The xc− cystine/glutamate antiporter: a mediator of pancreatic cancer growth with a role in drug resistance
Bibliographic record
Abstract
The x(c)(-) cystine transporter enhances biosynthesis of glutathione, a tripeptide thiol important in drug resistance and cellular defense against oxidative stress, by enabling cellular uptake of cystine, a rate-limiting precursor. Because it is known to regulate glutathione levels and growth of various cancer cell types, and is expressed in the pancreas, we postulate that it is involved in growth and drug resistance of pancreatic cancer. To examine this, we characterised expression of the x(c)(-) transporter in pancreatic cancer cell lines, MIA PaCa-2, PANC-1 and BxPC-3, as subjected to cystine-depletion and oxidative stress. The results indicate that these cell lines depend on x(c)(-)-mediated cystine uptake for growth, as well as survival in oxidative stress conditions, and can modulate x(c)(-) expression to accommodate growth needs. Immunohistochemical analysis showed that the transporter was differentially expressed in normal pancreatic tissues and overexpressed in pancreatic cancer tissues from two patients. Furthermore, gemcitabine resistance of cells was associated with elevated x(c)(-) expression and specific x(c)(-) inhibition by monosodium glutamate led to growth arrest. The results suggest that the x(c)(-) transporter by enhancing glutathione biosynthesis plays a major role in pancreatic cancer growth, therapy resistance and represents a potential therapeutic target for the disease.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".