Early stratification of radiotherapy response by activatable inflammation magnetic resonance imaging

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, Chunqi Qian, Jibin Song () and Xiaoyuan Chen ()
Additional contact information
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
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

Nature Communications, 2020, vol. 11, issue 1, 1-12

Abstract: 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.

Date: 2020
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DOI: 10.1038/s41467-020-16771-y

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