TMPRSS2-ERG activates NO-cGMP signaling in prostate cancer cells
Bibliographic record
Abstract
The aberrant activation of the ERG oncogenic pathway due to the TMPRSS2-ERG gene fusion is the major event that contributes to prostate cancer (PCa) development. However, the critical downstream effectors that can be therapeutically targeted remain to be identified. In this study, we have found that the expression of the α1 and β1 subunits of soluble guanylyl cyclase (sGC) was directly and specifically regulated by ERG in vitro and in vivo and was significantly associated with TMPRSS2-ERG fusion in clinical PCa cohorts. sGC is the major mediator of nitric oxide (NO)-cGMP signaling in cells that, upon NO binding, catalyzes the synthesis of cGMP and subsequently activates protein kinase G (PKG). We showed that cGMP synthesis was significantly elevated by ERG in PCa cells, leading to increased PKG activity and cell proliferation. Importantly, we also demonstrated that sGC inhibitor treatment repressed tumor growth in TMPRSS2-ERG-positive PCa xenograft models and can act in synergy with a potent AR antagonist, enzalutamide. This study strongly suggests that targeting NO-cGMP signaling pathways may be a novel therapeutic strategy to treat PCa with TMPRSS2-ERG gene fusion.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".