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Early stratification of radiotherapy response by activatable inflammation magnetic resonance imaging
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 re...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295999/ https://www.ncbi.nlm.nih.gov/pubmed/32541769 http://dx.doi.org/10.1038/s41467-020-16771-y |
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author | Zhou, Zijian Deng, Hongzhang Yang, Weijing Wang, Zhantong Lin, Lisen Munasinghe, Jeeva Jacobson, Orit Liu, Yijing Tang, Longguang Ni, Qianqian Kang, Fei Liu, Yuan Niu, Gang Bai, Ruiliang Qian, Chunqi Song, Jibin Chen, Xiaoyuan |
author_facet | Zhou, Zijian Deng, Hongzhang Yang, Weijing Wang, Zhantong Lin, Lisen Munasinghe, Jeeva Jacobson, Orit Liu, Yijing Tang, Longguang Ni, Qianqian Kang, Fei Liu, Yuan Niu, Gang Bai, Ruiliang Qian, Chunqi Song, Jibin Chen, Xiaoyuan |
author_sort | Zhou, Zijian |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7295999 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-72959992020-06-19 Early stratification of radiotherapy response by activatable inflammation magnetic resonance imaging Zhou, Zijian Deng, Hongzhang Yang, Weijing Wang, Zhantong Lin, Lisen Munasinghe, Jeeva Jacobson, Orit Liu, Yijing Tang, Longguang Ni, Qianqian Kang, Fei Liu, Yuan Niu, Gang Bai, Ruiliang Qian, Chunqi Song, Jibin Chen, Xiaoyuan Nat Commun Article 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. Nature Publishing Group UK 2020-06-15 /pmc/articles/PMC7295999/ /pubmed/32541769 http://dx.doi.org/10.1038/s41467-020-16771-y Text en © This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Zhou, Zijian Deng, Hongzhang Yang, Weijing Wang, Zhantong Lin, Lisen Munasinghe, Jeeva Jacobson, Orit Liu, Yijing Tang, Longguang Ni, Qianqian Kang, Fei Liu, Yuan Niu, Gang Bai, Ruiliang Qian, Chunqi Song, Jibin Chen, Xiaoyuan Early stratification of radiotherapy response by activatable inflammation magnetic resonance imaging |
title | Early stratification of radiotherapy response by activatable inflammation magnetic resonance imaging |
title_full | Early stratification of radiotherapy response by activatable inflammation magnetic resonance imaging |
title_fullStr | Early stratification of radiotherapy response by activatable inflammation magnetic resonance imaging |
title_full_unstemmed | Early stratification of radiotherapy response by activatable inflammation magnetic resonance imaging |
title_short | Early stratification of radiotherapy response by activatable inflammation magnetic resonance imaging |
title_sort | early stratification of radiotherapy response by activatable inflammation magnetic resonance imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295999/ https://www.ncbi.nlm.nih.gov/pubmed/32541769 http://dx.doi.org/10.1038/s41467-020-16771-y |
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