The International Tamoxifen Pharmacogenomics Consortium was established to address the controversy regarding cytochrome P450 2D6 (CYP2D6) status and clinical outcomes in tamoxifen therapy. We performed a meta-analysis on data from 4,973 tamoxifen-treated patients (12 globally distributed sites). Using strict eligibility requirements (postmenopausal women with estrogen receptor–positive breast cancer, receiving 20 mg/day tamoxifen for 5 years, criterion 1); CYP2D6 poor metabolizer status was associated with poorer invasive disease–free survival (IDFS: hazard ratio = 1.25; 95% confidence interval = 1.06, 1.47; P = 0.009). However, CYP2D6 status was not statistically significant when tamoxifen duration, menopausal status, and annual follow-up were not specified (criterion 2, n = 2,443; P = 0.25) or when no exclusions were applied (criterion 3, n = 4,935; P = 0.38). Although CYP2D6 is a strong predictor of IDFS using strict inclusion criteria, because the results are not robust to inclusion criteria (these were not defined a priori), prospective studies are necessary to fully establish the value of CYP2D6 genotyping in tamoxifen therapy.

The prevalence of genetic mutations among women with TNBC referred for genetic counseling is high and differs significantly by ethnicity/race and age. This data helps to refine mutation risk estimates among women with TNBC, allowing for more personalized genetic counseling potentially aiding in improved patient decision-making.

Tamoxifen decreases breast cancer recurrence, mortality, and breast cancer risk in high-risk women. Despite these proven benefits, tamoxifen use is often limited due to side effects. We identified predictors of tamoxifen-induced side effects based on clinical variables and serum tamoxifen metabolite biomarkers in a cross-sectional study of patients taking tamoxifen. We enrolled 241 women and collected data on demographics, tamoxifen use and side effects, as well as potential clinical and serum predictors. We used logistic regression models and adjusted for age, body mass index, ethnicity, education, prior post-menopausal hormone therapy, tamoxifen duration, and endoxifen levels to identify factors associated with side effects. Common tamoxifen attributed side effects were hot flashes (64%), vaginal dryness (35%), sleep problems (36%), weight gain (6%), and depression, irritability or mood swings (6%). In multi-variate models, tamoxifen duration, age, prior post-menopausal hormone therapy, and endoxifen levels all predicted side effects. Women who had been on tamoxifen for >12 months were less likely to report side effects (OR 0.15, 95% CI, 0.04–0.58) or severe side effects (OR 0.05, 95% CI, 0.005–0.58) compared to women on tamoxifen for <12 months. Compared to women younger than 50, women who were age 60–70 and older than 70 were less likely to report side effects (OR 0.22, 95% CI, 0.03–1.35; OR 0.13, 95% CI, 0.01–0.99; respectively). Women who previously took post-menopausal hormone therapy were more likely to report severe side effects. Women with higher endoxifen levels were more likely to report side effects (OR 1.67, 95% CI, 1.01–2.77 per standard deviation increase in endoxifen). Clinicians should consider closely monitoring adherence in women taking tamoxifen, especially in younger women, and women who previously took hormone therapy. The association between endoxifen levels and side effects is consistent with the data that suggest that endoxifen is the most highly active metabolite of tamoxifen.

Background: Genetic association studies using case-control designs are susceptible to false-positive and false-negative results if there are differences in genetic ancestry between cases and controls. We measured genetic ancestry among Latinas in a population-based case-control study of breast cancer and tested the association between ancestry and known breast cancer risk factors. We reasoned that if genetic ancestry is associated with known breast cancer risk factors, then the results of genetic association studies would be confounded. Methods: We used 44 ancestry informative markers to estimate individuals' genetic ancestry in 563 Latina participants. To test whether ancestry is a predictor of hormone therapy use, parity, and body mass index (BMI), we used multivariate logistic regression models to estimate odds ratios (OR) and 95% confidence intervals (95% CI) associated

Tamoxifen, a prodrug used for adjuvant breast cancer therapy, requires conversion to the active metabolite endoxifen through CYP 2D6. We aimed to construct an algorithm to predict endoxifen concentrations based on a patient’s CYP 2D6 genotype, demographic factors, and comedication use. Eighty-eight women enrolled in the UCSF TamGen II study and 81 women enrolled in a prospective study at Dana-Farber Cancer Institute were included in this analysis. All the women had been on tamoxifen for at least 3 months before blood collection. Demographic information included the patient’s age, race/ethnicity, body mass index (where available), and self-reported and measured medications and herbals that affect 2D6 activity. DNA was extracted and genotyped for 2D6 (Amplichip, Roche Diagnostics). An activity score was calculated based on genotypes and adjusted for use of medications known to inhibit 2D6. Serum was tested for tamoxifen and metabolite concentrations and for the presence of drugs by liquid chromatography/mass spectrometry. Univariate and multivariate regression analysis were computed for age, body mass index, ethnicity, and adjusted activity score to predict tamoxifen metabolite concentrations in the training data-set of UCSF patients, and the resulting algorithm was validated in the Dana-Farber patients. For the training set, the correlation coefficient (r2) for log endoxifen and N-desmethyl-tamoxifen:endoxifen ratio to activity score, age, and race, were 0.520 and 0.659, respectively; 0.324 and 0.567 for the validation; and 0.396 and 0.615 for both the datasets combined. An algorithm that incorporates genotype and demographic variables can be used to predict endoxifen concentrations for women on tamoxifen therapy. If endoxifen levels are confirmed to be predictive of tamoxifen benefit, then this algorithm may be helpful to determine which women warrant endoxifen testing.

BackgroundPharmacogenetic testing holds major promise in allowing physicians to tailor therapy to patients based on genotype. However, there is little data on the impact of pharmacogenetic test results on patient and clinician choice of therapy. CYP2D6 testing among tamoxifen users offers a potential test case of the use of pharmacogenetic testing in the clinic. We evaluated the effect of CYP2D6 testing in clinical practice to determine whether genotype results affected choice of hormone therapy in a prospective cohort study.MethodsWomen planning to take or currently taking tamoxifen were considered eligible. Participants were enrolled in an informational session that reviewed the results of studies of CYP2D6 genotype on breast cancer recurrence. CYP2D6 genotyping was offered to participants using the AmpliChip CYP450 Test. Women were classified as either poor, intermediate, extensive or ultra-rapid metabolizers. Results were provided to clinicians without specific treatment recommendations. Follow-up was performed with a structured phone interview 3 to 6 months after testing to evaluate changes in medication.ResultsA total of 245 women were tested and 235 completed the follow-up survey. Six of 13 (46%) women classified as poor metabolizers reported changing treatment compared with 11 of 218 (5%) classified as intermediate, extensive or ultra-rapid metabolizers (P < 0.001). There was no difference in treatment choices between women classified as intermediate and extensive metabolizers. In multi-variate models that adjusted for age, race/ethnicity, educational status, method of referral into the study, prior knowledge of CYP2D6 testing, the patients' CYP2D6 genotype was the only significant factor that predicted a change in therapy (odds ratio 22.8; 95% confidence interval 5.2 to 98.8). Genetic testing did not affect use of co-medications that interact with CYP2D6.ConclusionsCYP2D6 genotype testing led to changes in therapy among poor metabolizers, even in the absence of definitive data that an alternative medicine improved outcomes. Pharmacogenetic testing can affect choice of therapy, even in the absence of definitive data on clinical impact.

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