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Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response

Author

Listed:
  • Rohit Arora

    (University of Calgary)

  • Christian Cao

    (University of Calgary
    University of Toronto)

  • Mehul Kumar

    (University of Calgary
    University of Calgary)

  • Sarthak Sinha

    (University of Calgary)

  • Ayan Chanda

    (University of Calgary
    University of Calgary)

  • Reid McNeil

    (University of Calgary
    University of Calgary)

  • Divya Samuel

    (University of Calgary
    University of Calgary)

  • Rahul K. Arora

    (University of Calgary
    University of Oxford)

  • T. Wayne Matthews

    (University of Calgary
    University of Calgary)

  • Shamir Chandarana

    (University of Calgary
    University of Calgary)

  • Robert Hart

    (University of Calgary
    University of Calgary)

  • Joseph C. Dort

    (University of Calgary
    University of Calgary
    University of Calgary
    University of Calgary)

  • Jeff Biernaskie

    (University of Calgary
    University of Calgary
    University of Calgary
    University of Calgary)

  • Paola Neri

    (University of Calgary
    University of Calgary)

  • Martin D. Hyrcza

    (University of Calgary
    University of Calgary)

  • Pinaki Bose

    (University of Calgary
    University of Calgary
    University of Oxford
    University of Calgary)

Abstract

The spatial organization of the tumor microenvironment has a profound impact on biology and therapy response. Here, we perform an integrative single-cell and spatial transcriptomic analysis on HPV-negative oral squamous cell carcinoma (OSCC) to comprehensively characterize malignant cells in tumor core (TC) and leading edge (LE) transcriptional architectures. We show that the TC and LE are characterized by unique transcriptional profiles, neighboring cellular compositions, and ligand-receptor interactions. We demonstrate that the gene expression profile associated with the LE is conserved across different cancers while the TC is tissue specific, highlighting common mechanisms underlying tumor progression and invasion. Additionally, we find our LE gene signature is associated with worse clinical outcomes while TC gene signature is associated with improved prognosis across multiple cancer types. Finally, using an in silico modeling approach, we describe spatially-regulated patterns of cell development in OSCC that are predictably associated with drug response. Our work provides pan-cancer insights into TC and LE biology and interactive spatial atlases ( http://www.pboselab.ca/spatial_OSCC/ ; http://www.pboselab.ca/dynamo_OSCC/ ) that can be foundational for developing novel targeted therapies.

Suggested Citation

  • Rohit Arora & Christian Cao & Mehul Kumar & Sarthak Sinha & Ayan Chanda & Reid McNeil & Divya Samuel & Rahul K. Arora & T. Wayne Matthews & Shamir Chandarana & Robert Hart & Joseph C. Dort & Jeff Bier, 2023. "Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40271-4
    DOI: 10.1038/s41467-023-40271-4
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    Cited by:

    1. Kaichen Xu & Yan Lu & Suyang Hou & Kainan Liu & Yihang Du & Mengqian Huang & Hao Feng & Hao Wu & Xiaobo Sun, 2024. "Detecting anomalous anatomic regions in spatial transcriptomics with STANDS," Nature Communications, Nature, vol. 15(1), pages 1-23, December.
    2. Young Min Park & De-Chen Lin, 2023. "Moving closer towards a comprehensive view of tumor biology and microarchitecture using spatial transcriptomics," Nature Communications, Nature, vol. 14(1), pages 1-3, December.

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