MP35-15 DEVELOPING A PATIENT-DERIVED XENOGRAFT MODEL USING CHICKEN EMBRYOS TO PREDICT TARGETED THERAPY TUMOR RESISTANCE IN RENAL CELL CARCINOMAS

Abstract

You have accessJournal of UrologyKidney Cancer: Basic Research III1 Apr 2014MP35-15 DEVELOPING A PATIENT-DERIVED XENOGRAFT MODEL USING CHICKEN EMBRYOS TO PREDICT TARGETED THERAPY TUMOR RESISTANCE IN RENAL CELL CARCINOMAS Clarisse R. Mazzola, Chantalle Willie, Connor MacMillan, Khurram M. Siddiqui, Michele Billia, Jonathan I. Izawa, Ann F. Chambers, James Brugarolas, Ahn Tram, Nicholas Power, and Hon S. Leong Clarisse R. MazzolaClarisse R. Mazzola More articles by this author , Chantalle WillieChantalle Willie More articles by this author , Connor MacMillanConnor MacMillan More articles by this author , Khurram M. SiddiquiKhurram M. Siddiqui More articles by this author , Michele BilliaMichele Billia More articles by this author , Jonathan I. IzawaJonathan I. Izawa More articles by this author , Ann F. ChambersAnn F. Chambers More articles by this author , James BrugarolasJames Brugarolas More articles by this author , Ahn TramAhn Tram More articles by this author , Nicholas PowerNicholas Power More articles by this author , and Hon S. LeongHon S. Leong More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2014.02.1058AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Approximately 30% of patients with metastatic renal cell carcinoma (RCC) will have primary resistance to targeted agents. The remainder will develop resistance over a longer time course. Improved ability to predict patient response prior to the initiation of treatment may improve patient outcomes. Our aim was to develop a patient-derived xenograft model to determine the sensitivity of each RCC patient’s tumor cells to a defined targeted therapy prior to the start of systemic treatment. METHODS We developed a patient−derived xenograft model using chicken embryos that enables the investigator to evaluate the interplay of tumor angiogenesis, growth, and drug sensitivities. Seven patient-derived primary RCC cell lines were implanted into the chorioallantoic membrane (CAM, N>15/cell line) to assess the effect of sunitinib on tumor take ratios. Three of these cell lines are sensitive to sunitinib (XP206, XP158, XP185) and four are resistant to sunitinib (XP127, XP121, XP258, PF22), as determined previously in murine heterotopic models. A secondary cell line that is sensitive to sunitinib (786-0) was also implanted as a control. Each cell line was prepared for xenografting by mixing cell pellets with Matrigel and 10 uL of this mix was implanted into the CAM of day-9 chicken embryos. To evaluate sunitinib sensitivities in vivo, cell lines were pre−treated overnight with 5 uM of this drug. Intravital imaging was performed to assess tumor size. Tumor microvessel density was determined by histology of resected tumors. Tumor take rates were determined 6−8 days post implantation. RESULTS Using the 786-0 cell line, tumor take rates were 82% in vehicle treated tumors compared to 46% in sunitinib treated tumors. Using the 7 patient derived RCC cell lines implanted into the CAM, tumor take rates varied amongst cell lines (Table 1). Decreased tumor take rates were observed in sunitinib-sensitive cell lines treated with sunitinib, when compared to their vehicle-treated controls. Tumor xenografts underwent extensive angiogenesis as observed by IV injection of Dextran-Alexa555 (10 kDa size). CONCLUSIONS We believe our patient-derived xenograft model could be a useful tool for drug sensitivity evaluation, enabling the investigator to potentially individualize targeted treatments to each patient with metastatic RCC prior to initiating systemic therapy. Further studies will be performed using other drugs that are used in the treatment of RCCs. Table 1: Tumor Take Rates in our Patient-Derived Cell Lines Patient-Derived Cell Line Treatment Tumor Take Rate XP206-GFP Vehicle 68.8% (11/16) XP206-GFP Sunitinib 26.3% (5/18) XP185-GFP Vehicle 64.7% (11/17) XP185-GFP Sunitinib 25.0% (5/20) XP158-tdTomato Vehicle 59.1% (13/22) XP158-tdTomato Sunitinib 28.0% (7/25) XP121-GFP Vehicle 65.0% (13/20) XP121-GFP Sunitinib 52.4% (11/21) XP127-GFP Vehicle 58.8% (20/34) XP127-GFP Sunitinib 53.6% (15/28) XP258-GFP Vehicle 63.0% (17/27) XP258-GFP Sunitinib 65.2% (15/23) PF22-GFP Vehicle 21.6% (8/37) PF22-GFP Sunitinib 24.1% (7/29) © 2014FiguresReferencesRelatedDetails Volume 191Issue 4SApril 2014Page: e376 Advertisement Copyright & Permissions© 2014MetricsAuthor Information Clarisse R. Mazzola More articles by this author Chantalle Willie More articles by this author Connor MacMillan More articles by this author Khurram M. Siddiqui More articles by this author Michele Billia More articles by this author Jonathan I. Izawa More articles by this author Ann F. Chambers More articles by this author James Brugarolas More articles by this author Ahn Tram More articles by this author Nicholas Power More articles by this author Hon S. Leong More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...