The biology behind combining poly [ADP ribose] polymerase and androgen receptor inhibition for metastatic castration-resistant prostate cancer
Bibliographic record
Abstract
For about a decade, poly [ADP ribose] polymerases (PARP) inhibitors have been used almost exclusively to treat tumours that are deficient in one of the BRCA genes. In advanced prostate cancer, which is largely driven by the activity of the androgen receptor (AR), accumulating preclinical evidence has suggested an interplay between the AR and PARP, which could be therapeutically exploited independently of defects in the tumour's DNA homologous recombination repair (HRR) machinery. This includes the regulation of HRR genes by the AR, a mutual influence between the activities of PARP and the AR, and the co-localisation of BRCA2 to the retinoblastoma gene in the human genome. Based on these findings, randomised clinical trials have been initiated to study the addition of a PARP inhibitor to AR pathway inhibitor therapy. Three of four randomised studies demonstrated a significantly increased anti-tumour activity in men with metastatic prostate cancer, irrespective of HRR gene alterations. In this review, we summarise the available preclinical evidence that provides the rationale for the combination of inhibitors for PARP and the AR and discuss how it might contribute to the efficacy observed in the clinic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".