Non-CYP2D6 Variants Selected by a GWAS Improve the Prediction of Impaired Tamoxifen Metabolism in Patients with Breast Cancer
Abstract
:1. Introduction
2. Material and Methods
2.1. Ethics Statement
2.2. Clinical Cohort
2.3. Quantifying Tamoxifen and Its Metabolites in Plasma
2.4. CYP2D6 Genotyping
2.5. Genome-Wide Microarray Analysis
2.6. Verification Genotyping
2.7. Statistical Analyses
2.7.1. GWAS and Individual Genotyping
2.7.2. Prediction Modeling
3. Results
3.1. Association Analyses
3.2. Predictive Performance
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
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Total N = 287 | |||
---|---|---|---|
Genotype | Number of Patients (%) | (Z)-endoxifen (ng mL−1) Mean ± SD | Metabolic Ratio a Mean ± SD |
NM/UM | 18 (6.3) | 6.96 ± 3.75 | 0.0201 ± 0.0076 |
NM/NM | 90 (31.4) | 7.26 ± 3.18 | 0.0185 ± 0.0057 |
NM/IM | 44 (15.3) | 5.60 ± 3.26 | 0.0125 ± 0.0054 |
NM/PM | 99 (34.5) | 4.85 ± 2.46 | 0.0108 ± 0.0043 |
IM/IM | 3 (1.0) | 3.05 ± 1.91 | 0.0063 ± 0.0022 |
IM/PM | 12 (4.2) | 2.22 ± 0.87 | 0.0047 ± 0.0014 |
PM/PM | 21 (7.3) | 1.79 ± 0.66 | 0.0037 ± 0.0013 |
dbSNP ID a | Region b | MA | MAF c | OR (95% CI) | p-Value |
---|---|---|---|---|---|
rs9844493 | Chr3:67210593 | A | 0.482 | 1.59 (1.13–2.23) | 3.74 × 10−3 |
intergenic | |||||
rs1320308 | Chr5:76875427 | A | 0.447 | 0.51 (0.35–0.73) | 1.59 × 10−3 |
S100Z exon 6 (E23A) | |||||
rs6950784 | Chr7:155902980 | G | 0.519 | 1.93 (1.37–2.72) | 4.42 × 10−4 |
intergenic | |||||
rs980729 | Chr7:98697127 | A | 0.361 | 0.83 (0.59–1.1) | 1.22 × 10−3 |
intergenic | |||||
rs11780345 | Chr8:23194453 | C | 0.196 | 0.69 (0.49–0.97) | 5.57 × 10−5 |
TNFRSF10A intron 9 | |||||
rs11786748 | Chr8:27924000 | G | 0.403 | 1.95 (1.35–2.82) | 6.18 × 10−4 |
SCARA5 intron 3 | |||||
rs7988513 | Chr13:92232033 | C | 0.300 | 0.80 (0.57–1.14) | 7.9 × 10−3 |
GPC5 intron 7 | |||||
rs1052717 | Chr22:41885425 | A | 0.304 | 0.36 (0.25–0.50) | 1.36 × 10−7 |
SREBF2 intron 13 | |||||
rs1894714 | Chr22:41953130 | T | 0.188 | 4.31 (2.65–7.00) | 7.48 × 10−9 |
LINC00634 ncRNA | |||||
rs11914200 | Chr22:41982066 | A | 0.239 | 4.29 (2.82–6.55) | 4.73 × 10−12 |
SEPT3 intron 4 | |||||
rs8138080 | Chr22:42000367 | A | 0.261 | 5.55 (3.52–8.75) | 1.78 × 10−15 |
WBP2NL intron 2 | |||||
rs7245 | Chr22:42085845 | G | 0.326 | 0.28 (0.2–0.4) | 7.52 × 10−13 |
NDUFA6 3′ UTR | |||||
rs5751222 | Chr22:42121918 | A | 0.229 | 5.96 (3.55–10.00) | 2.31 × 10−12 |
NDUFA6-AS1 ncRNA | |||||
rs5751247 | Chr22:42237048 | C | 0.290 | 4.82 (3.09–7.52) | 2.81 × 10−13 |
TCF20 intron 3 | |||||
rs134906 | Chr22:42293364 | T | 0.333 | 0.37 (0.26–0.52) | 2.35 × 10−8 |
intergenic | |||||
rs28371725 | Chr22:42127803 | T | 0.064 | 2.24 (1.11–4.50) | 6.81 ×10−2 |
CYP2D6 intron 6 (SSV) | |||||
rs3892097 | Chr22:42128945 | T | 0.093 | 6.93 (3.92–12.24) | 1.98 × 10−12 |
CYP2D6 intron 3 (SSV) | |||||
rs1065852 | Chr22:42130692 | A | 0.238 | 6.85 (3.98–11.77) | 3.5 × 10−13 |
CYP2D6 exon 1 (P34S) |
Variable/ dbSNP ID a | Gene | −2 Log Likelihood | Rank | R2b | OR (95% CI) | p-Value | AUC c |
---|---|---|---|---|---|---|---|
CYP2D6 genotype | CYP2D6 | 254.137 | 1 | 0.427 | 16.13 (7.58–34.48) | 6.28 × 10−13 | 0.758 |
rs7245 | NDUFA6 | 238.013 | 2 | 0.482 | 0.40 (0.22–0.70) | 1.38 × 10−3 | 0.842 |
rs6950784 | Intergenic | 223.925 | 3 | 0.527 | 2.24 (1.40–3.59) | 7.94 × 10−4 | 0.871 |
rs1320308 | S100Z | 214.671 | 4 | 0.556 | 0.48 (0.29–0.81) | 6.26 × 10−3 | 0.879 |
rs11786748 | SCARA5 | 210.654 | 5 | 0.568 | 1.68 (1.01–2.80) | 0.047 | 0.880 |
dbSNP ID a | Gene | −2 Log Likelihood | Rank | R2b | OR (95% CI) | p-Value | AUC c |
---|---|---|---|---|---|---|---|
rs8138080 | WBP2NL | 278.432 | 1 | 0.337 | 3.73 (1.65–8.43) | 1.56 × 10−3 | 0.718 |
rs1320308 | S100Z | 264.234 | 2 | 0.390 | 0.48 (0.29–0.79) | 3.7 × 10−3 | 0.795 |
rs6950784 | Intergenic | 255.872 | 3 | 0.420 | 1.91 (1.25–2.92) | 2.81 × 10−3 | 0.819 |
rs7245 | NDUFA6 | 247.300 | 4 | 0.450 | 0.54 (0.30–0.95) | 0.034 | 0.830 |
rs1065852 | CYP2D6 | 242.012 | 5 | 0.468 | 2.78 (1.18–6.59) | 0.020 | 0.817 |
rs11786748 | SCARA5 | 237.058 | 6 | 0.485 | 1.70 (1.06–2.74) | 0.028 | 0.813 |
Parameter | Prediction Model Type | |
---|---|---|
Model 1 | Model 2 | |
AUC | 0.879 | 0.830 |
Sensitivity (%) | 87.8 | 80.1 |
Specificity (%) | 70.8 | 64.2 |
PPV (%) | 81.6 | 76.7 |
NPV (%) | 79.8 | 68.7 |
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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Hennig, E.E.; Piątkowska, M.; Goryca, K.; Pośpiech, E.; Paziewska, A.; Karczmarski, J.; Kluska, A.; Brewczyńska, E.; Ostrowski, J. Non-CYP2D6 Variants Selected by a GWAS Improve the Prediction of Impaired Tamoxifen Metabolism in Patients with Breast Cancer. J. Clin. Med. 2019, 8, 1087. https://doi.org/10.3390/jcm8081087
Hennig EE, Piątkowska M, Goryca K, Pośpiech E, Paziewska A, Karczmarski J, Kluska A, Brewczyńska E, Ostrowski J. Non-CYP2D6 Variants Selected by a GWAS Improve the Prediction of Impaired Tamoxifen Metabolism in Patients with Breast Cancer. Journal of Clinical Medicine. 2019; 8(8):1087. https://doi.org/10.3390/jcm8081087
Chicago/Turabian StyleHennig, Ewa E., Magdalena Piątkowska, Krzysztof Goryca, Ewelina Pośpiech, Agnieszka Paziewska, Jakub Karczmarski, Anna Kluska, Elżbieta Brewczyńska, and Jerzy Ostrowski. 2019. "Non-CYP2D6 Variants Selected by a GWAS Improve the Prediction of Impaired Tamoxifen Metabolism in Patients with Breast Cancer" Journal of Clinical Medicine 8, no. 8: 1087. https://doi.org/10.3390/jcm8081087
APA StyleHennig, E. E., Piątkowska, M., Goryca, K., Pośpiech, E., Paziewska, A., Karczmarski, J., Kluska, A., Brewczyńska, E., & Ostrowski, J. (2019). Non-CYP2D6 Variants Selected by a GWAS Improve the Prediction of Impaired Tamoxifen Metabolism in Patients with Breast Cancer. Journal of Clinical Medicine, 8(8), 1087. https://doi.org/10.3390/jcm8081087