Scoring drug efficacy by integrating drug-induced protein-protein interactions into cellular phenotypic information.
TL;DR
FRET-HCI enables discrimination of on-target drug effects from non-selective cytotoxicity, which not only reduces false positives inherent in image-based approaches but also provides a framework for ranking targeted drugs according to their on-target efficacy.
Abstract
Precision oncology aims to match cancer patients with the most effective therapeutic drugs. Although cancer genomics has been widely applied, its low matching rate limits its clinical value. Image-based functional precision oncology, which directly characterizes the responses of patient-derived cells to drugs, is expected to achieve higher matching rates. However, acquiring only phenotypic information from images cannot distinguish specific target engagement from non-selective cytotoxicity, which usually leads to some false-positive results. In this study, using live-cell FRET microscopy, we can simultaneously capture drug-induced modulation of target-associated protein-protein interactions (PPIs) and cellular phenotypic information from living cells in a single step. Then we established a drug efficacy scoring method that integrates drug-induced modulation of target-associated PPIs into cellular phenotypic information (FRET-HCI). FRET-HCI enables discrimination of on-target drug effects from non-selective cytotoxicity, which not only reduces false positives inherent in image-based approaches but also provides a framework for ranking targeted drugs according to their on-target efficacy.