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Novel approach for the detection of intraperitoneal micrometastasis using an ovarian cancer mouse model

Patients with epithelial ovarian cancer have the best overall survival when maximal surgical effort is accomplished. However, despite numerous technological advances, surgery still relies primarily on white-light reflectance and the surgeon’s vision. As such, micrometastases are usually missed and m...

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Autores principales: Alvero, Ayesha B., Kim, Dongin, Lima, Eydis, Sumi, Natalia J., Lee, Jung Seok, Cardenas, Carlos, Pitruzzello, Mary, Silasi, Dan-Arin, Buza, Natalia, Fahmy, Tarek, Mor, Gil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264387/
https://www.ncbi.nlm.nih.gov/pubmed/28120873
http://dx.doi.org/10.1038/srep40989
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author Alvero, Ayesha B.
Kim, Dongin
Lima, Eydis
Sumi, Natalia J.
Lee, Jung Seok
Cardenas, Carlos
Pitruzzello, Mary
Silasi, Dan-Arin
Buza, Natalia
Fahmy, Tarek
Mor, Gil
author_facet Alvero, Ayesha B.
Kim, Dongin
Lima, Eydis
Sumi, Natalia J.
Lee, Jung Seok
Cardenas, Carlos
Pitruzzello, Mary
Silasi, Dan-Arin
Buza, Natalia
Fahmy, Tarek
Mor, Gil
author_sort Alvero, Ayesha B.
collection PubMed
description Patients with epithelial ovarian cancer have the best overall survival when maximal surgical effort is accomplished. However, despite numerous technological advances, surgery still relies primarily on white-light reflectance and the surgeon’s vision. As such, micrometastases are usually missed and most patients clinically classified as a complete responder eventually recur and succumb to the disease. Our objective is to develop optical enhancers which can aid in the visualization of ovarian cancer micrometastasis. To this end we developed a nanoparticle (NP) platform, which is specifically targeted to the tumor microenvironment. Targeting is achieved by coating FDA-approved PLGA-PEG NP with the peptide sequence RGD, which binds with high affinity to αVβ3 integrins present in both the tumor-associated neovasculature and on the surface of ovarian cancer cells. Administration of the NP platform carrying fluorescent dyes to mice bearing intraperitoneal ovarian cancer allowed visualization of tumor-associated vasculature and its contrast against normal blood vessels. More importantly, we demonstrate the visualization of intraperitoneal ovarian cancer micrometastasis as small as 100 μm with optimal resolution. Finally, we demonstrate that the fluorescent dye cargo was able to penetrate intra-tumorally. Such modality could be used to allow microscopic surgical debulking to assure maximal surgical effort.
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spelling pubmed-52643872017-01-30 Novel approach for the detection of intraperitoneal micrometastasis using an ovarian cancer mouse model Alvero, Ayesha B. Kim, Dongin Lima, Eydis Sumi, Natalia J. Lee, Jung Seok Cardenas, Carlos Pitruzzello, Mary Silasi, Dan-Arin Buza, Natalia Fahmy, Tarek Mor, Gil Sci Rep Article Patients with epithelial ovarian cancer have the best overall survival when maximal surgical effort is accomplished. However, despite numerous technological advances, surgery still relies primarily on white-light reflectance and the surgeon’s vision. As such, micrometastases are usually missed and most patients clinically classified as a complete responder eventually recur and succumb to the disease. Our objective is to develop optical enhancers which can aid in the visualization of ovarian cancer micrometastasis. To this end we developed a nanoparticle (NP) platform, which is specifically targeted to the tumor microenvironment. Targeting is achieved by coating FDA-approved PLGA-PEG NP with the peptide sequence RGD, which binds with high affinity to αVβ3 integrins present in both the tumor-associated neovasculature and on the surface of ovarian cancer cells. Administration of the NP platform carrying fluorescent dyes to mice bearing intraperitoneal ovarian cancer allowed visualization of tumor-associated vasculature and its contrast against normal blood vessels. More importantly, we demonstrate the visualization of intraperitoneal ovarian cancer micrometastasis as small as 100 μm with optimal resolution. Finally, we demonstrate that the fluorescent dye cargo was able to penetrate intra-tumorally. Such modality could be used to allow microscopic surgical debulking to assure maximal surgical effort. Nature Publishing Group 2017-01-25 /pmc/articles/PMC5264387/ /pubmed/28120873 http://dx.doi.org/10.1038/srep40989 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Alvero, Ayesha B.
Kim, Dongin
Lima, Eydis
Sumi, Natalia J.
Lee, Jung Seok
Cardenas, Carlos
Pitruzzello, Mary
Silasi, Dan-Arin
Buza, Natalia
Fahmy, Tarek
Mor, Gil
Novel approach for the detection of intraperitoneal micrometastasis using an ovarian cancer mouse model
title Novel approach for the detection of intraperitoneal micrometastasis using an ovarian cancer mouse model
title_full Novel approach for the detection of intraperitoneal micrometastasis using an ovarian cancer mouse model
title_fullStr Novel approach for the detection of intraperitoneal micrometastasis using an ovarian cancer mouse model
title_full_unstemmed Novel approach for the detection of intraperitoneal micrometastasis using an ovarian cancer mouse model
title_short Novel approach for the detection of intraperitoneal micrometastasis using an ovarian cancer mouse model
title_sort novel approach for the detection of intraperitoneal micrometastasis using an ovarian cancer mouse model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264387/
https://www.ncbi.nlm.nih.gov/pubmed/28120873
http://dx.doi.org/10.1038/srep40989
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