Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a limited set of known driver mutations but considerable cancer cell heterogeneity. Phosphoproteomics provides a readout of aberrant signaling and has the potential to identify new targets and guide treatment decisions. Using two-step sequential phosphopeptide enrichment, we generate a comprehensive phosphoproteome and proteome of nine PDAC cell lines, encompassing more than 20,000 phosphosites on 5,763 phospho-proteins, including 316 protein kinases. By using integrative inferred kinase activity (INKA) scoring, we identify multiple (parallel) activated kinases that are subsequently matched to kinase inhibitors. Compared with high-dose single-drug treatments, INKA-tailored low-dose 3-drug combinations against multiple targets demonstrate superior efficacy against PDAC cell lines, organoid cultures, and patient-derived xenografts. Overall, this approach is particularly more effective against the aggressive mesenchymal PDAC model compared with the epithelial model in both preclinical settings and may contribute to improved treatment outcomes in PDAC patients.
Keywords: CP: Cancer; IMAC; drug combinations; kinase activity; kinases; pTyr IP; pancreatic ductal adenocarcinoma; personalized medicine; pharmacology; phosphoproteomics.
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