B-251 Clinical Implementation and Outcome Assessment of DPYD Pharmacogenomic Testing to Guide Fluoropyrimidines Dosing for Cancer Patients in Saskatchewan
Notice bibliographique
Résumé
Abstract Background 5-Fluorouracil (5-FU) and its prodrug Capecitabine are widely used chemotherapy drugs for treating various solid tumours, including colorectal, breast, and gastrointestinal cancers). Annually, around two million patients receive treatment with these drugs. However, a significant challenge with 5-FU treatment is toxicity. Between 10-30% of patients experience severe side effects, and in about 0.5-1% of cases, these toxicities can become life-threatening. The primary cause of this toxicity is a deficiency in the enzyme Dihydropyrimidine Dehydrogenase (DPD), critical for metabolizing 5-FU. Variants in the DPYD gene, which encodes DPD, reduce or lose the enzyme activity of DPD. Patients with DPD enzyme deficiency are at great risk of severe toxicity. In this study, we validated and implemented the DPYD genotyping assay for cancer patients in Saskatchewan, Canada, to guide fluoropyrimidine dosing. We further assessed the clinical outcome post-implementation in Saskatchewan. Methods Six clinically relevant variants of the DPYD gene associated with DPD deficiency recommended by the 2017 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline were included in the assay (transcript NM_000110.4), including *2A (rs3918290; c.1905+1G>A), *13 (rs55886062; c.1679T>G), c.2846A>T (rs67376798), and c.1129-5923C>G (rs75017182). The HapB3 haplotype was assessed by the c.1129-5923C>G (rs75017182) variant in combination with c.1236G>A (rs56038477) and c.483+18G>A (rs56276561). The Elucigene DPYD genotyping kit (Yourgene Health, UK) was used to detect these six semi-qualitatively. The validation process follows the technical standards for clinical pharmacogenomic testing and reporting established by the American College of Medical Genetics and Genomics. The assay*s sensitivity, specificity, accuracy, repeatability and reproducibility in detecting DPYD variants were included. Six months post-implementation of DPYD genotyping assays, patient outcomes were retrospectively evaluated. Patient demographics and clinical data were collected, including tumour types and staging, treatment regimen and dosage adjustment based on DPYD genotyping lab results, and toxicity incidence. This study adhered to institutional ethics guidelines. Results The DPYD pharmacogenomic assay demonstrated excellent performance with 100% sensitivity, specificity, accuracy, reproducibility, and repeatability. The detection limit was 1.25 ng/µL of DNA, ensuring high sensitivity. Over six months, 301 patient samples were tested, identifying 22 patients carrying at least one of the six DPYD variants. The most frequently observed allele was the HapB3 heterozygous genotype detected in 18 patients (5.9%). All detected variants exhibited reduced function or no function, with assigned DPD activity scores ranging from 1 to 1.5, indicating impaired fluoropyrimidines metabolism. Outcomes were evaluated for 21 enzyme-deficient patients, with 5-FU dose adjustments applied clinically. The majority of patients tolerate chemotherapy well without significant toxicity. Outcome evaluation for the 301 tested patients is ongoing. Conclusion DPYD testing allows for the early detection of DPD deficiencies, allowing personalized chemo drug dosing. These approaches improve patient outcomes and reduce the risk of severe side effects, highlighting the important roles in pharmacogenomics in personalized cancer treatment.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».