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- Creators: Computer Science and Engineering Program
Description
Mr. Green has stage 4 prostate cancer which has spread to the bones and liver and has become resistant to radiation and standard chemotherapy treatment. After 3 rounds of chemotherapy, his primary oncologist recommends that he participate in a clinical trial. He went to Dr. Red at the Saguaro Clinic after reading on the internet about a new Phase 1 clinical trial that the clinic is hosting, which is designed to target a specific receptor called AB-111 that may be present in malignant prostate, cervical, ovarian, and breast cells. After signing consent and completing the blood screens in the morning at the clinic, Mr. Green is told his liver enzymes are too high and the ranges specified in the protocol prohibit him from enrolling. Mr. Green is noticeably affected and distressed at this news, and Dr. Red recommends end-of-life care. Behind the scenes, this event is noted on official medical documents and trial study rosters as a "screen fail." This narrative, while fictional, is realistic because similar events occur in cancer clinical trial sites on a regular basis. I look at the inner "world" and mental journey of possible clinical trial candidates as they seek out information about clinical trials and gain understanding of their function \u2014 specifically in the context of Phase 1 cancer clinical trials. To whom is the language of the term "screen failure" useful? How does excluding individuals from clinical trials protect their health and does the integrity of the trial data supersede the person's curative goals? What is the message that cancer patients (potential research subjects) receive regarding clinical trials from sources outside their oncologists?
ContributorsMcKane, Alexandra (Author) / Maienschein, Jane (Thesis director) / Ellison, Karin (Committee member) / Foy, Joseph (Committee member) / Barrett, The Honors College (Contributor)
Created2013-12
Description
The interaction between England and Scotland is complicated and continually changing. Scottish writer Sir Walter Scott examines this long-standing relationship through his various writings. Scott conveys a presence that is both acutely aware of the damages enacted upon Scotland by various English political efforts, and sensitive to the delicate relationship that the two regions had begun to form during his lifetime. Through a critical analysis of Scott's novel, Rob Roy, one can see the various strategies Scott used to balance the need to address prior controversies within the relationship, and the petition to move beyond the prior conflict and develop a mutual understanding of each culture. Through this, Scott is able to regenerate a sense of Scottish nationalism for his people, and encourage improved relations within the British Isles.
ContributorsChotena, Chelsea (Author) / Facinelli, Diane (Thesis director) / Foy, Joseph (Committee member) / White, Julianne (Committee member) / Barrett, The Honors College (Contributor)
Created2013-05
Description
Cancer is the second leading cause of death in the United States. Cancer is a serious, complex disease which causes cells to grow uncontrollably, causing millions of deaths per year [1]. Cancer is usually caused by a combination of environmental variables and biological pathways. The pathways have a very robust structure normally, but are altered because of cancer, resulting in a loss of connectivity between pathways. In order detect these pathways, a PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) was created, which measures the relative rankings of the genes in each pathway. Applying this algorithm will allow us to figure out what pathways differed significantly in areas with cancer and areas without cancer. This would allow scientists to focus on specific pathways in order to learn more about the cancer and find more effective ways to treat it. So far, analysis using PoTRA has been successfully conducted on hepatocellular carcinoma (HCC) and its subtypes, resulting in all significant pathways found being cancer-associated. Now, using the TCGA data stored in Google Cloud's BigQuery, we created a pipeline to apply PoTRA to other cancer data sets and see how well it cross-applies to other cancers. The results show that even though some modification may need to be made to adapt to other datasets, many significant pathways were found for both HCC and breast cancer.
ContributorsMahesh, Sunny Nishant (Author) / Valentin, Dinu (Thesis director) / Liu, Li (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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
Big Data Network Analysis of Genetic Variation and Gene Expression in Individuals with Breast Cancer
Description
The advent of big data analytics tools and frameworks has allowed for a plethora of new approaches to research and analysis, making data sets that were previously too large or complex more accessible and providing methods to collect, store, and investigate non-traditional data. These tools are starting to be applied in more creative ways, and are being used to improve upon traditional computation methods through distributed computing. Statistical analysis of expression quantitative trait loci (eQTL) data has classically been performed using the open source tool PLINK - which runs on high performance computing (HPC) systems. However, progress has been made in running the statistical analysis in the ecosystem of the big data framework Hadoop, resulting in decreased run time, reduced storage footprint, reduced job micromanagement and increased data accessibility. Now that the data can be more readily manipulated, analyzed and accessed, there are opportunities to use the modularity and power of Hadoop to further process the data. This project focuses on adding a component to the data pipeline that will perform graph analysis on the data. This will provide more insight into the relation between various genetic differences in individuals with breast cancer, and the resulting variation - if any - in gene expression. Further, the investigation will look to see if there is anything to be garnered from a perspective shift; applying tools used in classical networking contexts (such as the Internet) to genetically derived networks.
ContributorsRandall, Jacob Christopher (Author) / Buetow, Kenneth (Thesis director) / Meuth, Ryan (Committee member) / Almalih, Sara (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
My mother died after a long battle with breast cancer in 2008. I was only nine when she was first diagnosed, and so much of my life has been shaped by her struggle for survival. She will always be the most amazing women I have ever known, and she taught me more about life, kindness, hope, and overcoming the odds than anyone else. I want to share my experience with you as a friend \u2014 not as a doctor, or a counselor, but as a friend. I want to tell you some of my stories with the emotions behind them. I will share how I learned t cope with whatever situation came our way and how I found unexpected ways to help my mom. I want you to find solace through our shared emotions even if they are at different times in our journeys. This is why in the following chapters, my stories are not chronological but categorized through the major emotions that drove my stories. I hope this book can help those who find themselves in similar situations to the one I found myself in when my mom picked me up from fourth grade with a bandana on her head instead of her normal, beautiful brown hair. This thesis is a creative exploration of emotions and finding hope in times of great loss.
ContributorsTornabene, Kathleen Elizabeth (Author) / Foy, Joseph (Thesis director) / Facinelli, Diane (Committee member) / Hyde, Suzanne (Committee member) / Barrett, The Honors College (Contributor)
Created2012-05
Description
Immunotherapy is an effective treatment for cancer which enables the patient's immune system to recognize tumor cells as pathogens. In order to design an individualized treatment, the t cell receptors (TCR) which bind to a tumor's unique antigens need to be determined. We created a convolutional neural network to predict the binding affinity between a given TCR and antigen to enable this.
ContributorsCai, Michael Ray (Author) / Lee, Heewook (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-12
Description
Molecular pathology makes use of estimates of tumor content (tumor percentage) for pre-analytic and analytic purposes, such as molecular oncology testing, massive parallel sequencing, or next-generation sequencing (NGS), assessment of sample acceptability, accurate quantitation of variants, assessment of copy number changes (among other applications), determination of specimen viability for testing (since many assays require a minimum tumor content to report variants at the limit of detection) may all be improved with more accurate and reproducible estimates of tumor content. Currently, tumor percentages of samples submitted for molecular testing are estimated by visual examination of Hematoxylin and Eosin (H&E) stained tissue slides under the microscope by pathologists. These estimations can be automated, expedited, and rendered more accurate by applying machine learning methods on digital whole slide images (WSI).
ContributorsCirelli, Claire (Author) / Yang, Yezhou (Thesis director) / Yalim, Jason (Committee member) / Velu, Priya (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05
Description
panCanSYGNAL is a web-application designed to allow cancer researchers to search the relationships between somatic mutations, regulators, and biclusters corresponding to many cancers using a Google-like searchable database.
ContributorsWatson, Jacob (Author) / Plaisier, Christopher (Thesis director) / Clough, Michael (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05
Description
This paper examines the physics behind cancer treatment and more specifically radiation therapy. A phenomenon known as Compton scattering has played a substantial role in the treatment of breast cancer and improvement of lives of women around the world. Through Compton scattering, radiation therapy has been tremendously improved and has allowed for the most accurate and effective treatment in breast cancer patients today.
ContributorsRombaoa, Matthew Bryce (Author) / Foy, Joseph (Thesis director) / Hines, Taylor (Committee member) / Barrett, The Honors College (Contributor) / School of Molecular Sciences (Contributor) / Department of Psychology (Contributor)
Created2023-05