Examining cell signaling activity during cell migration via fluorescence lifetime biosensors in Glioblastoma and Pancreatic Ductal Adenocarcinoma

University Of Minnesota, Minneapolis MN

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Abstract

Abstract A key feature of highly aggressive cancers is their invasiveness, where transformed cells disseminate by crawling through the local micro-environment, ultimately causing death as the tumor invades and metastasizes. If these processes of cell motility could be suppressed, it would potentially extend lifespan and increase the potential effectiveness for local and global therapeutic treatments. However, we do not adequately understand the mechanical and chemical basis of cancer cell migration in complex and mechanically challenging microenvironments. We are currently developing a mathematical/computational model through our Physical Sciences in Oncology Center that will allow us to simulate cancer migration on a computer, and, in the longer-term, perform virtual in silico drug screening. The goal of the proposed project is to integrate innovate new biosensors into our cell migration assays that will enable collection of real-time cell signaling data as the cells migrate. We hypothesize that the activation of cell signaling pathways detectable by the biosensors correlates with the cell migration dynamics described by our current models. Collection of these data may enable expansion of our cell migration simulator in ways that improve its ability to simulate cell migration dynamics by 1) adding new parameters to our model that incorporate signaling dynamics, and 2) to describe and quantify the relationship between cell signaling activity and existing model parameters. Given the high large public investment into therapeutic agents designed to disrupt cell signaling pathways, this new line of inquiry?made possible by the probes developed by Dr. Laurie Parker through the IMAT program?may accelerate our Center's ability to use our fundamental knowledge of cell migration dynamics to build a cell migration simulator that enables optimization of existing therapeutic agents and identifies compelling new therapeutic targets and strategies.