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Early stratification of radiotherapy response by activatable inflammation magnetic resonance imaging

Author

Listed:
  • Zijian Zhou

    (National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)

  • Hongzhang Deng

    (National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health
    Fuzhou University)

  • Weijing Yang

    (National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)

  • Zhantong Wang

    (National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)

  • Lisen Lin

    (Fuzhou University)

  • Jeeva Munasinghe

    (National Institutes of Health)

  • Orit Jacobson

    (National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)

  • Yijing Liu

    (National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)

  • Longguang Tang

    (National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)

  • Qianqian Ni

    (National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)

  • Fei Kang

    (National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)

  • Yuan Liu

    (National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)

  • Gang Niu

    (National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)

  • Ruiliang Bai

    (Zhejiang University)

  • Chunqi Qian

    (Michigan State University)

  • Jibin Song

    (Fuzhou University)

  • Xiaoyuan Chen

    (National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health)

Abstract

Tumor heterogeneity is one major reason for unpredictable therapeutic outcomes, while stratifying therapeutic responses at an early time may greatly benefit the better control of cancer. Here, we developed a hybrid nanovesicle to stratify radiotherapy response by activatable inflammation magnetic resonance imaging (aiMRI) approach. The high Pearson’s correlation coefficient R values are obtained from the correlations between the T1 relaxation time changes at 24–48 h and the ensuing adaptive immunity (R = 0.9831) at day 5 and the tumor inhibition ratios (R = 0.9308) at day 18 after different treatments, respectively. These results underscore the role of acute inflammatory oxidative response in bridging the innate and adaptive immunity in tumor radiotherapy. Furthermore, the aiMRI approach provides a non-invasive imaging strategy for early prediction of the therapeutic outcomes in cancer radiotherapy, which may contribute to the future of precision medicine in terms of prognostic stratification and therapeutic planning.

Suggested Citation

  • Zijian Zhou & Hongzhang Deng & Weijing Yang & Zhantong Wang & Lisen Lin & Jeeva Munasinghe & Orit Jacobson & Yijing Liu & Longguang Tang & Qianqian Ni & Fei Kang & Yuan Liu & Gang Niu & Ruiliang Bai &, 2020. "Early stratification of radiotherapy response by activatable inflammation magnetic resonance imaging," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16771-y
    DOI: 10.1038/s41467-020-16771-y
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    Cited by:

    1. Luyan Wu & Yusuke Ishigaki & Wenhui Zeng & Takashi Harimoto & Baoli Yin & Yinghan Chen & Shiyi Liao & Yongchun Liu & Yidan Sun & Xiaobo Zhang & Ying Liu & Yong Liang & Pengfei Sun & Takanori Suzuki & , 2021. "Generation of hydroxyl radical-activatable ratiometric near-infrared bimodal probes for early monitoring of tumor response to therapy," Nature Communications, Nature, vol. 12(1), pages 1-13, December.

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