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

通过磷酸化蛋白质组学时间序列分析网络阐明结肠癌耐药机制

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作者:George Rosenberger #, Wenxue Li #, Mikko Turunen #, Jing He #, Prem S Subramaniam, Sergey Pampou, Aaron T Griffin, Charles Karan, Patrick Kerwin, Diana Murray, Barry Honig, Yansheng Liu, Andrea Califano

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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