Glucose-dependent anaplerosis in cancer cells is required for cellular redox balance in the absence of glutamine
Bibliographic record
Abstract
Cancer cells have altered metabolism compared to normal cells, including dependence on glutamine (GLN) for survival, known as GLN addiction. However, some cancer cell lines do not require GLN for survival and the basis for this discrepancy is not well understood. GLN is a precursor for antioxidants such as glutathione (GSH) and NADPH, and GLN deprivation is therefore predicted to deplete antioxidants and increase reactive oxygen species (ROS). Using diverse human cancer cell lines we show that this occurs only in cells that rely on GLN for survival. Thus, the preference for GLN as a dominant antioxidant source defines GLN addiction. We show that despite increased glucose uptake, GLN addicted cells do not metabolize glucose via the TCA cycle when GLN is depleted, as revealed by (13)C-glucose labeling. In contrast, GLN independent cells can compensate by diverting glucose-derived pyruvate into the TCA cycle. GLN addicted cells exhibit reduced PDH activity, increased PDK1 expression, and PDK inhibition partially rescues GLN starvation-induced ROS and cell death. Finally, we show that combining GLN starvation with pro-oxidants selectively kills GLN addicted cells. These data highlight a major role for GLN in maintaining redox balance in cancer cells that lack glucose-dependent anaplerosis.
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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) | 0.000 | 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 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".