Department of Laboratory Medicine, San Francisco General Hospital, San Francisco, CA 94110, USA.
Breast Cancer Res Treat. 2012 Jun;133(2):677-83. doi: 10.1007/s10549-012-1963-2.
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 co-medication 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-desmethyltamoxifen: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.
他莫昔芬是一种用于辅助乳腺癌治疗的前药，需要通过 CYP2D6 转化为活性代谢物依西美坦。我们旨在构建一种算法，根据患者的 CYP2D6 基因型、人口统计学因素和合并用药情况预测依西美坦浓度。本分析纳入了 UCSF TamGen II 研究的 88 名女性和 Dana-Farber 癌症研究所前瞻性研究的 81 名女性。所有女性在采血前至少服用他莫昔芬 3 个月。人口统计学信息包括患者的年龄、种族/民族、体重指数（如有）以及自我报告和测量的影响 2D6 活性的药物和草药。提取 DNA 并进行 2D6 基因分型（Amplichip，罗氏诊断）。根据基因型计算活性评分，并根据已知抑制 2D6 的药物使用情况进行调整。通过液相色谱/质谱法检测血清中的他莫昔芬及其代谢物浓度以及药物存在情况。对 UCSF 患者的训练数据集中的年龄、体重指数、种族和调整后的活性评分进行单变量和多变量回归分析，以预测他莫昔芬代谢物浓度，并在 Dana-Farber 患者中验证该算法。对于训练集，对数依西美坦和 N-去甲基他莫昔芬：依西美坦比值与活性评分、年龄和种族的相关系数（r2）分别为 0.520 和 0.659；验证集分别为 0.324 和 0.567；两个数据集的总和分别为 0.396 和 0.615。一种包含基因型和人口统计学变量的算法可用于预测接受他莫昔芬治疗的女性的依西美坦浓度。如果依西美坦水平被证实可预测他莫昔芬的获益，那么该算法可能有助于确定哪些女性需要进行依西美坦检测。
