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Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Epithelial ovarian cancer is the most lethal gynecologic malignancy in the United States. Although patients initially respond to the current standard of care consisting of surgical debulking and combination chemotherapy consisting of platinum and taxane compounds, almost 90% of patients recur within...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MyJove Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4353409/ https://www.ncbi.nlm.nih.gov/pubmed/25407815 http://dx.doi.org/10.3791/51815 |
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author | Sumi, Natalia J. Lima, Eydis Pizzonia, John Orton, Sean P. Craveiro, Vinicius Joo, Wonduk Holmberg, Jennie C. Gurrea, Marta Yang-Hartwich, Yang Alvero, Ayesha Mor, Gil |
author_facet | Sumi, Natalia J. Lima, Eydis Pizzonia, John Orton, Sean P. Craveiro, Vinicius Joo, Wonduk Holmberg, Jennie C. Gurrea, Marta Yang-Hartwich, Yang Alvero, Ayesha Mor, Gil |
author_sort | Sumi, Natalia J. |
collection | PubMed |
description | Epithelial ovarian cancer is the most lethal gynecologic malignancy in the United States. Although patients initially respond to the current standard of care consisting of surgical debulking and combination chemotherapy consisting of platinum and taxane compounds, almost 90% of patients recur within a few years. In these patients the development of chemoresistant disease limits the efficacy of currently available chemotherapy agents and therefore contributes to the high mortality. To discover novel therapy options that can target recurrent disease, appropriate animal models that closely mimic the clinical profile of patients with recurrent ovarian cancer are required. The challenge in monitoring intra-peritoneal (i.p.) disease limits the use of i.p. models and thus most xenografts are established subcutaneously. We have developed a sensitive optical imaging platform that allows the detection and anatomical location of i.p. tumor mass. The platform includes the use of optical reporters that extend from the visible light range to near infrared, which in combination with 2-dimensional X-ray co-registration can provide anatomical location of molecular signals. Detection is significantly improved by the use of a rotation system that drives the animal to multiple angular positions for 360 degree imaging, allowing the identification of tumors that are not visible in single orientation. This platform provides a unique model to non-invasively monitor tumor growth and evaluate the efficacy of new therapies for the prevention or treatment of recurrent ovarian cancer. |
format | Online Article Text |
id | pubmed-4353409 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | MyJove Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-43534092015-03-12 Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence Sumi, Natalia J. Lima, Eydis Pizzonia, John Orton, Sean P. Craveiro, Vinicius Joo, Wonduk Holmberg, Jennie C. Gurrea, Marta Yang-Hartwich, Yang Alvero, Ayesha Mor, Gil J Vis Exp Cancer Biology Epithelial ovarian cancer is the most lethal gynecologic malignancy in the United States. Although patients initially respond to the current standard of care consisting of surgical debulking and combination chemotherapy consisting of platinum and taxane compounds, almost 90% of patients recur within a few years. In these patients the development of chemoresistant disease limits the efficacy of currently available chemotherapy agents and therefore contributes to the high mortality. To discover novel therapy options that can target recurrent disease, appropriate animal models that closely mimic the clinical profile of patients with recurrent ovarian cancer are required. The challenge in monitoring intra-peritoneal (i.p.) disease limits the use of i.p. models and thus most xenografts are established subcutaneously. We have developed a sensitive optical imaging platform that allows the detection and anatomical location of i.p. tumor mass. The platform includes the use of optical reporters that extend from the visible light range to near infrared, which in combination with 2-dimensional X-ray co-registration can provide anatomical location of molecular signals. Detection is significantly improved by the use of a rotation system that drives the animal to multiple angular positions for 360 degree imaging, allowing the identification of tumors that are not visible in single orientation. This platform provides a unique model to non-invasively monitor tumor growth and evaluate the efficacy of new therapies for the prevention or treatment of recurrent ovarian cancer. MyJove Corporation 2014-11-02 /pmc/articles/PMC4353409/ /pubmed/25407815 http://dx.doi.org/10.3791/51815 Text en Copyright © 2014, Journal of Visualized Experiments http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visithttp://creativecommons.org/licenses/by-nc-nd/3.0/ |
spellingShingle | Cancer Biology Sumi, Natalia J. Lima, Eydis Pizzonia, John Orton, Sean P. Craveiro, Vinicius Joo, Wonduk Holmberg, Jennie C. Gurrea, Marta Yang-Hartwich, Yang Alvero, Ayesha Mor, Gil Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence |
title | Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence |
title_full | Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence |
title_fullStr | Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence |
title_full_unstemmed | Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence |
title_short | Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence |
title_sort | murine model for non-invasive imaging to detect and monitor ovarian cancer recurrence |
topic | Cancer Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4353409/ https://www.ncbi.nlm.nih.gov/pubmed/25407815 http://dx.doi.org/10.3791/51815 |
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