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Prediction of Anti-cancer Nanotherapy Efficacy by Imaging
Anticancer nanotherapeutics have shown mixed results in clinical trials, raising the questions of whether imaging should be used to i) identify patients with a higher likelihood of nanoparticle accumulation, ii) assess nanotherapeutic efficacy before traditional measures show response, and iii) guid...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Ivyspring International Publisher
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5646731/ https://www.ncbi.nlm.nih.gov/pubmed/29071194 http://dx.doi.org/10.7150/ntno.20564 |
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author | Miller, Miles A. Arlauckas, Sean Weissleder, Ralph |
author_facet | Miller, Miles A. Arlauckas, Sean Weissleder, Ralph |
author_sort | Miller, Miles A. |
collection | PubMed |
description | Anticancer nanotherapeutics have shown mixed results in clinical trials, raising the questions of whether imaging should be used to i) identify patients with a higher likelihood of nanoparticle accumulation, ii) assess nanotherapeutic efficacy before traditional measures show response, and iii) guide adjuvant treatments to enhance therapeutic nanoparticle (TNP) delivery. Here we review the use of a clinically approved MRI nanoparticle (ferumoxytol, FMX) to predict TNP delivery and efficacy. It is becoming increasingly apparent that nanoparticles used for imaging, despite clearly distinct physicochemical properties, often co-localize with TNP in tumors. This evidence offers the possibility of using FMX as a generic “companion diagnostic” nanoparticle for multiple TNP formulations, thus potentially allowing many of the complex regulatory and cost challenges of other approaches to be avoided. |
format | Online Article Text |
id | pubmed-5646731 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Ivyspring International Publisher |
record_format | MEDLINE/PubMed |
spelling | pubmed-56467312017-10-25 Prediction of Anti-cancer Nanotherapy Efficacy by Imaging Miller, Miles A. Arlauckas, Sean Weissleder, Ralph Nanotheranostics Review Anticancer nanotherapeutics have shown mixed results in clinical trials, raising the questions of whether imaging should be used to i) identify patients with a higher likelihood of nanoparticle accumulation, ii) assess nanotherapeutic efficacy before traditional measures show response, and iii) guide adjuvant treatments to enhance therapeutic nanoparticle (TNP) delivery. Here we review the use of a clinically approved MRI nanoparticle (ferumoxytol, FMX) to predict TNP delivery and efficacy. It is becoming increasingly apparent that nanoparticles used for imaging, despite clearly distinct physicochemical properties, often co-localize with TNP in tumors. This evidence offers the possibility of using FMX as a generic “companion diagnostic” nanoparticle for multiple TNP formulations, thus potentially allowing many of the complex regulatory and cost challenges of other approaches to be avoided. Ivyspring International Publisher 2017-07-06 /pmc/articles/PMC5646731/ /pubmed/29071194 http://dx.doi.org/10.7150/ntno.20564 Text en © Ivyspring International Publisher This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/). See http://ivyspring.com/terms for full terms and conditions. |
spellingShingle | Review Miller, Miles A. Arlauckas, Sean Weissleder, Ralph Prediction of Anti-cancer Nanotherapy Efficacy by Imaging |
title | Prediction of Anti-cancer Nanotherapy Efficacy by Imaging |
title_full | Prediction of Anti-cancer Nanotherapy Efficacy by Imaging |
title_fullStr | Prediction of Anti-cancer Nanotherapy Efficacy by Imaging |
title_full_unstemmed | Prediction of Anti-cancer Nanotherapy Efficacy by Imaging |
title_short | Prediction of Anti-cancer Nanotherapy Efficacy by Imaging |
title_sort | prediction of anti-cancer nanotherapy efficacy by imaging |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5646731/ https://www.ncbi.nlm.nih.gov/pubmed/29071194 http://dx.doi.org/10.7150/ntno.20564 |
work_keys_str_mv | AT millermilesa predictionofanticancernanotherapyefficacybyimaging AT arlauckassean predictionofanticancernanotherapyefficacybyimaging AT weisslederralph predictionofanticancernanotherapyefficacybyimaging |