EXTH-50. THIOREDOXIN REDUCTASE1 AND MGMT SYNTHETIC LETHALITY ENHANCES CYTOTOXICITY OF PRIMA-1MET(APR-246) AND AURANOFIN IN GLIOBLASTOMA
Bibliographic record
Abstract
Abstract Glioblastoma multiforme (GBM), the most common and advanced primary brain malignancy in adults remains an incurable disease, despite aggressive treatment with surgery, radiation therapy and chemoradiation using the alkylating agent, Temozolomide (TMZ). PRIMA-1MET (APR-246), a small molecule designed to restore mutant (mut)p53 function has been shown to affect cellular redox status through targeting thioredoxin reductase 1 (TrxR1) in wild-type (wt)p53 cancer cells. We have recently shown that PRIMA-1MET exerts cytotoxic effects status preferentially in GBM cell lines expressing low levels of the DNA repair protein O6-methylguanine-DNA-methyltransferase (MGMT), known for its role in resistance to TMZ. We hypothesized that PRIMA-1MET mediates its growth inhibitory effects by modulating the redox balance and investigated the potential relationship between MGMT, redox balance and TrxR1. We show that PRIMA-1MET decreased TrxR1 expression levels preferentially in MGMT-low expressing isogenic GBM cell lines. Using pharmacological agents that modulate reactive oxygen species (ROS) levels i.e., ROS scavenger, N-acetylcysteine and ROS inducer, L-Buthionine-Sulfoximine, we show that PRIMA-1MET exerts its growth-inhibitory effects through increased ROS. Strikingly, we identified a novel positive relationship between MGMT and TrxR1, wherein high MGMT expression is associated with high expression of TrxR1 and low levels of ROS. Treatment with the MGMT inhibitor, O6-Benzylguanine, or the TrxR1-targeting FDA-approved drug Auranofin validated our findings. Interestingly, the latter exerted significantly more pronounced cytotoxic effects compared to PRIMA-1MET in GBM cell lines. Additional studies are warranted to assess PRIMA-1MET in combination with TrxR1-targeting therapies and propose repurposing of Auranofin as a novel strategy to improve the dismal outcome of patients with GBM.
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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) | 0.002 | 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".