ADRB2 expression in progressive metastatic castration-resistant prostate cancer.
Bibliographic record
Abstract
145 Background: The net oncogenic effect of the G protein-coupled receptor β2 adrenergic receptor ADRB2, which may induce neuroendocrine differentiation via cyclic AMP and protein kinase A and whose expression is epigenetically regulated by EZH2, is controversial. ADRB2 expression and associated clinical outcomes in metastatic castration-resistant prostate cancer (mCRPC) are unknown. Methods: This was a retrospective analysis of a cohort of men with mCRPC who were prospectively enrolled in the multi-center SU2C/PCF/AACR West Coast Prostate Cancer Dream Team study, in which biopsies of a metastatic site were obtained at disease progression. Specimens underwent laser capture microdissection and RNA-seq. ADRB2 expression was stratified by histology and transcriptional cluster based on prior unsupervised hierarchical transcriptome clustering, and correlated with EZH2 expression. ADRB2 expression (lowest quartile) was correlated with OS from time of biopsy by log rank test and a multivariable Cox proportional hazard model. Results: One-hundred and twenty-seven men with progressive mCRPC underwent metastatic biopsies and had sufficient tumor for RNA-seq. ADRB2 expression was lowest in the small cell-enriched transcriptional cluster (P<0.001), and correlated inversely with EZH2 expression (r=-0.28, P<0.01). Men with low ADRB2 expression had a shorter median OS than those with high (9.5 vs 18.9 mo, P=0.02). In multivariable analysis adjusting for small cell histology, performance status, LDH, and visceral metastases, high ADRB2 expression was associated with a trend towards longer OS (HR=0.65, 95% CI 0.41-1.02, P=0.06). Conclusions: Low ADRB2 expression is associated with worse OS in men with progressive mCRPC, and may be a means by which EZH2 confers resistance to antiandrogen therapy. Indirect ADRB2 stimulation with EZH2 inhibitors may improve outcomes. Validation in independent cohorts is necessary.
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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".