Abstract Cell migration is the major driver of invasion and metastasis during cancer progression. For cells to migrate, they need to integrate the force-generating and self-assembly dynamics of the actin-myosin cytoskeletal machinery to mechanically couple to the external environment through adhesion molecules such as integrins. Starting with our existing “motor-clutch” model for cell traction forces in compliant microenvironments, we have developed through our PSOC a whole cell migration model, which we call a “cell migration simulator.” However, it is not clear how the mechanical parameters that dictate cell adhesion and migration in our cell migration simulator are influenced by upstream signaling pathways. While standard methods of western blotting and immunohistochemistry are widely used, they do not provide dynamic spatial-temporal information within living cells. Similarly, more advanced methods, such as phosphoproteomics, do not provide dynamic information and generally provide only population averages rather than single cell information. Through IMAT funding, Dr. Parker has now developed novel fluorophore-tagged tyrosine kinase substrate peptides that exhibit changes in fluorescence lifetime upon phosphorylation and interaction with tyrosine phosphopeptide- binding SH2 domains. Thus, these probes enable detection of kinase signaling activity in living cells in space and time via fluorescence lifetime imaging microscopy (FLIM). Here we propose to validate and further test these probes using breast cancer cells that Dr. Parker has previously reported, and then extend their application to glioblastoma and pancreatic cancer cells that are the focus of our PSOC. By extending to these other cell types, we will be able to assess the robustness of the IMAT technology, and obtain the dynamic spatial-temporal data that we will need to extend our model to include inputs from key signaling pathways mediated by Abl, Syk, and Src. We will also go beyond standard glass dishes to test cells on deformable hydrogel surfaces of controlled Young's modulus, which will enable measurement of cell-generated traction forces and its correlation with signaling events. In both of these contexts, we will measure cell migration dynamics, cell spread area dynamics, and cell polarization dynamics, and correlate them with signaling dynamics. Finally, we will extend our assays into mouse tissue slices obtained from liver and brain, to mimic the metastatic (breast and pancreatic) and invasive (glioblastoma) tissue environments to assess feasibility of imaging in in vivo-like environments. Together, these studies will allow us to assess the robustness of the IMAT technology in the context of our PSOC goals, and provide a potentially novel methodology for quantitatively connecting key signaling pathways to our understanding of the mechanics of cell adhesion and migration in cancer.