Identification of Putative Androgen Receptor Interaction Protein Modules
Bibliographic record
Abstract
We have developed a novel androgen receptor (AR) expression system in the 293 human embryonic kidney cell line that recapitulates AR biochemical activity as a steroid hormone receptor in prostate cancer cells. We used this system to identify putative AR-binding proteins in the cytosolic and nuclear compartments of mammalian cells using a large scale co-immunoprecipitation strategy coupled to quantitative mass spectrometry. For example, the heat shock 70 and 90 chaperones, which are known regulators of steroid hormone receptor, were identified as AR-binding proteins. AR purification enriched for proteins involved in RNA processing, protein transport, and cytoskeletal organization, suggesting a functional link between AR and these protein modules in mammalian cells. For example, AR purification in the nuclear compartment led to the specific enrichment of alpha-actinin-4, clathrin heavy chain, and serine-threonine protein kinase C delta. Short interfering RNA knockdown studies and co-transcriptional reporter assays revealed that clathrin heavy chain possessed co-activator activity during AR-mediated transcription, whereas alpha-actinin-4 and protein kinase C delta displayed both co-activator and co-repressor activity during AR-mediated transcription that was dependent upon their relative expression levels. Lastly immunohistochemical staining of prostate tissue showed that alpha-actinin-4 levels decreased in the nucleus of high grade cancerous prostate samples, suggesting its possible deregulation in advanced prostate cancers as previously observed in late stage metastatic breast cancers. Taken together, these findings suggest AR binds to specific protein modules in mammalian cells and that these protein modules may provide a molecular framework for interrogating AR function in normal and cancerous prostate epithelial cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".