Nanoreporter PET predicts the efficacy of anti-cancer nanotherapy

Nanoparticle drug formulations are currently used as cancer treatment but the response in patients is highly variable. Here, the authors developed a Zirconium-89 nanoreporter able to predict using PET, therapeutic accumulation and efficacy of anti-cancer nanoparticle drug formulations when co-inject...

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Autores principales:	Carlos Pérez-Medina, Dalya Abdel-Atti, Jun Tang, Yiming Zhao, Zahi A. Fayad, Jason S. Lewis, Willem J. M. Mulder, Thomas Reiner
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2016
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/bedddcd02a6645ff8aef2ea1449bb3ee
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spelling	oai:doaj.org-article:bedddcd02a6645ff8aef2ea1449bb3ee2021-12-02T14:40:16ZNanoreporter PET predicts the efficacy of anti-cancer nanotherapy10.1038/ncomms118382041-1723https://doaj.org/article/bedddcd02a6645ff8aef2ea1449bb3ee2016-06-01T00:00:00Zhttps://doi.org/10.1038/ncomms11838https://doaj.org/toc/2041-1723Nanoparticle drug formulations are currently used as cancer treatment but the response in patients is highly variable. Here, the authors developed a Zirconium-89 nanoreporter able to predict using PET, therapeutic accumulation and efficacy of anti-cancer nanoparticle drug formulations when co-injected in a murine breast cancer model.Carlos Pérez-MedinaDalya Abdel-AttiJun TangYiming ZhaoZahi A. FayadJason S. LewisWillem J. M. MulderThomas ReinerNature PortfolioarticleScienceQENNature Communications, Vol 7, Iss 1, Pp 1-8 (2016)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Carlos Pérez-Medina Dalya Abdel-Atti Jun Tang Yiming Zhao Zahi A. Fayad Jason S. Lewis Willem J. M. Mulder Thomas Reiner Nanoreporter PET predicts the efficacy of anti-cancer nanotherapy
description	Nanoparticle drug formulations are currently used as cancer treatment but the response in patients is highly variable. Here, the authors developed a Zirconium-89 nanoreporter able to predict using PET, therapeutic accumulation and efficacy of anti-cancer nanoparticle drug formulations when co-injected in a murine breast cancer model.
format	article
author	Carlos Pérez-Medina Dalya Abdel-Atti Jun Tang Yiming Zhao Zahi A. Fayad Jason S. Lewis Willem J. M. Mulder Thomas Reiner
author_facet	Carlos Pérez-Medina Dalya Abdel-Atti Jun Tang Yiming Zhao Zahi A. Fayad Jason S. Lewis Willem J. M. Mulder Thomas Reiner
author_sort	Carlos Pérez-Medina
title	Nanoreporter PET predicts the efficacy of anti-cancer nanotherapy
title_short	Nanoreporter PET predicts the efficacy of anti-cancer nanotherapy
title_full	Nanoreporter PET predicts the efficacy of anti-cancer nanotherapy
title_fullStr	Nanoreporter PET predicts the efficacy of anti-cancer nanotherapy
title_full_unstemmed	Nanoreporter PET predicts the efficacy of anti-cancer nanotherapy
title_sort	nanoreporter pet predicts the efficacy of anti-cancer nanotherapy
publisher	Nature Portfolio
publishDate	2016
url	https://doaj.org/article/bedddcd02a6645ff8aef2ea1449bb3ee
work_keys_str_mv	AT carlosperezmedina nanoreporterpetpredictstheefficacyofanticancernanotherapy AT dalyaabdelatti nanoreporterpetpredictstheefficacyofanticancernanotherapy AT juntang nanoreporterpetpredictstheefficacyofanticancernanotherapy AT yimingzhao nanoreporterpetpredictstheefficacyofanticancernanotherapy AT zahiafayad nanoreporterpetpredictstheefficacyofanticancernanotherapy AT jasonslewis nanoreporterpetpredictstheefficacyofanticancernanotherapy AT willemjmmulder nanoreporterpetpredictstheefficacyofanticancernanotherapy AT thomasreiner nanoreporterpetpredictstheefficacyofanticancernanotherapy
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Nanoreporter PET predicts the efficacy of anti-cancer nanotherapy

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