NUDT15 Hydrolyzes 6-Thio-DeoxyGTP to Mediate the Anticancer Efficacy of 6-Thioguanine
Bibliographic record
Abstract
Thiopurines are a standard treatment for childhood leukemia, but like all chemotherapeutics, their use is limited by inherent or acquired resistance in patients. Recently, the nucleoside diphosphate hydrolase NUDT15 has received attention on the basis of its ability to hydrolyze the thiopurine effector metabolites 6-thio-deoxyGTP (6-thio-dGTP) and 6-thio-GTP, thereby limiting the efficacy of thiopurines. In particular, increasing evidence suggests an association between the NUDT15 missense variant, R139C, and thiopurine sensitivity. In this study, we elucidated the role of NUDT15 and NUDT15 R139C in thiopurine metabolism. In vitro and cellular results argued that 6-thio-dGTP and 6-thio-GTP are favored substrates for NUDT15, a finding supported by a crystallographic determination of NUDT15 in complex with 6-thio-GMP. We found that NUDT15 R139C mutation did not affect enzymatic activity but instead negatively influenced protein stability, likely due to a loss of supportive intramolecular bonds that caused rapid proteasomal degradation in cells. Mechanistic investigations in cells indicated that NUDT15 ablation potentiated induction of the DNA damage checkpoint and cancer cell death by 6-thioguanine. Taken together, our results defined how NUDT15 limits thiopurine efficacy and how genetic ablation via the R139C missense mutation confers sensitivity to thiopurine treatment in patients. Cancer Res; 76(18); 5501-11. ©2016 AACR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".