Abstract 2482: Development of novel small-molecule inhibitors of androgen receptor variants lacking the ligand-binding domain.
Bibliographic record
Abstract
Abstract Over 30,000 men die from prostate cancer in Canada and USA each year. Current therapeutic strategy for advanced prostate cancer is to suppress androgen receptor (AR) signaling by reducing level of androgens (via castration) and by antiandrogens to compete with endogenous androgens for binding in the AR ligand-binding domain (LBD). Despite of initial response, lethal ‘castration-resistant’ prostate cancer (CRPC) arises as a result of oncogenic reactivation of the AR. Current treatments for CRPC provide only a modest improvement in overall survival (a few months). It is now firmly established that reactivation of the AR signaling in CRPC is due to multiple mechanisms, including point mutations in the AR LBD and expression of AR variants lacking the LBD. Recently, a series of AR splice variants lacking the LBD, such as AR-v7, were identified from tissue specimen of CRPC patients. Significantly, AR-v7 is constitutively active even in the absence of androgens and it is thus no longer possible to be inhibited by conventional LBD-targeting antiandrogens (such as bicalutamide) or by androgen-depleting agents (such as Abirateron). This potentially provides a novel mechanism for the development of CRPC. Our recent work has identified a novel chemical compound that inhibits AR-v7 in reporter assays. We found this compound is also active against full-length ARs, including the wild type and multiple clinically-relevant mutant ARs, such as the T877A, H874Y and W741C mutants. Our study indicated this compound targets the N-terminal domain of the AR. We have obtained structure-activity relationship (SAR) of this compound. Citation Format: Xiaohong Tian, Weiguo Liu, Guoyan Geng, Jian Hui Wu. Development of novel small-molecule inhibitors of androgen receptor variants lacking the ligand-binding domain. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2482. doi:10.1158/1538-7445.AM2013-2482
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".