Emergence of β1 integrin-deficient breast tumours from dormancy involves both inactivation of p53 and generation of a permissive tumour microenvironment
Bibliographic record
Abstract
The molecular and cellular mechanisms underlying mammary tumour dormancy and cancer recurrence are unclear and remain to be elucidated. Here, we report that mammary epithelial-specific disruption of β1 integrin in a murine model of Luminal B human breast cancer drastically impairs tumour growth with proliferation block, apoptosis induction and cellular senescence. β1 integrin-deficient dormant lesions show activation of the tumour suppressor p53, and tumours that circumvent dormancy possess p53 mutation analogous to those in human disease. We further demonstrate that mammary epithelial deletion of p53 in β1 integrin-deficient mice fully rescues tumour dormancy and bypasses cellular senescence. Additionally, recurrent β1 integrin-deficient tumours exhibit fibrosis with increased cancer-associated fibroblast infiltration and extracellular matrix deposition, absent in fast-growing β1 integrin/p53-deficient lesions. Taken together, these observations argue that β1 integrin modulates p53-dependent cellular senescence resulting in tumour dormancy and that pro-tumourigenic stromal cues and intrinsic genetic mutation are required for dormancy exit.
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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".