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A Raman Imaging Approach Using CD47 Antibody-Labeled SERS Nanoparticles for Identifying Breast Cancer and Its Potential to Guide Surgical Resection

Raman spectroscopic imaging has shown great promise for improved cancer detection and localization with the use of tumor targeting surface enhanced Raman scattering (SERS) nanoparticles. With the ultrasensitive detection and multiplexing capabilities that SERS imaging has to offer, scientists have b...

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Autores principales: Davis, Ryan M., Campbell, Jos L., Burkitt, Sean, Qiu, Zhen, Kang, Soyoung, Mehraein, Mana, Miyasato, Dominie, Salinas, Helen, Liu, Jonathan T. C., Zavaleta, Cristina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6265869/
https://www.ncbi.nlm.nih.gov/pubmed/30463284
http://dx.doi.org/10.3390/nano8110953
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author Davis, Ryan M.
Campbell, Jos L.
Burkitt, Sean
Qiu, Zhen
Kang, Soyoung
Mehraein, Mana
Miyasato, Dominie
Salinas, Helen
Liu, Jonathan T. C.
Zavaleta, Cristina
author_facet Davis, Ryan M.
Campbell, Jos L.
Burkitt, Sean
Qiu, Zhen
Kang, Soyoung
Mehraein, Mana
Miyasato, Dominie
Salinas, Helen
Liu, Jonathan T. C.
Zavaleta, Cristina
author_sort Davis, Ryan M.
collection PubMed
description Raman spectroscopic imaging has shown great promise for improved cancer detection and localization with the use of tumor targeting surface enhanced Raman scattering (SERS) nanoparticles. With the ultrasensitive detection and multiplexing capabilities that SERS imaging has to offer, scientists have been investigating several clinical applications that could benefit from this unique imaging strategy. Recently, there has been a push to develop new image-guidance tools for surgical resection to help surgeons sensitively and specifically identify tumor margins in real time. We hypothesized that SERS nanoparticles (NPs) topically applied to breast cancer resection margins have the potential to provide real-time feedback on the presence of residual cancer in the resection margins during lumpectomy. Here, we explore the ability of SERS nanoparticles conjugated with a cluster of differentiation-47 (CD47) antibody to target breast cancer. CD47 is a cell surface receptor that has recently been shown to be overexpressed on several solid tumor types. The binding potential of our CD47-labeled SERS nanoparticles was assessed using fluorescence assisted cell sorting (FACS) on seven different human breast cancer cell lines, some of which were triple negative (negative expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2)). Xenograft mouse models were also used to assess the ability of our Raman imaging system to identify tumor from normal tissue. A ratiometric imaging strategy was used to quantify specific vs. nonspecific probe binding, resulting in improved tumor-to-background ratios. FACS analysis showed that CD47-labeled SERS nanoparticles bound to seven different breast cancer cell lines at levels 12-fold to 70-fold higher than isotype control-labeled nanoparticles (p < 0.01), suggesting that our CD47-targeted nanoparticles actively bind to CD47 on breast cancer cells. In a mouse xenograft model of human breast cancer, topical application of CD47-targeted nanoparticles to excised normal and cancer tissue revealed increased binding of CD47-targeted nanoparticles on tumor relative to normal adjacent tissue. The findings of this study support further investigation and suggest that SERS nanoparticles topically applied to breast cancer could guide more complete surgical resection during lumpectomy.
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spelling pubmed-62658692018-12-06 A Raman Imaging Approach Using CD47 Antibody-Labeled SERS Nanoparticles for Identifying Breast Cancer and Its Potential to Guide Surgical Resection Davis, Ryan M. Campbell, Jos L. Burkitt, Sean Qiu, Zhen Kang, Soyoung Mehraein, Mana Miyasato, Dominie Salinas, Helen Liu, Jonathan T. C. Zavaleta, Cristina Nanomaterials (Basel) Article Raman spectroscopic imaging has shown great promise for improved cancer detection and localization with the use of tumor targeting surface enhanced Raman scattering (SERS) nanoparticles. With the ultrasensitive detection and multiplexing capabilities that SERS imaging has to offer, scientists have been investigating several clinical applications that could benefit from this unique imaging strategy. Recently, there has been a push to develop new image-guidance tools for surgical resection to help surgeons sensitively and specifically identify tumor margins in real time. We hypothesized that SERS nanoparticles (NPs) topically applied to breast cancer resection margins have the potential to provide real-time feedback on the presence of residual cancer in the resection margins during lumpectomy. Here, we explore the ability of SERS nanoparticles conjugated with a cluster of differentiation-47 (CD47) antibody to target breast cancer. CD47 is a cell surface receptor that has recently been shown to be overexpressed on several solid tumor types. The binding potential of our CD47-labeled SERS nanoparticles was assessed using fluorescence assisted cell sorting (FACS) on seven different human breast cancer cell lines, some of which were triple negative (negative expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2)). Xenograft mouse models were also used to assess the ability of our Raman imaging system to identify tumor from normal tissue. A ratiometric imaging strategy was used to quantify specific vs. nonspecific probe binding, resulting in improved tumor-to-background ratios. FACS analysis showed that CD47-labeled SERS nanoparticles bound to seven different breast cancer cell lines at levels 12-fold to 70-fold higher than isotype control-labeled nanoparticles (p < 0.01), suggesting that our CD47-targeted nanoparticles actively bind to CD47 on breast cancer cells. In a mouse xenograft model of human breast cancer, topical application of CD47-targeted nanoparticles to excised normal and cancer tissue revealed increased binding of CD47-targeted nanoparticles on tumor relative to normal adjacent tissue. The findings of this study support further investigation and suggest that SERS nanoparticles topically applied to breast cancer could guide more complete surgical resection during lumpectomy. MDPI 2018-11-20 /pmc/articles/PMC6265869/ /pubmed/30463284 http://dx.doi.org/10.3390/nano8110953 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Davis, Ryan M.
Campbell, Jos L.
Burkitt, Sean
Qiu, Zhen
Kang, Soyoung
Mehraein, Mana
Miyasato, Dominie
Salinas, Helen
Liu, Jonathan T. C.
Zavaleta, Cristina
A Raman Imaging Approach Using CD47 Antibody-Labeled SERS Nanoparticles for Identifying Breast Cancer and Its Potential to Guide Surgical Resection
title A Raman Imaging Approach Using CD47 Antibody-Labeled SERS Nanoparticles for Identifying Breast Cancer and Its Potential to Guide Surgical Resection
title_full A Raman Imaging Approach Using CD47 Antibody-Labeled SERS Nanoparticles for Identifying Breast Cancer and Its Potential to Guide Surgical Resection
title_fullStr A Raman Imaging Approach Using CD47 Antibody-Labeled SERS Nanoparticles for Identifying Breast Cancer and Its Potential to Guide Surgical Resection
title_full_unstemmed A Raman Imaging Approach Using CD47 Antibody-Labeled SERS Nanoparticles for Identifying Breast Cancer and Its Potential to Guide Surgical Resection
title_short A Raman Imaging Approach Using CD47 Antibody-Labeled SERS Nanoparticles for Identifying Breast Cancer and Its Potential to Guide Surgical Resection
title_sort raman imaging approach using cd47 antibody-labeled sers nanoparticles for identifying breast cancer and its potential to guide surgical resection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6265869/
https://www.ncbi.nlm.nih.gov/pubmed/30463284
http://dx.doi.org/10.3390/nano8110953
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