BIMG-05. TO BE OR NOT TO BE GLYCOLYTIC: DEUTERATED GLUCOSE-BASED ASSESSMENT OF THE WARBURG EFFECT ALLOWS NON-INVASIVE IMAGING OF TUMOR BURDEN AND TREATMENT RESPONSE IN MUTANT IDH GLIOMAS <i>IN VIVO</i>
Bibliographic record
Abstract
Abstract The Warburg effect, characterized by elevated glucose uptake and flux to lactate, is a metabolic hallmark of cancer. Recent studies have identified deuterium 2H-magnetic resonance spectroscopy (MRS) using 6,6’-2H-glucose as a novel method of imaging the Warburg effect in high-grade primary glioblastomas (GBMs). However, its utility for imaging low-grade gliomas has not been tested. The goal of this study was to determine whether 6,6’-2H-glucose can be used for imaging tumor burden and treatment response in mutant isocitrate dehydrogenase (IDHmut) low-grade gliomas in vivo. We examined mice bearing orthotopic tumors of the patient-derived BT257 astrocytoma model. 1H-MRS, providing a readout of steady-state metabolite levels, confirmed the presence of 2-hydroxyglutarate, the product of IDHmut, in BT257 tumor tissue but not normal brain. Previous studies comparing IDHmut gliomas with GBMs suggest that IDHmut gliomas undergo lactate dehydrogenase silencing, potentially leading to a non-glycolytic phenotype. Nevertheless, our results indicated that, compared to normal brain, glucose uptake and concomitant flux to lactate were significantly higher in BT257 tumor tissue. Importantly, 6,6’-2H-glucose metabolism to lactate was observed in BT257 tumor-bearing mice, but not tumor-free mice. Furthermore, imaging studies confirmed spatial localization of lactate production to the tumor vs. contralateral normal brain. We then examined the ability of 6,6’-2H-glucose to assess treatment response. Poly-(adenosine 5′-diphosphate-ribose) polymerase inhibitors (PARPi) inhibit IDHmut glioma growth and are in clinical trials for IDHmut glioma patients. Treatment with the PARPi niraparib reduced 6,6’-2H-glucose flux to lactate in BT257 tumor-bearing mice. Importantly, this reduction was observed at early time-points when no difference in tumor volume could be detected using anatomical imaging, pointing to the ability of 6,6’-2H-glucose to assess pseudoprogression. Collectively, our results suggest that IDHmut gliomas display a glycolytic phenotype amenable to non-invasive 2H-MRS-based imaging of tumor burden and treatment response.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".