Postsurgical adjuvant or metastatic renal cell carcinoma therapy models reveal potent antitumor activity of metronomic oral topotecan with pazopanib
Bibliographic record
Abstract
Renal cell carcinoma (RCC), normally considered an intrinsically chemotherapy-resistant cancer, is currently treated with targeted biologic therapies, including antiangiogenic tyrosine kinase inhibitors (TKIs), such as pazopanib. The efficacy of these agents is limited by both intrinsic and acquired resistance. Death is almost always due to advanced metastatic disease, a treatment circumstance seldom modeled in preclinical (mouse) drug testing. Similarly, therapy results using postsurgical adjuvant therapy models of microscopic disease have not been reported. Using in vivo selection and transfection of established human RCC cell lines (786-0 and SN12-PM6), we derived clonal luciferase-expressing variants capable of spontaneous metastasis from an orthotopic primary tumor to organs typical of clinical RCC, including bone, lungs, and brain. The bioluminescence and consistent metastatic spread of von Hippel-Lindau-wild type SN12-PM6-1 cells allowed for the establishment of perioperative therapy models of RCC. We report that the combination of daily low-dose metronomic topotecan with pazopanib has highly potent antiprimary tumor as well as both postsurgical adjuvant and metastatic therapy efficacy despite lack of an antimetastatic effect of pazopanib monotherapy. The combination therapy resulted in sustained metastatic tumor cell dormancy, but tumor progression occurred upon treatment cessation. We also obtained evidence for a direct effect of pazopanib on RCC cells, resulting in increased intracellular concentration of topotecan. Our results suggest that this type of treatment combination should be considered for clinical evaluation in early- or late-stage metastatic disease, even for tumors seemingly intrinsically "resistant" to antiangiogenic TKIs or chemotherapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".