Two Distinct Molecular Mechanisms Underlying Cytarabine Resistance in Human Leukemic Cells
Bibliographic record
Abstract
To understand the mechanism of cellular resistance to the nucleoside analogue cytarabine (1-beta-D-arabinofuranosylcytosine, AraC), two resistant derivatives of the human leukemic line CCRF-CEM were obtained by stepwise selection in different concentrations of AraC. CEM/4xAraC cells showed low AraC resistance, whereas CEM/20xAraC cells showed high resistance. Both cell lines showed similar patterns of cross-resistance to multiple cytotoxic nucleoside analogues, with the exception that CEM/20xAraC cells remained sensitive to 5-fluorouridine and 2-deoxy-5-fluorouridine. Both cell lines were sensitive to 5-fluorouracil and to a variety of natural product drugs. Although both CEM/4xAraC and CEM/20xAraC cells displayed reduced intracellular accumulation of [(3)H]AraC, only CEM/4xAraC cells showed reduced uptake of [(3)H]uridine, which was used to assess nucleoside transport activities. Genes encoding proteins known to be involved in nucleoside transport, efflux, and metabolism were analyzed for the presence of mutations in the two cell lines. In CEM/4xAraC cells, independent mutations were identified at each allele of human equilibrative nucleoside transporter 1 (hENT1; SLC29A1), one corresponding to a single-nucleotide change in exon 4, the other being a complex intronic mutation disrupting splicing of exon 13. In contrast to CEM/20xAraC cells, CEM/4xAraC cells did not bind the hENT1/SLC29A1 ligand nitrobenzylmercaptopurine ribonucleoside and lacked detectable hENT1/SLC29A1 protein. In CEM/20xAraC cells, independent intronic mutations impairing splicing of exons 2 and 3 were found at each allele of the deoxycytidine kinase gene. These studies point to at least two distinct mechanisms of AraC resistance in leukemic 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".