Impact of Metabolizing Enzymes on Drug Response of Endocrine Therapy in Breast Cancer

Pilar H Saladores; Jana C Precht; Werner Schroth; Hiltrud Brauch; Matthias Schwab

Disclosures

Expert Rev Mol Diagn. 2013;13(4):349-65. 

In This Article

Impact of CYP2D6 in Endocrine Therapy

The overwhelming evidence of the pharmacokinetic association between CYP2D6 genotype and plasma endoxifen levels has led to the focus of how CYP2D6 genotype translates to tamoxifen outcome. The current understanding is that CYP2D6 matters[54] based on a large study conducted in Germany and the USA.[41] The study included 1325 of mostly postmenopausal patients with ER-positive breast cancer who underwent tamoxifen monotherapy. Patients carrying at least one PM or IM allele had higher rates of recurrence, worse event-free survival and worse disease-free survival compared with those carrying two copies of EM alleles. Overall survival, however, was not statistically different when classified by CYP2D6 genotype. This retrospective study has recently been challenged by pharmacogenetic analyses performed in patients previously investigated for the superiority of tamoxifen versus AI, the ATAC and the BIG 1-98 trials.[55,56] Although these new pharmacogenetic studies did not observe a correlation between CYP2D6 and tamoxifen outcome, it has become clear that their data cannot be interpreted owing to serious methodological issues pointing to the critical issue of DNA source – that is, germline versus tumor genome.[54,57–59] The genomic region surrounding the CYP2D6 locus at chromosome 22q13 is frequently deleted in breast cancer, causing loss of heterozygosity.[60] As the BIG 1-98 and ATAC studies used DNA derived from FFPE,[55,56] the strong departure from Hardy–Weinberg equilibrium of CYP2D6*4 genotypes in their pharmacogenetic studies suggests that their genotyping most likely reflected the tumor and not the constitutional genotype, leading to errors in the prediction of CYP2D6 phenotype and consequently, to false-negative interpretation of study results. As it stands, subsequent studies must now be more carefully designed with regard to the source of DNA and CYP2D6 genotyping methods in order to produce reliable data and interpretation.

Another important issue within the context of molecular CYP2D6 diagnostics for tamoxifen metabolizer phenotype is the possibility of the misclassification of CYP2D6 phenotypes due to insufficient coverage of CYP2D6 alleles by genotyping. It has been clearly shown that it is not sufficient to genotype the *4 allele alone because this will either only detect 70% of PM or misclassify a substantial proportion of subjects (up to 30%) as the wrong phenotype.[40,61]

As discussed in the previous section, phenocopying is a major confounder of the CYP2D6 phenotype as comedication with inhibitors like SSRIs may result in diminished tamoxifen efficacy and decreased clinical benefit. Altogether, Table 4 summarizes the major confounders based on CYP2D6 genotype-predicted phenotypes that may impact tamoxifen outcome and have so far been discussed in this review. In addition, it is important to note that a single factor alone is not sufficient in explaining the frequently observed heterogeneity in CYP2D6 outcome studies. In fact, clinical outcome is influenced not only by genetic factors, but also by a combination of several nongenetic factors: combination therapies, nonadherence, increased tamoxifen dosing, AI switch during endocrine therapy and so on.[62]

While the technical issues require thorough attention in CYP2D6 genotyping, it is of interest that a most recent study showed that PMs derived a slight clinical benefit when switching from tamoxifen to AIs during their 5-year treatment compared with those who remained on tamoxifen for the entire duration of therapy.[63] This crossover study calls attention to the fact that AI use may be clinically advantageous, which is in line with the notion that CYP2D6 PM patients have less benefit from tamoxifen as compared with EM patients.[41] Therefore, CYP2D6 molecular diagnostics can provide a means to identify patients poorly responding to tamoxifen and allows for evidence-based assignments of AI treatment, thereby improving clinical outcome.

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