Tyrosine Kinase Inhibitors Reduce Glucose Uptake by Binding to an Exofacial Site on hGLUT‐1: Influence on <sup>18</sup>F‐FDG PET Uptake
Bibliographic record
Abstract
Positron emission tomography (PET) using 2‐deoxy‐2‐[ 18 F]fluoro‐ d ‐glucose ([ 18 F]FDG), a marker of energy metabolism and cell proliferation, is routinely used in the clinic to assess patient response to chemotherapy and to monitor tumor growth. Treatment with some tyrosine kinase inhibitors (TKIs) causes changes in blood glucose levels in both nondiabetic and diabetic patients. We evaluated the interaction of several classes of TKIs with human glucose transporter‐1 (hGLUT‐1) in FaDu and GIST‐1 cells by measuring [ 3 H]2‐deoxy‐ d ‐glucose ([ 3 H]2‐DG) and [ 3 H]FDG uptake. Uptake of both was inhibited to varying extents by the TKIs, and representative TKIs from each class showed competitive inhibition of [ 3 H]2‐DG uptake. In GIST‐1 cells, [ 3 H]FDG uptake inhibition by temsirolimus and nilotinib was irreversible, whereas inhibition by imatinib, gefitinib, and pazopanib was reversible. Molecular modeling studies showed that TKIs form multiple hydrogen bonds with polar residues of the sugar binding site (i.e., Q161, Q282, Q283, N288, N317, and W388), and van der Waals interactions with the H‐pocket site. Our results showed interaction of TKIs with amino acid residues at the glucose binding site to inhibit glucose uptake by hGLUT‐1. We hypothesize that inhibition of hGLUT‐1 by TKIs could alter glucose levels in patients treated with TKIs, leading to hypoglycemia and fatigue, although further studies are required to evaluate roles of other SLC2 and SLC5 members. In addition, TKIs could affect tumor [ 18 F]FDG uptake, increasingly used as a marker of tumor response. The hGLUT‐1 inhibition by TKIs may have implications for routine [ 18 F]FDG‐PET monitoring of tumor response in patients.
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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 | 0.001 |
| 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".