Increasing evidence has demonstrated that the dynamical behaviors of kinase signaling, i.e., kinetic patterns of activation/deactivation process, can dictate the cells' responses to different perturbations. Understanding such dynamics can help to predict cell fates, such as live/dead outcomes of drug treatments. However, this task requires resolving single-cell kinase signaling dynamics in the context of cellular phenotypes, which is technologically challenging. Although genetically encoded reporting systems can address some of the needs, its implementation is restricted to easily transfectable cell lines, thereby limiting its translational impacts. To overcome those challenges, our group has developed a chemical method for studying kinase signaling activities in living single cells, using cyclic peptide-based imaging probes. In this MIRA proposal, we seek to expand the chemical toolkit to include multicyclic peptide-based affinity tags and develop a repertoire of highly specific imaging probes (Project 1a). We will also explore chemical strategies to devise a universal probe delivery tag (Project 1b). By combining these tools with other well-established single-cell technologies and multivariate analysis methods, we plan to address two outstanding biological questions: How do the unique kinetic features of protein kinase signaling activities link to phenotypical heterogeneity (Project 2)? How does diverse kinase signaling dynamics orchestrate cellular responses to external perturbations, such as live/dead outcomes of targeted kinase inhibitors (Project 3)? To answer those questions, we performed preliminary studies focusing on AKT signaling using a human glioblastoma cell line. We found that inhibiting AKT or its upstream signaling protein (EGFR) can both significantly change the kinetic features of AKT signaling. We also demonstrated that a neural network algorithm could predict whether a cell can survive AKT inhibition, using the kinetic patterns of AKT signaling profile as the input. Based on our data, we propose two hypotheses: First, the pattern of kinase signaling kinetics is shaped by the abundance and activities of upstream signaling proteins. Second, early responses in kinase signaling govern therapeutic outcomes of targeted kinase inhibitors. In projects 2&3, we will test those hypotheses by studying kinase signaling dynamics in a panel of cell lines, with and without external perturbations. We will initiate the studies with a focus on AKT signaling, and as new imaging probes from Project 1 become available, we will expand our work to include other signaling modules. Successful execution of the proposed research will provide a suite of novel chemical probes and enabling technologies for interrogating kinase signaling dynamics at single-cell resolution. It will also generate insights into how such dynamics connects to phenotypical heterogeneity and governs specific cellular responses.
Protein kinase signaling dynamics is highly heterogeneous in diseases such as cancer, but the biological origin and implications of such heterogeneity remain elusive. We plan to develop novel imaging probes and analytical methods for studying protein kinase signaling dynamics at single-cell resolution. Our results will help to understand the regulatory mechanisms that shape the kinetic patterns of protein kinase signaling activities and inform about therapeutic outcomes.
