Impact of <i>CYP2D6</i>, <i>CYP3A5</i>, <i>CYP2C9</i> and <i>CYP2C19</i> polymorphisms on tamoxifen pharmacokinetics in Asian breast cancer patients
Notice bibliographique
Résumé
WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • Tamoxifen is metabolized to active metabolites, 4‐hydroxytamoxifen and endoxifen, by multiple cytochrome P450 (CYP) enzymes including CYP2D6, CYP3A4/5, CYP2C9/19, CYP1A2 and CYP2B6. • The steady‐state plasma concentrations of tamoxifen and its metabolites can be affected by variations in the activity of these enzymes. • Although CYP2D6*4 and *10 have been shown to influence the plasma concentration of endoxifen in Caucasian and Korean patients respectively, there is still a paucity of data on CYP2D6 pharmacogenetics in other Orientals such as Chinese, Malays and Indians. WHAT THIS STUDY ADDS • Pharmacogenetic analyses of a comprehensive panel of CYP2D6 polymorphisms (*2, *2A, *3, *4, *5, *6, *7, *8, *9, *10, *12, *14, *17, *29, *41 and *xN) were performed in three distinct Asian ethnic groups and breast cancer patients with CYP2D6*5 and *10 found to be highly prevalent. • Both CYP2D6*5 and *10 were significantly associated with lower endoxifen and higher N‐desmethyltamoxifen concentrations as well as a lower rate of metabolic conversion of N‐desmethyltamoxifen to endoxifen. • Polymorphisms present in CYP3A5, CYP2C9 and CYP2C19 were not found to be significantly associated with plasma concentrations of analytes suggesting that these enzymes may be playing minor roles in the metabolic pathway of tamoxifen compared with CYP2D6. AIM To investigate the impact of genetic polymorphisms in CYP2D6, CYP3A5, CYP2C9 and CYP2C19 on the pharmacokinetics of tamoxifen and its metabolites in Asian breast cancer patients. METHODS A total of 165 Asian breast cancer patients receiving 20 mg tamoxifen daily and 228 healthy Asian subjects (Chinese, Malay and Indian; n= 76 each) were recruited. The steady‐state plasma concentrations of tamoxifen and its metabolites were quantified using high‐performance liquid chromatography. The CYP2D6 polymorphisms were genotyped using the INFINITI™ CYP450 2D6I assay, while the polymorphisms in CYP3A5, CYP2C9 and CYP2C19 were determined via direct sequencing. RESULTS The polymorphisms, CYP2D6*5 and *10, were significantly associated with lower endoxifen and higher N‐desmethyltamoxifen (NDM) concentrations. Patients who were *1/*1 carriers exhibited 2.4‐ to 2.6‐fold higher endoxifen concentrations and 1.9‐ to 2.1‐fold lower NDM concentrations than either *10/*10 or *5/*10 carriers (P < 0.001). Similarly, the endoxifen concentrations were found to be 1.8‐ to 2.6‐times higher in *1/*5 or *1/*10 carriers compared with *10/*10 and *5/*10 carriers (P≤ 0.001). Similar relationships were observed between the CYP2D6 polymorphisms and metabolic ratios of tamoxifen and its metabolites. No significant associations were observed with regards to the polymorphisms in CYP3A5, CYP2C9 and CYP2C19. CONCLUSIONS The present study in Asian breast cancer patients showed that CYP2D6*5/*10 and *10/*10 genotypes are associated with significantly lower concentrations of the active metabolite of tamoxifen, endoxifen. Identifying such patients before the start of treatment may be useful in optimizing therapy with tamoxifen. The role of CYP3A5, CYP2C9 and CYP2C19 seem to be minor.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».