Single-Nucleotide Polymorphisms in <i>Aldo-Keto</i> and <i>Carbonyl Reductase</i> Genes Are Not Associated with Acute Cardiotoxicity after Daunorubicin Chemotherapy
Bibliographic record
Abstract
BACKGROUND: Evidence suggests that interpatient variability in anthracycline metabolic rate may contribute to the cardiotoxicity associated with anthracycline-based chemotherapy. Therefore, polymorphisms in the anthracycline metabolizing enzymes have been proposed as potential biomarkers of anthracycline-induced cardiotoxicity (AIC). METHODS: We have previously shown that 13 of the naturally occurring nonsynonymous single-nucleotide polymorphisms (nsSNP) in the aldo-keto reductases (AKR) and carbonyl reductases (CBR) reduce anthracycline metabolic rate in vitro. Here, we test these SNPs individually and jointly for association with daunorubicin-induced cardiotoxicity in patients with acute myeloid leukemia (AML). RESULTS: Five of the 13 nsSNPs exhibiting an in vitro effect on anthracycline metabolism were detected among the 185 patients with AML. No association was found between the SNPs and daunorubicin-induced cardiotoxicity in either individual or joint effect analyses. CONCLUSIONS: Despite the shown in vitro effect of nsSNPs in reductase genes on anthracycline metabolic rate, on their own these SNPs do not explain enough variability in cardiotoxicity to be useful markers of this adverse event. IMPACT: The results of this study provide important information for biomarker studies on side effects of anthracycline chemotherapy.
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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 | 0.001 |
| 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".