Model mimicking clinical profile of patients with ovarian cancer @ Yale School of Medicine
Reporter: Aviva Lev-Ari, PhD, RN
Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
1Department of Obstetrics, Gynecology and Reproductive Sciences, Reproductive Immunology Unit, Yale University School of Medicine, 2NatureMost Laboratories, 3Bruker Preclinical Imaging
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http://www.jove.com/video/51815/murine-model-for-non-invasive-imaging-to-detect-monitor-ovarian
Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Natalia J. Sumi, 1 Eydis Lima, 1 John Pizzonia, 2 Sean P. Orton, 3 Vinicius Craveiro, 1 Wonduk Joo, 1Jennie C. Holmberg, 1 Marta Gurrea, 1 Yang Yang-Hartwich, 1 Ayesha Alvero, 1 and Gil Mor 1
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Abstract
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.
Keywords: Cancer Biology, Issue 93, ovarian cancer, recurrence, in vivo imaging, tumor burden, cancer stem cells, chemotherapy
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SOURCE
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4353409/
Not actually very exciting. People have been doing this for the past eight years. Second they do not truly have a representative model of ovarian cancer since they are not measuring either the ascitic disease or small nodular disease. They only correlate with gross nodules and not representative of total disease. Third their variability is too great and imaging this way can be very expensive not to mention it all depends on being able to transfect mCherry into a cell line, which is extremely difficult if not impossible for some cell lines or primary tumors. Fourth this is an immunocompromised model and people have already developed immunocompetent models, therefore they should be thinking more on this line of thought. It is very difficult to interpret results of immunotherapies in immunocompromised xenograft studies.
Correspondence to: Ayesha Alvero at ude.elay@orevla.ahseya
I am suggesting that you will send an e-mail with the four point that you made above