Synergistic Dual Targeting of Thioredoxin and Glutathione Systems Irrespective of p53 in Glioblastoma Stem Cells
Bibliographic record
Abstract
Glioblastoma (GBM) is an incurable primary brain cancer characterized by increased reactive oxygen species (ROS) production. The redox-sensitive tumor suppressor gene TP53, wild-type (wt) for 70% of patients, regulates redox homeostasis. Glioblastoma stem cells (GSCs) increase thioredoxin (Trx) and glutathione (GSH) antioxidant systems as survival redox-adaptive mechanisms to maintain ROS below the cytotoxic threshold. Auranofin, an FDA-approved anti-rheumatoid drug, inhibits thioredoxin reductase 1 (TrxR1). L-buthionine sulfoximine (L-BSO) and the natural product piperlongumine (PPL) inhibit the GSH system. We evaluated the cytotoxic effects of Auranofin alone and in combination with L-BSO or PPL in GBM cell lines and GSCs with a known TP53 status. The Cancer Genome Atlas/GBM analysis revealed a significant positive correlation between wtp53 and TrxR1 expression in GBM. Auranofin induced ROS-dependent cytotoxicity within a micromolar range in GSCs. Auranofin decreased TrxR1 expression, AKT (Ser-473) phosphorylation, and increased p53, p21, and PARP-1 apoptotic cleavage in wtp53-GSCs, while mutant-p53 was decreased in a mutant-p53 GSC line. Additionally, p53-knockdown in a wtp53-GSC line decreased TrxR1 expression and significantly increased sensitivity to Auranofin, suggesting the role of wtp53 as a negative redox-sensitive mechanism in response to Auranofin in GSCs. The combination of Auranofin and L-BSO synergistically increased ROS, decreased IC50s, and induced long-term cytotoxicity irrespective of p53 in GBM cell lines and GSCs. Intriguingly, Auranofin increased the expression of glutathione S-transferase pi-1 (GSTP-1), a target of PPL. Combining Auranofin with PPL synergistically decreased IC50s to a nanomolar range in GSCs, supporting the potential to repurpose Auranofin and PPL in 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) | 0.001 | 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".