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- W2912724170 abstract "Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of death from cancer. Because most patients are not diagnosed before the cancer has reached a metastatic state, after cells have acquired an altered mechanobiome, finding ways to lessen the cell's ability to navigate diverse microenvironments could reduce the invasiveness of the disease. One way to do this is through altering the cell's cytoskeletal structure using small molecules. We have identified a small molecule, 4-Hydroxyacetophenone (4-HAP), which we have shown alters cellular mechanics though the targeting of Myosin II in Dictyostelium. To better understand the mechanism by which 4-HAP alters the cytoskeleton and metastatic state of pancreatic cancer cells, we grew pancreatic cancer tissue spheroids of myosin IIA (myh9) and myosin IIC (myh14) knockdowns. By treating the spheroids with 4-HAP, we can visualize alterations to the cytoskeleton in a multicellular system. Additionally, hemisplenectomies were performed on mice to model metastasis. To quantify these sets of images, we designed computer vision algorithms to extract biologically relevant parameters. The results of the analysis indicate that knocking down Myosin IIA increases cancer cell dissemination and that 4-HAP works primary though Myosin IIC to reduce tumor load. To explore the role of the mechanobiome in pancreatic cancer and how small molecules like 4-HAP may be used as treatments, we are developing an in silico model of PDAC using hybrid modeling. By developing a computational model of PDAC, we may be able to test hypotheses about the effects of small molecules like 4-HAP that will synergize with experimental approaches. Additionally, these models can guide development of the best strategies for manipulating the diseased system towards a healthier state." @default.
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- W2912724170 date "2019-02-01" @default.
- W2912724170 modified "2023-10-14" @default.
- W2912724170 title "Computer Aided Small Molecule Modulation of Pancreatic Cancer Mechanobiology" @default.
- W2912724170 doi "https://doi.org/10.1016/j.bpj.2018.11.2237" @default.
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