Exploiting Mouse Models to Recapitulate Clinical Tumor Dormancy and Recurrence in Breast Cancer
Bibliographic record
Abstract
Breast cancer recurrence and metastasis from activated dormant tumors remain the leading causes in disease morbidity. Women with estrogen receptor-positive breast cancer that accounts for nearly 80% of all cases face a lifelong risk of relapse after initial treatment. The biology of dormant tumors and dormant cancer cells that give rise to recurrent disease and metastasis remain to be understood for us to overcome the clinical challenges that they bring. The selection and optimization of preclinical models to recapitulate dormancy and recurrence in patients is critical for studying the underlying cellular and environmental factors. Here, we provide a brief review of studies that utilize mouse models to dissect the mechanisms of dormancy and therapeutic strategies to avert recurrence. This review specifically accentuates the versatility and benefits of immunocompetent transgenic mouse models that can be manipulated to recapitulate primary dormancy, metastatic dormancy, and post-therapy dormancy.
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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) | 0.002 | 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) | 0.001 | 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 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".