p38 MAPK Inhibition Mitigates Hypoxia-Induced AR Signaling in Castration-Resistant Prostate Cancer
Bibliographic record
Abstract
BACKGROUND: Aberrant androgen receptor (AR) signaling is a major driver of castration-resistant prostate cancer (CRPC). Tumor hypoxia increases AR signaling and is associated with treatment resistance in prostate cancer. Heat shock protein 27 (Hsp27) is a molecular chaperone that is activated in response to heat shock and hypoxia. Hsp27 has previously been reported to facilitate AR nuclear translocation in a p38 mitogen-activated protein kinase (MAPK) dependent manner in castration-sensitive prostate cancer cell lines. Here, we evaluated the potential for inhibiting p38 MAPK/Hsp27 mediated AR signaling under normoxia and hypoxia in experimental models of CRPC. METHODS: We inhibited p38 MAPK with SB203580 in prostate cancer cell lines and measured Hsp27 phosphorylation, AR activity, cell proliferation, and clonogenicity under normoxia and hypoxia. AR activity was measured using an androgen response element driven reporter assay and qPCR to measure expression of AR target genes. Xenograft-bearing mice were treated with SB203580 to measure tumor growth and serum prostate specific antigen (PSA). RESULTS: Our results indicate that p38 MAPK and Hsp27 are activated under normoxia and hypoxia in response to androgens in CRPC cells. p38 MAPK inhibition diminished Hsp27 activation and the hypoxia-mediated increase in AR activity. Additionally, inhibition of p38 MAPK activity decreased proliferation and survival of CRPC cells in vitro and prolonged the survival of tumor-bearing mice. CONCLUSIONS: These results suggest that p38 MAPK inhibition may represent a therapeutic strategy to disrupt AR signaling in the heterogeneous CRPC tumor microenvironment.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".