The Chemopreventive Agent Myoinositol Inhibits Akt and Extracellular Signal-Regulated Kinase in Bronchial Lesions from Heavy Smokers
Bibliographic record
Abstract
Myoinositol is an isomer of glucose that has chemopreventive activity in animal models of cancer. In a recent phase I clinical trial, myoinositol administration correlated with a statistically significant regression of preexisting bronchial dysplastic lesions in heavy smokers. To shed light on the potential mechanisms involved, activation of Akt and extracellular signal-regulated kinase (ERK), two kinases that control cellular proliferation and survival, was assessed in 206 paired bronchial biopsies from 21 patients who participated in this clinical trial. Before myoinositol treatment, strongly positive staining for activation of Akt was detected in 27% of hyperplastic/metaplastic lesions and 58% of dysplastic lesions (P = 0.05, chi(2) test). There was also a trend toward increased activation of ERK (28% in regions of hyperplasia/metaplasia to 42% of dysplastic lesions). Following myoinositol treatment, significant decreases in Akt and ERK phosphorylation were observed in dysplastic (P < 0.01 and 0.05, respectively) but not hyperplastic/metaplastic lesions (P > 0.05). In vitro, myoinositol decreased endogenous and tobacco carcinogen-induced activation of Akt and ERK in immortalized human bronchial epithelial cells, which decreased cell proliferation and induced a G(1)-S cell cycle arrest. These results show that the phenotypic progression of premalignant bronchial lesions from smokers correlates with increased activation of Akt and ERK and that these kinases are targets of myoinositol. Moreover, they suggest that myoinositol might cause regression of bronchial dysplastic lesions through inhibition of active Akt and ERK.
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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".