<scp>GRB10</scp> sustains <scp>AR</scp> activity by interacting with <scp>PP2A</scp> in prostate cancer cells
Bibliographic record
Abstract
Prostate cancer (PCa) progression is driven by androgen receptor (AR) signaling. Unfortunately, androgen-deprivation therapy and the use of even more potent AR pathway inhibitors (ARPIs) cannot bring about a cure. ARPI resistance (ie, castration-resistant PCa, CRPC) will inevitably develop. Previously, we demonstrated that GRB10 is an AR transcriptionally repressed gene that functionally contributes to CRPC development and ARPI resistance. GRB10 expression is elevated prior to CRPC development in our patient-derived xenograft models and is significantly upregulated in clinical CRPC samples. Here, we analyzed transcriptomic data from GRB10 knockdown in PCa cells and found that AR signaling is downregulated. While the mRNA expression of AR target genes decreased upon GRB10 knockdown, AR expression was not affected at the mRNA or protein level. We further found that phosphorylation of AR serine 81 (S81), which is critical for AR transcriptional activity, is decreased by GRB10 knockdown and increased by its overexpression. Luciferase assay using GRB10-knockdown cells also indicate reduced AR activity. Immunoprecipitation coupled with mass spectrometry revealed an interaction between GRB10 and the PP2A complex, which is a known phosphatase of AR. Further validations and analyses showed that GRB10 binds to the PP2Ac catalytic subunit with its PH domain. Mechanistically, GRB10 knockdown increased PP2Ac protein stability, which in turn decreased AR S81 phosphorylation and reduced AR activity. Our findings indicate a reciprocal feedback between GRB10 and AR signaling, implying the importance of GRB10 in PCa progression.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".