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Multi-omic single-cell snapshots reveal multiple independent trajectories to drug tolerance in a melanoma cell line

Author

Listed:
  • Yapeng Su

    (California Institute of Technology
    California Institute of Technology
    Institute for Systems Biology)

  • Melissa E. Ko

    (Stanford University School of Medicine)

  • Hanjun Cheng

    (Institute for Systems Biology)

  • Ronghui Zhu

    (California Institute of Technology)

  • Min Xue

    (California Institute of Technology
    University of California, Riverside)

  • Jessica Wang

    (California Institute of Technology)

  • Jihoon W. Lee

    (California Institute of Technology)

  • Luke Frankiw

    (California Institute of Technology)

  • Alexander Xu

    (Institute for Systems Biology)

  • Stephanie Wong

    (California Institute of Technology)

  • Lidia Robert

    (University of California, Los Angeles)

  • Kaitlyn Takata

    (California Institute of Technology)

  • Dan Yuan

    (Institute for Systems Biology)

  • Yue Lu

    (Institute for Systems Biology)

  • Sui Huang

    (Institute for Systems Biology)

  • Antoni Ribas

    (University of California, Los Angeles
    UCLA
    UCLA
    UCLA)

  • Raphael Levine

    (UCLA
    UCLA
    The Hebrew University)

  • Garry P. Nolan

    (Stanford University)

  • Wei Wei

    (Institute for Systems Biology
    UCLA
    UCLA)

  • Sylvia K. Plevritis

    (Stanford University)

  • Guideng Li

    (Chinese Academy of Medical Sciences and Peking Union Medical College
    Suzhou Institute of Systems Medicine)

  • David Baltimore

    (California Institute of Technology)

  • James R. Heath

    (California Institute of Technology
    Institute for Systems Biology
    UCLA
    UCLA)

Abstract

The determination of individual cell trajectories through a high-dimensional cell-state space is an outstanding challenge for understanding biological changes ranging from cellular differentiation to epigenetic responses of diseased cells upon drugging. We integrate experiments and theory to determine the trajectories that single BRAFV600E mutant melanoma cancer cells take between drug-naive and drug-tolerant states. Although single-cell omics tools can yield snapshots of the cell-state landscape, the determination of individual cell trajectories through that space can be confounded by stochastic cell-state switching. We assayed for a panel of signaling, phenotypic, and metabolic regulators at points across 5 days of drug treatment to uncover a cell-state landscape with two paths connecting drug-naive and drug-tolerant states. The trajectory a given cell takes depends upon the drug-naive level of a lineage-restricted transcription factor. Each trajectory exhibits unique druggable susceptibilities, thus updating the paradigm of adaptive resistance development in an isogenic cell population.

Suggested Citation

  • Yapeng Su & Melissa E. Ko & Hanjun Cheng & Ronghui Zhu & Min Xue & Jessica Wang & Jihoon W. Lee & Luke Frankiw & Alexander Xu & Stephanie Wong & Lidia Robert & Kaitlyn Takata & Dan Yuan & Yue Lu & Sui, 2020. "Multi-omic single-cell snapshots reveal multiple independent trajectories to drug tolerance in a melanoma cell line," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-15956-9
    DOI: 10.1038/s41467-020-15956-9
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