Abstract B02: Ultrasound evaluation of anti-angiogenic therapy on patient-derived renal cell carcinoma xenograft tumors in the chicken embryo model
Bibliographic record
Abstract
Abstract Introduction: The avian embryo patient-derived xenograft (PDX) model's use as a platform for pre-clinical drug testing is a promising application. However, conventional methods of monitoring, such as tumor-take rates, light microscopy, and histology, either do not provide sufficient detail for in-depth therapy evaluation or are reserved for end-point analysis. Ultrasound monitoring permits non-destructive longitudinal evaluation of tumor growth, progression, and angiogenesis in the chorioallantoic membrane (CAM) xenograft ex ovo model. High-frequency ultrasound was selected for its low cost, lack of ionizing radiation, and high spatial and temporal resolutions. Methods: A subset of tumor initiating cells (RCC243) was isolated from a patient-derived parental renal carcinoma cell line (RCC22). Cells were grown to confluence, pelleted, and combined with an equal volume of Matrigel. On the ninth day of embryonic development (EDD-9), the CAM surface of 8 animals was pierced, and 10µL of the cell-Matrigel mix was deposited into the opening. Half of the embryos were treated every two days with 10µL of TAK-441, a Hedgehog inhibitor with hypothesized anti-angiogenic effects. Three-dimensional anatomical (B-mode) and contrast-enhanced images were acquired using a Vevo 2100 ultrasound system (VisualSonics Inc.) equipped with a 20 MHz linear array transducer. On EDD-18, tumor volumes were assessed using the B-mode images. The CAM vasculature was then cannulated with a glass capillary needle, and a 50µL solution of Vevo MicroMarker (VisualSonics Inc.) microbubble contrast agent (2 x 109 microbubbles/mL) was injected in a pulsatile manner. Tumor blood perfusion (blood volume, velocity, and flow) was then assessed using destruction-reperfusion contrast ultrasound. Image analysis was performed within manually segmented tumor volumes. Results: Hedgehog inhibition of RCC243 tumors via TAK-441 therapy produced a significant decrease in mean tumor volume (vehicle: 187.68 ± 69.55 mm3 vs. treatment: 78.94 ± 52.35 mm3; p < 0.05) and blood flow (vehicle: 645.7 ± 261.5 mm3/min vs. treatment: 190.8 ± 133.4 mm3/min; p < 0.05). There was a non-significant trend of reduced blood volume (vehicle: 97.0 ± 64.7 mm3 vs. treatment: 33.7 ± 23.8 mm3; p = 0.12), and flow velocity (vehicle: 6.34 ± 1.07 mm/s vs. treatment: 5.52 ± 1.18 mm/s; p = 0.34) in the treated tumors. Conclusions: This proof of principal study shows that tumors implanted in an ex ovo chick CAM model can successfully be imaged using high-frequency ultrasound and quantitative measures of tumor volume, blood volume, velocity and flow can be obtained. Responses to anti-angiogenic therapy can be successfully quantified. This approach to therapy evaluation is inexpensive and permits observation of tumor-induced angiogenesis over a 9 day timeframe. Citation Format: Matthew R. Lowerison, Chantalle J. Willie, Siddika Pardhan, Nicholas E. Power, Ann F. Chambers, Hon S. Leong, James C. Lacefield. Ultrasound evaluation of anti-angiogenic therapy on patient-derived renal cell carcinoma xenograft tumors in the chicken embryo model. [abstract]. In: Proceedings of the AACR Special Conference: Tumor Angiogenesis and Vascular Normalization: Bench to Bedside to Biomarkers; Mar 5-8, 2015; Orlando, FL. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl):Abstract nr B02.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".