nach oben

Breast Cancer Research and Treatment

Erschienen in:

Open Access 17.08.2018 | Clinical trial

Genetic polymorphisms of 3′-untranslated region of SULT1A1 and their impact on tamoxifen metabolism and efficacy

verfasst von: A. B. Sanchez-Spitman, V. O. Dezentjé, J. J. Swen, D. J. A. R. Moes, H. Gelderblom, Henk-Jan Guchelaar

Erschienen in: Breast Cancer Research and Treatment | Ausgabe 2/2018

Abstract

Purpose

Tamoxifen has a wide inter-variability. Recently, two SNPs in the 3′-untranslated region (UTR) of the SULT1A1 gene, rs6839 and rs1042157, have been associated with decreased SULT1A1 activity. The aim of this study is to investigate the role of the rs6839 and rs1042157 on tamoxifen metabolism and relapse-free survival (RFS) in women diagnosed with early-breast cancer receiving tamoxifen.

Methods

Samples from 667 patients collected in the CYPTAM study (NTR1509) were used for genotyping (CYP2D6, SULT1A1 rs6839 and rs1042157) and measurements of tamoxifen and metabolites. Patients were categorized in three groups depending on the decreased SULT1A1 activity due to rs6839 and rs1042157: low activity group (rs6839 (GG) and rs1042157 (TT)); high activity group (rs6839 (AA) and rs1042157 (CC)); and medium activity group (all the other combinations of rs6839 and rs1042157). Associations between SULT1A1 phenotypes and clinical outcome (RFS) were explored.

Results

In the low SULT1A1 activity group, higher endoxifen and 4-hydroxy-tamoxifen concentrations were found, compared to the medium and high activity group (endoxifen: 31.23 vs. 30.51 vs. 27.00, p value: 0.016; 4-hydroxy-tamoxifen: 5.55 vs. 5.27 vs. 4.94, p value:0.05). In terms of relapse, the low activity group had a borderline better outcome compared to the medium and high SULT1A1 activity group (adjusted Hazard ratio: 0.297; 95% CI 0.088–1.000; p value: 0.05).

Conclusion

Our results suggested that rs6839 and rs1042157 SNPs have a minor effect on the concentrations and metabolic ratios of tamoxifen and its metabolites, and RFS in women receiving adjuvant tamoxifen.

Supplementary material 1 (DOCX 15 KB)

Supplementary material 2 (DOCX 14 KB)

Electronic supplementary material

The online version of this article (https://doi.org/10.1007/s10549-018-4923-7) contains supplementary material, which is available to authorized users.

Introduction

Tamoxifen is commonly used as adjuvant endocrine therapy to treat patients diagnosed with breast cancer [1, 2]. Being a prodrug, tamoxifen is bioactivated by several cytochrome P-450 enzymes to its primary metabolites, 4-hydroxy-tamoxifen, and N-desmethyl-tamoxifen (NDM-tamoxifen). Thereafter, conversion into endoxifen takes place (Fig. 1), mainly controlled by CYP2D6, among other enzymes. Around 92% of tamoxifen metabolism accounts for the biotransformation of tamoxifen into NDM-tamoxifen, whereas the conversion of tamoxifen into 4-hydroxy-tamoxifen only represents 7% [3].

Both endoxifen and 4-hydroxy-tamoxifen have equal affinity for the estrogen receptor α [4], but endoxifen is considered the most clinically relevant tamoxifen metabolite, since it is found in 5–10 times higher concentrations than 4-hydroxy-tamoxifen [5]. While CYP2D6 is the rate-limiting enzyme in tamoxifen metabolism, it cannot fully explain the inter-patient variability of tamoxifen metabolism [6]. Other genetic polymorphisms in different enzymes than CYP2D6 have been suggested to influence tamoxifen metabolism as well [7].

Sulfotransferases (SULTs) are classified as phase II enzymes involved in the biotransformation of a variety of drugs [7, 8]. By adding a sulfonyl group to xeno- and endobiotics, more hydrophilic molecules are obtained facilitating their renal excretion [8, 9]. SULT1A1 is the most expressed isoform of the SULT enzymes in the human liver [10, 11]. In tamoxifen metabolism, SULT1A1 mainly catalyzes the transformation of 4-hydroxy-tamoxifen into inactive 4-hydroxy-tamoxifen sulfate and endoxifen into inactive endoxifen sulfate (Fig. 1). In addition, SULT1A1 is also involved in the inactivation of NDM-tamoxifen, after several consecutive reactions, into Metabolite E sulfate [3, 9, 12, 13].

Several SULT1A1 Single-Nucleotide Polymorphisms (SNPs) have been described and found associated with clinical outcome in tamoxifen-treated patients. Nowell [14] and Wegman [15] reported that SULT1A1*2/*2 carriers had worse outcome in breast cancer patients treated with tamoxifen compared to both homozygous and heterozygous SULT1A1*1 carriers. However, studies performed later did not reproduce these results, since no significant associations were found [16‐18]. Consequently, the effect of SULT1A1 and clinical outcome among tamoxifen-treated patients is still unclear.

SULT1A1 genetic variation and its influence on tamoxifen and its metabolites concentrations and metabolic ratios (MR) have been described. While Jin [19] and Fernandez-Santander [20] showed no association between SULT1A1 genotypes and tamoxifen and its metabolites concentrations, Gjerde and colleagues found an association between SULT1A1 genotype and the metabolic ratios (MR) of NDM-tamoxifen/tamoxifen (Fig. 1) [21].

In the same manner, copy number variation in SULT1A1 has been described as a prominent contributor to the inter-variability of SULT1A1 enzymatic activity [22]. Hebbring and colleagues reported an in vitro association between CNV and SULT1A1 enzyme activity. The role of SULT1A1 CNVs in tamoxifen efficacy has also been examined, but no significant relationship after 14 years of follow-up between disease-free survival and SULT1A1 CNVs was found [22]. However, this result might be explained by ethnic differences in the enrolled women, who were primarily Caucasian. Indeed, SULT1A1 CNV is most frequently seen in African-American individuals, but infrequently occurs in other ethnicities [22].

Recently, two other SULT1A1 SNPs, rs6839 and rs1042157, have been identified and characterized in the 3′-untranslated region (UTR) of the SULT1A1 gene [23]. According to the authors, both SNPs are in linkage disequilibrium (D′ = 0.83) and associated with decreased activity of the SULT1A1 enzymatic activity. To date, only two studies have analyzed the effect of both SNPs and cancer risk [24, 25].

To the best of our knowledge, the role of rs6839 and rs1042157 in tamoxifen metabolism and RFS has not yet been examined. Therefore, the aim of the current study is to explore the role of the rs6839 and rs1042157 SNPs on tamoxifen pharmacokinetics and RFS in the CYPTAM cohort of women with early breast cancer using adjuvant tamoxifen [26, 27].

Methods

Study design and objectives: effect of 3′-UTR of SULT1A1 SNPs on tamoxifen metabolism and clinical outcome.

The CYPTAM study (NTR1509) is a completed prospective clinical study carried out in Belgium and The Netherlands [26]. The aim of this clinical study was to investigate CYP2D6 predicted phenotypes and endoxifen serum concentrations with clinical outcome (relapse-free and disease-free survival, and overall survival). Briefly, women using tamoxifen at a daily dose of 20 mg as adjuvant endocrine therapy for early breast cancer were asked to participate in this multicenter study. The study protocol of the CYPTAM study was approved by The Medical Ethical Committee of the Leiden University Medical Center (The Netherlands). Written informed consent was obtained from all of the included patients. Pregnancy, breast feeding, and previous malignancy were considered exclusion criteria, with the exception of appropriately treated patients with in-situ cervix carcinoma and basal cell carcinoma. After receiving tamoxifen for a minimum of two months, whole blood and serum samples were collected for genotyping and determination of tamoxifen and its metabolites (NDM-tamoxifen, 4-hydroxy-tamoxifen and endoxifen), respectively.

To investigate the role of rs6839 and rs1042157 SNPs, serum and whole blood samples and clinical data and follow-up from women enrolled in the CYPTAM were readily available for analysis. Since both rs6839 and rs1042157 SNPs are in linkage disequilibrium, groups were required in order to understand the combined effect of both SNPs on tamoxifen metabolism and efficacy. Therefore, three different groups were made according to the known effect of rs6839 and rs1042157 on SULT1A1 enzyme activity. These groups were defined as low, medium, and high SULT1A1 activity groups, as follows: low activity group was defined as the combination of rs6839 (GG) and rs1042157 (TT); high activity group was compound by rs6839 (AA) and rs1042157 (CC); medium activity group was formed by the following combinations: rs6839 (AG) and rs1042157 (CC); rs6839 (AA) and rs1042157 (CT); rs6839 (AG) and rs1042157 (CT); rs6839 (GG) and rs1042157 (CT); rs6839 (AA) and rs1042157 (TT); and rs6839 (AG) and rs1042157 (TT).

The first objective of this pharmacogenetic study was to compare the combined effect of both SNPs on tamoxifen metabolism by comparing differences in endoxifen concentrations and metabolic ratios of tamoxifen and its metabolites (NDM-tamoxifen, 4-hydroxy-tamoxifen, and endoxifen) across the different groups. The secondary objective of this research was to investigate the impact of the 3′- UTR SULT1A1 SNPs groups on tamoxifen efficacy. In the CYPTAM study, the primary endpoint was relapse-free survival (RFS), defined as the time from study enrolment until loco-regional recurrence, second breast cancer, or distant recurrence. If patients switched to an aromatase inhibitor, patients were censored at the time of tamoxifen discontinuation [26].

Tamoxifen and its metabolites measurements

In order to ensure tamoxifen and metabolite steady-state concentrations, a minimum of two-month treatment with tamoxifen was required before sampling. To adequately assess tamoxifen and its metabolites trough levels, samples were collected at least twelve hours after the last tamoxifen intake.

Concentrations were determined using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The bioanalytical assay was developed and validated by the laboratory of Clinical Pharmacy and Toxicology Department at Leiden University Medical Center, and it is a method comparable to another method already reported [28].

Genotyping: CYP2D6, rs6839, and rs1042157

CYP2D6 genotyping was performed with Amplichip CYP450 test (Roche Diagnostic, Indianapolis, US) to evaluate the major CYP2D6 alleles in DNA previously retrieved from the CYPTAM patients. More detailed information regarding the CYP2D6 genotypes is described elsewhere [29, 30]. Genotype analysis for rs6839 and rs1042157 was performed using Pyrosequencing (Qiagen, Venlo, The Netherlands) following standard procedures and the instructions of the manufacturer.

Statistical analysis

To test linkage disequilibrium between both rs6839 and rs1042157, D′ was calculated with Chi-square statistics (χ²). Metabolic ratios were defined as concentration of substrate divided by metabolite concentration. ANOVA test was used to compare mean concentration levels and metabolic ratios of tamoxifen and its metabolites (NDM-tamoxifen, 4-hydroy-tamoxifen and endoxifen) between the low, medium, and high SULT1A1 activity groups. Multiple linear regression analysis was used to analyze the contributions of rs6839 and rs1042157. By using the base model in which the CYP2D6 status only partly contributes to explaining the total variability of concentrations and metabolic ratios of tamoxifen, endoxifen, 4-hydroxy-tamoxifen, and NDM-tamoxifen, these 3′-UTR SULT1A1 rs6839 and rs1042157 SNPs were added to the model to investigate their effects on the total variance.

Cox regression analysis was performed to assess whether RFS varied according to the different baseline characteristics across all the groups. If in the univariable analysis, a covariable had a p value below 0.1, this covariable was fitted in the multivariable model. Due to their clinical importance for the survival outcome in breast cancer patients, tumor and nodal stage, Her2 receptor status, and histological grade and classification were also included in the multivariable analysis, regardless of the results in the univariable analysis. Kaplan–Meier method was used to estimate the distributions of RFS, whereas a log-rank test was performed to compare the clinical outcome with genetic 3′-UTR SULT1A1 rs6839 and rs1042157 SNPs. Statistical analyses were assessed with IBM SPSS for Windows, Version 23.0. In all cases, p values below 0.05 were considered statistically significant.

Results

Study population

In the CYPTAM study, 667 women were included in 25 Dutch and Belgian hospitals. More detailed clinical characteristics of the included patients in the core CYPTAM study are reported elsewhere [30, 31].

For the purpose of this pharmacogenetic study, three groups with low, medium, and high SULT1A1 activity groups were made. At enrolment, all groups of patients were comparable regarding mean age, tumor and nodal stage, histologic grade and classification, HER2 and progesterone receptor status, type of main surgery (mastectomy or breast conserving surgery) and axillar surgery (sentinel node procedure only or axillary lymph node dissection), adjuvant radiotherapy and chemotherapy, and treatment with trastuzumab (p value > 0.05). An overview of the baseline characteristics of the enrolled patients by the three groups is listed in Table 1.

Table 1

Baseline characteristics of the CYPTAM patients by 3’ UTR SULT1A1 high, medium, and low activity groups

		3′ UTR SULT1A1 rs6839 and rs1042157 SNPs groups						p value
		High activity group (N = 231)		Medium activity group (N = 324)		Low activity group (N = 105)
		N	(%)	N	(%)	N	(%)
Age at enrolment	Mean in years (SD)	56.2	11.2	56.9	11.4	54.6	9.8	0.155
Tumor stage	T1	121	52.4	170	52.5	58	55.2	0.936
	T2	96	41.6	137	42.3	41	39.0
	T3/T4	12	5.2	12	3.7	4	3.8
	Not specified	2	0.9	5	1.5	2	1.9
Nodal stage	N0	110	47.6	158	48.8	45	42.9	0.719
	N1	92	39.8	129	39.8	43	41.0
	N2	19	8.2	27	8.3	10	9.5
	N3	10	4.3	8	2.5	6	5.7
	Not specified	0	0.0	2	0.6	1	1.0
Histological classification	Ductal adenocarcinoma	178	77.1	248	76.5	78	74.3	0.738
	Lobular adenocarcinoma	35	15.2	42	13.0	14	13.3
	Other	18	7.8	32	9.9	12	11.4
	Not specified	0	0.0	2	0.6	1	1.0
Histological grade	G1	36	15.6	42	13.0	16	15.2	0.702
	G2	124	53.7	189	58.3	61	58.1
	G3	70	30.3	89	27.5	26	24.8
	Not specified	1	0.4	4	1.2	2	1.9
Progesterone receptor status	Positive	186	80.5	256	79.0	85	81.0	0.973
	Negative	42	18.2	63	19.4	18	17.1
	Not specified	3	1.3	5	1.5	2	1.9
HER2 receptor status	0	135	58.4	209	64.5	58	55.2	0.449
	1+	68	29.4	71	21.9	28	26.7
	2+	11	4.8	17	5.2	7	6.7
	3+	17	7.4	25	7.7	11	10.5
	Not specified	0	0.0	2	0.6	1	1.0
FISH	Positive (amplification)	17	7.4	29	9.0	11	10.5	0.584
	Negative	214	92.6	293	90.4	93	88.6
	Not specified	0	0.0	2	0.6	1	1.0
Surgery	Mastectomy	116	50.2	142	43.8	47	44.8	0.347
	Breast conserving	114	49.4	180	55.6	56	53.3
	Not specified	1	0.4	2	0.6	2	1.9
Surgery axilla	Sentinel node procedure only	110	47.6	164	50.6	55	52.4	0.517
	Axillary lymph node dissection	120	51.9	158	48.8	48	45.7
	Not specified	1	0.4	2	0.6	2	1.9
Adjuvant radiotherapy	Yes	156	67.5	231	71.3	71	67.6	0.546
	No	75	32.5	91	28.1	33	31.4
	Not specified	0	0.0	2	0.6	1	1.0
Adjuvant chemotherapy	Yes	137	59.3	198	61.1	66	62.9	0.664
	No	94	40.7	124	38.3	38	36.2
	Not specified	0	0.0	2	0.6	1	1.0
Trastuzumab therapy	Yes	19	8.2	28	8.6	10	9.5	0.442
	No	212	91.8	291	89.8	94	89.5
	Not specified	0	0.0	5	1.5	1	1.0

3′UTR 3′ Untranslated region; SD standard deviation

Genotype distributions: rs6839 and rs1042157 SNPs

Genotype distribution for rs1042157 was consistent with Hardy–Weinberg equilibrium (χ2 = 2.98, p = 0.084), while for rs6839 it was found not to be in Hardy–Weinberg equilibrium (χ2 = 13.44, p = 0.00025). However, genotype frequencies of rs6839 were similar to allelic frequencies reported previously for the Caucasian population and described on the National Center for Biotechnology Information website (NCBI, http://www.ncbi.nlm.nih.gov). Linkage Disequilibrium was analyzed for both 3′-UTR SULT1A1 variants and a significantly strong association was found for rs6839 and rs1042157 (D′ = 0.74, p < 0.0001). The variant allele frequencies of rs6839 and 1,042,157 are described in Supplementary Table 1.

Association between tamoxifen and its metabolites and 3′-UTR SULT1A1 groups

The mean concentration levels of tamoxifen and NDM-tamoxifen across the 3′-UTR SULT1A1 groups did not significantly differ (p > 0.05). In contrast, endoxifen and 4-hydroxy-tamoxifen mean concentrations in the low activity group were statistically significantly higher, compared to the other groups (endoxifen: p value = 0.016; 4-hydroxy-tamoxifen: p value = 0.050). Figure 2 shows the associations comparing low, medium, and high activity groups regarding the mean concentrations and metabolic ratios of tamoxifen and its metabolites. Of note, endoxifen and 4-hydroxy-tamoxifen concentrations were 15.7% and 12.3% higher in the low activity group compared to the high activity group (endoxifen: 31.23 vs. 27.00 nM; 4-hydroxy-tamoxifen: 5.55 vs. 4.94 nM). In Table 2,

Table 2

Overview of mean concentration levels and metabolic ratios of tamoxifen, endoxifen, 4-hydroxy-tamoxifen and NDM-tamoxifen by high, medium and low activity groups

	Tamoxifen (nM) (SD)	Endoxifen (nM) (SD)	4-hydroxy-tamoxifen (nM) (SD)	NDM-Tamoxifen (nM) (SD)	MR tamoxifen/NDM-tamoxifen (SD)	MR tamoxifen/4-hydroxy-tamoxifen (SD)	MR 4-hydroxy-tamoxifen/endoxifen (SD)	MR NDM-tamoxifen / endoxifen (SD)
High activity group (N = 231)	308.20 (113.17)	27.00 (14.69)	4.94 (2.02)	619.54 (231.10)	0.51 (0.13)	66.82 (23.62)	0.21 (0.09)	32.74 (27.18)
Medium activity group (N = 324)	312.12 (128.38)	30.51 (15.66)	5.27 (2.24)	584.42 (224.65)	0.54 (0.14)	63.94 (26.85)	0.19 (0.08)	26.04 (22.25)
Low activity group (N = 105)	319.84 (122.13)	31.23 (18.29)	5.55 (2.78)	621.20 (210.66)	0.52 (0.13)	64.52 (31.77)	0.21 (0.10)	30.88 (33.42)
p value	0.650	0.016	0.050	0.148	0.027	0.544	0.025	0.010

SD standard deviation; MR metabolic ratio

an overview of the mean concentration levels and metabolic ratios of tamoxifen, endoxifen, 4-hydroyx-tamoxifen, and NDM-tamoxifen is presented.

Clinical outcome and 3′-UTR SULT1A1 groups

An overall log-rank test comparing the low, medium, and high SULT1A1 activity groups, did not show differences in RFS across the groups, since no statistically significance was obtained (p value = 0.127; see Fig. 3). Interestingly, when comparing the low and high activity groups, a statistical difference in RFS was found (Log-rank test: p value = 0.042; see Fig. 3).

In the same line, the uni- and multivariable Cox regression analyses also found a trend towards better RFS in the low activity group (Adjusted HR:0.297; 95% CI 0.088–1.000; p value: 0.05; see Table 3),

Table 3

Cox regression analysis

	Univariable analysis			Multivariable analysis^a
	HR	95 % CI	p value	HR	95 % CI	p value
Age at enrolment (years)	1.017	0.994–1.040	0.146
Tumor size
T1	1.000	Reference	(0.316)	1.00	Reference	(0.291)
T2	1.534	0.880–2.657	0.132	1.266	0.722–2.219	0.410
T3/T4	1.419	0.424–4.745	0.570	0.478	0.127–1.804	0.276
Nodal status
N0	1.000	Reference	(0.053)	1.00	Reference	(0.075)
N1	1.610	0.867–2.968	0.131	1.691	0.897–3.188	0.104
N2	2.388	1.029–5.542	0.043	2.562	1.088–6.030	0.031
N3	3.342	1.230–9.081	0.018	2.898	1.012–8.302	0.048
Grade
G1	1.000	Reference	(0.420)	1.00	Reference	(0.153)
G2	0.899	0.409–1.977	0.792	0.592	0.261–1.345	0.211
G3	1.330	0.580–3.051	0.500	1.052	0.446–2.483	0.908
HER status
Negative	1.000	Reference		1.00	Reference
Positive	1.402	0.634–3.101	0.404	1.771	0.773–4.059	0.177
Histologic classification
Ductal classification	1.000	Reference	(< 0.001)	1.000	Reference	(< 0.001)
Lobular classification	3.435	1.927–6.121	< 0.001	4.497	2.340–8.643	< 0.001
Others	1.139	0.403–3.222	0.806	1.467	0.509–4.222	0.478
Progesterone status
Negative	1.000	Reference
Positive	0.630	0.337–1.175	0.146
Surgery
Mastectomy	1.00	Reference
Breast conserving	0.838	0.491–1.431	0.518
Surgery axilla
Sentinel node procedure	1.00	Reference
Axillary lymph node dissection	1.523	0.879–2.640	0.134
Chemotherapy
No	1.000	Reference
Yes	0.923	0.522–1.630	0.781
Radiotherapy
No	1.000	Reference
Yes	0.793	0.455–1.383	0.414
Trastuzumab treatment
No	1.000	Reference
Yes	1.430	0.646–3.164	0.378
3′UTR SULT1A1 groups
High activity group	1.000	Reference	(0.156)	1.000	Reference	(0.131)
Medium activity group	0.939	0.5434–1.622	0.820	0.991	0.564–1.739	0.974
Low activity group	0.310	0.093–1.031	0.056	0.297	0.088-1.000	0.050
3′UTR SULT1A1 groups
High activity group	1.000	Reference		1.000	Reference
Low activity group	0.308	0.093–1.022	0.054	0.286	0.084–0.976	0.046

^aAdjusted for Her2Neu status, histologic grade and classification, tumor size and nodal stage. 3′UTR 3′ untranslated region

compared to the medium and high activity group. A comparison between the extreme groups, low and high SULT1A1 activity, revealed a significantly lower risk for recurrence in the low activity group in both uni- and multivariable Cox regression analyses (Adjusted HR: 0.286; 95% CI 0.084–0.976; p value: 0.046; see Table 3).

Association of tamoxifen metabolism with rs6839 and rs1042157 SNPs

Genetic variances in CYP2D6 only partly contribute to explaining the inter-patient variability (R²) of tamoxifen and its metabolites concentrations and metabolic ratios [29, 32]. When rs6839 and rs1042157 SNPs were fitted in the model, the inter-patient variability (R²) of (log-transformed) concentrations and metabolic ratios of tamoxifen and its metabolites increased for all the cases, by 0.4 to 1.3%. Also, the explained variance (R²) of the (log-transformed) concentrations of endoxifen only marginally improved from 42.3 to 43.6%. An overview of the rs6839 and rs1042157 covariate analysis is presented in Supplementary Table 2.

Discussion

This is the first study in which the role of 3′-UTR SULT1A1 rs6839 and rs1042157 SNPs on tamoxifen metabolism and clinical outcome in early-breast cancer patients was examined. This study shows that patients with low SULT1A1 activity [rs6839 (GG) and rs1042157 (TT)] reached higher endoxifen and 4-hydroxy-tamoxifen concentration levels, but this small effect did not translate in improved RFS.

SULT1A1 is an important enzyme in tamoxifen elimination and it is involved in two relevant parts of the tamoxifen metabolic pathway: the transformation of 4-hydroxy-tamoxifen and endoxifen into 4-hydroxy-tamoxifen sulfate and endoxifen sulfate, respectively. As described by Yu and colleagues, 3′UTR SULT1A1 rs6839 and rs1042157 SNPs are associated with a decreased SULT1A1 enzymatic activity, and both SNPs contribute to explaining the variability of SULT1A1 enzyme activity [23]. Based on the results of Yu and colleagues, we hypothesized that lower SULT1A1 enzymatic activity conferred by the presence of rs6839 and rs1042157 SNPs would translate in higher concentrations of endoxifen and 4-hydroxy-tamoxifen. Our results confirmed this hypothesis, since higher concentrations of both endoxifen and 4-hydroxy-tamoxifen were found.

The transformation from tamoxifen into NDM-tamoxifen represents 92% of tamoxifen metabolism, while the metabolic conversion from tamoxifen into 4-hydroxy-tamoxifen accounts for only 7% of tamoxifen metabolism [3]. Accordingly, differences in NDM-tamoxifen concentrations would not be as relevant as compared to the other metabolites, whereas small variations in endoxifen and 4-hydroxy-tamoxifen concentrations might be more significant. Our results suggest that the route 4-hydroxy-tamoxifen to endoxifen, might be more important in the presence of a decreased activity of SULT1A1 enzyme, as a consequence of the lower elimination of endoxifen and 4-hydroxy-tamoxifen.

In line with these results, a lower risk for relapse was found in the low activity group, compared to the high activity group. While the increased endoxifen concentration levels and better clinical outcome are completely in line, we feel that this interpretation should be carefully considered, since the association between endoxifen concentration and clinical outcome remains uncertain.

Both endoxifen and 4-hydroxy-tamoxifen have comparable anti-estrogenic activity [4], yet only endoxifen is seen as the most active metabolite of tamoxifen metabolite, since it is found in higher concentrations than 4-hydroxy-tamoxifen [5]. Therefore, the relationship between endoxifen concentration levels and RFS has been investigated, but different ranges for endoxifen concentration have been proposed. For instance, Madelensky et al. described a 26% lower chance of relapse for patients with an endoxifen concentration level above 16 nM (5.97 ng/ml) [33], whereas Helland and colleagues reported an even lower limit of 9 nM (3.36 ng/ml) for better clinical outcomes [34]. In contrast, Neven and colleagues failed to find an association between endoxifen concentration levels and progression-free survival in the metastatic and neoadjuvant setting [35]. In line with these authors, no association between endoxifen concentration and RFS was found in the core CYPTAM study [26, 27]. In the present study, a 15.7% increase of the mean endoxifen serum concentration was found in patients with low SULT1A1 activity, while the explained variance of the concentrations of endoxifen only slightly improved (from 42.3 to 43.6%). Accordingly, the combination of the lack of association between endoxifen concentration and RFS in combination with a barely improved explained variance of endoxifen concentrations, it seems unlikely that there is a true association between SULT1A1 and RFS caused by the tenue differences in endoxifen concentration levels. Alternative explanations may involve the role of genetic variations in SULT1A1 in breast cancer risk [36] or in endogenous estrogen metabolism [37].

A potential limitation in our analysis might be the fact that rs6839 was not found in HWE. For the pyrosequencing analysis, quality controls were used, and the call-rate in the samples was above 90%, avoiding therefore any technical problem to be reason for this HWE deviation. Also, we performed the pyrosequencing analysis in isolated DNA from whole blood samples. By this way, we prevented any HWE discrepancy due to potential loss of heterozygosity and HWE using tumor material. The rs6839 genotype frequencies were comparable to those reported in the NCBI database [38]. Another possible weakness in our study might be due to the lack of direct measurement of endoxifen sulfate and 4-hydroxy-tamoxifen sulfate levels; instead, we indirectly assessed effects of the SULT1A1 SNPs by measuring endoxifen and 4-hydroxy-tamoxifen.

In summary, our results suggest that rs6839 and rs1042157 SNPs have a minor effect on the concentrations and metabolic ratios of tamoxifen and its metabolites, and RFS in women receiving adjuvant tamoxifen, but this impact is not likely to be clinically meaningful.

Acknowledgements

We are grateful to Roche for kindly providing the Amplichip P450 tests, to the IKNL for data management, and to ZOLEON for its grant.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical Approval

All procedures performed in the study described in this manuscript were in accordance with the ethical standards of the institutional and/or national research committee.

Informed consent was obtained from all individual participants included in the study.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Unsere Produktempfehlungen

e.Med Interdisziplinär

Kombi-Abonnement

Für Ihren Erfolg in Klinik und Praxis - Die beste Hilfe in Ihrem Arbeitsalltag

Mit e.Med Interdisziplinär erhalten Sie Zugang zu allen CME-Fortbildungen und Fachzeitschriften auf SpringerMedizin.de.

Jetzt testen ¹

e.Med Gynäkologie

Kombi-Abonnement

Mit e.Med Gynäkologie erhalten Sie Zugang zu CME-Fortbildungen der beiden Fachgebiete, den Premium-Inhalten der Fachzeitschriften, inklusive einer gedruckten gynäkologischen oder urologischen Zeitschrift Ihrer Wahl.

Jetzt testen ²

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 15 KB)

Supplementary material 2 (DOCX 14 KB)

Clemons M, Danson S, Howell A (2002) Tamoxifen (“Nolvadex”): a review. Cancer Treat Rev 28(4):165–180CrossRef

Jordan VC (2008) Tamoxifen: catalyst for the change to targeted therapy. Eur J Cancer 44(1):30–38CrossRef

Klein DJ, Thorn CF, Desta Z, Flockhart DA, Altman RB, Klein TE (2013) PharmGKB summary: tamoxifen pathway, pharmacokinetics. Pharmacogenet Genomics 23(11):643–647CrossRef

Johnson MD, Zuo H, Lee KH, Trebley JP, Rae JM, Weatherman RV, Desta Z, Flockhart DA, Skaar TC (2004) Pharmacological characterization of 4-hydroxy-N-desmethyl tamoxifen, a novel active metabolite of tamoxifen. Breast Cancer Res Treat 85(2):151–159CrossRef

Lim YC, Desta Z, Flockhart DA, Skaar TC (2005) Endoxifen (4-hydroxy-N-desmethyl-tamoxifen) has anti-estrogenic effects in breast cancer cells with potency similar to 4-hydroxy-tamoxifen. Cancer Chemother Pharmacol 55(5):471–478CrossRef

Del Re M, Citi V, Crucitta S, Rofi E, Belcari F, van Schaik RH, Danesi R (2016) Pharmacogenetics of CYP2D6 and tamoxifen therapy: light at the end of the tunnel? Pharmacol Res 107:398–406CrossRef

Binkhorst L, Mathijssen RH, Jager A, van Gelder T (2015) Individualization of tamoxifen therapy: much more than just CYP2D6 genotyping. Cancer Treat Rev 41(3):289–299CrossRef

Nowell S, Falany CN (2006) Pharmacogenetics of human cytosolic sulfotransferases. Oncogene 25(11):1673–1678CrossRef

Kiyotani K, Mushiroda T, Nakamura Y, Zembutsu H (2012) Pharmacogenomics of tamoxifen: roles of drug metabolizing enzymes and transporters. Drug Metab Pharmacokinet 27(1):122–131CrossRef

10.

Daniels J, Kadlubar S (2014) Pharmacogenetics of SULT1A1. Pharmacogenomics 15(14):1823–1838CrossRef

11.

Li X, Anderson RJ (1999) Sulfation of iodothyronines by recombinant human liver steroid sulfotransferases. Biochem Biophys Res Commun 263(3):632–639CrossRef

12.

Lu X, Jiang K, Han L, Zhang M, Zhou Y, Ma Y, Zhou Y, Meng S (2015) Sulfonation of curcuminoids: characterization and contribution of individual SULT enzymes. Mol Nutr Food Res 59(4):634–645CrossRef

13.

Desta Z, Ward BA, Soukhova NV, Flockhart DA (2004) Comprehensive evaluation of tamoxifen sequential biotransformation by the human cytochrome P450 system in vitro: prominent roles for CYP3A and CYP2D6. J Pharmacol Exp Ther 310(3):1062–1075CrossRef

14.

Nowell S, Sweeney C, Winters M, Stone A, Lang NP, Hutchins LF, Kadlubar FF, Ambrosone CB (2002) Association between sulfotransferase 1A1 genotype and survival of breast cancer patients receiving tamoxifen therapy. J Natl Cancer Inst 94(21):1635–1640CrossRef

15.

Wegman P, Elingarami S, Carstensen J, Stal O, Nordenskjold B, Wingren S (2007) Genetic variants of CYP3A5, CYP2D6, SULT1A1, UGT2B15 and tamoxifen response in postmenopausal patients with breast cancer. Breast Cancer Res 9(1):R7CrossRef

16.

Grabinski JL, Smith LS, Chisholm GB, Drengler R, Rodriguez GI, Lang AS, Kalter SP, Garner AM, Fichtel LM, Hollsten J et al (2006) Genotypic and allelic frequencies of SULT1A1 polymorphisms in women receiving adjuvant tamoxifen therapy. Breast Cancer Res Treat 95(1):13–16CrossRef

17.

Serrano D, Lazzeroni M, Zambon CF, Macis D, Maisonneuve P, Johansson H, Guerrieri-Gonzaga A, Plebani M, Basso D, Gjerde J et al (2011) Efficacy of tamoxifen based on cytochrome P450 2D6, CYP2C19 and SULT1A1 genotype in the Italian Tamoxifen Prevention Trial. Pharmacogenomics J 11(2):100–107CrossRef

18.

Moyer AM, Suman VJ, Weinshilboum RM, Avula R, Black JL, Safgren SL, Kuffel MJ, Ames MM, Ingle JN, Goetz MP (2011) SULT1A1, CYP2C19 and disease-free survival in early breast cancer patients receiving tamoxifen. Pharmacogenomics 12(11):1535–1543CrossRef

19.

Jin Y, Desta Z, Stearns V, Ward B, Ho H, Lee KH, Skaar T, Storniolo AM, Li L, Araba A et al (2005) CYP2D6 genotype, antidepressant use, and tamoxifen metabolism during adjuvant breast cancer treatment. J Natl Cancer Inst 97(1):30–39CrossRef

20.

Fernandez-Santander A, Gaibar M, Novillo A, Romero-Lorca A, Rubio M, Chicharro LM, Tejerina A, Bandres F (2013) Relationship between genotypes Sult1a2 and Cyp2d6 and tamoxifen metabolism in breast cancer patients. PLoS ONE 8(7):e70183CrossRef

21.

Gjerde J, Hauglid M, Breilid H, Lundgren S, Varhaug JE, Kisanga ER, Mellgren G, Steen VM, Lien EA (2008) Effects of CYP2D6 and SULT1A1 genotypes including SULT1A1 gene copy number on tamoxifen metabolism. Ann Oncol 19(1):56–61CrossRef

22.

Hebbring SJ, Moyer AM, Weinshilboum RM (2008) Sulfotransferase gene copy number variation: pharmacogenetics and function. Cytogenet Genome Res 123(1–4):205–210CrossRef

23.

Yu X, Dhakal IB, Beggs M, Edavana VK, Williams S, Zhang X, Mercer K, Ning B, Lang NP, Kadlubar FF et al (2010) Functional genetic variants in the 3′-untranslated region of sulfotransferase isoform 1A1 (SULT1A1) and their effect on enzymatic activity. Toxicol Sci 118(2):391–403CrossRef

24.

Hogervorst JG, van den Brandt PA, Godschalk RW, van Schooten FJ, Schouten LJ (2016) The influence of single nucleotide polymorphisms on the association between dietary acrylamide intake and endometrial cancer risk. Sci Rep 6:34902CrossRef

25.

Ferrucci LM, Cross AJ, Gunter MJ, Ahn J, Mayne ST, Ma X, Chanock SJ, Yeager M, Graubard BI, Berndt SI et al (2010) Xenobiotic metabolizing genes, meat-related exposures, and risk of advanced colorectal adenoma. World Rev Nutr Diet 101:34–45CrossRef

26.

The CYPTAM study. http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=1509. Accessed 24 May 2018

27.

Sanchez-Spitman AB, Dezentjé VO, Swen JJ, Moes DJAR, Batman E, Smorenburg CH, Jongen L, Los M, Guchelaar HJ, Neven P, Gelderblom H (2018) A prospective study on the effect of endoxifen concentration and CYP2D6 phenotypes on clinical outcome in early stage breast cancer patients receiving adjuvant tamoxifen. J Clin Oncol 36(15):523CrossRef

28.

Teunissen SF, Rosing H, Koornstra RHT, Linn SC, Schellens JHM, Schinkel AH, Beijnen JH (2009) Development and validation of a quantitative assay for the analysis of tamoxifen with its four main metabolites and the flavonoids daidzein, genistein and glycitein in human serum using liquid chromatography coupled with tandem mass spectrometry. J Chromatogr B 877(24):2519–2529CrossRef

29.

Dezentje VO, den Hartigh J, Guchelaar H, Hessing T, van der Straaten T, Vletter-Bogaartz JM, Vree R, Maartense E, Smorenburg CH, Putter H et al: Association between endoxifen serum concentration and predicted CYP2D6 phenotype in a prospective cohort of patients with early-stage breast cancer. J Clin Oncol 2011, 29(15):562CrossRef

30.

Sanchez Spitman AB, Moes D, Gelderblom H, Dezentje VO, Swen JJ, Guchelaar HJ (2017) Effect of CYP3A4*22, CYP3A5*3, and CYP3A combined genotypes on tamoxifen metabolism. Eur J Clin Pharmacol 73(12):1589–1598CrossRef

31.

Sanchez-Spitman AB, Moes DA, Gelderblom H, Dezentje VO, Swen JJ, Guchelaar HJ (2017) The effect of rs5758550 on CYP2D6*2 phenotype and formation of endoxifen in breast cancer patients using tamoxifen. Pharmacogenomics 18(12):1125–1132CrossRef

32.

Dezentje VO, van Schaik RH, Vletter-Bogaartz JM, van der Straaten T, Wessels JA, Kranenbarg EM, Berns EM, Seynaeve C, Putter H, van de Velde CJ et al (2013) CYP2D6 genotype in relation to tamoxifen efficacy in a Dutch cohort of the tamoxifen exemestane adjuvant multinational (TEAM) trial. Breast Cancer Res Treat 140(2):363–373CrossRef

33.

Madlensky L, Natarajan L, Tchu S, Pu M, Mortimer J, Flatt SW, Nikoloff DM, Hillman G, Fontecha MR, Lawrence HJ et al (2011) Tamoxifen metabolite concentrations, CYP2D6 genotype, and breast cancer outcomes. Clin Pharmacol Ther 89(5):718–725CrossRef

34.

Helland T, Henne N, Bifulco E, Naume B, Borgen E, Kristensen VN, Kvaloy JT, Lash TL, Alnaes GIG, van Schaik RH et al (2017) Serum concentrations of active tamoxifen metabolites predict long-term survival in adjuvantly treated breast cancer patients. Breast Cancer Res 19(1):125CrossRef

35.

Neven P, Jongen L, Lintermans A, Van Asten K, Blomme C, Lambrechts D, Poppe A, Wildiers H, Dieudonne AS, Brouckaert O et al (2018) Tamoxifen metabolism and efficacy in breast cancer- a prospective multicentre trial. Clin Cancer Res 24(10):2312–2318CrossRef

36.

Daniels J, Kadlubar S (2013) Sulfotransferase genetic variation: from cancer risk to treatment response. Drug Metab Rev 45(4):415–422CrossRef

37.

Bugano DD, Conforti-Froes N, Yamaguchi NH, Baracat EC (2008) Genetic polymorphisms, the metabolism of estrogens and breast cancer: a review. Eur J Gynaecol Oncol 29(4):313–320PubMed

38.

Reference SNP Cluster Report: rs6839. https://www.ncbi.nlm.nih.gov/projects/SNP/snp_ref.cgi?rs=6839. Accessed 24 May 2018

Titel: Genetic polymorphisms of 3′-untranslated region of SULT1A1 and their impact on tamoxifen metabolism and efficacy
verfasst von: A. B. Sanchez-Spitman
V. O. Dezentjé
J. J. Swen
D. J. A. R. Moes
H. Gelderblom
Henk-Jan Guchelaar
Publikationsdatum: 17.08.2018
Verlag: Springer US
Erschienen in: Breast Cancer Research and Treatment / Ausgabe 2/2018
Print ISSN: 0167-6806
Elektronische ISSN: 1573-7217
DOI: https://doi.org/10.1007/s10549-018-4923-7

Springer Medizin

Genetic polymorphisms of 3′-untranslated region of SULT1A1 and their impact on tamoxifen metabolism and efficacy