Dataset Information

The formation of estrogen-like tamoxifen metabolites and their influence on enzyme activity and gene expression of ADME genes.

ABSTRACT: Tamoxifen, a standard therapy for breast cancer, is metabolized to compounds with anti-estrogenic as well as estrogen-like action at the estrogen receptor. Little is known about the formation of estrogen-like metabolites and their biological impact. Thus, we characterized the estrogen-like metabolites tamoxifen bisphenol and metabolite E for their metabolic pathway and their influence on cytochrome P450 activity and ADME gene expression. The formation of tamoxifen bisphenol and metabolite E was studied in human liver microsomes and Supersomes™. Cellular metabolism and impact on CYP enzymes was analyzed in upcyte® hepatocytes. The influence of 5 µM of tamoxifen, anti-estrogenic and estrogen-like metabolites on CYP activity was measured by HPLC MS/MS and on ADME gene expression using RT-PCR analyses. Metabolite E was formed from tamoxifen by CYP2C19, 3A and 1A2 and from desmethyltamoxifen by CYP2D6, 1A2 and 3A. Tamoxifen bisphenol was mainly formed from (E)- and (Z)-metabolite E by CYP2B6 and CYP2C19, respectively. Regarding phase II metabolism, UGT2B7, 1A8 and 1A3 showed highest activity in glucuronidation of tamoxifen bisphenol and metabolite E. Anti-estrogenic metabolites (Z)-4-hydroxytamoxifen, (Z)-endoxifen and (Z)-norendoxifen inhibited the activity of CYP2C enzymes while tamoxifen bisphenol consistently induced CYPs similar to rifampicin and phenobarbital. On the transcript level, highest induction up to 5.6-fold was observed for CYP3A4 by tamoxifen, (Z)-4-hydroxytamoxifen, tamoxifen bisphenol and (E)-metabolite E. Estrogen-like tamoxifen metabolites are formed in CYP-dependent reactions and are further metabolized by glucuronidation. The induction of CYP activity by tamoxifen bisphenol and the inhibition of CYP2C enzymes by anti-estrogenic metabolites may lead to drug-drug-interactions.

SUBMITTER: Johanning J

PROVIDER: S-EPMC5866846 | biostudies-other | 2018 Mar

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

The formation of estrogen-like tamoxifen metabolites and their influence on enzyme activity and gene expression of ADME genes.

Johänning Janina J Kröner Patrick P Thomas Maria M Zanger Ulrich M UM Nörenberg Astrid A Eichelbaum Michel M Schwab Matthias M Brauch Hiltrud H Schroth Werner W Mürdter Thomas E TE

Archives of toxicology 20171228 3

Tamoxifen, a standard therapy for breast cancer, is metabolized to compounds with anti-estrogenic as well as estrogen-like action at the estrogen receptor. Little is known about the formation of estrogen-like metabolites and their biological impact. Thus, we characterized the estrogen-like metabolites tamoxifen bisphenol and metabolite E for their metabolic pathway and their influence on cytochrome P450 activity and ADME gene expression. The formation of tamoxifen bisphenol and metabolite E was ...[more]

PMID: 29285606

Similar Datasets

Project description:Angus-cross steers (n = 144; 359 kg ± 13.4) were used to assess the effect of dietary Mn and steroidal implants on performance, trace minerals (TM) status, hepatic enzyme activity, hepatic gene expression, and serum metabolites. Steers (n = 6/pen) were stratified by BW in a 3 × 2 factorial. GrowSafe bunks recorded individual feed intake (experimental unit = steer; n = 24/treatment). Dietary treatments included (MANG; 8 pens/treatment; Mn as MnSO4): (1) no supplemental Mn (analyzed 14 mg Mn/kg DM; Mn0); (2) 20 mg supplemental Mn/kg DM (Mn20); (3) 50 mg supplemental Mn/kg DM (Mn50). Within MANG, steers received a steroidal implant treatment (IMP) on day 0: (1) no implant; NO; or (2) combination implant (Revalor-200; REV). Liver biopsies for TM analysis and qPCR, and blood for serum glucose, insulin, non-esterified fatty acids, and urea-N (SUN) analysis were collected on days 0, 20, 40, and 77. Data were analyzed as a randomized complete block with a factorial arrangement of treatments including fixed effects of Mn treatment (MANG) and implant (IMP) using PROC MIXED of SAS 9.4 using initial BW as a covariate. Liver TM, serum metabolite, enzyme activity, and gene expression data were analyzed as repeated measures. No MANG × IMP effects were noted (P ≥ 0.12) for growth performance or carcass characteristic measures. Dietary Mn did not influence final body weight, overall ADG, or overall G:F (P ≥ 0.14). Liver Mn concentration increased with supplemental Mn concentration (MANG; P = 0.01). An IMP × DAY effect was noted for liver Mn (P = 0.01) where NO and REV were similar on day 0 but NO cattle increased liver Mn from days 0 to 20 while REV liver Mn decreased. Relative expression of MnSOD in the liver was greater in REV (P = 0.02) compared to NO and within a MANG × IMP effect (P = 0.01) REV increased liver MnSOD activity. These data indicate current NASEM Mn recommendations are adequate to meet the demands of finishing beef cattle given a steroidal implant. Despite the roles of Mn in metabolic pathways and antioxidant defense, a basal diet containing 14 mg Mn/kg DM was sufficient for the normal growth of finishing steers. This study also provided novel insight into how implants and supplemental Mn influence genes related to arginine metabolism, urea synthesis, antioxidant capacity, and TM homeostasis as well as arginase and MnSOD activity in hepatic tissue of beef steers.

Project description:BackgroundEstrogen receptors alpha (ER) are implicated in many types of female cancers, and are the common target for anti-cancer therapy using selective estrogen receptor modulators (SERMs, such as tamoxifen). However, cell-type specific and patient-to-patient variability in response to SERMs (from suppression to stimulation of cancer growth), as well as frequent emergence of drug resistance, represents a serious problem. The molecular processes behind mixed effects of SERMs remain poorly understood, and this strongly motivates application of systems approaches. In this work, we aimed to establish a mathematical model of ER-dependent gene expression to explore potential mechanisms underlying the variable actions of SERMs.ResultsWe developed an equilibrium model of ER binding with 17β-estradiol, tamoxifen and DNA, and linked it to a simple ODE model of ER-induced gene expression. The model was parameterised on the broad range of literature available experimental data, and provided a plausible mechanistic explanation for the dual agonism/antagonism action of tamoxifen in the reference cell line used for model calibration. To extend our conclusions to other cell types we ran global sensitivity analysis and explored model behaviour in the wide range of biologically plausible parameter values, including those found in cancer cells. Our findings suggest that transcriptional response to tamoxifen is controlled in a complex non-linear way by several key parameters, including ER expression level, hormone concentration, amount of ER-responsive genes and the capacity of ER-tamoxifen complexes to stimulate transcription (e.g. by recruiting co-regulators of transcription). The model revealed non-monotonic dependence of ER-induced transcriptional response on the expression level of ER, that was confirmed experimentally in four variants of the MCF-7 breast cancer cell line.ConclusionsWe established a minimal mechanistic model of ER-dependent gene expression, that predicts complex non-linear effects in transcriptional response to tamoxifen in the broad range of biologically plausible parameter values. Our findings suggest that the outcome of a SERM's action is defined by several key components of cellular micro-environment, that may contribute to cell-type-specific effects of SERMs and justify the need for the development of combinatorial biomarkers for more accurate prediction of the efficacy of SERMs in specific cell types.

Dataset Information

The formation of estrogen-like tamoxifen metabolites and their influence on enzyme activity and gene expression of ADME genes.

Publications

The formation of estrogen-like tamoxifen metabolites and their influence on enzyme activity and gene expression of ADME genes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets