Matching Items (164)
Description
The purpose of this thesis creative project was to create an educational video to present research findings on the increasingly important issue of human biospecimen preanalytic variables. When a human biospecimen, such as blood, urine, or tissue, is removed from the body, it is subjected to a plethora of variables that are not recorded or regulated in a vast majority of cases. Frequently, these samples arrive at the research or pathology lab with an unknown history, then undergo analysis for translational research purposes, or to guide clinical management decisions. Thus, compromised specimen quality caused by preanalytic variables has substantial, and potentially devastating, downstream effects. To identify the preanalytic variables with the greatest impact on blood and tissue specimen quality, 45 articles were gathered using PubMed and Google Scholar databases and cited. Based on the articles, the top five variables with the most detrimental effects were identified for both blood and tissue samples. Multiple sets of parameters ensuring specimen fitness were compared for each of the five variables for each specimen type. Then, specific parameters guaranteeing the fitness of the greatest number of analytes were verified. To present the research findings in greater detail, a paper was written that focused on identifying the top variables and key parameters to ensure analyte fitness. To present the overall issue in an easy-to-digest format, a storyboard and script were created as a guideline for a final video project. Ultimately, two alternate versions of the video were created to pertain to the audience of choice (one version for patients, one version for professionals). It is the hope that these videos will be used as educational tools to continue efforts to standardize and enforce human biospecimen preanalytic variable parameters. This is a necessary step to improve the accuracy of our biomedical research data and the healthcare of patients worldwide.
ContributorsAzcarate, Heather (Author) / Compton, Carolyn (Thesis director) / LaBaer, Joshua (Committee member) / Borges, Chad (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor)
Created2018-12
Description
Cleavage and polyadenylation is a step in mRNA processing in which the 3’UTR is cleaved and a polyA tail is added to create a final mature transcript. This process relies on RNA sequence elements that guide a large multimeric protein complex named the Cleavage and Polyadenylation Complex to dock on the 3’UTR and execute the cleavage reaction. Interactions of the complex with the RNA and specific dynamics of complex recruitment and formation still remain largely uncharacterized. In our lab we have identified an Adenosine residue as the nucleotide most often present at the cleavage site, although it is unclear whether this specific element is a required instructor of cleavage and polyadenylation. To address whether the Adenosine residue is necessary and sufficient for the cleavage and polyadenylation reaction, we mutated this nucleotide at the cleavage site in three C. elegans protein coding genes, forcing the expression of these wt and mutant 3’UTRs, and studied how the cleavage and polyadenylation machinery process these genes in vivo. We found that interrupting the wt sequence elements found at the cleavage site interferes with the cleavage and polyadenylation reaction, suggesting that the sequence close to the end of the transcript plays a role in modulating the site of the RNA cleavage. This activity is also gene-specific. Genes such as ges-1 showed little disruption in the cleavage of the transcript, with similar location occurring in both the wt and mutant 3’UTRs. On the other hand, mutation of the cleavage site in genes such as Y106G6H.9 caused the activation of new cryptic cleavage sites within the transcript. Taken together, my experiments suggest that the sequence elements at the cleavage site somehow participate in the reaction to guide the cleavage reaction to occur at an exact site. This work will help to better understand the mechanisms of transcription termination in vivo and will push forward research aimed to study post-transcriptional gene regulation in eukaryotes.
ContributorsSteber, Hannah Suzanne (Author) / Mangone, Marco (Thesis director) / Harris, Robin (Committee member) / LaBaer, Joshua (Committee member) / School of Life Sciences (Contributor, Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Magnetic resonance imaging (MRI) data of metastatic brain cancer patients at the Barrow Neurological Institute sparked interest in the radiology department due to the possibility that tumor size distributions might mimic a power law or an exponential distribution. In order to consider the question regarding the growth trends of metastatic brain tumors, this thesis analyzes the volume measurements of the tumor sizes from the BNI data and attempts to explain such size distributions through mathematical models. More specifically, a basic stochastic cellular automaton model is used and has three-dimensional results that show similar size distributions of those of the BNI data. Results of the models are investigated using the likelihood ratio test suggesting that, when the tumor volumes are measured based on assuming tumor sphericity, the tumor size distributions significantly mimic the power law over an exponential distribution.
ContributorsFreed, Rebecca (Co-author) / Snopko, Morgan (Co-author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
Cancer is one of the leading causes of death globally according to the World Health Organization. Although improved treatments and early diagnoses have reduced cancer related mortalities, metastatic disease remains a major clinical challenge. The local tumor microenvironment plays a significant role in cancer metastasis, where tumor cells respond and adapt to a plethora of biochemical and biophysical signals from stromal cells and extracellular matrix (ECM) proteins. Due to these complexities, there is a critical need to understand molecular mechanisms underlying cancer metastasis to facilitate the discovery of more effective therapies. In the past few years, the integration of advanced biomaterials and microengineering approaches has initiated the development of innovative platform technologies for cancer research. These technologies enable the creation of biomimetic in vitro models with physiologically relevant (i.e. in vivo-like) characteristics to conduct studies ranging from fundamental cancer biology to high-throughput drug screening. In this review article, we discuss the biological significance of each step of the metastatic cascade and provide a broad overview on recent progress to recapitulate these stages using advanced biomaterials and microengineered technologies. In each section, we will highlight the advantages and shortcomings of each approach and provide our perspectives on future directions.
ContributorsPeela, Nitish (Author) / Nikkhah, Mehdi (Thesis director) / LaBaer, Joshua (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Glioblastoma is the most aggressive and lethal brain tumor, due to its resistance to current conventional therapy. The resistance to chemo- and radiotherapy has been attributed to a special population of cells known as glioma stem cells. Previous literature has shown the importance of a Central Nervous System-restricted transcription factor OLIG2 in maintaining the tumor-propagating potential of these glioma stem cells. OLIG2's function was further elucidated, with its pro-mitogenic function due to its ability to negatively regulate the p53 pathway by suppressing the acetylation of the p53 protein's C terminal domain. Past work in our lab has confirmed that one of OLIG2's partner proteins is Histone Deacetylase 1 (HDAC1). In vitro experiments have also shown that targeting HDAC1 using hairpin RNA in glioma stem cells negatively impacts proliferation. In a survival study using a murine glioma model, targeting Hdac1 using hairpin RNA is shown to reduce tumor burden and increase survival. In this paper, we demonstrate that silencing Hdac1 expression reduces proliferation, increases cell death, likely a result of increased acetylation of p53. Olig2 expression levels seem to be unaffected in GSCs, demonstrating that the Hdac1 protein ablation is indeed lethal to GSCs. This work builds upon previously collected results, confirming that Hdac1 is a potential surrogate target for Olig2's pro-mitotic function in regulating the p53 pathway.
ContributorsLoo, Vincent You Wei (Author) / LaBaer, Joshua (Thesis director) / Mehta, Shwetal (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
CREB3L1 has been previously shown to auto-acetylate itself when prepared from HeLa cell based in vitro protein expression lysates. To circumvent the concerns of the contamination of co-purified human proteins from HeLa lysates, the protein was purified through insect cell transfection in vitro. The objective of this study was to assay the auto-acetylation activity of CREB3L1 prepared from insect cells using the baculovirus expression vector system (BEVS). To this end, His-tagged CREB3L1 was affinity purified from Hi5 cells using an IMAC column and used for acetylation assay. Samples were taken different time points and auto-acetylation was by western using antibodies specific to acetylated lysines. Auto-acetylation activity was observed after overnight incubation. Future experiments will focus on the improvement of purification yield and the identification of the substrates and interacting proteins of CREB3L1 to better understand the biological functions of this novel acetyltransferase.
ContributorsSchwab, Anna (Author) / LaBaer, Joshua (Thesis director) / Qiu, Ji (Committee member) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Prostate cancer is the second most common kind of cancer in men. Fortunately, it has a 99% survival rate. To achieve such a survival rate, a variety of aggressive therapies are used to treat prostate cancers that are caught early. Androgen deprivation therapy (ADT) is a therapy that is given in cycles to patients. This study attempted to analyze what factors in a group of 79 patients caused them to stick with or discontinue the treatment. This was done using naïve Bayes classification, a machine-learning algorithm. The usage of this algorithm identified high testosterone as an indicator of a patient persevering with the treatment, but failed to produce statistically significant high rates of prediction.
ContributorsMillea, Timothy Michael (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and includes chemotherapy, radiation therapy, and surgical removal if the tumor is surgically accessible. Treatment seldom results in a significant increase in longevity, partly due to the lack of precise information regarding tumor size and location. This lack of information arises from the physical limitations of MR and CT imaging coupled with the diffusive nature of glioblastoma tumors. GBM tumor cells can migrate far beyond the visible boundaries of the tumor and will result in a recurring tumor if not killed or removed. Since medical images are the only readily available information about the tumor, we aim to improve mathematical models of tumor growth to better estimate the missing information. Particularly, we investigate the effect of random variation in tumor cell behavior (anisotropy) using stochastic parameterizations of an established proliferation-diffusion model of tumor growth. To evaluate the performance of our mathematical model, we use MR images from an animal model consisting of Murine GL261 tumors implanted in immunocompetent mice, which provides consistency in tumor initiation and location, immune response, genetic variation, and treatment. Compared to non-stochastic simulations, stochastic simulations showed improved volume accuracy when proliferation variability was high, but diffusion variability was found to only marginally affect tumor volume estimates. Neither proliferation nor diffusion variability significantly affected the spatial distribution accuracy of the simulations. While certain cases of stochastic parameterizations improved volume accuracy, they failed to significantly improve simulation accuracy overall. Both the non-stochastic and stochastic simulations failed to achieve over 75% spatial distribution accuracy, suggesting that the underlying structure of the model fails to capture one or more biological processes that affect tumor growth. Two biological features that are candidates for further investigation are angiogenesis and anisotropy resulting from differences between white and gray matter. Time-dependent proliferation and diffusion terms could be introduced to model angiogenesis, and diffusion weighed imaging (DTI) could be used to differentiate between white and gray matter, which might allow for improved estimates brain anisotropy.
ContributorsAnderies, Barrett James (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Stepien, Tracy (Committee member) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Almost every form of cancer deregulates the expression and activity of anabolic glycosyltransferase (GT) enzymes, which incorporate particular monosaccharides in a donor acceptor as well as linkage- and anomer-specific manner to assemble complex and diverse glycans that significantly affect numerous cellular events, including tumorigenesis and metastasis. Because glycosylation is not template-driven, GT deregulation yields heterogeneous arrays of aberrant intact glycan products, some in undetectable quantities in clinical bio-fluids (e.g., blood plasma). Numerous glycan features (e.g., 6 sialylation, β-1,6-branching, and core fucosylation) stem from approximately 25 glycan “nodes:” unique linkage specific monosaccharides at particular glycan branch points that collectively confer distinguishing features upon glycan products. For each node, changes in normalized abundance (Figure 1) may serve as nearly 1:1 surrogate measure of activity for culpable GTs and may correlate with particular stages of carcinogenesis. Complementary to traditional top down glycomics, the novel bottom-up technique applied herein condenses each glycan node and feature into a single analytical signal, quantified by two GC-MS instruments: GCT (time-of-flight analyzer) and GCMSD (transmission quadrupole analyzers). Bottom-up analysis of stage 3 and 4 breast cancer cases revealed better overall precision for GCMSD yet comparable clinical performance of both GC MS instruments and identified two downregulated glycan nodes as excellent breast cancer biomarker candidates: t-Gal and 4,6-GlcNAc (ROC AUC ≈ 0.80, p < 0.05). Resulting from the activity of multiple GTs, t-Gal had the highest ROC AUC (0.88) and lowest ROC p‑value (0.001) among all analyzed nodes. Representing core-fucosylation, glycan node 4,6-GlcNAc is a nearly 1:1 molecular surrogate for the activity of α-(1,6)-fucosyltransferase—a potential target for cancer therapy. To validate these results, future projects can analyze larger sample sets, find correlations between breast cancer stage and changes in t-Gal and 4,6-GlcNAc levels, gauge the specificity of these nodes for breast cancer and their potential role in other cancer types, and develop clinical tests for reliable breast cancer diagnosis and treatment monitoring based on t-Gal and 4,6-GlcNAc.
ContributorsZaare, Sahba (Author) / Borges, Chad (Thesis director) / LaBaer, Joshua (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Disturbances in the protein interactome often play a large role in cancer progression. Investigation of protein-protein interactions (PPI) can increase our understanding of cancer pathways and will disclose unknown targets involved in cancer disease biology. Although numerous methods are available to study protein interactions, most platforms suffer from drawbacks including high false positive rates, low throughput, and lack of quantification. Moreover, most methods are not compatible for use in a clinical setting. To address these limitations, we have developed a multiplexed, in-solution protein microarray (MISPA) platform with broad applications in proteomics. MISPA can be used to quantitatively profile PPIs and as a robust technology for early detection of cancers. This method utilizes unique DNA barcoding of individual proteins coupled with next generation sequencing to quantitatively assess interactions via barcode enrichment. We have tested the feasibility of this technology in the detection of patient immune responses to oropharyngeal carcinomas and in the discovery of novel PPIs in the B-cell receptor (BCR) pathway. To achieve this goal, 96 human papillomavirus (HPV) antigen genes were cloned into pJFT7-cHalo (99% success) and pJFT7-n3xFlag-Halo (100% success) expression vectors. These libraries were expressed via a cell-free in vitro transcription-translation system with 93% and 96% success, respectively. A small-scale study of patient serum interactions with barcoded HPV16 antigens was performed and a HPV proteome-wide study will follow using additional patient samples. In addition, 15 query proteins were cloned into pJFT7_nGST expression vectors, expressed, and purified with 93% success to probe a library of 100 BCR pathway proteins and detect novel PPIs.
ContributorsRinaldi, Capria Lakshmi (Author) / LaBaer, Joshua (Thesis director) / Mangone, Marco (Committee member) / Borges, Chad (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12