<i>O6-Methylguanine-DNA Methyltransferase</i> Regulation by p53 in Astrocytic Cells
Bibliographic record
Abstract
Methylation of the O6-methylguanine-DNA methyltransferase (MGMT) gene promoter (i.e., gene silencing) occurs in 40% to 50% of patients with glioblastoma and predicts benefit from temozolomide chemotherapy; when unmethylated, MGMT repairs DNA damage induced by temozolomide, contributing to chemoresistance. In this study, we tested the hypothesis that MGMT is regulated by p53 in astrocytic cells, the precursors of which may give rise to glioblastoma. p53 is of interest because, in addition to often being mutated in glioblastoma, inactivation sensitizes some astrocytoma cell lines to temozolomide. MGMT expression was examined in neonatal murine astrocytes and SF767 human astrocytic glioma cells following p53 inactivation by knockout (murine only) or RNAi methods. MGMT mRNA and protein were detected in murine wild-type p53 astrocytes. However, in knockout murine astrocytes and wild-type cells in which p53 was inhibited by RNAi, MGMT expression was reduced by >90%. This effect of p53 on MGMT expression was unrelated to MGMT promoter methylation-in both wild-type and p53-null astrocytes, the MGMT promoter was unmethylated. In wild-type astrocytes, the p53 protein localized to a regulatory region of the MGMT promoter. In SF767 human astrocytic glioma cells, transient knockdown of p53 led to the down-regulation of MGMT gene expression. In murine astrocytes and SF767 cells, p53 regulates MGMT expression without affecting promoter methylation; in astrocytes, this effect may be due to direct binding of p53 to the MGMT promoter. These results imply that the best use of temozolomide requires a thorough understanding of MGMT regulation.
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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".