Evidence for Transcriptional Regulation of the Glucose-6-Phosphate Transporter by HIF-1<i>α</i>: Targeting G6PT with Mumbaistatin Analogs in Hypoxic Mesenchymal Stromal Cells
Bibliographic record
Abstract
Mesenchymal stromal cell (MSC) markers are expressed on brain tumor-initiating cells involved in the development of hypoxic glioblastoma. Given that MSCs can survive hypoxia and that the glucose-6-phosphate transporter (G6PT) provides metabolic control that contributes to MSC mobilization and survival, we investigated the effects of low oxygen (1.2% O(2)) exposure on G6PT gene expression. We found that MSCs significantly expressed G6PT and the glucose-6-phosphatase catalytic subunit beta, whereas expression of the glucose-6-phosphatase catalytic subunit alpha and the islet-specific glucose-6-phosphatase catalytic subunit-related protein was low to undetectable. Analysis of the G6PT promoter sequence revealed potential binding sites for hypoxia inducible factor (HIF)-1alpha and for the aryl hydrocarbon receptor (AhR) and its dimerization partner, the AhR nuclear translocator (ARNT), AhR:ARNT. In agreement with this, hypoxia and the hypoxia mimetic cobalt chloride induced the expression of G6PT, vascular endothelial growth factor (VEGF), and HIF-1alpha. Gene silencing of HIF-1alpha prevented G6PT and VEGF induction in hypoxic MSCs whereas generation of cells stably expressing HIF-1alpha resulted in increased endogenous G6PT gene expression. A semisynthetic analog of the polyketide mumbaistatin, a potent G6PT inhibitor, specifically reduced MSC-HIF-1alpha cell survival. Collectively, our data suggest that G6PT may account for the metabolic flexibility that enables MSCs to survive under conditions characterized by hypoxia and could be specifically targeted within developing tumors.
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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".