Effect of genetic variability in 20 pharmacogenes on concentrations of tamoxifen and its metabolites

Background: Tamoxifen, as a treatment of estrogen receptor positive (ER+) breast cancer, is a weak anti-estrogen that requires metabolic activation to form metabolites with higher anti-estrogenic activity. Endoxifen is the most-studied active tamoxifen metabolite, and endoxifen concentrations are highly associated with CYP2D6 activity. Associations of tamoxifen efficacy with measured or CYP2D6-predicted endoxifen concentrations have been inconclusive. Another active metabolite, 4-OHtam, and other, less active metabolites, Z-4′-endoxifen and Z-4′-OHtam, have also been reported to be associated with tamoxifen efficacy. Method: Genotype for 20 pharmacogenes was determined by VeriDose® Core Panel and VeriDose®CYP2D6 CNV Panel, followed by translation to metabolic activity phenotype following standard activity scoring. Concentrations of tamoxifen and seven metabolites were measured by UPLC-MS/MS in serum samples collected from patients receiving 20 mg tamoxifen per day. Metabolic activity was tested for association with tamoxifen and its metabolites using linear regression with adjustment for upstream metabolites to identify genes associated with each step in the tamoxifen metabolism pathway. Results: A total of 187 patients with genetic and tamoxifen concentration data were included in the analysis. CYP2D6 was the primary gene associated with the tamoxifen metabolism pathway, especially the conversion of tamoxifen to endoxifen. CYP3A4 and CYP2C9 were also responsible for the metabolism of tamoxifen. CYP2C9 especially impacted the hydroxylation to 4-OHtam, and this involved the OATP1B1 (SLCO1B1) transporter. Conclusion: Multiple genes are involved in tamoxifen metabolism and multi-gene panels could be useful to predict active metabolite concentrations and guide tamoxifen dosing.publishedVersio

Effect of genetic variability in 20 pharmacogenes on concentrations of tamoxifen and its metabolites

Background: Tamoxifen, as a treatment of estrogen receptor positive (ER+) breast cancer, is a weak anti-estrogen that requires metabolic activation to form metabolites with higher anti-estrogenic activity. Endoxifen is the most-studied active tamoxifen metabolite, and endoxifen concentrations are highly associated with CYP2D6 activity. Associations of tamoxifen efficacy with measured or CYP2D6-predicted endoxifen concentrations have been inconclusive. Another active metabolite, 4-OHtam, and other, less active metabolites, Z-4′-endoxifen and Z-4′-OHtam, have also been reported to be associated with tamoxifen efficacy. Method: Genotype for 20 pharmacogenes was determined by VeriDose® Core Panel and VeriDose®CYP2D6 CNV Panel, followed by translation to metabolic activity phenotype following standard activity scoring. Concentrations of tamoxifen and seven metabolites were measured by UPLC-MS/MS in serum samples collected from patients receiving 20 mg tamoxifen per day. Metabolic activity was tested for association with tamoxifen and its metabolites using linear regression with adjustment for upstream metabolites to identify genes associated with each step in the tamoxifen metabolism pathway. Results: A total of 187 patients with genetic and tamoxifen concentration data were included in the analysis. CYP2D6 was the primary gene associated with the tamoxifen metabolism pathway, especially the conversion of tamoxifen to endoxifen. CYP3A4 and CYP2C9 were also responsible for the metabolism of tamoxifen. CYP2C9 especially impacted the hydroxylation to 4-OHtam, and this involved the OATP1B1 (SLCO1B1) transporter. Conclusion: Multiple genes are involved in tamoxifen metabolism and multi-gene panels could be useful to predict active metabolite concentrations and guide tamoxifen dosing

Success predictors of adjuvant chemotherapy in node-negative breast cancer patients under 55 years

Abstract. Background: Adjuvant systemic chemotherapy (ASCT) in lymph node-negative breast (LN−) cancers improves survival. The majority of (LN−) patients receive ASCT when the St. Gallen criteria or its modifications are used, as accurate identifiers which patients benefit from ASCT are lacking. This may imply over-treatment in many patients. Aim: To evaluate which patients or primary tumor factors predict ASCT success. Material and method: Retrospective analysis by single and multivariate survival analysis of clinical and tumor characteristics in (LN−) breast cancers <55 years, related to ASCT (n = 125) or-not (n = 516). Results: The two patient groups did not differ in age, tumor diameter, grade, type, number of mitoses and other factors. Fourteen-year survival for the ASCT and non-ASCT patients was 83% and 74% (Hazard Ratio = HR = 0.33; p < 0.0001, 9% absolute = 12% relative difference). Subgroup analysis showed that the recurrence-free survival = RFS of ASCT treated vs. non-treated patients differed in patients with grade 1 cancers (p = 0.008), grade 2 cancers (p = 0.004), grades 3 (p = 0.02), tumors under and 2 cm (p = 0.001 and 0.0002), oestrogen receptor-positive or -negative tumors (p = 0.003, 0.04), MAI < 10 and 10 (p = 0.005, 0.003) and fibrotic focus absent (p = 0.002). With multivariate analysis the most important predictor of ASCT effect was the MAI. In patients with slowly proliferating tumors (MAI < 3) no advantage was found between patients treated-or-not with adjuvant chemotherapy (RFS = 92% and 91%, p = 0.13, p = 0.63 for overall survival), contrasting those with MAI 3 (p = 0.0001; HR = 0.32, 95% CI 0.18-0.58). Conclusion: MAI is the strongest predictor of adjuvant systemic chemotherapy success. In patients with MAI < 3 (31% of all patients), ASCT does not improve survival