Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis

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Abstract

Aberrant signaling pathway activity is a hallmark of tumorigenesis and progression, which has guided targeted inhibitor design for over 30 years. Yet, adaptive resistance mechanisms, induced by rapid, context-specific signaling network rewiring, continue to challenge therapeutic efficacy. Leveraging progress in proteomic technologies and network-based methodologies, we introduce Virtual Enrichment-based Signaling Protein-activity Analysis (VESPA)—an algorithm designed to elucidate mechanisms of cell response and adaptation to drug perturbations—and use it to analyze 7-point phosphoproteomic time series from colorectal cancer cells treated with clinically-relevant inhibitors and control media. Interrogating tumor-specific enzyme/substrate interactions accurately infers kinase and phosphatase activity, based on their substrate phosphorylation state, effectively accounting for signal crosstalk and sparse phosphoproteome coverage. The analysis elucidates time-dependent signaling pathway response to each drug perturbation and, more importantly, cell adaptive response and rewiring, experimentally confirmed by CRISPR knock-out assays, suggesting broad applicability to cancer and other diseases.

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APA

Rosenberger, G., Li, W., Turunen, M., He, J., Subramaniam, P. S., Pampou, S., … Califano, A. (2024). Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis. Nature Communications, 15(1). https://doi.org/10.1038/s41467-024-47957-3

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