Patient characteristics
A total of 667 female patients were enrolled in the CYPTAM study from February 2008 till December 2010 from 19 participating hospitals in The Netherlands and 6 hospitals in Belgium. The mean age of included patients was 56.4 years and in 79.5% were progesterone receptor-positive tumors. Table 1 lists the clinically and demographically relevant details of the CYPTAM patients.
Table 1 Baseline characteristics of the CYPTAM patients
CYP2D6 genotypes
Whole blood samples from 656 patients were available for genotyping. Of these, no genotype was obtained for 29 samples (4.4%), while for 637 patients (95.5%), CYP2D6 genotyping was successful, leading to a CYP2D6 predicted phenotype classification of 5 UMs (0.8%), 317 EMs (47.5%), 211 hetEMs (31.6%), 58 IMs (8.7%), and 47 PMs (7.0%).
CYP3A4 genotypes
The cohort consisted of 563 (84.4%) CYP3A4*1/*1 carriers, 73 (10.9%) CYP3A4*1/*22 carriers, and 1 (0.1%) CYP3A4*22/*22 carrier. Unfortunately, genotyping failed in 30 samples (4.5%). CYP3A4 frequency and genotyping in the study population are shown in Table 2. Genotype distributions were in Hardy-Weinberg equilibrium and no linkage disequilibrium was observed between the CYP3A4*22 single nucleotide polymorphism (SNP) and the CYP3A5*3 allele (LD < 0.1).
Table 2 Genotype distribution and frequency in the study population
CYP3A5 genotypes
Frequencies and distribution in the study population are listed in Table 2. The most frequent genotype was CYP3A5*3/*3, followed by CYP3A5*1/*3 and CYP3A5*1/*1, consisting of 554 (83.1%), 94 (14.1%), and 4 patients (0.6%), respectively. In 15 cases (2.2%), no genotype was obtained. Genotype distributions were in Hardy-Weinberg equilibrium and no linkage disequilibrium was observed between the CYP3A4*22 SNP and the CYP3A5*3 allele (LD < 0.1).
CYP3A4/CYP3A5 genotype clusters
C1, C2, C3, and C4 clusters were formed as described to analyze the additional combined effect of the CYP3A4 and CYP3A5 genotype on the CYP2D6 genotype. C1 consisted of 63 individuals (9.4%), 471 individuals for C2 (70.6%), 10 cases for C3 (1.5%), and 88 cases for C4 (13.2%). In 35 cases, no combined cluster could be made due to previous missing data.
Association of tamoxifen and its metabolites to CYP3A4 genotype, CYP3A5 genotype, and CYP3A4/5 combined genotypes
A substantial variation in the metabolic ratios of tamoxifen and its metabolites between individuals was observed. An overview of the mean and standard deviations (SD) of tamoxifen and its metabolite metabolic ratios by CYP3A4, CYP3A5 genotypes and CYP3A clusters is presented in Table 3.
Table 3 Summary of CYP3A4 and CYP3A5 covariate analysis
The metabolic ratio tamoxifen/NDM-tamoxifen was statistically different (p < 0.001) between CYP3A4*22/*22 and CYP3A4*1/*22 or CYP3A4*1/*1 individuals, whereas other metabolic ratios (tamoxifen/4-hydroxy-tamoxifen, 4-hydroxy-tamoxifen/endoxifen, and NDM-tamoxifen) did not show any difference. The metabolic ratios of tamoxifen did not show any difference between CYP3A5*1/*3 or CYP3A5*1/*1 and CYP3A5*3/*3 individuals (p > 0.05). Figure 2 shows the comparisons of tamoxifen and its metabolite metabolic ratios stratified by the CYP3A4 and CYP3A5 genotypes.
At the same time, only the metabolic ratio of tamoxifen/NDM-tamoxifen was significantly different among CYP3A4/5 combined genotypes (C1, C2, C3, and C4) (p < 0.001). The other metabolic ratios (tamoxifen/4-hydroxy-tamoxifen, 4-hydroxy-tamoxifen/endoxifen, and NDM-tamoxifen/endoxifen) did not significantly differ between the different CYP3A4/5 clusters. Figure 3 presents a comparison between the different CYP3A4/5 clusters by the diverse metabolic ratios.
The mean concentrations of tamoxifen, 4-hydroxy-tamoxifen, and NDM-tamoxifen of CYP3A4*22 carriers were statistically higher (p < 0.05). Endoxifen mean concentrations were not statistically higher (p = 0.088), but a trend toward higher endoxifen concentrations was observed among CYP3A4*22 individuals. An overview of mean concentrations of tamoxifen and its metabolites in the different groups is presented in Supplementary Table 1 and Supplementary Figs 1 and 2.
Association between metabolic ratios of tamoxifen and its metabolites to CYP2D6, CYP3A4/5, and combined genotypes
The explained variability (R
2) of (log-transformed) metabolic ratios of tamoxifen/NDM-tamoxifen, tamoxifen/4-hydroxy-tamoxifen, 4-hydroxy-tamoxifen/endoxifen, and NDM-tamoxifen/endoxifen due to genetic variations in CYP2D6 was 21.8%, 21.9%, 44.9%, and 57.0%, respectively.
A multiple linear regression indicated a combined analyses accounting for CYP2D6 and CYP3A4 (CYP3A4*22 and CYP3A4*1) genotypes significantly improved the prediction of the metabolic ratio tamoxifen/NDM-tamoxifen from 21.8 to 23.9%, whereas the explained variability for other metabolic ratios only showed marginal improvements.
Another multiple linear regression was used to test the effect of CYP2D6 and CYP3A5 (CYP3A5*3 and CYP3A5*1) genotypes together. However, no statistically significant difference of the explained variability was found (p > 0.05) compared to CYP2D6 alone.
In a third linear regression, the combined role of CYP2D6 and CYP3A clusters (C1, C2, C3, and C4) together was tested. Still, no significant improvements in the explained variability (R
2) were observed. A summary of CYP3A4, CYP3A5, and CYP3A covariate analysis is presented in Table 4.
Table 4 Overview of the means and standard deviations of tamoxifen, and its metabolite concentrations and metabolic ratios according to CYP3A4, CYP3A5 genotypes and CYP3A cluster
The explained variability (R
2) of (log-transformed) concentrations of tamoxifen, endoxifen, 4-hydroxy-tamoxifen, and NDM-tamoxifen due to genetic variations in CYP2D6, CYP3A4, and CYP3A5 genotype, and CYP3A combined genotypes is presented in Supplementary Table 2. The explained variability of (log-transformed) concentrations of endoxifen due to CYP3A4*22 genotype marginally increased from 42.3 to 42.8% (p < 0.001).