The PI3K/Akt/mTOR pathway as a preventive target in melanoma brain metastasis
Bibliographic record
Abstract
BACKGROUND: Brain metastases (BM) are a frequent complication of malignant melanoma (MM), with limited treatment options and poor survival. Prevention of BM could be more effective and better tolerated than treating established BM in various conditions. METHODS: To investigate the temporospatial dynamics of PI3K/Akt/mTOR (PAM) pathway activation during BM formation and the preventive potential of its inhibition, in vivo molecular imaging with an Akt biosensor was performed, and long-term intravital multiphoton microscopy through a chronic cranial window in mice. RESULTS: In vivo molecular imaging revealed invariable PAM pathway activation during the earliest steps of brain colonization. In order to perform a long-term intravascular arrest and to extravasate, circulating MM cells needed to activate their PAM pathway during this process. However, the PAM pathway was quite heterogeneously activated in established human brain metastases, and its inhibition with the brain-penetrant PAM inhibitor GNE-317 resulted in only modest therapeutic effects in mice. In contrast, giving GNE-317 in preventive schedules that included very low doses effectively reduced the growth rate and number of BM in two MM mouse models over time, and led to an overall survival benefit. Longitudinal intravital multiphoton microscopy found that the first, rate-limiting steps of BM formation-permanent intravascular arrest, extravasation, and initial perivascular growth-are most vulnerable to dual PI3K/mTOR inhibition. CONCLUSION: These findings establish a key role of PAM pathway activation for critical steps of early metastatic brain colonization and reveal its pharmacological inhibition as a potent avenue to prevent the formation of clinically relevant BM.
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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 | 0.000 |
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".