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Disrupting cellular memory to overcome drug resistance

Author

Listed:
  • Guillaume Harmange

    (University of Pennsylvania)

  • Raúl A. Reyes Hueros

    (University of Pennsylvania)

  • Dylan L. Schaff

    (University of Pennsylvania)

  • Benjamin Emert

    (California Institute of Technology)

  • Michael Saint-Antoine

    (University of Delaware)

  • Laura C. Kim

    (University of Pennsylvania)

  • Zijian Niu

    (University of Pennsylvania
    University of Pennsylvania)

  • Shivani Nellore

    (University of Pennsylvania
    University of Pennsylvania)

  • Mitchell E. Fane

    (Fox Chase Cancer Center)

  • Gretchen M. Alicea

    (Johns Hopkins School of Public Health)

  • Ashani T. Weeraratna

    (Johns Hopkins School of Public Health
    Johns Hopkins School of Medicine)

  • M. Celeste Simon

    (University of Pennsylvania
    University of Pennsylvania)

  • Abhyudai Singh

    (University of Delaware)

  • Sydney M. Shaffer

    (University of Pennsylvania
    University of Pennsylvania)

Abstract

Gene expression states persist for varying lengths of time at the single-cell level, a phenomenon known as gene expression memory. When cells switch states, losing memory of their prior state, this transition can occur in the absence of genetic changes. However, we lack robust methods to find regulators of memory or track state switching. Here, we develop a lineage tracing-based technique to quantify memory and identify cells that switch states. Applied to melanoma cells without therapy, we quantify long-lived fluctuations in gene expression that are predictive of later resistance to targeted therapy. We also identify the PI3K and TGF-β pathways as state switching modulators. We propose a pretreatment model, first applying a PI3K inhibitor to modulate gene expression states, then applying targeted therapy, which leads to less resistance than targeted therapy alone. Together, we present a method for finding modulators of gene expression memory and their associated cell fates.

Suggested Citation

  • Guillaume Harmange & Raúl A. Reyes Hueros & Dylan L. Schaff & Benjamin Emert & Michael Saint-Antoine & Laura C. Kim & Zijian Niu & Shivani Nellore & Mitchell E. Fane & Gretchen M. Alicea & Ashani T. W, 2023. "Disrupting cellular memory to overcome drug resistance," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41811-8
    DOI: 10.1038/s41467-023-41811-8
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    1. A. S. Eisele & M. Tarbier & A. A. Dormann & V. Pelechano & D. M. Suter, 2024. "Gene-expression memory-based prediction of cell lineages from scRNA-seq datasets," Nature Communications, Nature, vol. 15(1), pages 1-16, December.

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