A-674563, a putative AKT1 inhibitor that also suppresses CDK2 activity, inhibits human NSCLC cell growth more effectively than the pan-AKT inhibitor, MK-2206
Bibliographic record
Abstract
AKT is a serine-threonine kinase implicated in tumorigenesis as a central regulator of cellular growth, proliferation, survival, and metabolism. Activated AKT is commonly overexpressed in non-small cell lung cancer (NSCLC) and accordingly AKT inhibitors are under clinical investigation for NSCLC treatment. Thus far, the AKT inhibitors being evaluated broadly target all three (1-3) AKT isoforms but recent evidence suggests opposing roles in lung tumorigenesis where loss of Akt1 inhibits while the loss of Akt2 enhances lung tumor development. Based on these findings, we hypothesized that selective inhibition of AKT-1 would be a more effective therapeutic strategy than pan-AKT inhibition for NSCLC treatment. Using six NSCLC cell lines, we found that the AKT-1 inhibitor, A-674563, was significantly more effective at reducing NSCLC cell survival relative to the pan-AKT inhibitor MK-2206. Comparison of the downstream effects of the inhibitors suggests that altered cell cycle progression and off-target CDK2 inhibition are likely vital to the improved efficacy of A-674563 over MK-2206.
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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".