Opposite Effects of SET7/9 on Apoptosis of Human Acute Myeloid Leukemia Cells and Lung Cancer Cells
Bibliographic record
Abstract
SET7/9 is a protein lysine methyltransferases (PLMTs or PKMTs) which methylates both histone H3K4 and non-histone proteins including transcriptional factors, tumor suppressors, and membrane-associated receptors. Methylation of these proteins alters protein activity and leads to changes in cellular behavior and a series of biological processes. This study aims to investigate the role of SET7/9 in human acute myeloid leukemia (AML) and non-small-cell lung cancer (NSCLC). We examined the expression of SET7/9 in AML cells and NSCLC cells and detected the methylation status of the SET7/9 promoter region. To evaluate the effect of SET7/9 expression changes on cell apoptosis, cell apoptosis rates were determined after SET7/9 overexpression or down-regulation. Our results showed that SET7/9 induces apoptosis of AML cells and inhibits apoptosis of NSCLC cells, suggesting differential effects of SET7/9 on cellular apoptosis and carcinogenesis depending on different cancer types and genetic contexts. Furthermore, we also demonstrated that SET7/9 suppresses cell apoptosis via modulation of E2F1 under circumstance of p53 deficiency in NSCLC cells.
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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".