Cooperation between Dmp1 Loss and Cyclin D1 Overexpression in Breast Cancer
Bibliographic record
Abstract
Cyclin D1 is a component of the core cell-cycle machinery and is frequently overexpressed in breast cancer. It physically interacts with the tumor suppressor Dmp1 that attenuates the oncogenic signals from Ras and HER2 by inducing Arf/p53-dependent cell-cycle arrest. Currently, the biological significance of Dmp1-cyclin D1 interplay in breast cancer has not been determined. Here, we show that cyclin D1 bound to Dmp1 to activate both Arf and Ink4a promoters and, consequently, induced apoptosis or G2/M cell-cycle delay in normal cells to protect them from neoplastic transformation. The cyclin D1-induced Ink4a/Arf gene expression was dependent on Dmp1 because the induction was not detected in Dmp1-deficient or DMP1-depleted cells. Arf/Ink4a expression was increased in pre-malignant mammary glands from Dmp1(+/+);MMTV-cyclin D1 and Dmp1(+/+);MMTV-D1T286A mice but significantly down-regulated in those from Dmp1-deficient mice. Selective Dmp1 deletion was found in 21% of the MMTV-D1 and D1T286A mammary carcinomas, and the Dmp1 heterozygous status significantly accelerated mouse mammary tumorigenesis with reduced apoptosis and increased metastasis. Overall, our study reveals a pivotal role of combined Dmp1 loss and cyclin D1 overexpression in breast cancer.
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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 | 0.000 |
| 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 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".