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A Simplified Computational Approach to Model Pancreatic Ductal Adenocarcinoma Treatment with Gemcitabine
Mayer, Lauren
Mayer, Lauren
Abstract
While long non-coding RNAs (lncRNAs) have been utilized in other cancer therapy treatments, their role in regulating cancer stem cells is not well understood. Recent laboratory work appears to show a possible relationship between cancer stem cells and lncRNA. Additionally, recent studies suggest that HOTTIP and that the HOTTIP/WDR5/HOXA9/Wnt axis could possibly be utilized as a therapeutic target for pancreatic ductal adenocarcinoma (PDAC) (Fu et al., 2017). Moreover, studies show upregulating ubiquitination of the protein WT1 may help prevent metastasis of PDAC (Li et al., 2014). To analyze quantitatively the effects that targeting these pathways may have on PDAC, a proposed computational model was developed and was to be finely tuned using estimates for each of the model’s variables from publications in the scientific literature. However, due to the unprecedented circumstances that 2020 was riddled with, this work was forced in February of 2021 to take a turn towards an even more computational outcome. This updated thesis builds upon the work of four previously published mathematical models, makes additional alterations, and combines them to create a simplified model of PDAC treatment with the chemotherapeutic gemcitabine. The final deliverable of this thesis is a Python program which simplistically models PDAC treatment with gemcitabine in hopes to aid future scientists in resolving patient issues with this form of treatment for PDAC. Discovery of these published mathematical models at the beginning of the Spring 2021 semester planted the seed to create a Python program that forms a conjunction between them and hopefully a stepping stone towards an eventual solution to the chemoresistance patients with PDAC exhibit towards gemcitabine. This would ultimately allow for PDAC patients to be treated with gemcitabine rather than for scientists to try continuously and fruitlessly to discover a new therapeutic to eradicate PDAC. Moreover, this program's interface is extremely abstract to a degree that individuals with no coding experience will be able to utilize it. The overall hope for this program is that scientists and medical professionals alike may be able to utilize it as a tool to progress towards a more personalized treatment for an individual with PDAC (or even an eventual cure for PDAC) utilizing gemcitabine.
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2021-05-01
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Neuroscience