Matching Items (57)
Description
Phenotypic and molecular profiling demonstrates a high degree of heterogeneity in the breast tumors. TP53 tumor suppressor is mutated in 30% of all breast tumors and the mutation frequency in basal-like subtype is as high as 80% and co-exists with several other somatic mutations in different genes. It was hypothesized that tumor heterogeneity is a result of a combination of neo-morphic functions of specific TP53 driver mutations and distinct co-mutations or the co-drivers for each type of TP53 mutation. The 10 most common p53 missense mutant proteins found in breast cancer patients were ectopically expressed in normal-like mammary epithelial cells and phenotypes associated with various hallmarks of cancer examined. Supporting the hypothesis, a wide spectrum of phenotypic changes in cell survival, resistance to apoptosis and anoikis, cell migration, invasion and polarity was observed in the mutants compared to wildtype p53 expressing cells. The missense mutants R248W, R273C and Y220C were most aggressive. Integrated analysis of ChIP and RNA seq showed distinct promoter binding profiles of the p53 mutant proteins different than wildtype p53, implying altered transcriptional activity of mutant p53 proteins and the phenotypic heterogeneity of tumors. Enrichment and model-based pathway analyses revealed dysregulated adherens junction and focal adhesion pathways associated with the aggressive p53 mutants. As several somatic mutations co-appear with mutant TP53, we performed a functional assay to fish out the relevant collaborating driver mutations, the co-drivers. When PTEN was deleted by CRISPR-Cas9 in non-invasive p53-Y234C mutant cell, an increase in cell invasion was observed justifying the concept of co-drivers. A genome wide CRISPR library-based screen on p53-Y234C and R273C cells identified separate candidate co-driver mutations that promoted cell invasion. The top candidates included several mutated genes in breast cancer patients harboring TP53 mutations and were associated with cytoskeletal and apoptosis resistance pathways. Overall, the combined approach of molecular profiling and functional genomics screen highlighted distinct sets of co-driver mutations that can lead to heterogeneous phenotypes and promote aggressiveness in cells with different TP53 mutation background, which can guide development of novel targeted therapies.
ContributorsPal, Anasuya (Author) / LaBaer, Joshua (Thesis advisor) / Roberson, Robert (Committee member) / Van Horn, Wade (Committee member) / Maley, Carlo (Committee member) / Arizona State University (Publisher)
Created2019
Description
Understanding intratumor heterogeneity and their driver genes is critical to
designing personalized treatments and improving clinical outcomes of cancers. Such
investigations require accurate delineation of the subclonal composition of a tumor, which
to date can only be reliably inferred from deep-sequencing data (>300x depth). The
resulting algorithm from the work presented here, incorporates an adaptive error model
into statistical decomposition of mixed populations, which corrects the mean-variance
dependency of sequencing data at the subclonal level and enables accurate subclonal
discovery in tumors sequenced at standard depths (30-50x). Tested on extensive computer
simulations and real-world data, this new method, named model-based adaptive grouping
of subclones (MAGOS), consistently outperforms existing methods on minimum
sequencing depth, decomposition accuracy and computation efficiency. MAGOS supports
subclone analysis using single nucleotide variants and copy number variants from one or
more samples of an individual tumor. GUST algorithm, on the other hand is a novel method
in detecting the cancer type specific driver genes. Combination of MAGOS and GUST
results can provide insights into cancer progression. Applications of MAGOS and GUST
to whole-exome sequencing data of 33 different cancer types’ samples discovered a
significant association between subclonal diversity and their drivers and patient overall
survival.
designing personalized treatments and improving clinical outcomes of cancers. Such
investigations require accurate delineation of the subclonal composition of a tumor, which
to date can only be reliably inferred from deep-sequencing data (>300x depth). The
resulting algorithm from the work presented here, incorporates an adaptive error model
into statistical decomposition of mixed populations, which corrects the mean-variance
dependency of sequencing data at the subclonal level and enables accurate subclonal
discovery in tumors sequenced at standard depths (30-50x). Tested on extensive computer
simulations and real-world data, this new method, named model-based adaptive grouping
of subclones (MAGOS), consistently outperforms existing methods on minimum
sequencing depth, decomposition accuracy and computation efficiency. MAGOS supports
subclone analysis using single nucleotide variants and copy number variants from one or
more samples of an individual tumor. GUST algorithm, on the other hand is a novel method
in detecting the cancer type specific driver genes. Combination of MAGOS and GUST
results can provide insights into cancer progression. Applications of MAGOS and GUST
to whole-exome sequencing data of 33 different cancer types’ samples discovered a
significant association between subclonal diversity and their drivers and patient overall
survival.
ContributorsAhmadinejad, Navid (Author) / Liu, Li (Thesis advisor) / Maley, Carlo (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2019
Description
The human papillomavirus (HPV) is a double-stranded DNA virus responsible for causing upwards of 80% of head and neck cancers in the oropharyngeal region. Current treatments, including surgery, chemotherapy, and/or radiation, are aggressive and elicit toxic effects. HPV is a pathogen that expresses viral-specific oncogenic proteins that play a role in cancer progression. These proteins may serve as potential targets for immunotherapeutic applications. Engineered T cell receptor (TCR) therapy may be an advantageous approach for HPV-associated cancers. In TCR therapy, TCRs are modified to express a receptor that is specific to an immunogenic antigen (part of the virus/cancer capable of eliciting an immune response). Since HPV-associated oropharyngeal cancers typically express unique viral proteins, it is important to identify the TCRs capable of recognizing these proteins. Evidence supports that head and neck cancers typically experience high levels of immune cell infiltration and are subsequently associated with increased survival rates. Most of the immune cell infiltrations in HPV+ HNSCC are CD8+ T lymphocytes, drawing attention to their prospective use in cellular immunotherapies. While TCRs are highly specific, the TCR repertoire is extremely diverse; enabling the immune system to fight off numerous pathogens. In project 1, I review approaches to analyzing TCR diversity and explore the use of DNA origami in retrieving paired TCR sequences from a population. The results determine that DNA origami can be used within a monoclonal population but requires further optimization before being applied in a polyclonal setting. In project 2, I investigate HPV-specific T-cell dysfunction; I detect low frequency HPV-specific CD8+ T cells, determine that they are tumor specific, and show that HPV+HNSCC patients exhibit increased epitope-specific levels of CD8+T cell exhaustion. In project 3, I apply methods to expand and isolate TCRαβ sequences derived from donors stimulated with a previously identified HPV epitope. Single-cell analysis provide ten unique TCRαβ pairs with corresponding CDR3 sequences that may serve as therapeutic candidates. This thesis contributes to fundamental immunology by contributing to the knowledge of T cell dysfunction within HPV+HNSCC and further reveals TCR gene usage within an HPV stimulated population, thus identifying potential TCR pairs for adoptive cell therapies.
ContributorsUlrich, Peaches Rebecca (Author) / Anderson, Karen S (Thesis advisor) / Lake, Douglas (Committee member) / Maley, Carlo (Committee member) / Varsani, Arvind (Committee member) / Arizona State University (Publisher)
Created2020
Description
Proteins are a large collection of biomolecules that orchestrate the vital
cellular processes of life. The last decade has witnessed dramatic advances in the
field of proteomics, which broadly include characterizing the composition, structure,
functions, interactions, and modifications of numerous proteins in biological systems,
and elucidating how the miscellaneous components collectively contribute to the
phenotypes associated with various disorders. Such large-scale proteomics studies
have steadily gained momentum with the evolution of diverse high-throughput
technologies. This work illustrates the development of novel high-throughput
proteomics platforms and their applications in translational and structural biology. In
Chapter 1, nucleic acid programmable protein arrays displaying the human
proteomes were applied to immunoprofiling of paired serum and cerebrospinal fluid
samples from patients with Alzheimer’s disease. This high-throughput
immunoproteomic approach allows us to investigate the global antibody responses
associated with Alzheimer’s disease and potentially identify the diagnostic
autoantibody biomarkers. In Chapter 2, a versatile proteomic pipeline based on the
baculovirus-insect cell expression system was established to enable high-throughput
gene cloning, protein production, in vivo crystallization and sample preparation for Xray diffraction. In conjunction with the advanced crystallography methods, this endto-end pipeline promises to substantially facilitate the protein structural
determination. In Chapter 3, modified nucleic acid programmable protein arrays
were developed and used for probing protein-protein interactions at the proteome
level. From the perspective of biomarker discovery, structural proteomics, and
protein interaction networks, this work demonstrated the power of high-throughput
proteomics technologies in myriad applications for proteome-scale structural,
functional, and biomedical research.
cellular processes of life. The last decade has witnessed dramatic advances in the
field of proteomics, which broadly include characterizing the composition, structure,
functions, interactions, and modifications of numerous proteins in biological systems,
and elucidating how the miscellaneous components collectively contribute to the
phenotypes associated with various disorders. Such large-scale proteomics studies
have steadily gained momentum with the evolution of diverse high-throughput
technologies. This work illustrates the development of novel high-throughput
proteomics platforms and their applications in translational and structural biology. In
Chapter 1, nucleic acid programmable protein arrays displaying the human
proteomes were applied to immunoprofiling of paired serum and cerebrospinal fluid
samples from patients with Alzheimer’s disease. This high-throughput
immunoproteomic approach allows us to investigate the global antibody responses
associated with Alzheimer’s disease and potentially identify the diagnostic
autoantibody biomarkers. In Chapter 2, a versatile proteomic pipeline based on the
baculovirus-insect cell expression system was established to enable high-throughput
gene cloning, protein production, in vivo crystallization and sample preparation for Xray diffraction. In conjunction with the advanced crystallography methods, this endto-end pipeline promises to substantially facilitate the protein structural
determination. In Chapter 3, modified nucleic acid programmable protein arrays
were developed and used for probing protein-protein interactions at the proteome
level. From the perspective of biomarker discovery, structural proteomics, and
protein interaction networks, this work demonstrated the power of high-throughput
proteomics technologies in myriad applications for proteome-scale structural,
functional, and biomedical research.
ContributorsTang, Yanyang (Author) / LaBaer, Joshua (Thesis advisor) / Anderson, Karen S (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2020
Description
Recent studies have shown that human papillomavirus (HPV) plays a role in development of cancers, one of which is head and neck cancer. There is strong and consistent molecular evidence demonstrating that human papillomavirus (HPV) is an etiological cause of these oropharyngeal cancers. Despite the introduction of HPV vaccines, there is still an increase in human papillomavirus associated OPC (HPVOPC) and it is expected that the incidence of head and neck cancer, specifically oropharyngeal cancer (OPC) will increase. The aim of this study is to utilize human papillomavirus (HPV) seropositivity for rapid detection of HPV early specific antigen-antibodies using a lateral flow assay.
Human papillomavirus (HPV) 16 proteins of interest, E7, E6 and CE2 were expressed and purified in E. coli for detection of specific antibodies using lateral flow assay because viral and host factors impact the serologic responses to HPV early antigens in HPV-positive oropharyngeal cancer. 17 samples and 5 controls with already known antibody reactivity from ELISA analysis were selected for HPV serologic responses. The lateral flow strip was evaluated for its color band intensity using Image J software. Peak area was used to quantify the color intensity of the lateral flow strip. Out of the 17 samples, 11 (64.7%) showed high antibody levels to E7, 12 (70.6%) showed high Ab levels to E6 and 6 (35.3%) showed high Ab levels to CE2. Correlation coefficient between antibody detection by sight and ELISA for E7, CE2 and E6 were 0.6614, 0.4845 and 0.2372 respectively and correlation coefficient between lateral flow assay and ELISA for E7, CE2 and E6 were 0.3480, 0.1716 and 0.1644 respectively. This further proves patients or samples with HPV 16 oropharyngeal cancer have detectable antibodies to early E7, E6 and E2 proteins, which are potential biomarkers for HPV-associated oropharyngeal cancer.
Human papillomavirus (HPV) 16 proteins of interest, E7, E6 and CE2 were expressed and purified in E. coli for detection of specific antibodies using lateral flow assay because viral and host factors impact the serologic responses to HPV early antigens in HPV-positive oropharyngeal cancer. 17 samples and 5 controls with already known antibody reactivity from ELISA analysis were selected for HPV serologic responses. The lateral flow strip was evaluated for its color band intensity using Image J software. Peak area was used to quantify the color intensity of the lateral flow strip. Out of the 17 samples, 11 (64.7%) showed high antibody levels to E7, 12 (70.6%) showed high Ab levels to E6 and 6 (35.3%) showed high Ab levels to CE2. Correlation coefficient between antibody detection by sight and ELISA for E7, CE2 and E6 were 0.6614, 0.4845 and 0.2372 respectively and correlation coefficient between lateral flow assay and ELISA for E7, CE2 and E6 were 0.3480, 0.1716 and 0.1644 respectively. This further proves patients or samples with HPV 16 oropharyngeal cancer have detectable antibodies to early E7, E6 and E2 proteins, which are potential biomarkers for HPV-associated oropharyngeal cancer.
ContributorsLadipo, Evelyn (Author) / Anderson, Karen S (Thesis advisor) / Hogue, Brenda G (Committee member) / Hou, Ching-Wen (Committee member) / Arizona State University (Publisher)
Created2019
Description
Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide and exhibits a male-bias in occurrence and mortality. Previous studies have provided insight into the role of inherited genetic regulation of transcription in modulating sex-differences in HCC etiology and mortality. This study uses pathway analysis to add insight into the biological processes that drive sex-differences in HCC etiology as well as a provide additional framework for future studies on sex-biased cancers. Gene expression data from normal, tumor adjacent, and HCC liver tissue were used to calculate pathway scores using a tool called PathOlogist that not only takes into consideration the molecules in a biological pathway, but also the interaction type and directionality of the signaling pathways. Analysis of the pathway scores uncovered etiologically relevant pathways differentiating male and female HCC. In normal and tumor adjacent liver tissue, males showed higher activity of pathways related to translation factors and signaling. Females did not show higher activity of any pathways compared to males in normal and tumor adjacent liver tissue. Work suggest biologic processes that underlie sex-biases in HCC occurrence and mortality. Both males and females differed in the activation of pathways related apoptosis, cell cycle, signaling, and metabolism in HCC. These results identify clinically relevant pathways for future research and therapeutic targeting.
ContributorsRehling, Thomas E (Author) / Buetow, Kenneth (Thesis advisor) / Wilson, Melissa (Committee member) / Maley, Carlo (Committee member) / Arizona State University (Publisher)
Created2021
Description
Cooperative cellular phenotypes are universal across multicellular life. Division of labor, regulated proliferation, and controlled cell death are essential in the maintenance of a multicellular body. Breakdowns in these cooperative phenotypes are foundational in understanding the initiation and progression of neoplastic diseases, such as cancer. Cooperative cellular phenotypes are straightforward to characterize in extant species but the selective pressures that drove their emergence at the transition(s) to multicellularity have yet to be fully characterized. Here we seek to understand how a dynamic environment shaped the emergence of two mechanisms of regulated cell survival: apoptosis and senescence. We developed an agent-based model to test the time to extinction or stability in each of these phenotypes across three levels of stochastic environments.
ContributorsDanesh, Dafna (Author) / Maley, Carlo (Thesis director) / Aktipis, Athena (Committee member) / Compton, Zachary (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2021-12
Description
The representation of a patient’s characteristics as the parameters of a model is a key component in many studies of personalized medicine, where the underlying mathematical models are used to describe, explain, and forecast the course of treatment. In this context, clinical observations form the bridge between the mathematical frameworks and applications. However, the formulation and theoretical studies of the models and the clinical studies are often not completely compatible, which is one of the main obstacles in the application of mathematical models in practice. The goal of my study is to extend a mathematical framework to model prostate cancer based mainly on the concept of cell-quota within an evolutionary framework and to study the relevant aspects for the model to gain useful insights in practice. Specifically, the first aim is to construct a mathematical model that can explain and predict the observed clinical data under various treatment combinations. The second aim is to find a fundamental model structure that can capture the dynamics of cancer progression within a realistic set of data. Finally, relevant clinical aspects such as how the patient's parameters change over the course of treatment and how to incorporate treatment optimization within a framework of uncertainty quantification, will be examined to construct a useful framework in practice.
ContributorsPhan, Tin (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric J (Committee member) / Crook, Sharon (Committee member) / Maley, Carlo (Committee member) / Bryce, Alan (Committee member) / Arizona State University (Publisher)
Created2021
Cancer autoantibody biomarker discovery and validation using nucleic acid programmable protein array
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 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
Description
Trichoplax adhaerens (Placozoa) is the simplest multicellular animal to be described. This organism lacks nervous tissue, muscle tissue and organs, and is composed of only five cell types organized into three layers. Placozoa are gaining popularity as a model organism due to their simple make-up and completely sequenced genome. The complete sequencing of this organism’s genome has revealed the presence of important genes in cancer such as TP53 and MDM2 genes. Along with the presence of these genes, there are also additional pathways commonly deregulated in cancer that are well conserved in this organism. T. adhaerens are able to survive exposure to 160Gy and even 240Gy of X-ray radiation. Though small dark bodies form within the main body, they tend to extrude those masses, and continue to reproduce afterwards. After exposure to both grades of radiation, there was a greater increase in the apparent population size of the treated population than the control population. There was also a greater decrease in surface area of the organisms exposed to 160Gy than the control organisms. This increase in population and decrease in surface area of the treated organisms could be due to the extruded bodies. We hypothesize that the observed extrusion is a novel cancer defense mechanism for ridding the animal of damaged or mutated cells. This hypothesis should be tested through longitudinal observation and genetic analysis of the extruded bodies.
ContributorsYi, Avalon (Author) / Fortunato, Angelo (Thesis director) / Maley, Carlo (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12