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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2022
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.
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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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