Abstract 1714: Transcriptional networks downstream of the AR identify clinically relevant prostate cancer targets
Bibliographic record
Abstract
Abstract The AR signalling axis is central to Prostate Cancer (PrCa) biology, shown by its use in both screening (PSA) and treatment of the disease (androgen deprivation therapy). Identifying direct target genes of the AR will provide a better understanding the key signalling pathways controlled by the AR in PrCa and could lead to improved biomarkers and future therapeutic targets for the disease. To this end we have performed fine mapping of androgen responsive gene expression in prostate cancer cell lines using Illumina bead-arrays, coupled with AR chromatin-immunoprecipitation and Solexa sequencing technology (ChIP-seq). This approach generated over ten thousand candidate AR target genes. We have then undertaken large scale, cross-platform validation using BioTrove Realtime PCR panels which allow the measurement of >600 transcripts simultaneously. Using this combination of approaches we have identified and validated several hundred AR regulated genes. We found that metabolic enzymes and kinases were significantly enriched in the set of direct AR regulated genes. In nine independent clinical gene expression studies we found that the most consistently up-regulated AR target gene was a calcium regulated kinase. At the protein level this kinase showed increased expression in two independent patient cohorts. A small molecule inhibitor of this kinase reduced the growth of a panel of PrCa cell lines in vitro and tumour growth in xenograft models. Interestingly, we found that the levels of this AR regulated kinase were reduced in clinical PrCa following androgen deprivation therapy, but were raised in Castrate Resistant disease. Therefore, we have identified an AR regulate kinase which contributes to tumour growth and is a potential marker and therapeutic target in both hormone naïve and anti-androgen resistant disease. In summary, these data show that combining expression analysis, ChIP-seq and high through-put validation has identified a framework to understand the oncogenic functions of the AR in prostate cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1714.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".