Genetic Variation in miR-27a Is Associated with Fluoropyrimidine-Associated Toxicity in Patients with Dihydropyrimidine Dehydrogenase Variants after Genotype-Guided Dose Reduction
Bibliographic record
Abstract
Dihydropyrimidine dehydrogenase (DPYD) is the rate-limiting enzyme involved in the metabolism of fluoropyrimidine-based chemotherapy. However, single-nucleotide variants (SNVs) in DPYD only partially explain fluoropyrimidine-induced toxicity. The expression of DPYD has previously been shown to be regulated by microRNA-27a (miR-27a) and a common miR-27a SNV (rs895819) has been associated with an increased risk of toxicity in patients harboring a DPYD variant who received standard fluoropyrimidine dosing. We investigated if the miR-27a rs895819 SNV was associated with toxicity in DPYD wildtype patients and carriers of DPYD variants who received a reduced dose. The regulation of DPYD using miR-27a was investigated in HepG2 cells utilizing a miR-27a mimic. miR-27a overexpression decreased DPYD mRNA expression compared to control cells (p < 0.0001). In a cohort of patients that received pre-emptive DPYD genotyping, 45 patients had a DPYD variant and 180 were wildtype. Patients heterozygous for rs895819 had an increased risk of toxicity, which was seen in both patients who were wildtype for DPYD variants (OR (95%CI) = 1.99 (1.00–3.99)) and DPYD variant carriers (OR (95%CI) = 8.10 (1.16–86.21)). Therefore, miR-27a rs895819 may be a clinically relevant predictor of fluoropyrimidine-associated toxicities. Furthermore, toxicity was more profound in DPYD variant carriers, even after DPYD genotype-guided dose reduction. This suggests that patients may benefit from miR-27a genotyping to guide fluoropyrimidine dosing.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".