A Novel Fluorescence Imaging Platform to Predict Response to Combinatorial Tyrosine Kinase Inhibitors - PROJECT SUMMARY Deregulation of kinase function in cell signaling pathways is implicated in numerous cancers. In response, kinase inhibitors (KIs) have been developed to interact with these kinases for highly specific treatment. Though nearly 50 KIs have been FDA-approved, KI monotherapy is seldom curative, likely owing to tumor heterogeneity and acquired resistance. For example, intra-tumoral heterogeneity can result in the treatment of sensitive cell sub- populations, while simultaneously promoting the outgrowth of resistant “persister cells.” In response, effective combination therapies must be tailored to known resistance mechanisms to efficiently engage with their targets and exploit cellular vulnerabilities. However, standard drug screening tools (e.g., plasma analysis, western blot [WB]) are bulk in nature, and no established technology exists to quantify KI target engagement, concomitant with local protein expression, while assessing tumor response heterogeneity. To address these shortcomings, our group has (1) developed protocols to fluorescently label KIs (and other small molecule therapeutics) that mimic the native drug, (2) advanced a novel intracellular paired agent imaging (iPAI) platform to quantify drug target availability (DTA) with these fluorescent KIs, and (3) established and validated a highly multiplexed im- munostaining strategy utilizing DNA barcoded antibodies, enabling in situ cyclic immunofluorescence (cyCIF) imaging. In this proposal, we will combine these three complementary innovations into a fluorescence imaging platform we call TRIPODD (Therapeutic Response Imaging through Proteomics and Optical Drug Distribution and binding). Herein, we will use TRIPODD to demonstrate the capability of iPAI to predict mono- and combina- torial KI drug response and uncover drug resistance mechanisms across whole tumor specimens with single- cell resolution. To achieve this, iPAI will be expanded to three-color imaging (i.e., two-drug DTA) while cyCIF will be applied to monitor proteomic therapeutic response to gain a mechanistic understanding of clinically relevant combination therapy outcomes. Epidermal growth factor receptor mutation positive (EGFRmut+) non-small cell lung carcinoma (NSCLC), which currently lacks curative treatment, will serve as our model system. We hypoth- esize that TRIPODD—as the first technology capable of comparing drug distribution and binding (iPAI) directly to proteomic markers (cyCIF) at the cellular level—will be critical to uncovering salient mechanisms of therapeutic response and resistance in NSCLC and ultimately enable tailored therapeutic strategy optimization based on predictive algorithms. This hypothesis will be tested through the following specific aims: Aim 1: Demonstrate that TRIPODD can quantify targeted KI-monotherapy response. Aim 2: Establish TRIPODD protocols to accu- rately characterize KI-combinatorial therapy outcomes. Successful completion of this proposal will yield an opti- mized fluorescence imaging toolbox (TRIPODD) that will provide an unprecedented view of the spatial correla- tions between drug distribution/binding (iPAI) and the underlying tumor/microenvironment proteome (cyCIF), enabling mechanistic understanding of NSCLC treatment strategies.
