Dasatinib enhances tumor growth in gemcitabine-resistant orthotopic bladder cancer xenografts
Bibliographic record
Abstract
Systemic chemotherapy with gemcitabine and cisplatin is standard of care for patients with metastatic urothelial bladder cancer. However, resistance formation is common after initial response. The protein Src is known as a proto-oncogene, which is overexpressed in various human cancers. Since there are controversial reports about the role of Src in bladder cancer, we evaluated the efficacy of the Src kinase inhibitor dasatinib in the urothelial bladder cancer cell line RT112 and its gemcitabine-resistant sub-line RT112 r GEMCI 20 in vitro and in vivo. RT112 urothelial cancer cells were adapted to growth in the presence of 20 ng/ml gemcitabine (RT112 r GEMCI 20 ) by continuous cultivation at increasing drug concentrations. Cell viability was determined by MTT assay, cell growth kinetics were determined by cell count, protein levels were measured by western blot, and cell migration was evaluated by scratch assays. In vivo tumor growth was tested in a murine orthotopic xenograft model using bioluminescent imaging. Dasatinib exerted similar effects on Src signaling in RT112 and RT112 r GEMCI 20 cells but RT112 r GEMCI 20 cells were less sensitive to dasatinib-induced anti-cancer effects (half maximal inhibitory concentration (IC 50 ) of dasatinib in RT112 cells: 349.2 ± 67.2 nM; IC 50 of dasatinib in RT112 r GEMCI 20 cells: 1081.1 ± 239.2 nM). Dasatinib inhibited migration of chemo-naive and gemcitabine-resistant cells. Most strikingly, dasatinib treatment reduced RT112 tumor growth and muscle invasion in orthotopic xenografts, while it was associated with increased size and muscle-invasive growth in RT112 r GEMCI 20 tumors. Dasatinib should be considered with care for the treatment of urothelial cancer, in particular for therapy-refractory cases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".