Matching Items (6)
Filtering by

Clear all filters

150288-Thumbnail Image.png
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

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
151170-Thumbnail Image.png
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

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
157231-Thumbnail Image.png
Description
Valley Fever (VF), is a potentially lethal fungal pneumonia caused by Coccidioides spp., which is estimated to cause ~15-30% of all community-acquired pneumonias in the highly endemic Greater Phoenix and Tucson areas of Arizona. However, an accurate antigen-based diagnostic is still lacking. In order to identify protein and glycan antigen

Valley Fever (VF), is a potentially lethal fungal pneumonia caused by Coccidioides spp., which is estimated to cause ~15-30% of all community-acquired pneumonias in the highly endemic Greater Phoenix and Tucson areas of Arizona. However, an accurate antigen-based diagnostic is still lacking. In order to identify protein and glycan antigen biomarkers of infection, I used a combination of genomics, proteomics and glycomics analyses to provide evidence of genus-specific proteins and glycosylations. The next goal was to determine if Coccidioides-specific glycans were present in biological samples from VF patients. Urine collected from 77 humans and 63 dogs were enriched for glycans and evaluated by mass spectrometry for Coccidioides-specific glycans and evaluated against a panel of normal donor urines, urines from patients infected with other fungi, and fungal cultures from closely related pneumonia-causing fungi. A combination of 6 glycan biomarkers was 100% sensitive and 100% specific in the diagnosis of human VF subjects, while only 3 glycan biomarkers were needed for 100% sensitivity and 100 specificity in the diagnosis of dog VF subject. Additionally, a blinded trial of 23 human urine samples was correctly able to classify urine samples with 93.3% sensitivity and 100% specificity. The results of this research provides evidence that Coccidioides genus-specific glycosylations have potential as antigens in diagnostic assays.
ContributorsMitchell, Natalie M (Author) / Lake, Douglas F (Thesis advisor) / Bean, Heather D (Committee member) / Grys, Thomas E (Committee member) / Magee, Dewey M (Committee member) / Arizona State University (Publisher)
Created2019
155443-Thumbnail Image.png
Description
Physical activity, sedentary behaviors, and sleep are often associated with cardiometabolic biomarkers commonly found in metabolic syndrome. These relationships are well studied, and yet there are still questions on how each activity may affect cardiometabolic biomarkers. The objective of this study was to examine data from the BeWell24 studies to

Physical activity, sedentary behaviors, and sleep are often associated with cardiometabolic biomarkers commonly found in metabolic syndrome. These relationships are well studied, and yet there are still questions on how each activity may affect cardiometabolic biomarkers. The objective of this study was to examine data from the BeWell24 studies to evaluate the relationship between objectively measured physical activity and sedentary behaviors and cardiometabolic biomarkers in middle age adults, while also determining if sleep quality and duration mediates this relationship. A group of inactive participants (N = 29, age = 52.1 ± 8.1 years, 38% female) with increased risk for cardiometabolic disease were recruited to participate in BeWell24, a trial testing the impact of a lifestyle-based, multicomponent smartphone application targeting sleep, sedentary, and more active behaviors. During baseline, interim (4 weeks), and posttest visits (8 weeks), biomarker measurements were collected for weight (kg), waist circumference (cm), glucose (mg/dl), insulin (uU/ml), lipids (mg/dl), diastolic and systolic blood pressures (mm Hg), and C reactive protein (mg/L). Participants wore validated wrist and thigh sensors for one week intervals at each time point to measure sedentary behavior, physical activity, and sleep outcomes. Long bouts of sitting time (>30 min) significantly affected triglycerides (beta = .15 (±.07), p<.03); however, no significant mediation effects for sleep quality or duration were present. No other direct effects were observed between physical activity measurements and cardiometabolic biomarkers. The findings of this study suggest that reductions in long bouts of sitting time may support reductions in triglycerides, yet these effects were not mediated by sleep-related improvements.
ContributorsLanich, Boyd (Author) / Buman, Matthew (Thesis advisor) / Ainsworth, Barbara (Committee member) / Huberty, Jennifer (Committee member) / Arizona State University (Publisher)
Created2017
154028-Thumbnail Image.png
Description
In the U.S., breast cancer (BC) incidences among African American (AA) and CA (CA) women are similar, yet AA women have a significantly higher mortality rate. In addition, AA women often present with tumors at a younger age, with a higher tumor grade/stage and are more likely to be diagnosed

In the U.S., breast cancer (BC) incidences among African American (AA) and CA (CA) women are similar, yet AA women have a significantly higher mortality rate. In addition, AA women often present with tumors at a younger age, with a higher tumor grade/stage and are more likely to be diagnosed with the highly aggressive triple-negative breast cancer (TNBC) subtype. Even within the TNBC subtype, AA women have a worse clinical outcome compared to CA. Although multiple socio-economic and lifestyle factors may contribute to these observed health disparities, it is essential that the underlying biological differences between CA and AA TNBC are identified. In this study, gene expression profiling was performed on archived FFPE samples, obtained from CA and AA women diagnosed with early stage TNBC. Initial analysis revealed a pattern of differential expression in the AA cohort compared to CA. Further molecular characterization results showed that the AA cohort segregated into 3-TNBC molecular subtypes; Basal-like (BL2), Immunomodulatory (IM) and Mesenchymal (M). Gene expression analyses resulted in 190 differentially expressed genes between the AA and CA cohorts. Pathway enrichment analysis demonstrated that differentially expressed genes were over-represented in cytoskeletal remodeling, cell adhesion, tight junctions, and immune response in the AA TNBC -cohort. Furthermore, genes in the Wnt/β-catenin pathway were over-expressed. These results were validated using RT-qPCR on an independent cohort of FFPE samples from AA and CA women with early stage TNBC, and identified Caveolin-1 (CAV1) as being significantly expressed in the AA-TNBC cohort. Furthermore, CAV1 was shown to be highly expressed in a cell line panel of TNBC, in particular, those of the mesenchymal and basal-like molecular subtype. Finally, silencing of CAV1 expression by siRNA resulted in a significant decrease in proliferation in each of the TNBC cell lines. These observations suggest that CAV1 expression may contribute to the more aggressive phenotype observed in AA women diagnosed with TNBC.
ContributorsGetz, Julie (Author) / Baumbach-Reardon, Lisa L (Thesis advisor) / Lake, Douglas F (Thesis advisor) / Bussey, Kimberly (Committee member) / Kusumi, Kenro (Committee member) / Arizona State University (Publisher)
Created2015
153561-Thumbnail Image.png
Description
Currently in the US, many patients with cancer do not benefit from the population-based screening, due to challenges associated with the existing cancer screening scheme. Blood-based diagnostic assays have the potential to detect diseases in a non-invasive way. Proteins released from small early tumors may only be present intermittently and

Currently in the US, many patients with cancer do not benefit from the population-based screening, due to challenges associated with the existing cancer screening scheme. Blood-based diagnostic assays have the potential to detect diseases in a non-invasive way. Proteins released from small early tumors may only be present intermittently and get diluted to tiny concentrations in the blood, making them difficult to use as biomarkers. However, they can induce autoantibody (AAb) responses, which can amplify the signal and persist in the blood even if the antigen is gone. Circulating autoantibodies is a promising class of molecules that have potential to serve as early detection biomarkers for cancers. This Ph.D thesis aims to screen for autoantibody biomarkers for the early detection of two deadly cancer, basal-like breast cancer and lung adenocarcinoma. First, a method was developed to display proteins in both native and denatured conformation on protein array. This method adopted a novel protein tag technology, called HaloTag, to covalently immobilize proteins on glass slide surface. The covalent attachment allowed these proteins to endure harsh treatment without getting dissociated from slide surface, which enabled the profiling of antibody responses against both conformational and linear epitopes. Next, a plasma screening protocol was optimized to significantly increase signal to noise ratio of protein array based AAb detection. Following this, the AAb responses in basal-like breast cancer were explored using nucleic acid programmable protein arrays (NAPPA) containing 10,000 full-length human proteins in 45 cases and 45 controls. After verification in a large sample set (145 basal-like breast cancer cases / 145 controls / 70 non-basal breast cancer) by ELISA, a 13-AAb classifier was developed to differentiate patients from controls with a sensitivity of 33% at 98% specificity. Similar approach was also applied to the lung cancer study to identify AAbs that distinguished lung cancer patients from computed-tomography positive benign pulmonary nodules (137 lung cancer cases, 127 smoker controls, 170 benign controls). In this study, two panels of AAbs were discovered that showed promising sensitivity and specificity. Six out of eight AAb targets were also found to have elevated mRNA level in lung adenocarcinoma patients using TCGA data. These projects as a whole provide novel insights on the association between AAbs and cancer, as well as general B cell antigenicity against self-proteins.
ContributorsWang, Jie (Author) / LaBaer, Joshua (Thesis advisor) / Anderson, Karen S (Committee member) / Lake, Douglas F (Committee member) / Chang, Yung (Committee member) / Arizona State University (Publisher)
Created2015