display to elucidate temporal mechanisms of TBI has yet to reach its full potential.
My dissertation employs a unique target identification pipeline that entails in vivo dAb phage display and next generation sequencing (NGS) analysis to screen for temporal biomarkers of TBI. Using a mouse model of controlled cortical impact (CCI) injury, targeting motifs were designed based on the heavy complementarity determining region (HCDR3) structure of dAbs with preferential binding to acute (1 day) and subacute (7 days) post-injury timepoints. Bioreactivity for these two constructs was validated via immunohistochemistry. Further, immunoprecipitation-mass spectrometry analysis identified temporally distinct candidate biological targets in brain tissue lysate.
The pipeline of phage display followed by NGS analysis demonstrated a unique approach to discover motifs that are sensitive to the heterogeneous and diverse pathology caused by neural injury. This strategy successfully achieves 1) target motif identification for TBI at distinct timepoints and 2) characterization of their spatiotemporal specificity.
Domain antibody fragment (dAb) phage display, a powerful screening technique to uncover protein-protein interactions, has been applied to biomarker discovery in various cancers and more recently, neurological conditions such as Alzheimer’s Disease and stroke. The small size of dAbs (12-15 kDa) and ability to screen against brain vasculature make them ideal for interacting with the neural milieu in vivo. Despite these characteristics, implementation of dAb phage display to elucidate temporal mechanisms of TBI has yet to reach its full potential.
My dissertation employs a unique target identification pipeline that entails in vivo dAb phage display and next generation sequencing (NGS) analysis to screen for temporal biomarkers of TBI. Using a mouse model of controlled cortical impact (CCI) injury, targeting motifs were designed based on the heavy complementarity determining region (HCDR3) structure of dAbs with preferential binding to acute (1 day) and subacute (7 days) post-injury timepoints. Bioreactivity for these two constructs was validated via immunohistochemistry. Further, immunoprecipitation-mass spectrometry analysis identified temporally distinct candidate biological targets in brain tissue lysate.
The pipeline of phage display followed by NGS analysis demonstrated a unique approach to discover motifs that are sensitive to the heterogeneous and diverse pathology caused by neural injury. This strategy successfully achieves 1) target motif identification for TBI at distinct timepoints and 2) characterization of their spatiotemporal specificity.
ContributorsMartinez, Briana Isabella (Author) / Stabenfeldt, Sarah E (Thesis advisor) / Lifshitz, Jonathan (Committee member) / Sierks, Michael (Committee member) / Kleim, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2020
Description
Little is known about how cognitive and brain aging patterns differ in older adults with autism spectrum disorder (ASD). However, recent evidence suggests that individuals with ASD may be at greater risk of pathological aging conditions than their neurotypical (NT) counterparts. A growing body of research indicates that older adults with ASD may experience accelerated cognitive decline and neurodegeneration as they age, although studies are limited by their cross-sectional design in a population with strong age-cohort effects. Studying aging in ASD and identifying biomarkers to predict atypical aging is important because the population of older individuals with ASD is growing. Understanding the unique challenges faced as autistic adults age is necessary to develop treatments to improve quality of life and preserve independence. In this study, a longitudinal design was used to characterize cognitive and brain aging trajectories in ASD as a function of autistic trait severity. Principal components analysis (PCA) was used to derive a cognitive metric that best explains performance variability on tasks measuring memory ability and executive function. The slope of the integrated persistent feature (SIP) was used to quantify functional connectivity; the SIP is a novel, threshold-free graph theory metric which summarizes the speed of information diffusion in the brain. Longitudinal mixed models were using to predict cognitive and brain aging trajectories (measured via the SIP) as a function of autistic trait severity, sex, and their interaction. The sensitivity of the SIP was also compared with traditional graph theory metrics. It was hypothesized that older adults with ASD would experience accelerated cognitive and brain aging and furthermore, age-related changes in brain network topology would predict age-related changes in cognitive performance.
For both cognitive and brain aging, autistic traits and sex interacted to predict trajectories, such that older men with high autistic traits were most at risk for poorer outcomes. In men with autism, variability in SIP scores across time points trended toward predicting cognitive aging trajectories. Findings also suggested that autistic traits are more sensitive to differences in brain aging than diagnostic group and that the SIP is more sensitive to brain aging trajectories than other graph theory metrics. However, further research is required to determine how physiological biomarkers such as the SIP are associated with cognitive outcomes.
ContributorsSullivan, Georgia (Author) / Braden, Blair (Thesis advisor) / Kodibagkar, Vikram (Thesis advisor) / Schaefer, Sydney (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2022