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

Author

Listed:
  • George Rosenberger

    (Columbia University Irving Medical Center)

  • Wenxue Li

    (Yale University)

  • Mikko Turunen

    (Columbia University Irving Medical Center)

  • Jing He

    (Columbia University Irving Medical Center
    Regeneron Genetics Center)

  • Prem S. Subramaniam

    (Columbia University Irving Medical Center)

  • Sergey Pampou

    (Columbia University Irving Medical Center
    Columbia University Irving Medical Center)

  • Aaron T. Griffin

    (Columbia University Irving Medical Center
    Columbia University Irving Medical Center)

  • Charles Karan

    (Columbia University Irving Medical Center
    Columbia University Irving Medical Center)

  • Patrick Kerwin

    (Columbia University Irving Medical Center)

  • Diana Murray

    (Columbia University Irving Medical Center)

  • Barry Honig

    (Columbia University Irving Medical Center
    Columbia University Irving Medical Center
    Columbia University Irving Medical Center
    Columbia University)

  • Yansheng Liu

    (Yale University
    Yale University School of Medicine)

  • Andrea Califano

    (Columbia University Irving Medical Center
    Columbia University Irving Medical Center
    Columbia University Irving Medical Center
    Columbia University Irving Medical Center)

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.

Suggested Citation

  • 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 , 2024. "Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis," Nature Communications, Nature, vol. 15(1), pages 1-27, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47957-3
    DOI: 10.1038/s41467-024-47957-3
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