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Supercontinuum-tailoring multicolor imaging reveals spatiotemporal dynamics of heterogeneous tumor evolution

Author

Listed:
  • Xiujuan Gao

    (Huazhong University of Science and Technology
    Huazhong University of Science and Technology)

  • Xinyuan Huang

    (Huazhong University of Science and Technology
    Huazhong University of Science and Technology)

  • Zhongyun Chen

    (Huazhong University of Science and Technology
    Huazhong University of Science and Technology)

  • Liu Yang

    (Huazhong University of Science and Technology
    Huazhong University of Science and Technology)

  • Yifu Zhou

    (Huazhong University of Science and Technology
    Huazhong University of Science and Technology)

  • Zhenxuan Hou

    (Huazhong University of Science and Technology
    Huazhong University of Science and Technology)

  • Jie Yang

    (Huazhong University of Science and Technology
    Huazhong University of Science and Technology)

  • Shuhong Qi

    (Huazhong University of Science and Technology
    Huazhong University of Science and Technology)

  • Zheng Liu

    (Hainan University)

  • Zhihong Zhang

    (Huazhong University of Science and Technology
    Huazhong University of Science and Technology
    Hainan University
    State Key Laboratory of Digital Medical Engineering)

  • Qian Liu

    (Hainan University
    State Key Laboratory of Digital Medical Engineering)

  • Qingming Luo

    (Hainan University
    State Key Laboratory of Digital Medical Engineering)

  • Ling Fu

    (Huazhong University of Science and Technology
    Huazhong University of Science and Technology
    Hainan University
    State Key Laboratory of Digital Medical Engineering)

Abstract

Tumor heterogeneity and tumor evolution contribute to cancer treatment failure. To understand how selective pressures drive heterogeneous tumor evolution, it would be useful to image multiple important components and tumor subclones in vivo. We propose a supercontinuum-tailoring two-photon microscope (SCT-TPM) and realize simultaneous observation of nine fluorophores with a single light beam, breaking through the ‘color barrier’ of intravital two-photon fluorescence imaging. It achieves excitation multiplexing only by modulating the phase of fiber supercontinuum (SC), allowing to capture rapid events of multiple targets with maintaining precise spatial alignment. We employ SCT-TPM to visualize the spatiotemporal dynamics of heterogeneous tumor evolution under host immune surveillance, particularly the behaviors and interactions of six tumor subclones, immune cells and vascular network, and thus infer the trajectories of tumor progression and clonal competition. SCT-TPM opens up the possibility of tumor lineage tracking and mechanism exploration in living biological systems.

Suggested Citation

  • Xiujuan Gao & Xinyuan Huang & Zhongyun Chen & Liu Yang & Yifu Zhou & Zhenxuan Hou & Jie Yang & Shuhong Qi & Zheng Liu & Zhihong Zhang & Qian Liu & Qingming Luo & Ling Fu, 2024. "Supercontinuum-tailoring multicolor imaging reveals spatiotemporal dynamics of heterogeneous tumor evolution," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-53697-1
    DOI: 10.1038/s41467-024-53697-1
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    References listed on IDEAS

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    1. Doron Meshulach & Yaron Silberberg, 1998. "Coherent quantum control of two-photon transitions by a femtosecond laser pulse," Nature, Nature, vol. 396(6708), pages 239-242, November.
    2. Daniel D. Lee & H. Sebastian Seung, 1999. "Learning the parts of objects by non-negative matrix factorization," Nature, Nature, vol. 401(6755), pages 788-791, October.
    3. Alex M. Valm & Sarah Cohen & Wesley R. Legant & Justin Melunis & Uri Hershberg & Eric Wait & Andrew R. Cohen & Michael W. Davidson & Eric Betzig & Jennifer Lippincott-Schwartz, 2017. "Applying systems-level spectral imaging and analysis to reveal the organelle interactome," Nature, Nature, vol. 546(7656), pages 162-167, June.
    4. Lu Wei & Zhixing Chen & Lixue Shi & Rong Long & Andrew V. Anzalone & Luyuan Zhang & Fanghao Hu & Rafael Yuste & Virginia W. Cornish & Wei Min, 2017. "Super-multiplex vibrational imaging," Nature, Nature, vol. 544(7651), pages 465-470, April.
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