Loss of Fbxw7 Impairs Development of and Induces Heterogeneous Tumor Formation in the Mouse Mammary Gland
Bibliographic record
Abstract
Abstract Fbxw7 is an F-box protein that contributes to regulation of cell proliferation and cell fate determination as well as to tumor suppression in various tissues. In this study, we generated mice with mammary gland–specific ablation of Fbxw7 (Blg-Cre/Fbxw7F/F mice) and found that most neonates born to mutant dams die soon after birth as a result of defective maternal lactation. The mammary gland of mutant dams was markedly atrophic and manifested both excessive cell proliferation and apoptosis in association with the accumulation of Notch1 and p63. Despite the hypoplastic nature of the mutant mammary gland, Blg-Cre/Fbxw7F/F mice spontaneously developed mammary tumors that resembled basal-like carcinoma with marked intratumoral heterogeneity. Additional inactivation of Trp53 in Blg-Cre/Fbxw7F/F mice further promoted onset and development of mammary tumors, suggesting that spontaneous mutation of Trp53 may facilitate transition of hypoplastic mammary lesions to aggressive cancer in mice lacking Fbxw7. RNA-sequencing analysis of epithelial- and mesenchymal-like cell lines from a Blg-Cre/Fbxw7F/F mouse tumor revealed an increased mutation rate and structural alterations in the tumor and differential expression of upstream transcription factors including known targets of Fbxw7. Together, our results implicate Fbxw7 in the regulation of cell differentiation and in tumor suppression in the mammary gland. Loss of Fbxw7 increases mutation rate and chromosome instability, activates signaling pathways governed by transcription factors regulated by Fbxw7, and triggers the development of mammary tumors with prominent heterogeneity. Significance: Mammary gland–specific ablation of Fbxw7 in mice results in defective gland development and spontaneous mammary tumor formation reminiscent of human basal-like carcinoma with intratumoral heterogeneity.
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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) | 0.001 | 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 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".