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A flexible electronic strain sensor for the real-time monitoring of tumor regression
Assessing the efficacy of cancer therapeutics in mouse models is a critical step in treatment development. However, low-resolution measurement tools and small sample sizes make determining drug efficacy in vivo a difficult and time-intensive task. Here, we present a commercially scalable wearable el...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9481124/ https://www.ncbi.nlm.nih.gov/pubmed/36112679 http://dx.doi.org/10.1126/sciadv.abn6550 |
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author | Abramson, Alex Chan, Carmel T. Khan, Yasser Mermin-Bunnell, Alana Matsuhisa, Naoji Fong, Robyn Shad, Rohan Hiesinger, William Mallick, Parag Gambhir, Sanjiv Sam Bao, Zhenan |
author_facet | Abramson, Alex Chan, Carmel T. Khan, Yasser Mermin-Bunnell, Alana Matsuhisa, Naoji Fong, Robyn Shad, Rohan Hiesinger, William Mallick, Parag Gambhir, Sanjiv Sam Bao, Zhenan |
author_sort | Abramson, Alex |
collection | PubMed |
description | Assessing the efficacy of cancer therapeutics in mouse models is a critical step in treatment development. However, low-resolution measurement tools and small sample sizes make determining drug efficacy in vivo a difficult and time-intensive task. Here, we present a commercially scalable wearable electronic strain sensor that automates the in vivo testing of cancer therapeutics by continuously monitoring the micrometer-scale progression or regression of subcutaneously implanted tumors at the minute time scale. In two in vivo cancer mouse models, our sensor discerned differences in tumor volume dynamics between drug- and vehicle-treated tumors within 5 hours following therapy initiation. These short-term regression measurements were validated through histology, and caliper and bioluminescence measurements taken over weeklong treatment periods demonstrated the correlation with longer-term treatment response. We anticipate that real-time tumor regression datasets could help expedite and automate the process of screening cancer therapies in vivo. |
format | Online Article Text |
id | pubmed-9481124 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-94811242022-09-29 A flexible electronic strain sensor for the real-time monitoring of tumor regression Abramson, Alex Chan, Carmel T. Khan, Yasser Mermin-Bunnell, Alana Matsuhisa, Naoji Fong, Robyn Shad, Rohan Hiesinger, William Mallick, Parag Gambhir, Sanjiv Sam Bao, Zhenan Sci Adv Physical and Materials Sciences Assessing the efficacy of cancer therapeutics in mouse models is a critical step in treatment development. However, low-resolution measurement tools and small sample sizes make determining drug efficacy in vivo a difficult and time-intensive task. Here, we present a commercially scalable wearable electronic strain sensor that automates the in vivo testing of cancer therapeutics by continuously monitoring the micrometer-scale progression or regression of subcutaneously implanted tumors at the minute time scale. In two in vivo cancer mouse models, our sensor discerned differences in tumor volume dynamics between drug- and vehicle-treated tumors within 5 hours following therapy initiation. These short-term regression measurements were validated through histology, and caliper and bioluminescence measurements taken over weeklong treatment periods demonstrated the correlation with longer-term treatment response. We anticipate that real-time tumor regression datasets could help expedite and automate the process of screening cancer therapies in vivo. American Association for the Advancement of Science 2022-09-16 /pmc/articles/PMC9481124/ /pubmed/36112679 http://dx.doi.org/10.1126/sciadv.abn6550 Text en Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Physical and Materials Sciences Abramson, Alex Chan, Carmel T. Khan, Yasser Mermin-Bunnell, Alana Matsuhisa, Naoji Fong, Robyn Shad, Rohan Hiesinger, William Mallick, Parag Gambhir, Sanjiv Sam Bao, Zhenan A flexible electronic strain sensor for the real-time monitoring of tumor regression |
title | A flexible electronic strain sensor for the real-time monitoring of tumor regression |
title_full | A flexible electronic strain sensor for the real-time monitoring of tumor regression |
title_fullStr | A flexible electronic strain sensor for the real-time monitoring of tumor regression |
title_full_unstemmed | A flexible electronic strain sensor for the real-time monitoring of tumor regression |
title_short | A flexible electronic strain sensor for the real-time monitoring of tumor regression |
title_sort | flexible electronic strain sensor for the real-time monitoring of tumor regression |
topic | Physical and Materials Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9481124/ https://www.ncbi.nlm.nih.gov/pubmed/36112679 http://dx.doi.org/10.1126/sciadv.abn6550 |
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