592 ULTRASOUND-GUIDED INTRAMURAL INOCULATION OF ORTHOTOPIC BLADDER CANCER XENOGRAFTS
Bibliographic record
Abstract
You have accessJournal of UrologyBladder Cancer: Basic Research (I)1 Apr 2013592 ULTRASOUND-GUIDED INTRAMURAL INOCULATION OF ORTHOTOPIC BLADDER CANCER XENOGRAFTS Wolfgang Jaeger, Igor Moskalev, Tetsutaro Hayashi, Shannon Awrey, Alan I. So, Kaixin Zhang, Ladan Fazli, Estelle Li, Dirk Lange, Joachim W. Thueroff, and Peter C. Black Wolfgang JaegerWolfgang Jaeger Vancouver, Canada More articles by this author , Igor MoskalevIgor Moskalev Vancouver, Canada More articles by this author , Tetsutaro HayashiTetsutaro Hayashi Vancouver, Canada More articles by this author , Shannon AwreyShannon Awrey Vancouver, Canada More articles by this author , Alan I. SoAlan I. So Vancouver, Canada More articles by this author , Kaixin ZhangKaixin Zhang Vancouver, Canada More articles by this author , Ladan FazliLadan Fazli Vancouver, Canada More articles by this author , Estelle LiEstelle Li Vancouver, Canada More articles by this author , Dirk LangeDirk Lange Vancouver, Canada More articles by this author , Joachim W. ThueroffJoachim W. Thueroff Mainz, Germany More articles by this author , and Peter C. BlackPeter C. Black Vancouver, Canada More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2013.02.1988AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Orthotopic bladder cancer xenografts are essential for testing the antineoplastic effect of novel therapies or molecular manipulations of cell lines in vivo. Current xenografts rely on tumor cell inoculation by either intravesical instillation or direct injection into the bladder wall. Intravesical instillation is limited by the lack of cell lines that are tumorigenic when delivered in this manner. The invasive model inflicts morbidity on the mice by the need for laparotomy and mobilization of the bladder. Furthermore this surgical approach is complex and time-consuming. We have therefore developed a novel and rapid technique for inoculating cancer cells into the bladder wall by ultrasound-guided percutaneous injection. METHODS Three bladder cancer cell lines (UM-UC1 luc, UM-UC3 luc and UM-UC13 luc) were inoculated into 50 athymic nude mice by high-precision percutaneous injection under ultrasound guidance (VisualSonics Vevo 770). PBS was first injected between the muscle wall and the mucosa to separate these layers, and the cells were then injected into this space. Bioluminescence and ultrasound were used to monitor tumor growth. Contrast-enhanced ultrasound (microbubbles) was used to study changes in UM-UC13 tumor perfusion with systemic gemcitabine/cisplatin treatment. To demonstrate proof of principle that therapeutic agents can be injected into established xenografts under ultrasound guidance, oncolytic virus (VSV) was injected into UM-UC3 tumors. Xenograft tissue was harvested for immunohistochemistry after 23-37 days. RESULTS Percutaneous injection of tumor cells into the bladder wall was performed efficiently (mean time: 5.7min) and without complications or mortality in all 50 animals. Ultrasound and bioluminescence imaging confirmed presence of tumor in the anterior bladder wall in all animals on day 3 after inoculation. The average tumor volumes increased steadily to an end volume of 288.7ml (+/− 60.1), 78.3ml (+/− 13.4) and 394.4ml (+/− 72.4) for UM-UC3 luc, UM-UC13 luc and UM-UC1 luc, respectively. Immunohistochemical staining for VSV-G demonstrated virus uptake in all UM-UC3 luc tumors after intratumoral injection. The UM-UC13 luc tumors showed a marked decrease in size (26.5ml vs. 153.9ml) and microbubble perfusion in response to chemotherapy. CONCLUSIONS We have developed a safe and rapid method for creating orthotopic bladder cancer xenograft in a novel, minimally invasive fashion. In our hands this has replaced the traditional model requiring laparotomy, which is less time efficient and is associated with greater morbidity for the mice. © 2013 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 189Issue 4SApril 2013Page: e242 Advertisement Copyright & Permissions© 2013 by American Urological Association Education and Research, Inc.MetricsAuthor Information Wolfgang Jaeger Vancouver, Canada More articles by this author Igor Moskalev Vancouver, Canada More articles by this author Tetsutaro Hayashi Vancouver, Canada More articles by this author Shannon Awrey Vancouver, Canada More articles by this author Alan I. So Vancouver, Canada More articles by this author Kaixin Zhang Vancouver, Canada More articles by this author Ladan Fazli Vancouver, Canada More articles by this author Estelle Li Vancouver, Canada More articles by this author Dirk Lange Vancouver, Canada More articles by this author Joachim W. Thueroff Mainz, Germany More articles by this author Peter C. Black Vancouver, Canada More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.015 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".