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Mapping lung cancer epithelial-mesenchymal transition states and trajectories with single-cell resolution

Author

Listed:
  • Loukia G. Karacosta

    (Stanford University
    Stanford University)

  • Benedict Anchang

    (Stanford University
    Stanford University)

  • Nikolaos Ignatiadis

    (Stanford University)

  • Samuel C. Kimmey

    (Stanford University)

  • Jalen A. Benson

    (Stanford University)

  • Joseph B. Shrager

    (Stanford University)

  • Robert Tibshirani

    (Stanford University
    Stanford University)

  • Sean C. Bendall

    (Stanford University)

  • Sylvia K. Plevritis

    (Stanford University
    Stanford University)

Abstract

Elucidating the spectrum of epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) states in clinical samples promises insights on cancer progression and drug resistance. Using mass cytometry time-course analysis, we resolve lung cancer EMT states through TGFβ-treatment and identify, through TGFβ-withdrawal, a distinct MET state. We demonstrate significant differences between EMT and MET trajectories using a computational tool (TRACER) for reconstructing trajectories between cell states. In addition, we construct a lung cancer reference map of EMT and MET states referred to as the EMT-MET PHENOtypic STAte MaP (PHENOSTAMP). Using a neural net algorithm, we project clinical samples onto the EMT-MET PHENOSTAMP to characterize their phenotypic profile with single-cell resolution in terms of our in vitro EMT-MET analysis. In summary, we provide a framework to phenotypically characterize clinical samples in the context of in vitro EMT-MET findings which could help assess clinical relevance of EMT in cancer in future studies.

Suggested Citation

  • Loukia G. Karacosta & Benedict Anchang & Nikolaos Ignatiadis & Samuel C. Kimmey & Jalen A. Benson & Joseph B. Shrager & Robert Tibshirani & Sean C. Bendall & Sylvia K. Plevritis, 2019. "Mapping lung cancer epithelial-mesenchymal transition states and trajectories with single-cell resolution," Nature Communications, Nature, vol. 10(1), pages 1-15, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-13441-6
    DOI: 10.1038/s41467-019-13441-6
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    Cited by:

    1. Guidantonio Malagoli Tagliazucchi & Anna J. Wiecek & Eloise Withnell & Maria Secrier, 2023. "Genomic and microenvironmental heterogeneity shaping epithelial-to-mesenchymal trajectories in cancer," Nature Communications, Nature, vol. 14(1), pages 1-20, December.

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