The Atypical Cyclin-Like Protein Spy1 Overrides p53-Mediated Tumour Suppression and Promotes Susceptibility to Breast Tumorigenesis
Bibliographic record
Abstract
Abstract Breast cancer is the most common cancer to affect women and one of the leading causes of cancer related deaths. Maintenance of genomic stability and proper regulation of cell cycle checkpoints play a critical role in preventing the accumulation of deleterious mutations. Perturbations in the expression or activity of mediators of cell cycle progression or checkpoint activation represent important events that may increase susceptibility to the onset of carcinogenesis. The atypical cyclin-like protein Spy1 was isolated in a screen for novel genes that could bypass the DNA damage response. Clinical data demonstrates that protein levels of Spy1 are significantly elevated in ductal and lobular carcinoma of the breast. Using a transgenic mouse driving expression of Spy1 in the mammary epithelium we demonstrate that sustained elevation of Spy1 leads to enhanced proliferation and an increased susceptibility to mammary tumour formation. We find that Spy1 is targeted for degradation by the tumour suppressor p53 to protect checkpoint control. When crossed with p53 deficient mice, elevation of Spy1 leads to an increase in hyperplastic alveolar nodules. Targeting cyclin-like protein activity may therefore represent a mechanism of re-sensitizing cells to important cell cycle checkpoints in a therapeutic setting.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".