Nitric oxide‐mediated regulation of hypoxia‐induced B16F10 melanoma metastasis
Bibliographic record
Abstract
Tumour hypoxia is associated with resistance to therapy and with increased invasion and metastatic potential. Recent studies in our laboratory have shown that the hypoxic up-regulation of tumour cell invasiveness and chemoresistance is in part due to reduced nitric oxide (NO) signaling. Using B16F10 murine melanoma cells, we demonstrate here that the increased metastatic potential associated with exposure to hypoxia is mediated by a reduction in cGMP-dependent NO-signaling. Pre-incubation of B16F10 cells in hypoxia (1% vs. 20% O(2)) for 12 hr increased lung colonization ability by over 4-fold. This effect of hypoxia on metastasis was inhibited by co-incubation with low concentrations of the NO-mimetic drugs glyceryl trinitrate (GTN) and diethylenetriamine NO adduct (DETA/NO). In a manner similar to hypoxia, pharmacological inhibition of NO synthesis resulted in a significant increase in lung nodule formation, an effect that was prevented by co-incubation with GTN. An important NO-signaling pathway involves the activation of soluble guanylyl cyclase and the consequential generation of cGMP. Culture in the presence of a non-hydrolysable cGMP analogue (8-Br-cGMP) abrogated the hypoxia-induced lung nodule formation, suggesting that the effects of NO on metastasis are mediated via a cGMP-dependent pathway. These findings suggest that a novel mechanism whereby hypoxia regulates metastatic potential involves a downstream inhibition of cGMP-dependent NO signaling.
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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".