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Presentation by Luca Gerosa at the single-cell proteomics conference: http://single-cell.net https://web.northeastern.edu/scp2019/ Playlist of all videos http://bit.ly/SCP2019-Videos See more related videos at http://bit.ly/Slavov-Videos Cancer cells treated with targeted inhibitors of oncogenic pathways can escape treatment through homeostatic adaptation of their signaling networks, a phenomenon termed ‘adaptive resistance’. Our limited ability to predict the response of signaling pathways to drug perturbations is a key obstacle to design drug strategies that can prevent adaptive resistance. Here, we use experiments and computational modeling to build predictive models of drug adaptation in colorectal, thyroid and skin cancers bearing BRAF V600E, a mutation that is present in up to 50% of these cancers and is responsible for hyper-activation of the pro-growth RAF/MEK/ERK signaling pathway. We hypothesize that adaptive resistance to targeted kinase inhibitors in these cancers is governed by their lineage-specific receptor dynamics and feedback regulation strengths. By incorporating the biochemistry of ERK signaling and the mechanisms of action of targeted drugs into an Ordinary Differential Equation model, we reproduced the adaptive response of these cancers to targeted inhibitors. To validate and extend the model, we generated time-course, single-cell data using multiplexed immunofluorescence and live-cell imaging and discovered that single-cell ERK signaling dynamics determine the adaptive drug resistance of these cancers. For more details see the bioRxiv preprint at: https://www.biorxiv.org/content/10.11...