An orthotopic prostate cancer model for new treatment development using syngeneic or patient‐derived tumors
Bibliographic record
Abstract
BACKGROUND: There are limited preclinical orthotopic prostate cancer models due to the technical complexity of surgical engraftment and tracking the tumor growth in the mouse prostate gland. Orthotopic xenografts recapitulate the tumor microenvironment, tumor stromal interactions, and clinical behavior to a greater extent than xenografts grown at subcutaneous or intramuscular sites. METHODS: This study describes a novel micro-surgical technique for orthotopically implanting intact tumors pieces from cell line derived (transgenic adenocarcinoma mouse prostate [TRAMP]-C2) or patient derived (neuroendocrine prostate cancer [NEPC]) tumors in the mouse prostate gland and monitoring tumor growth using magnetic resonance (MR) imaging. RESULTS: The TRAMP-C2 tumors grew rapidly to a predetermined endpoint size of 10 mm within 3 weeks, whereas the NEPC tumors grew at a slower rate over 7 weeks. The tumors were readily detected by MR and confidently identified when they were approximately 2-3 mm in size. The tumors were less well-defined on CT. The TRAMP-C2 tumors were characterized by amorphous sheets of poorly differentiated cells similar to a high-grade prostatic adenocarcinoma and frequent macroscopic peritoneal and lymph node metastases. In contrast, the NEPC's displayed a neuroendocrine morphology with polygonal cells arranged in nests and solid sheets and high count. There was a local invasion of the bladder and other adjacent tissues but no identifiable metastases. The TRAMP-C2 tumors were more hypoxic than the NEPC tumors. CONCLUSIONS: This novel preclinical orthotopic prostate cancer mouse model is suitable for either syngeneic or patient derived tumors and will be effective in developing and advancing the current selection of treatments for patients with prostate cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".