EXPRESSION OF ANDROGEN RECEPTOR IN BREAST CANCER BRAIN METASTASES
Bibliographic record
Abstract
Abstract Given availability of central nervous system (CNS)-penetrant systemic therapies that target the androgen receptor (AR), we evaluated the expression of the AR “target” in breast cancer brain metastases (BrM). METHODS: An established, retrospective cohort of 57 patients with metastatic breast cancer who underwent surgery for BrM at the Sunnybrook Odette Cancer Centre (SOCC) between 1999 and 2013 was studied. AR expression in BrM samples was assessed in triplicate using immunohistochemistry (IHC). AR positive status was defined as nuclear AR expression ≥10% in tumor-infiltrating cells as a percentage of tumor area using the SP107 antibody. RESULTS: The median age of patients was 52 years (range 32-85 years). 17 (30%) patients had hormone receptor positive (HR+) /HER2-negative, 28 (49%) had HER2+, and 12 (21%) had triple negative breast cancer (TNBC) BrM. The median expression of AR was 20% (CI 1.6-38.3%) and 32 of 57 (56%) BrM were AR positive based on a cut-point of ≥10%. A significantly smaller proportion of patients with TNBC had AR+ BrM (n=2/12, 17%), compared to patients with HR+/HER2-ve (n= 9/17, 53%) or HER2+ (n=21/28, 75%) disease (p=0.04). Patients with AR positive versus AR negative BrM had similar overall survival (12.5 vs. 7.9 months, p= 0.6), brain-specific progression-free survival (8.0 vs. 5.1 months, p= 0.95), and time from breast cancer diagnosis to BrM diagnosis (51 vs. 29 months, p=0.16). CONCLUSION: AR is expressed in the majority of breast cancer BrM and represents a promising therapeutic target.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".