Image-Based Phenotypic Profiling Enables Rapid and Accurate Assessment of EGFR-Activating Mutations in Tissues from Lung Cancer Patients

Determining mutations in the kinase domain of the epidermal growth factor receptor (EGFR) is critical for the effectiveness of EGFR tyrosine kinase inhibitors (TKIs) in lung cancer. Yet, DNA-based sequencing analysis of tumor samples is time-consuming and only provides gene mutation information on EGFR, making it challenging to design effective EGFR-TKI therapeutic strategies. Here, we present a new image-based method involving the rational design of a quenched probe based on EGFR-TKI to identify mutant proteins, which permits specific and "no-wash" real-time imaging of EGFR in living cells only upon covalent targeting of the EGFR kinase. We also show that the probe enables distinguishing EGFR mutant tumor-bearing mice from wild-type tumor-bearing mice via fluorescence-intensity-based imaging with high signal contrast. More interestingly, the image-based phenotypic approach can be used to predict EGFR mutations in tumors from lung cancer patients with an accuracy of 94%. Notably, when immunohistochemistry analysis is integrated, an improved accuracy of 98% is achieved. These data delineate a drug-based phenotypic imaging approach for in-biopsy visualization and define functional groups of EGFR mutants that can effectively guide EGFR-TKI therapeutic decision-making besides gene mutation analysis.