Urothelial tumor initiation requires deregulation of multiple signaling pathways: implications in target-based therapies
Bibliographic record
Abstract
Although formation of urothelial carcinoma of the bladder (UCB) requires multiple steps and proceeds along divergent pathways, the underlying genetic and molecular determinants for each step and pathway remain undefined. By developing transgenic mice expressing single or combinatorial genetic alterations in urothelium, we demonstrated here that overcoming oncogene-induced compensatory tumor barriers was critical for urothelial tumor initiation. Constitutively active Ha-ras (Ras*) elicited urothelial hyperplasia that was persistent and did not progress to tumors over a 10 months period. This resistance to tumorigenesis coincided with increased expression of p53 and all pRb family proteins. Expression of a Simian virus 40 T antigen (SV40T), which disables p53 and pRb family proteins, in urothelial cells expressing Ras* triggered early-onset, rapidly-growing and high-grade papillary UCB that strongly resembled the human counterpart (pTaG3). Urothelial cells expressing both Ras* and SV40T had defective G(1)/S checkpoint, elevated Ras-GTPase and hyperactivated AKT-mTOR signaling. Inhibition of the AKT-mTOR pathway with rapamycin significantly reduced the size of high-grade papillary UCB but hyperactivated mitogen-activated protein kinase (MAPK). Inhibition of AKT-mTOR, MAPK and STAT3 altogether resulted in much greater tumor reduction and longer survival than did inhibition of AKT-mTOR pathway alone. Our studies provide the first experimental evidence delineating the combinatorial genetic events required for initiating high-grade papillary UCB, a poorly defined and highly challenging clinical entity. Furthermore, they suggest that targeted therapy using a single agent such as rapamycin may not be highly effective in controlling high-grade UCB and that combination therapy employing inhibitors against multiple targets are more likely to achieve desirable therapeutic outcomes.
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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".