Crosstalk between the Androgen Receptor and β-Catenin in Castrate-Resistant Prostate Cancer
Bibliographic record
Abstract
The androgen-signaling pathway plays an important role in the development and hormonal progression of prostate cancer to the castrate-resistant stage (also called androgen-independent or hormone refractory). The Wnt pathway and beta-catenin contribute to prostate biology and pathology. Here application of Affymetrix GeneChip analysis revealed the genomic similarity of the LNCaP hollow fiber model to clinical samples and identified genes with differential expression during hormonal progression. The fiber model samples clustered according to the expression profile of androgen-regulated genes to provide genomic evidence for the reactivation of the AR signaling pathway in castrate-resistant prostate cancer. Pathway-based characterization of gene expression identified activation of the Wnt pathway. Together with the increased expression of AR and beta-catenin, there was increased nuclear colocalization and interaction of endogenous AR and beta-catenin in castrate-resistant prostate cancer from castrated mice. Surprisingly, no interaction or colocalization of AR and beta-catenin could be detected in xenografts from noncastrated mice. These studies provide the first in vivo evidence to support aberrant activation of the AR through the Wnt/beta-catenin signaling pathway during progression of prostate cancer to the terminal castrate-resistant stage.
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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 | 0.001 | 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".