CYP3A4 and seasonal variation in vitamin D status in addition to CYP2D6 contribute to therapeutic endoxifen level during tamoxifen therapy

Wendy A. Teft, Inna Y. Gong, Brian Dingle, Kylea Potvin, Jawaid Younus, Theodore A. Vandenberg, Muriel Brackstone, Francisco E. Perera, Yun-Hee Choi, Guangyong Zou, Robin M. Legan, Rommel G. Tirona, Richard B. Kim

Tamoxifen is a widely utilized adjuvant anti-estrogen agent for hormone receptor-positive breast cancer, known to undergo CYP2D6-mediated bioactivation to endoxifen. However, little is known regarding additional genetic and non-genetic determinants of optimal endoxifen plasma concentration. Therefore, 196 breast cancer patients on tamoxifen were enrolled in this prospective study over a 24-month period. Blood samples were collected for pharmacogenetic and drug-level analysis of tamoxifen and metabolites. Regression analysis indicated that besides CYP2D6, the recently described CYP3A4*22 genotype, seasonal variation, and concomitant use of CYP2D6-inhibiting antidepressants were significant predictors of endoxifen concentration. Of note, genetic variation explained 33 % of the variability while non-genetic variables accounted for 13 %. Given the proposed notion of a sub-therapeutic endoxifen concentration for predicting breast cancer recurrence, we set the therapeutic threshold at 18 nM, the 20th percentile for endoxifen level among enrolled patients in this cohort. Nearly 70 % of CYP2D6 poor metabolizers as well as extensive metabolizers on potent CYP2D6-inhibiting antidepressants exhibited endoxifen levels below 18 nM, while carriers of CYP3A4*22 were twofold less likely to be in sub-therapeutic range. Unexpectedly, endoxifen levels were 20 % lower during winter months than mean levels across seasons, which was also associated with lower vitamin D levels. CYP3A4*22 genotype along with sunshine exposure and vitamin D status may be unappreciated contributors of tamoxifen efficacy. The identified covariates along with demographic variables were integrated to create an endoxifen concentration prediction algorithm to pre-emptively evaluate the likelihood of individual patients falling below the optimal endoxifen concentration.