O(6)-Methylguanine-DNA Methyltransferase Is a Novel Negative Effector of Invasion in Glioblastoma Multiforme
Bibliographic record
Abstract
The dismal prognosis of glioblastoma multiforme (GBM) is mostly due to the high propensity of GBM tumor cells to invade. We reported an inverse relationship between GBM angiogenicity and expression of the DNA repair protein O(6)-methylguanine-DNA methyltransferase (MGMT), which has been extensively characterized for its role in resistance to alkylating agents used in GBM treatment. In the present study, given the major role of angiogenesis and invasion in GBM aggressiveness, we aimed to investigate the relationship between MGMT expression and GBM invasion. Stable overexpression of MGMT in the U87MG cell line significantly decreased invasion, altered expression of invasion-related genes, decreased expression of α(5)β(1) integrin and focal adhesion kinase, and reduced their spindle-shaped morphology and migration compared with the empty vector control. Conversely, short hairpin RNA-mediated stable knockdown of MGMT or its pharmacologic depletion in the MGMT-positive T98G cell line were required for increased invasion. The inverse relationship between MGMT and invasion was further validated in primary GBM patient-derived cell lines. Using paraffin-embedded tumors from patients with newly diagnosed GBM (n = 59), tumor MGMT promoter hypermethylation (MGMT gene silencing) was significantly associated with increased immunohistochemical expression of the proinvasive matricellular protein secreted protein acidic and rich in cysteine (SPARC; P = 0.039, χ(2) test). Taken together, our findings highlight for the first time the role of MGMT as a negative effector of GBM invasion. Future studies are warranted to elucidate the role of SPARC in the molecular mechanisms underlying the inverse relationship between MGMT and GBM invasion and the potential use of MGMT and SPARC as biomarkers of GBM invasion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".