Metabolic imaging detects elevated glucose flux through the pentose phosphate pathway associated with TERT expression in low-grade gliomas
Bibliographic record
Abstract
BACKGROUND: Telomerase reverse transcriptase (TERT) is essential for tumor proliferation, including in low-grade oligodendrogliomas (LGOGs). Since TERT is silenced in normal cells, it is also a therapeutic target. Therefore, noninvasive methods of imaging TERT are needed. Here, we examined the link between TERT expression and metabolism in LGOGs, with the goal of leveraging this information for noninvasive magnetic resonance spectroscopy (MRS)-based metabolic imaging of LGOGs. METHODS: Immortalized normal human astrocytes with doxycycline-inducible TERT silencing, patient-derived LGOG cells, orthotopic tumors, and LGOG patient biopsies were studied to determine the mechanistic link between TERT expression and glucose metabolism. The ability of hyperpolarized [U-13C, U-2H]-glucose to noninvasively assess TERT expression was tested in live cells and orthotopic tumors. RESULTS: TERT expression was associated with elevated glucose flux through the pentose phosphate pathway (PPP), elevated NADPH, which is a major product of the PPP, and elevated glutathione, which is maintained in a reduced state by NADPH. Importantly, hyperpolarized [U-13C, U-2H]-glucose metabolism via the PPP noninvasively reported on TERT expression and response to TERT inhibition in patient-derived LGOG cells and orthotopic tumors. Mechanistically, TERT acted via the sirtuin SIRT2 to upregulate the glucose transporter GLUT1 and the rate-limiting PPP enzyme glucose-6-phosphate dehydrogenase. CONCLUSIONS: We have, for the first time, leveraged a mechanistic understanding of TERT-associated metabolic reprogramming for noninvasive imaging of LGOGs using hyperpolarized [U-13C, U-2H]-glucose. Our findings provide a novel way of imaging a hallmark of tumor immortality and have the potential to improve diagnosis and treatment response assessment for LGOG 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".