Project description:Hepatocellular carcinoma (HCC) is a complex and deadly disease lacking druggable genetic mutations. The limited efficacy of systemic treatments for advanced HCC implies that novel predictive biomarkers and drug targets are urgently needed. Most HCC drugs target protein kinases and their kinase-dependent signaling networks to drive HCC progression. To identify HCC signaling networks that determine responses to kinase inhibitors (KIs), we apply a pharmacoproteomics approach integrating kinome activity in 17 HCC cell lines with their responses to 299 KIs, resulting in a comprehensive dataset of pathway-based drug response signatures. By profiling patient HCC samples, we identify signatures of clinical HCC drug responses in individual tumors. Our analyses reveal kinase networks promoting the epithelial-mesenchymal transition (EMT) and drug resistance, including a FZD2-AXL-NUAK1/2 signaling module, whose inhibition reverses the EMT and sensitizes HCC cells to drugs. Our approach identifies cancer drug targets and molecular signatures of drug response for personalized oncology.
