Decreased eukaryotic initiation factors expression upon temozolomide treatment—potential novel implications for eIFs in glioma therapy
Bibliographic record
Abstract
PURPOSE: Since glioma therapy is currently still limited until today, new treatment options for this heterogeneous group of tumours are of great interest. Eukaryotic initiation factors (eIFs) are altered in various cancer entities, including gliomas. The purpose of our study was to evaluate the potential of eIFs as novel targets in glioma treatment. METHODS: We evaluated eIF protein expression and regulation in 22 glioblastoma patient-derived xenografts (GBM PDX) after treatment with established cytostatics and with regards to mutation profile analyses of GBM PDX. RESULTS: We observed decreased expression of several eIFs upon temozolomide (TMZ) treatment independent from the phosphatidylinositol 3-kinase (PI3K)/ AKT/ mammalian target of the rapamycin (mTOR) signalling pathway. These effects of TMZ treatment were not present in TMZ-resistant PDX. Combination therapy of regorafenib and TMZ re- established the eIF/AKT/mTOR axis. CONCLUSION: Our study provides novel insights into chemotherapeutic effects on eIF regulation in gliomas and suggests that eIFs are interesting candidates for future research to improve glioma therapy.
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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 | 0.000 |
| 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".