Environmental cystine drives glutamine anaplerosis and sensitizes cells to glutaminase inhibition
Bibliographic record
Abstract
Abstract Many cancer cell lines depend on extracellular glutamine as a major tri-carboxylic acid (TCA) cycle anaplerotic substrate to support proliferation in vitro . However, recent studies have suggested that some cells that depend on glutamine anaplerosis in culture rely much less on glutamine catabolism to proliferate in vivo , with environmental differences between tumors and cell culture influencing the extent of glutamine catabolism. Here we sought to better understand the environmental differences that cause differential dependence on glutamine for TCA cycle anaplerosis. We find that cells cultured in adult bovine serum, a condition that more closely reflects the nutrients available to cells in vivo , leads to decreased glutamine catabolism and reliance on glutamine anaplerosis compared to standard tissue culture conditions. By analyzing the nutrient differences between bovine serum and media, we find that levels of a single nutrient, cystine, can account for the differential dependence on glutamine in these different environmental contexts. Further, we show that cystine levels dictate glutamine dependence via the cystine/glutamate antiporter xCT/ SLC7A11 , and that environmental cystine levels in conjunction with xCT/SLC7A11 expression is necessary and sufficient to drive increased glutamine anaplerosis, defining important determinants of glutamine anaplerosis and glutaminase dependence in cancer cells.
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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) | 0.002 | 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".