DDDR-46. TARGETING TRANSGLUTAMINASE 2 (TGM2) ENHANCES SENSITIVITY OF GLIOBLASTOMA CELL LINES TO RADIOTHERAPY AND TEMOZOLOMIDE
Bibliographic record
Abstract
Abstract Glioblastoma (GBM), the most aggressive and common primary brain tumor in adults, remains highly resistant to conventional therapeutics, including radiation therapy (RT), largely due to its molecular heterogeneity. Few biomarkers have been identified that successfully guide or predict treatment response. Transglutaminase 2 (TGM2), a ubiquitous multifunctional enzyme involved in numerous signal transduction pathways related to tumorigenesis, has recently been suggested to drive chemoradioresistance. Here, we investigate the effects of disrupting TGM2 by pharmacologic inhibition or CRISPR knockout (TGM2-KO) on GBM cell’s response to RT and Temozolomide (TMZ) chemotherapy. Using western blotting and clonogenic assays, we show that the allosteric TGM2 inhibitor, GK921, stabilizes p53 expression and impedes reproductive ability at IC50 and IC25 concentrations. TGM2-KO and GK921 (at IC10 and lower) sensitized GBM cell lines to RT with almost equivalent efficacy, resulting in a 2- to 3-fold suppression of clonal expansion compared to scramble controls or irradiation alone. We also demonstrate increased sensitivity of GBM cell lines to TMZ upon inhibition of TGM2 by GK921. Our findings indicate that the use of TGM2 inhibitors, such as GK921, could enhance the efficacy of RT and the potency of TMZ, positioning TGM2 as a promising therapeutic target that may improve standard treatment of GBM cells expressing TGM2.
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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".