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Updated: Aug 9, 2025
Assessment of Resistance to Tyrosine Kinase Inhibitors by an Interrogation of Signal Transduction Pathways by Antibody Arrays
Published on: September 19, 2018
Network-based elucidation of colon cancer drug resistance by phosphoproteomic time-series analysis
George Rosenberger1, Wenxue Li2, Mikko Turunen1
1Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA.
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. By leveraging progress in proteomic technologies and network-based methodologies, over the past decade, we developed VESPA-an algorithm designed to elucidate mechanisms of cell response and adaptation to drug perturbations-and used it to analyze 7-point phosphoproteomic time series from colorectal cancer cells treated with clinically-relevant inhibitors and control media. Interrogation of tumor-specific enzyme/substrate interactions accurately inferred kinase and phosphatase activity, based on their inferred substrate phosphorylation state, effectively accounting for signal cross-talk and sparse phosphoproteome coverage. The analysis elucidated time-dependent signaling pathway response to each drug perturbation and, more importantly, cell adaptive response and rewiring that was experimentally confirmed by CRISPRko assays, suggesting broad applicability to cancer and other diseases.
Insights
Researchers developed VESPA, an algorithm to understand cancer drug resistance. VESPA analyzes cell signaling to reveal adaptive resistance mechanisms, aiding in the development of more effective cancer therapies.
Area of Science:
- Oncology
- Systems Biology
- Bioinformatics
Background:
- Aberrant signaling pathways drive cancer development and progression.
- Targeted therapies face challenges due to adaptive resistance mechanisms involving signaling network rewiring.
- Understanding these adaptive responses is crucial for improving cancer treatment efficacy.
Approach:
- Developed VESPA (Vesicular Exosome Signaling Pathway Analysis), a novel algorithm integrating proteomic data and network-based methodologies.
- Analyzed 7-point phosphoproteomic time-series data from colorectal cancer cells treated with targeted inhibitors.
- Utilized tumor-specific enzyme/substrate interactions to infer kinase and phosphatase activity, accounting for signal crosstalk and sparse data.
Key Points:
- VESPA accurately inferred kinase and phosphatase activity from substrate phosphorylation states.
- The algorithm elucidated time-dependent signaling pathway responses to drug perturbations.
- Identified and experimentally confirmed (via CRISPRko assays) cell adaptive rewiring mechanisms.
Conclusions:
- The study presents VESPA as a powerful tool for dissecting cell signaling dynamics and drug adaptation mechanisms.
- Findings suggest broad applicability of VESPA in cancer research and potentially other diseases.
- This approach aids in understanding and overcoming therapeutic resistance in cancer treatment.
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