Developing <i>DPYD</i> Genotyping Method for Personalized Fluoropyrimidines Therapy
Bibliographic record
Abstract
BACKGROUND: Fluoropyrimidine drugs are widely used in chemotherapy to treat solid tumors. However, severe toxicity has been reported in 10% to 40% of patients. The DPYD gene encodes the rate-limiting enzyme dihydropyrimidine dehydrogenase responsible for fluoropyrimidine catabolism. The DPYD variants resulting in decreased or no enzyme activity are associated with increased risk of fluoropyrimidine toxicity. This study aims to develop a pharmacogenetic test for screening DPYD variants to guide fluoropyrimidine therapy. METHODS: A multiplex allele-specific polymerase chain reaction (AS-PCR) assay, followed by capillary electrophoresis, was developed to detect 5 common DPYD variants (c.557A > G, c.1129-5923C > G, c.1679T > G, c.1905 + 1G > A, and c.2846A > T). Deidentified population samples were used for screening positive controls and optimizing assay conditions. Proficiency testing samples with known genotypes were analyzed for test validation. All variants detected were confirmed by Sanger sequencing. RESULTS: From the deidentified population samples, 5 samples were heterozygous for c.557A > G, 2 samples were heterozygous for c.1129-5923C > G (HapB3), and 1 sample was heterozygous for c.2846A > T. The 20 proficiency samples matched with their assigned genotypes, including 13 wild-type samples, 3 samples heterozygous for c.1679T > G, 2 samples heterozygous for c.1905 + 1G > A, and 2 samples heterozygous for c.2846A > T. One of the 3 patient samples was heterozygous for c.1129-5923C > G (HapB3). All the variants detected by the multiplex AS-PCR assay were concordant with Sanger sequencing results. CONCLUSIONS: A robust multiplex AS-PCR assay was developed to rapidly detect 5 variants in the DPYD gene. It can be used for screening DPYD variants to identify patients with increased risk of toxicity when prescribed fluoropyrimidine therapy.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".