Matching Items (164)
Description
Breast cancer is the leading cause of cancer-related deaths of women in the united states. Traditionally, Breast cancer is predominantly treated by a combination of surgery, chemotherapy, and radiation therapy. However, due to the significant negative side effects associated with these traditional treatments, there has been substantial efforts to develop alternative therapies to treat cancer. One such alternative therapy is a peptide-based therapeutic cancer vaccine. Therapeutic cancer vaccines enhance an individual's immune response to a specific tumor. They are capable of doing this through artificial activation of tumor specific CTLs (Cytotoxic T Lymphocytes). However, in order to artificially activate tumor specific CTLs, a patient must be treated with immunogenic epitopes derived from their specific cancer type. We have identified that the tumor associated antigen, TPD52, is an ideal target for a therapeutic cancer vaccine. This designation was due to the overexpression of TPD52 in a variety of different cancer types. In order to start the development of a therapeutic cancer vaccine for TPD52-related cancers, we have devised a two-step strategy. First, we plan to create a list of potential TPD52 epitopes by using epitope binding and processing prediction tools. Second, we plan to attempt to experimentally identify MHC class I TPD52 epitopes in vitro. We identified 942 potential 9 and 10 amino acid epitopes for the HLAs A1, A2, A3, A11, A24, B07, B27, B35, B44. These epitopes were predicted by using a combination of 3 binding prediction tools and 2 processing prediction tools. From these 942 potential epitopes, we selected the top 50 epitopes ranked by a combination of binding and processing scores. Due to the promiscuity of some predicted epitopes for multiple HLAs, we ordered 38 synthetic epitopes from the list of the top 50 epitope. We also performed a frequency analysis of the TPD52 protein sequence and identified 3 high volume regions of high epitope production. After the epitope predictions were completed, we proceeded to attempt to experimentally detected presented TPD52 epitopes. First, we successful transduced parental K562 cells with TPD52. After transduction, we started the optimization process for the immunoprecipitation protocol. The optimization of the immunoprecipitation protocol proved to be more difficult than originally believed and was the main reason that we were unable to progress past the transduction of the parental cells. However, we believe that we have identified the issues and will be able to complete the experiment in the coming months.
ContributorsWilson, Eric Andrew (Author) / Anderson, Karen (Thesis director) / Borges, Chad (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The Experimental Data Processing (EDP) software is a C++ GUI-based application to streamline the process of creating a model for structural systems based on experimental data. EDP is designed to process raw data, filter the data for noise and outliers, create a fitted model to describe that data, complete a probabilistic analysis to describe the variation between replicates of the experimental process, and analyze reliability of a structural system based on that model. In order to help design the EDP software to perform the full analysis, the probabilistic and regression modeling aspects of this analysis have been explored. The focus has been on creating and analyzing probabilistic models for the data, adding multivariate and nonparametric fits to raw data, and developing computational techniques that allow for these methods to be properly implemented within EDP. For creating a probabilistic model of replicate data, the normal, lognormal, gamma, Weibull, and generalized exponential distributions have been explored. Goodness-of-fit tests, including the chi-squared, Anderson-Darling, and Kolmogorov-Smirnoff tests, have been used in order to analyze the effectiveness of any of these probabilistic models in describing the variation of parameters between replicates of an experimental test. An example using Young's modulus data for a Kevlar-49 Swath stress-strain test was used in order to demonstrate how this analysis is performed within EDP. In order to implement the distributions, numerical solutions for the gamma, beta, and hypergeometric functions were implemented, along with an arbitrary precision library to store numbers that exceed the maximum size of double-precision floating point digits. To create a multivariate fit, the multilinear solution was created as the simplest solution to the multivariate regression problem. This solution was then extended to solve nonlinear problems that can be linearized into multiple separable terms. These problems were solved analytically with the closed-form solution for the multilinear regression, and then by using a QR decomposition to solve numerically while avoiding numerical instabilities associated with matrix inversion. For nonparametric regression, or smoothing, the loess method was developed as a robust technique for filtering noise while maintaining the general structure of the data points. The loess solution was created by addressing concerns associated with simpler smoothing methods, including the running mean, running line, and kernel smoothing techniques, and combining the ability of each of these methods to resolve those issues. The loess smoothing method involves weighting each point in a partition of the data set, and then adding either a line or a polynomial fit within that partition. Both linear and quadratic methods were applied to a carbon fiber compression test, showing that the quadratic model was more accurate but the linear model had a shape that was more effective for analyzing the experimental data. Finally, the EDP program itself was explored to consider its current functionalities for processing data, as described by shear tests on carbon fiber data, and the future functionalities to be developed. The probabilistic and raw data processing capabilities were demonstrated within EDP, and the multivariate and loess analysis was demonstrated using R. As the functionality and relevant considerations for these methods have been developed, the immediate goal is to finish implementing and integrating these additional features into a version of EDP that performs a full streamlined structural analysis on experimental data.
ContributorsMarkov, Elan Richard (Author) / Rajan, Subramaniam (Thesis director) / Khaled, Bilal (Committee member) / Chemical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Ira A. Fulton School of Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Agrobacterium tumefaciens has the ability to transfer its tumor inducing (Ti) plasmid into plant cells. In the last decade, agroinfiltration of Nicotiana benthamiana plants has shown promising results for recombinant protein production. However, A. tumefaciens produce endotoxins in the form of lipopolysaccharides (LPS), a component of their outer membrane that can induce organ failure and septic shock. Therefore, we aimed to detoxify A. tumefaciens by modifying their Lipid A structure, the toxic region of LPS, via mutating the genes for lipid A biosynthesis. Two mutant strains of A. tumefaciens were infiltrated into N. benthamiana stems to test for tumor formation to ensure that the detoxifying process did not compromise the ability of gene transfer. Our results demonstrated that A. tumefaciens with both single and double mutations retained the ability to form tumors. Thus, these mutants can be utilized to generate engineered A. tumefaciens strains for the production of plant-based pharmaceuticals with low endotoxicity.
ContributorsHaseefa, Fathima (Author) / Chen, Qiang (Thesis director) / Mason, Hugh (Committee member) / Hurtado, Jonathan (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This project aims to tackle two perspectives: to design and express an enzyme that can perform single-molecule modifications for identification, and to determine the inclusion of the last adenosine in mature mRNAs within the metazoan, Caenorhabditis elegans. Starting with the first perspective, the enzymatic group that was utilized was methyltransferases. Methyltransferases have gained great interest in biotechnology and academia due to their ability to make single-molecule modifications to a wide variety of biomolecules, ranging from proteins to RNA. Of these methyltransferases, the subset that has the greatest interest for this study are RNA methyltransferases. Of the known RNA methyltransferases, human METTL16 was chosen for this project, due to its ability to modify adenosines at the N6 position (m6A), specificity for its consensus motif, and its promise in chimeric enzymatic complexes. As a result of these properties, this study looks to design METTl16-based complexes for the purpose of identifying single nucleotides in RNA.
The second perspective involves pre-mRNA cleavage and polyadenylation of the 3’ untranslated region (3’UTR). Cleavage of pre-mRNAs within C.elegans appears to prefer an adenosine, leading to the term “terminal adenosine” (terminal-A). Since RNA cleavage and polyadenylation is highly conserved across metazoans, we can utilize the model system, C. elegans, to apply our findings to humans. Utilizing METTL16’s ability to modify adenosines, it is theorized that it may be possible to modify the terminal-A in vivo within C. elegans. To confirm the functionality and utilization of METTL16, a novel methodology is currently being developed called the terminal adenosine methylation (TAM) assay. The TAM assay takes advantage of METTL16’s N-terminal RNA binding domain (RBD) and methyltransferase domain – called the “core” – to methylate the terminal adenosine of probe mRNA transcripts prior to cleavage in vivo. To determine if the adenosine is present within mature mRNAs, sequencing will determine if there is a m6A present, confirming that CPSF-3 cleaves either upstream or downstream of the terminal-A.
Ultimately, this project focuses on designing METTL16 complexes for mRNA modification, testing the functionality of these constructs in vitro, and developing transgenic C. elegans strains to express the METTL16 complexes. The bioconjugation capabilities of RNA methyltransferases allow for concepts such as the TAM assay to be viable, as well as make way for future prospects of methyltransferases as a biotechnical tool.
ContributorsMurray, Jillian (Author) / Mangone, Marco (Thesis director) / Lapinaite, Audrone (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of Molecular Sciences (Contributor)
Created2024-05