The Prognostic Implication of the Basal-Like (Cyclin Ehigh/p27low/p53+/Glomeruloid-Microvascular-Proliferation+) Phenotype of <b> <i>BRCA1</i> </b>-Related Breast Cancer
Bibliographic record
Abstract
Previous studies have shown that BRCA1-related breast cancers are often high-grade tumors that do not express estrogen receptors, HER2, p27(Kip1), or cyclin D1, but do express p53 and cyclin E. In addition, the expression of cytokeratin 5/6 (CK5/6), indicating a basal epithelial phenotype, is frequent in BRCA1-related breast cancer. Here, in a series of 247 breast cancers, we demonstrate that CK5/6 expression was associated with nearly all of the features of BRCA1-related breast cancer and was also associated with a poor prognosis. In a parsimonious multivariable proportional hazards model, protein levels of cyclin E, p27(Kip1), p53, and the presence of glomeruloid microvascular proliferation all independently predicted outcome after breast cancer. In this model, only cyclin E and p27(Kip1) levels were independent predictors in lymph node-negative cancers, whereas glomeruloid microvascular proliferation and tumor size independently predicted outcome in node-positive disease. The molecular determinants of the basal epithelial phenotype encapsulate many of the key features of breast cancers occurring in germ-line BRCA1 mutation carriers and have independent prognostic value. Basal breast cancer deserves recognition as an important subtype of 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 | 0.001 | 0.002 |
| 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".