Abstract 920: Mislocalization of the polarity protein Scribble promotes tumorigenesis in the mouse mammary gland
Bibliographic record
Abstract
Abstract Recent evidence from our lab has demonstrated that the basolateral polarity protein Scribble is frequently mislocalized in human tumors and can cooperate with ErbB2 and Myc to induce mammary tumors. However, we do not know if mislocalization of Scribble can initiate cell transformation and tumorigenesis. To test the hypothesis that Scr mislocalization can induce tumorigenesis, we generated transgenic mice expressing a Scr point mutant that has been shown to mislocalize to the cytosol, under the control of the MMTV promoter (ScrP305L). ScrP305L mice develop mammary tumors with long latency, suggesting that secondary genetic events are required for tumor initiation. The tumors are histologically diverse, and immunohistochemical and gene expression analysis indicate that they express high levels of basal markers, including cytokeratins 5, 6 and 14, and low levels of the luminal marker E-cadherin. Inspection of the developing virgin mammary gland reveals that Scr mislocalization impairs tertiary branching and ductal density. While primary and secondary ducts appear normal, tertiary branches fail to form, suggesting a defect in luminal differentiation. These changes can be observed as early as eight weeks after birth; however, by one year of age, multifocal hyperplasias are apparent in most mice. We conclude that mislocalization of Scribble in the mouse mammary gland impairs luminal differentiation, resulting in branching defects and, through acquisition of secondary genetic events, tumors of varying histotype. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 920. doi:10.1158/1538-7445.AM2011-920
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".