GLUT1 and TUBB4 in Glioblastoma Could be Efficacious Targets
Bibliographic record
Abstract
Glioblastoma multiforme (GBM) is the most aggressive and deadly brain tumor, portending a median 13-month survival even following gross total resection with adjuvant chemotherapy and radiotherapy. This prognosis necessitates improved therapies for the disease. A target of interest for novel chemotherapies is the Warburg Effect, which describes the tumor's shift away from oxidative phosphorylation towards glycolysis. Here, we elucidate GLUT1 (Glucose transporter 1) and one of its associated binding partners, TUBB4 (Tubulin 4), as potentially druggable targets in GBM. Using data mining approach, we demonstrate that GLUT1 is overexpressed as a function of tumor grade in astrocytoma's and that its overexpression is associated with poorer prognosis. Using both mass spectrometry performed on hGBM (human glioblastoma patient specimen) and in silico modeling, we show that GLUT1 interacts with TUBB4, and more accurately demonstrates GLUT1's binding with fasentin. Proximity ligation assay (PLA) and immunoprecipitation studies confirm GLUT1 interaction with TUBB4. Treatment of GSC33 and GSC28 cells with TUBB4 inhibitor, CR-42-24, reduces the expression of GLUT1 however, TUBB4 expression is unaltered upon fasentin treatment. Using human pluripotent stem cell antibody array, we demonstrate reduced levels of Oct3/4, Nanog, Sox2, Sox17, Snail and VEGFR2 (Vascular endothelial growth factor receptor 2) upon CR-42-24 treatment. Overall, our data confirm that silencing TUBB4 or GLUT1 reduce GSC tumorsphere formation, self-renewal and proliferation in vitro. These findings suggest GLUT1 and its binding partner TUBB4 as druggable targets that warrant further investigation in GBM.
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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".