Androgen receptor levels are upregulated by Akt in prostate cancer
Bibliographic record
Abstract
Multiple lines of evidence suggest a functional link between the androgen receptor (AR) and the serine/threonine kinase Akt in the development and progression of prostate cancer. To investigate the impact of Akt activity on AR homeostasis, we treated androgen-dependent LNCaP and LAPC-4 prostate cancer cells with Akt inhibitor. Akt inhibition decreased AR expression, suggesting that Akt activity was required for regulation of AR protein levels. However, while androgen-independent LNCaP-abl cells also showed diminished AR protein levels in response to Akt inhibition, treatment of androgen-independent LNCaP-AI cells failed to alter AR protein levels upon similar treatment, suggesting that AR protein levels in these androgen-independent prostate cells were regulated by mechanisms independent of Akt activation. Regulation of AR, downstream of activated Akt, also was observed in vivo when examining transgenic mice that overexpress constitutively active mutant myristoylated (myr)-Akt1 in the prostate. Transgenic mice expressing activated myr-Akt1 exhibited higher levels of AR mRNA and protein. Expression of activated myr-Akt1 did not alter prostate cell growth and no significant size differences between prostate tissues derived from transgenic animals were observed when comparing transgenic mice with wild-type mice. Still, transgenic mice overexpressing Akt exhibited higher levels of γH2AX and phosphorylated Chk2 in prostate tissue. These changes in markers associated with oncogene-induced senescence confirmed significant altered signaling in the transgenic mouse model. Overall, results presented here suggest that AR levels are regulated by the Akt pathway.
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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) | 0.002 | 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".