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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, Xiaoyuan Chen

2020Nature Communications95 citationsDOIOpen Access PDF

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 T 1 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.

Topics & Concepts

Magnetic resonance imagingMedicineRadiation therapyInflammationAcquired immune systemOncologyInternal medicineImmunologyImmune systemRadiologyNanoplatforms for cancer theranosticsPhotoacoustic and Ultrasonic ImagingMRI in cancer diagnosis
Early stratification of radiotherapy response by activatable inflammation magnetic resonance imaging | Litcius