Human concentrative nucleoside transporter 1-mediated uptake of 5-azacytidine enhances DNA demethylation
Bibliographic record
Abstract
The DNA methyltransferase inhibitors 5-azacytidine (5-azaCyd) and 5-aza-2'-deoxycytidine have found increasing use for the treatment of myeloid leukemias and solid tumors. Both nucleoside analogues must be transported into cells and phosphorylated before they can be incorporated into DNA and inactivate DNA methyltransferases. The members of the human equilibrative and concentrative nucleoside transporter families mediate transport of natural nucleosides and some nucleoside analogues into cells. However, the molecular identity of the transport proteins responsible for mediating the uptake of 5-azanucleosides has remained unknown. To this end, we have generated a stably transfected Madin-Darby canine kidney strain II cell line expressing recombinant hCNT1. An antiserum directed against hCNT1 specifically detected the protein in the apical membrane of hCNT1-expressing Madin-Darby canine kidney cells. Using [14C]5-azaCyd, we show here that hCNT1 mediated the Na+-dependent uptake of this drug with a Km value of 63 micromol/L. Na+-dependent transport of radiolabeled cytidine, uridine, and 5-fluoro-5'-deoxyuridine further showed the functionality of the transporter. hCNT1-expressing cells were significantly more sensitive to 5-azaCyd, and drug-dependent covalent trapping of DNA methyltransferase 1 was substantially more pronounced. Importantly, these results correlated with a significant sensitization of hCNT1-expressing cells toward the demethylating effects of 5-azaCyd and 5-aza-2'-deoxycytidine. In conclusion, our study identifies 5-azaCyd as a novel substrate for hCNT1 and provides direct evidence that hCNT1 is involved in the DNA-demethylating effects of this drug.
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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) | 0.001 | 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".