The complex role of transglutaminase 2 in glioblastoma proliferation
Bibliographic record
Abstract
BACKGROUND: Glioblastomas (GBMs) are a heterogeneous group of primary brain tumors. These tumors are resistant to therapeutic interventions and invariably recur after surgical resection. The multifunctional protein transglutaminase 2 (TG2) has been shown to promote cell survival in a number of different tumors. There is also evidence that TG2 may be a pro-survival factor in GBMs. However, the roles that TG2 plays in facilitating GBM survival and proliferation have not yet been clearly delineated . METHODS: The functions of TG2 are often cell- and context-specific. Therefore, in this study we examined the ability of TG2 to facilitate GBM proliferation using colony formation assays and 5-ethynyl-2'-deoxyuridine (EdU) incorporation in several different GBM cell lines as well as neurospheres derived from patient tumors representing the 3 major subtypes of GBM tumors (mesenchymal, proneural, and classical) and maintained in the absence of serum. TG2 knockdown or selective TG2 inhibitors were used to modulate TG2 expression and activity. RESULTS: We show that TG2 plays differential roles in the proliferative process depending on the cell type. In most, but not all, GBM models TG2 plays a crucial role in the proliferative process, and some but not all TG2 inhibitors were highly effective at reducing proliferation in a large subset of the GBM models. CONCLUSION: Our results show that TG2 plays an important-but notoriously context-specific-role in GBM cell biology. Nonetheless, as future studies unravel the genetic "fingerprints" that make TG2 inhibitors effective, this information could be exploited to develop TG2 inhibitors into personalized GBM therapies.
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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".