Abstract
Covalent inhibitors of the KRASG12C oncoprotein have recently been developed and are being evaluated in clinical trials. Resistance to targeted therapies is common and may limit long-term efficacy of KRAS inhibitors (KRASi). To identify pathways of adaptation to KRASi and predict drug combinations that circumvent resistance, we use mass-spectrometry-based quantitative temporal proteomics to profile the proteomic response to KRASi in pancreatic and lung cancer 2D and 3D cellular models. We quantify 10,805 proteins, representing the most comprehensive KRASi proteome (https://manciaslab.shinyapps.io/KRASi/). Our data reveal common mechanisms of acute and long-term response between KRASG12C-driven tumors. Based on these proteomic data, we identify potent combinations of KRASi with phosphatidylinositol 3-kinase (PI3K), HSP90, CDK4/6, and SHP2 inhibitors, in some instances converting a cytostatic response to KRASi monotherapy to a cytotoxic response to combination treatment. Overall, using quantitative temporal proteomics, we comprehensively characterize adaptations to KRASi and identify combinatorial regimens with potential therapeutic utility.
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