Rb deletion in mouse mammary progenitors induces luminal-B or basal-like/EMT tumor subtypes depending on p53 status
Bibliographic record
Abstract
Breast cancer is a highly heterogeneous disease, with several different subtypes being characterized by distinct histology, gene expression patterns, and genetic alterations. The tumor suppressor gene retinoblastoma 1 (RB1) is frequently lost in both luminal-B and triple-negative tumor (TNT; i.e., estrogen receptor-, progesterone receptor-, and human epidermal growth factor receptor 2-negative) breast cancer subtypes. However, a causal role for RB1 loss in different subtypes remains undefined. Here we report that deletion of Rb alone or together with its relative p107 in mouse mammary stem/bipotent progenitor cells induced focal acinar hyperplasia with squamous metaplasia. These lesions progressed into histologically diverse, transplantable mammary tumors with features of either luminal-B or TNT subtypes. The TNTs included basal-like tumors as well as tumors that exhibited epithelial-to-mesenchymal transition (EMT). The EMT-type tumors and a subset of the basal-like tumors, but not luminal-B-like tumors, expressed mutant forms of the tumor suppressor p53. Accordingly, targeted deletion of both Rb and p53 in stem/bipotent progenitors led to histologically uniform, aggressive, EMT-type tumors. Reintroduction of Rb into these tumor cells suppressed growth in vitro and tumor formation in vivo. These results establish a causal role for Rb loss in breast cancer in mice and demonstrate that cooperating oncogenic events, such as mutations in p53, dictate tumor subtype after Rb inactivation.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".