Ultra Performance Liquid Chromatography-Tandem Mass

Article pubs.acs.org/ac

Ultra Performance Liquid Chromatography-Tandem Mass Spectrometry Method for Profiling of Steroid Metabolome in Human Tissue Nilesh W. Gaikwad* Departments of Nutrition and Environmental Toxicology, University of California, Davis, California 95616, United States

ABSTRACT: In humans, steroids play a broad and vital role in regulation of gene expression, secondary sexual characteristics, maturation, reproduction, cardiovascular health, neurological functions, etc., but imbalance in steroid metabolism is also linked to development and progression of many diseases, such as cancer, neurodegenerative diseases, and cardiovascular diseases. Hence, measurement of steroids in biological samples is essential to monitor human health. Currently, there is radioimmunoassay, gas chromatography−mass spectrometry (GC/MS), and liquid chromatography−mass spectrometry (LC-MS) methods developed for steroid measurements in biological samples. However, these methods require elaborate sample preparation procedures and have concerns(s) related to reproducibility, dynamic range, time, costs, and most importantly the total coverage of steroids. Also currently, there is no method available for comprehensive steroid profiling in a single LC-MS run that includes androgens, corticosteroids, progestogens, estrogens, estrogen metabolites, estrogen conjugates, and estrogen-DNA adducts as well as exogenous steroid derivatives. Here, I present a global steroid metabolic profiling method based on liquid−liquid extraction (LLE) followed by ultra performance liquid chromatography (UPLC)-tandem mass spectrometry (MS/MS) for simultaneous measurement of over 100 indigenous as well as exogenous steroids in about 12 min, without derivatization. The method was successfully applied to determine steroid hormone levels in the breast tissue of healthy women. Overall presence of all major classes of steroids as well as estrogen derivatives was detected in breast tissue.

S

estrogens plays a significant role in the carcinogenicity, which are oxidized to the 2-OH and 4-OH catechol estrogens by the phase I enzymes (Figure 1). 4-Hydroxyestrone was found to be carcinogenic in the male Syrian golden hamster kidney tumor model, whereas 2-hydroxylated metabolites were without activity.14,15 Similarly, Newbold and Liehr have shown that 4hydroxyestradiol induced uterine tumors in 66% of CD-1 mice, whereas mice treated with 2-hydroxyestradiol or E2 had much lower uterine tumor incidences.16 Oxidative enzymes, metal ions, and in some cases molecular oxygen can catalyze the oxidation of catechols to reactive o-quinones, which can cause damage within cells by alkylation of cellular nucleophiles (proteins, DNA).17 In an earlier study, we have shown that in healthy women the urinary levels of methoxy-estrogens and

teroids, androgens, corticosteroids, estrogens, and progestogens control many physiological processes in humans including reproduction, secondary sexual characteristics, maturation, reproduction, gene expression, cardiovascular health, and neurological functions,1 but they, especially estrogens, are also implicated in the development and/or progression of many diseases, such as breast cancer,2 ovarian cancer,3 prostate cancer,4 endometrial cancer,5 osteoporosis,6 neurodegenerative diseases,7 cardiovascular disease,8 and obesity.9 There is a clear association between cumulative exposure of exogenous and indigenous estrogens and the risk of breast and other cancers.10 Epidemiologic studies have indicated that breast cancer risk is higher in women with early menarche and late menopause, who have longer exposure to estrogens. Estrogen-replacement therapy has also been implicated as a risk factor for breast cancer in postmenopausal women.11 Obese postmenopausal women have higher serum concentrations of estrogen and are at risk of breast cancer.12,13 Gathering evidence suggests that oxidative metabolism of © 2013 American Chemical Society

Received: January 2, 2013 Accepted: April 18, 2013 Published: April 18, 2013 4951

dx.doi.org/10.1021/ac400016e | Anal. Chem. 2013, 85, 4951−4960

Analytical Chemistry

Article

Figure 1. Proposed steroid metabolic pathways. Carcinogenic pathways are highlighted in red, whereas protective pathways are in green.

biological samples. Electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) are routinely used in qualitative and quantitative analysis of steroids. Recently, LCESI-MS methods for simultaneous quantitation of 28 steroids in animal tissue28 and 24 steroid hormones in human urine in a single 50 min run29 are reported. Furthermore, LC-APCI-MS methods are also used for determination of 7 endogenous adrenal steroids in human serum,30 16 estrogen derivatives in rat hepatocytes, 4 catechol estrogens in rat brains31 and human urine,32 and 34 anabolic steroids in bovine muscle.33 In the recent past, LC-APPI (atmospheric pressure photo ionization)MS methods were also developed and employed as well to determine nonpolar steroids.34,35 However, currently there is no method available for comprehensive steroid profiling in a single LC-MS run that can measure androgens, corticosteroids, progestogens, estrogens, estrogen metabolites, estrogen conjugates, and estrogen-DNA adducts as well as exogenous steroids. Earlier, we have developed solid phase extraction/ultra performance liquid chromatography (UPLC)-MS methodologies and applied them for the construction of estrogen metabolome in human samples.18,19,36−38 Using this assay, we discovered clear differences between metabolic profiles of healthy controls vs pathologic cases, resulting in successful identification of biomarker that could be used in breast, nonHodgkin lymphoma,36 and prostate cancer37 as well as in Parkinson’s disease.38 In this study, we present a novel targeted metabolic profiling method based on UPLC-tandem mass

thiol conjugates of catechol estrogen are high and the level of estrogen-DNA adducts are low. In contrast, women with breast cancer had lower levels of estrogen metabolites and conjugates and higher levels of estrogen-DNA adducts.18,19 Comprehensive analysis of steroids, thus, is important in accessing the human health and in personalized medicine. However, currently, there are no methods available for analysis of steroid metabolome (Figure 1) composed of androgens, corticosteroids, progestogens, estrogens, and their metabolites. Physiological steroid levels are generally low and vary among individuals based on many aspects such as sex, gender, age, etc. The current most widely used techniques for steroid measurements involve radioimmunoassay,20 gas chromatography−mass spectrometry (GC/MS),21,22 and liquid chromatography−mass spectrometry (LC-MS).23,24 The immunoassay based measurements are simple and sensitive but may have concerns with reproducibility, cross reactivity, dynamic range, and matrix effects and cannot analyze multiple steroids in a single assay.20,25,26 GC/MS and LC-MS methods have large dynamic range, and several determinations of the steroids can be done simultaneously. GC/MS has been extensively used in steroid analysis; however, steroid measurements from biospecimens require elaborate and tedious sample preparation procedures. Prior to GC/MS analysis, steroid derivatization is required as a part of sample preparation to increase the volatility and thermal stability of the molecules and to improve chromatographic separation and detection.22,27 In recent years, LC-MS has been shown to be very useful in determining steroid levels in the 4952


4953

38 39

37

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

no.a

pregnenolone 17-hydroxypregnenolone androstenolone (DHEA) 5-androstenediol progesterone 17-hydroxyprogesterone cortexolone cortisol cortexone corticosterone aldosterone androstenedione testosterone allodihydrotestosterone estrone (E1) estradiol (E2) 11α-hydroxy_E1 11β-hydroxy_E1 11α-hydroxy_E2 11β-hydroxy_E2 9,11-dehydro_E1 9,11-dehydro_E2 11-ketoestrone 3-methoxyestrone estradiol-3-glucuronate estradiol-17-glucuronate 4-hydroxyestrone 4-hydroxyestradiol 4-methoxyestrone 4-methoxyestradiol 4-methoxyestriol 4-hydroxy-E1-2-glutatione 4-hydroxy-E2-2-glutatione 4-hydroxy-E1-2-cysteine 4-hydroxy-E2-2-cysteine 4-hydroxy-E1-2-Nacetylcysteine 4-hydroxy-E2-2-Nacetylcysteine 4-hydroxy-E1-1-N-3-adenine 4-hydroxy-E2-1-N-3-adenine

compound

PI PI

PI

PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI NI NI PI PI PI PI PI PI PI PI PI PI

mode

420.3 422.3

450.1

317.3 333.4 289.3 273.3 315.3 331.4 347.3 363.4 331.3 347.3 361.3 287.3 289.3 291.3 271.2 255.3 287.3 287.3 289.3 289.3 271.3 269.3 285.3 285.3 471.3 447.3 287.3 271.3 301.3 303.3 319.3 592.3 594.4 406.2 408.2 448.3

parent

135.9 136.0

162.1

281.1 297.1 197.0 255.1 97.1 97.1 97.2 121.1 97.1 121.0 299.1 97.0 96.9 159.0 253.2 159.0 251.2 111.1 253.1 106.0 159.3 209.0 267.1 147.1 198.9 84.7 269.0 174.8 163.2 136.8 137.3 317.1 318.9 284.3 286.5 161.8

daughter

6.2 6.0

7.3

8.4 9.6 9.7 9.1 11.2 9.5 8.5 7.5 9.9 8.4 7.1 9.8 9.4 10.2 9.6 9.4 7.5 11.1 9.7 9.4 9.6 9.4 8.2 11.7 7.4 7.4 8.8 8.2 10.1 9.2 8.3 6.6 6.5 8.1 7.9 7.9

Rt

0.9769 0.9748 0.9796

0.012b 0.024b

0.9825 0.6430 0.9402 0.9811 0.9923 0.9926 0.9904 0.9701 0.9974 0.9925 0.9629 0.9906 0.9888 0.8795 0.9596 0.9903 0.9854 0.9569 0.9942 0.6273 0.9758 0.9884 0.9869 0.9935 0.9789 0.9909 0.9274 0.9179 0.9740 0.8696 0.9449 0.9662 0.9591 0.8798 0.8465 0.9625

r2

0.223

1.580 1.504 0.087b 0.172 0.003b 0.007b 0.007b 0.068b 0.015b 0.072b 0.693 0.009b 0.009b 0.344 0.009b 0.009b 0.087b 0.873 0.173 1.734 0.092b 0.093b 0.088b 0.009b 1.062 0.111 0.002b 0.347 0.083b 3.307 15.703 0.042b 0.169 0.025b 0.614 0.224

LOD, pmole

Table 1. Mass Spectrometric and Method Validation Parameters

2.5−20000 5−20000

25−20000

250−20000 250−20000 25−20000 5−20000 0.5−20000 0.5−20000 5−20000 1−20000 5−20000 5−20000 25−20000 0.5−20000 0.5−20000 10−20000 0.5−20000 2.5−20000 2.5−20000 0.5−20000 25−20000 0.5−20000 1−20000 2.5−20000 25−20000 1−20000 50−20000 5−20000 0.5−20000 10−20000 2.5−20000 100−20000 250−20000 10−20000 100−20000 25−20000 100−20000 25−20000

linear range, pg/μL

4.2 3.8

9.7

5.8 8.0 1.5 9.9 3.1 2.9 6.7 13.0 7.8 8.9 16.7 2.7 3.1 12.8 3.9 2.6 18.6 19.7 5.7 12.1 7.0 6.1 5.9 6.8 13.1 4.7 6.8 5.6 6.1 9.6 23.7 8.8 13.4 9.9 10.4 7.5

98 98

95

97 96 99 95 98 99 97 94 96 96 92 99 98 94 98 99 91 89 97 94 96 97 97 97 93 98 97 97 97 95 83 96 92 95 95 96

%RE (A)

5000 pg/μL %CV (P)

5.1 6.8

7.2

11.4 17.7 7.1 7.7 3.8 3.9 4.4 7.1 6.9 2.2 8.0 3.6 2.5 6.4 7.1 19.7 12.3 29.2 9.5 13.6 8.9 6.7 5.0 3.0 18.1 4.9 4.4 6.3 5.1 25.0 77.7 5.5 12.3 7.3 11.4 6.0

97 97

96

94 90 96 96 98 98 98 96 97 99 96 98 99 97 96 90 94 83 95 92 96 97 97 99 91 98 98 97 97 86 45 97 94 96 93 97

%RE (A)

2500 pg/μL %CV (P)

5.2 11.1

12.6

20.4 36.4 9.8 4.4 4.6 2.8 16.7 4.3 5.6 9.1 16.7 4.0 7.3 3.2 8.9 12.5 6.1 42.6 15.3 10.5 8.2 26.7 9.6 6.6 33.4 7.2 21.0 7.3 11.3 25.7 51.9 9.7 28.8 4.7 31.0 18.2

97 94

94

88 79 95 98 98 99 92 98 97 95 92 98 96 98 96 94 97 75 92 94 96 85 95 97 83 96 89 96 94 85 63 95 86 98 84 91

%RE (A)

1000 pg/μL %CV (P)

9.5 17.2

5.6

21.2 16.4 12.4 12.5 6.6 7.1 13.3 12.2 6.3 4.8 17.4 4.3 8.2 14.9 10.1 17.6 14.3 33.5 16.0 24.7 7.7 16.1 7.5 12.2 31.2 4.8 17.7 9.7 7.4 44.2 18.3 8.6 15.3 17.1 38.6 11.5

95 91

97

89 88 94 94 97 96 93 94 97 98 90 98 96 93 95 91 93 83 92 88 96 92 96 94 84 98 91 95 96 74 87 96 92 91 78 93

%RE (A)

500 pg/μL %CV (P)

9.0 18.2

39.5

21.0 75.0 19.7 7.3 3.2 11.4 14.4 11.7 7.7 15.0 29.2 6.5 8.8 12.8 22.7 10.6 34.7 68.8 11.5 14.6 12.8 19.8 15.2 6.1 67.0 8.2 19.9 10.7 11.5 123.3 50.4 35.0 59.5 14.0 1.0 23.0

95 91

80

85 47 90 96 98 94 93 94 96 93 83 97 96 94 89 95 83 66 94 93 94 90 92 97 53 96 90 95 94 13 64 82 70 93 99 89

%RE (A)

250 pg/μL %CV (P)

Analytical Chemistry Article


4-hydroxy-E1-1-N-7-guanine 4-hydroxy-E2-1-N-7-guanine 2-hydroxyestrone 2-hydroxyestradiol 2-hydroxy-E1-1 + 4-glutatione 2-hydroxy-E2-1 + 4-glutatione 2-hydroxy-E1-1 + 4-cysteine 2-hydroxy-E2-1 + 4-cysteine 2-hydroxy-E1-1 + 4-Nacetylcysteine 2-hydroxy-E2-1 + 4-Nacetylcysteine 2-hydroxy-E1-6-N-3-adenine 2-hydroxy-E2-6-N-3-adenine 2-hydroxyestriol 3-methoxy-2-OH-estrone 2-methoxy-3-OH-estrone 2-methoxy-3-OH-estradiol 2,3-dimethoxyestrone 2,3-dimethoxyestradiol 6α-hydroxyestradiol 6β-hydroxyestradiol 6-ketoestrone 6-ketoestradiol 6-dehydroestradiol 6-dehydroestrone 16α-hydroxyestrone 17-epiestriol estriol 16,17-epiestriol 16-epiestriol estriol-3-sulfate estriol-3-glucuronate 3-methoxy estriol 16-keto-17β-estradiol 6-ketoestriol 7-dsehydroestradiol equilin dihydroequilin-3-SO4 equilin-3-SO4 estrone-9-N3-Ade

40 41 42 43 44 45 46 47 48

50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78

49

compound

no.a

Table 1. continued

PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI NI PI PI PI PI PI PI PI PI PI

PI

PI PI PI PI PI PI PI PI PI

mode

420.0 422.2 287.3 301.3 301.3 303.3 315.3 317.3 271.2 271.2 285.3 287.3 271.2 269.3 287.3 289.3 289.3 289.3 289.4 367.2 487.3 285.3 287.2 303.3 271.3 269.3 373.2 347.2 404.3

450.1

436.2 438.1 287.3 271.2 592.2 594.1 406.0 408.3 448.3

parent

135.9 136.0 269.0 137.0 189.2 137.2 201.0 302.2 156.9 156.9 133.0 121.2 137.2 156.9 251.0 271.2 225.4 106.1 106.1 287.3 198.9 266.9 251.4 107.0 229.8 211.1 332.0 267.3 269.0

162.0

152.0 272.0 268.9 175.1 463.2 465.4 316.9 319.0 161.9

daughter

6.1 5.9 8.6 10.1 10.1 9.5 11.0 10.7 6.9 6.6 8.1 7.9 8.3 9.4 9.8 9.4 9.7 9.4 9.4 6.5 5.5 9.1 7.6 6.2 12.4 9.4 9.7 8.4 6.4

7.3

6.3 6.3 8.7 8.3 6.6 6.6 8.2 7.2 7.7

Rt

0.119 0.119 0.008b 0.166 0.008b 0.331 0.032b 0.079b 0.173 0.173 0.088b 0.087b 0.092b 0.019b 0.175 0.173 0.347 3.468 3.468 12.806 2.153 0.002b 3.492 0.331 3.699 0.019b 1.342 6.749 0.124

0.557

0.230 0.229 0.349 0.347 0.423 0.421 0.247 0.614 0.112

LOD, pmole

0.9742 0.8714 0.9691 0.9767 0.9819 0.9827 0.9987 0.9819 0.9412 0.9861 0.9469 0.9743 0.7277 0.9384 0.9916 0.9776 0.9103 0.8397 0.8312 0.7324 0.9784 0.9653 0.7780 0.8905 0.9847 0.9530 0.9602 0.9566 0.9661

0.9829

0.9634 0.9606 0.9182 0.9692 0.9594 0.9028 0.9640 0.9495 0.9705

r2

25−20000 50−20000 5−20000 10−20000 0.5−20000 25−20000 2.5−20000 2.5−20000 5−20000 25−20000 2.5−20000 10−20000 50−20000 2.5−20000 25−20000 50−20000 25−20000 5−20000 10−20000 500−20000 250−20000 0.5−20000 100−20000 10−20000 2.5−20000 2.5−20000 50−20000 250−20000 10−20000

50−20000

25−20000 10−20000 1−20000 5−20000 25−20000 100−20000 25−20000 50−20000 10−20000

linear range, pg/μL

4.1 5.7 12.1 7.1 3.3 16.2 7.1 7.0 25.9 10.7 7.2 8.0 15.8 6.1 12.2 10.3 11.3 15.2 15.2 29.3 10.4 4.2 20.1 10.1 35.5 8.7 9.2 19.1 15.6

12.3

14.8 3.3 10.2 11.8 13.6 14.9 16.3 10.4 8.2

98 97 94 96 98 92 96 95 87 94 96 96 92 97 94 95 94 92 91 83 94 98 88 95 79 96 95 86 92

94

93 98 95 94 93 93 92 95 96

%RE (A)

5000 pg/μL %CV (P)

10.0 4.9 13.6 11.2 5.0 18.6 3.9 17.4 13.2 10.2 5.4 4.6 7.7 8.7 6.3 10.7 15.9 13.8 6.8 15.2 14.1 4.7 10.1 9.8 41.4 7.0 7.3 7.4 8.9

7.8

12.5 9.9 13.5 11.7 8.6 6.9 9.4 12.2 3.6

95 98 92 94 98 89 98 91 93 95 97 98 96 96 96 94 91 92 96 91 92 98 95 95 71 97 96 96 96

96

94 95 93 94 96 97 95 94 98

%RE (A)

2500 pg/μL %CV (P)

6.4 6.4 20.2 7.5 13.7 26.3 7.1 3.2 4.1 17.7 12.6 11.3 22.1 22.0 13.8 26.1 17.9 24.8 28.1 18.5 26.7 8.2 19.8 5.1 120.1 14.8 15.4 32.4 14.9

10.4

9.2 8.5 19.1 15.4 5.6 14.2 10.9 13.3 16.6

97 97 90 96 93 85 96 98 98 91 94 94 89 89 93 87 91 86 84 89 87 96 90 97 31 93 92 77 93

95

95 96 90 92 97 93 95 93 92

%RE (A)

1000 pg/μL %CV (P)

9.7 31.3 14.8 22.4 12.0 38.5 9.9 15.1 13.8 14.8 10.9 11.2 21.7 9.3 26.0 26.9 11.9 12.8 17.1 68.1 48.5 5.6 16.9 16.7 16.5 13.5 15.2 84.6 2.8

8.7

16.4 27.3 18.4 21.3 20.7 18.4 26.9 12.5 13.5

95 84 93 89 94 81 95 92 93 93 95 94 89 95 87 84 94 93 90 52 76 97 90 92 90 93 92 40 98

96

92 86 91 89 90 91 87 94 93

%RE (A)

500 pg/μL %CV (P)

30.8 32.9 16.1 35.6 9.8 44.9 13.3 10.1 8.2 16.8 24.1 24.9 17.4 7.0 40.2 38.9 41.3 25.3 24.1 68.7 75.6 10.1 78.9 20.8 45.4 8.0 13.9 68.7 6.6

9.4

40.0 62.7 17.4 13.8 17.8 35.3 25.0 6.9 17.1

85 84 92 82 95 78 93 95 96 92 88 88 91 96 80 81 79 87 88 51 56 95 61 90 68 96 93 51 97

95

80 69 91 93 91 82 87 97 91

%RE (A)

250 pg/μL %CV (P)


4954


4955

b

PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI PI NI PI PI PI PI PI

mode 406.3 315.3 313.3 297.3 357.3 329.2 371.3 429.3 355.3 331.3 331.3 373.3 415.3 415.3 415.3 415.3 311.3 255.3 371.2 373.3 255.3 271.2 389.3

parent 271.0 107.1 253.1 255.1 135.2 269.2 329.2 267.3 313.4 289.0 253.1 313.2 295.4 355.2 295.0 355.1 210.9 159.1 177.2 255.1 158.9 252.9 253.1

daughter 6.0 11.1 10.5 11.1 10.2 10.6 11.3 10.6 12.4 8.7 8.9 10.4 11.9 11.9 11.9 11.9 11.1 9.9 11.6 9.9 6.5 7.0 8.0

Rt 0.247 0.08b 0.160 0.07b 1.402 0.003b 0.006b 0.023b 0.141 0.303 0.303 0.268 0.241 0.006b 0.06b 0.121 0.081b 0.001b 0.007b 0.268 0.001b 0.064b 0.257

LOD, pmole 0.9336 0.9960 0.9973 0.9960 0.9722 0.9444 0.9967 0.9997 0.9819 0.9825 0.9415 0.9958 0.8913 0.9650 0.9639 0.9373 0.9458 0.9339 0.9863 0.9467 0.9608 0.8435 0.9587

r2 50−20000 10−20000 10−20000 2.5−20000 100−20000 1−20000 0.5−20000 2.5−20000 25−20000 50−20000 25−20000 10−20000 10−20000 1−20000 5−20000 25−20000 5−20000 0.5−20000 2.5−20000 25−20000 1−20000 2.5−20000 25−20000

linear range, pg/μL 14.6 6.0 5.0 7.6 2.6 5.8 5.9 7.4 13.0 12.3 3.8 9.3 4.0 3.1 1.4 4.1 5.7 5.2 11.7 6.2 0.9 10.5 10.1

93 97 97 96 99 97 97 96 93 94 98 95 98 98 99 98 97 97 94 97 100 95 95

%RE (A)

5000 pg/μL %CV (P) 12.3 9.8 12.5 8.5 4.5 1.3 8.6 6.7 19.0 18.3 2.6 4.4 10.7 5.1 2.4 3.5 11.4 2.7 8.9 4.2 2.2 18.2 5.6

93 95 93 96 98 99 96 97 90 89 99 98 95 97 99 98 94 99 96 98 99 91 97

%RE (A)

2500 pg/μL %CV (P) 26.2 6.7 7.0 7.4 17.3 1.1 4.9 10.1 14.2 14.1 16.9 10.7 7.6 4.3 3.4 4.1 11.1 6.2 6.6 3.9 7.2 12.2 14.0

85 97 96 96 91 99 98 95 92 92 92 95 96 98 98 98 94 97 97 98 96 94 93

%RE (A)

1000 pg/μL %CV (P) 22.4 9.8 26.2 12.2 33.4 3.1 10.8 13.9 15.6 42.3 20.4 22.2 7.0 9.2 8.0 15.1 28.1 7.5 9.7 7.7 5.0 17.5 2.8

87 95 87 94 83 98 95 93 92 76 90 89 96 95 96 92 86 96 95 96 98 91 99

%RE (A)

500 pg/μL %CV (P) 66.1 18.3 21.7 13.0 30.2 3.5 13.1 4.0 21.6 67.6 20.9 45.5 11.2 13.8 4.1 16.0 22.9 8.9 18.8 10.2 7.6 16.8 27.4

67 91 89 94 85 98 93 98 89 66 90 77 94 93 98 92 89 96 91 95 96 92 86

%RE (A)

250 pg/μL %CV (P)

List of the 101 steroids and estrogen-related compounds with the masses of parent and daughter ions that were used for MRM method optimization. Compound #86 through #101 are ester derivatives. Analytes that are detected in the low range, LOD < 0.100 (arbitrary).

estradiol-9-N3-Ade estradiol-3-acetate estrone-3-acetate estradiol-3,17α-diacetate estradiol-3,17β-diacetate 2-hydroxyestradiol-17-acetate 6-ketoestradiol-3,17-diacetate 6-ketoestriol triacetate 6-dehydroestradiol diacetate estriol-3-acetate estriol-16-acetate estriol-16,17-diacetate 17-epiestriol-triacetate estriol triacetate 16,17-epiestriol-triacetate 16-epiestriol-triacetate equilinacetate eEstradiol-3-hemisuccinate estrone-3-hemisuccinate estradiol-17-hemisuccinate estradiol-3,17-dihemisuccinate estriol-3-hemisuccinate estriol-16-hemisuccinate

79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101

a

compound

no.a

Table 1. continued




Article

Figure 2. Liquid−liquid extraction (LLE) recovery of a standard 101 steroids and estrogen-related compounds. The 100 μL aliquots from 100 mg of human breast tissue homogenates were spiked with the total 12.5 pg/μL of 101 steroids and estrogen-related compounds before and after (control) LLE with 100 μL of CH3OH, final solvent ratio CH3OH/H2O (1:1). Samples were further processed as described in the Sample Preparation and Analysis section. The recovery of each compound was determined by comparing the experimental values to the controls. The data presented is an average of three measurements.

the carrier solution, and mass spectra were recorded. The masses of parent ion and daughter ions were obtained in the MS and MS/MS operations. MS/MS parameters were further used in the multiple reaction monitoring (MRM) method for UPLC/MS/MS operation. Analytical separations of the mixture of 101 standards were conducted on the UPLC system using an Acquity UPLC HSS T3 1.8 μm 1 × 150 mm analytical column kept at 50 °C and at a flow rate of 0.15 mL/min. The gradient started with 100% A (0.1% formic acid in H2O) and 0% B (0.1% formic acid in CH3CN), after 2 min, changed to 80% A over 2 min, and then 45% A over 5 min, followed by 20% A in 2 min. Finally, over 1 min, it was changed to the original 100% A, resulting in a total separation time of 12 min. The elutions from the UPLC column were introduced to the mass spectrometer, and resulting data were analyzed and processed using MassLynx 4.1 software. Method Validation. Human breast tissues were used for method validation. Recovery and linearity as well as accuracy, precision, and limit of detection were determined for all 101 analytes. To calculate limits of detection, various concentrations, 0.05, 0.1, 0.25, 0.5, 1.0, 2.5, 5.0, 10, 25, 50, 100, 250, 500, 1000 pg/μL, of the analytes were injected to UPLC/MSMS. The injected amount that resulted in a peak with a height at least 3 times as high as the baseline noise level was used as the limit of detection. The intraday precision and accuracy were determined by calculating the percent coefficient of variation (%CV) and relative error (%RE) of the measurement of five replicates of each of the validation standard concentrations, 250, 500, 1000, 2500, and 5000 pg/μL, analyzed on the same day. Sample Preparation and Analysis. Ten breast tissue samples of women (26−53 yrs range, median age 47 yrs; 9 white and 1 asian) were obtained from UC Davis, Cancer Center Biospecimen Repository, which were approved for use by the Internal Review Board. Weighed (100 mg) breast tissue

spectrometry (MS/MS) for steroid metabolome composed of androgens, corticosteroids, progestogens, estrogens, estrogen metabolites, estrogen conjugates, and estrogen-DNA adducts as well as exogenous steroids, allowing quantification of over 100 steroids in about 12 min. Imbalance in steroid metabolism has been associated with many diseases; our goal here is to develop a method for a facile and clinically viable steroid assay to determine human health.

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EXPERIMENTAL SECTION Reference standards (Table 1) #1−31, 42, 43, 52−77, and 80− 101 were purchased from Steraloids (Newport, RI), whereas, #32−41, 44−51, 78 and 79 were synthesized by using the reported procedures.39−41 All solvents were HPLC grade, and all other chemicals used were of the highest grade available. For each analyte, stock solutions of 1 mg/mL concentrations were prepared in a methanol/water (1:1 v/v) mixture. In some cases, with the solubility problem, either water or methanol was used for preparing stock solution. Stock steroid mixture was prepared by mixing 20 μL of 1 mg/mL solution of each steroid and adjusting the final volume to 1 mL by using methanol/ water (1:1 v/v). All the stock solutions were stored at −80 °C. MS, MS/MS, and UPLC-MS/MS Analysis of Estrogen Metabolites. A Xevo-TQ triple quadruple mass spectrometer (Waters, Milford, MA, USA) recorded MS and MS/MS spectra using electro spray ionization (ESI) in positive ion (PI) and negative ion (NI) mode, capillary voltage of 3.0 kV, extractor cone voltage of 3 V, and detector voltage of 650 V. Cone gas flow was set at 50 L/h, and desolvation gas flow was maintained at 600 L/h. Source temperature and desolvation temperatures were set at 150 and 350 °C, respectively. The collision energy was varied to optimize daughter ions. The acquisition range was 20−500 Da. The test samples (compounds 1−101) at 5 μg/mL were introduced to the source at a flow rate of 5 μL/min by using acetonitrile/water (1:1) and 0.1% formic acid mixture as 4956



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samples were ground and suspended in 4 mL of a 1:1 water/ methanol mixture. The suspension was homogenized, and the resulting homogenate was cooled on ice. The precipitated material was removed by centrifuging at high speed for 5 min, and the supernatant was removed and evaporated in a SpeedVaac (Labconco Inc.) followed by lyophilizer (Labconco Inc.). The residue was suspended in 150 μL of CH3OH/H2O (1:1), filtered through a 0.2 μm ultracentrifuge filter (Millipore inc.) and subjected to UPLC/MS-MS analysis. Ten samples were run in duplicate during UPLC-MS/MS analysis. Samples were placed in an Acquity sample manager which was cooled to 5 °C to preserve the analytes. Pure standards were used to optimize the UPLC-MS/MS conditions prior to sample analysis. Also, the standard mixture was run before the first sample, after the fifth sample, and after the last (10th) sample to prevent errors due to matrix effect and day-today instrument variations. In addition, immediately after the initial standard and before the first sample, two spiked samples were run to calibrate for the drift in the retention time of all analytes due to the matrix effect. After standard and spiked sample runs, blank was injected to wash the injector and remove carry over effect.

Table 2. Accuracy and Precision of LLE

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RESULTS AND DISCUSSION Small molecule metabolites such as streroids have immense effect on human health. Estrogens and androgens estrogens are involved in growth and function of the reproductive organs, development of secondary sexual characteristics, and behavioral patterns in humans. Progestogens serve as a precursor to other steroids. Corticosteroids are involved in the regulation of many aspects of metabolism, stress and immune response, inflammation, electrolyte, and water levels. In addition, balance of various steroid metabolic pathways has been shown to be associated with human health. Thus, measurement of steroid metabolome in biological samples can play a pivotal role in determining human health and diagnosis. The data presented here shows a simple low cost liquid−liquid extraction (LLE) method for extraction of 101 endogenous and exogenous steroids from tissue samples followed by their UPLC-MS/MS measurements in 12 min. In spite of recent advances, development of analytical methods for global analysis of steroids has been challenging due to their low levels, diversity in their chemical and physical properties, viz., polarity and stability, dynamic range of their physiological concentrations, and variation in physiological conditions. Hence, current SPE extraction methods are not efficient in extracting various classes of steroids together. In addition, some of the present methods, especially GC/MS, require a derivatization step. Moreover, although there are existing LC-MS/MS based methods, these cannot be employed for high throughput analysis due to extended anlytical time and costs per analysis or coverage of steroids. To overcome these problems, LLE strategies were employed for tissue analysis. Extraction of tissue homogenate samples with methanol provided wide steroid coverage (Figure 2). Average extraction recovery of 101 steroids was 89.2% with standard deviation ±22 (Figure 2), and the average %CV for recovery was 18.7 ± 18.2 (Table 2). In general, average recoveries for androgens (#3, 4, 12, 13, 14), corticosterones (#7, 8, 10, 11), catecholestrogens (#27, 28, 42, 43), methoxyestrogens (#24, 29, 30, 31, 53−57, 71), hydroxyestrogens (#17−20, 52, 58, 59, 67, 68), 2-catechol adducts (#50, 51), acetates (#80, 81, 84, 88, 89, 95), triacetates (#86, 91−94), and hemisuccinates (#96−

compound no.

%CV (P)

%RE (A)

compound no.

%CV (P)

%RE (A)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51

88 25 19 8 7 6 18 14 9 32 53 8 3 22 6 20 5 6 12 10 18 2 2 19 23 17 4 9 13 24 4 34 19 20 47 10 7 13 11 6 19 3 21 31 13 66 47 3 25 4 4

49 86 89 95 96 97 90 92 95 82 69 95 98 88 97 88 97 97 93 94 90 99 99 89 86 90 98 95 93 86 98 80 89 88 73 94 96 92 93 96 89 98 88 82 93 62 73 98 85 98 98

52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101

5 45 6 36 5 2 5 19 9 25 56 10 12 16 86 9 10 2 62 4 36 4 4 8 8 69 30 70 25 10 16 32 14 3 11 21 9 23 29 10 7 26 11 12 6 16 17 5 4 18

97 74 96 79 97 99 97 89 95 85 68 94 93 91 50 95 94 99 64 98 79 97 98 96 95 60 83 60 85 94 91 81 92 98 94 88 95 87 83 94 96 85 94 93 96 91 90 97 98 90

101) were above 90%. Estrogens (#15, 16, 66), ketoestrogens (#23, 60, 61, 72), 4-catechol adducts (#38−41), and diacetates (# 82,83,85,87,90) had an average recovery between 80 and 90%, whereas for progestogens (# 1,2,5,6,9), dehydroestrogens (# 21, 22, 62, 63, 74), 2-catechol conjugates (#44−49), and 4catechol conjugates (#32−37) recovery was between 70 and 80%. Moderate recovery in progestogens and dehydroestrogens suggests the water/methanol (1:1) mixture may not be a good 4957



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Figure 3. Typical chromatogram of representative steroids and estrogen metabolites, which were obtained in a single injection of breast tissue extract.

estrones (ketones) leaving all the estradiol related metabolites unmeasured. Another method reported earlier is capable of quantifying 15 estrogens and estrogen metabolites simultaneously.43 This method uses two/three step sample preparation. First, the serum samples are extracted with dichloromethane, and then, they are derivatized with dansyl chloride. A single HPLC run for the sample analysis is about 75 min, whereas our method does not require derivatization, and a single step LLE followed by UPLC-MS/MS measures over 100 indigenous as well as exogenous steroids in 12 min. The developed method was validated by determining limit of quantification, linear dynamic range, recovery, precision, and accuracy (Table 1). The analytical parameter determinations of the targeted endogenous as well as exogenous steroids were done using standard mixtures. The results indicated that the LOD was in the range of 0.001−15.7 pmole, suggesting that the developed method is highly sensitive for simultaneous quantification of a complete panel of steroids. The linearity of the method was determined from the calibration curves constructed for each analyte in human breast tissue matrixes. Regression analysis showed that the correlation coefficients (R2) were above 0.90 for most of the analytes in breast tissue matrixes (Table 1). The data for accuracy, precision, and recovery are presented in Table 1. The median values for intraday variance were below 20% at 250 and 500 pg/μL concentrations, whereas they were 11.1, 7.7, and 8.2% at 1000,

extraction solvent system for these analytes, whereas 2-catechol conjugates and 4-catechol conjugates may have undergone oxidation. Mass spectrometry methods were optimized to detect the majority of steroids (total 97) under positive ionization mode; only 4 analytes were detected in negative ionization mode resulting in improved sensitivity due to fewer polarity switches (Table 1). This was achieved by adding 0.1% formic acid to the carrier solution when the MRM method was developed and then 0.1% formic acid to both, A and B, mobile phases. MRM transitions were then optimized to ensure optimal detection responses and specificity. Further use of UPLC, equipped with a 1 × 150 mm, 1.8 μm analytical column significantly reduced chromatography time for 101 steroids to just 12 min, resulting in reduction of potential costs per sample. In recent years, UPLC or U-HPLC has been demonstrated to outperform traditional HPLC separations resulting in higher efficiencies and sensitivity. Furthermore, the method described in this manuscript has many advantages over the current LCMS methods that focus on estrogens and estrogen metabolites; for example, a recent method reports a stable isotope dilution liquid chromatography/selected reaction monitoring/mass spectrometry assay for serum estrone, 16α-hydroxyestrone, 4methoxyestrone, and 2-methoxyestrone.42 This method requires a three step, i.e., LLE followed by derivatization followed by SPE, sample preparation. In addition, the Girard P reagent used for derivatization only forms Schiff’s base with 4958



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National Cancer Institute funded Biospecimen Repository for biospecimens.

2500, and 5000 pg/μL concentrations, respectively, indicating moderately good precision of the method. Sample analysis also showed good accuracy at all five concentration levels (RE < 10%), and the average extraction recovery was greater than 90%. These results support that this method is dependable and reproducible for the simultaneous analysis of 101 endogenous and exogenous steroids from various metabolic networks. Finally, targeted UPLC-MS/MS based metabolomic analysis was performed on human breast tissues to investigate total steroid anabolic/catabolic pathways in normal human breast. The multiple reaction monitoring (MRM) chromatograms of representative steroids and estrogen metabolites, which were obtained in a single 12 min injection of breast tissue extract, are shown in Figure 3. The average levels of steroids and estrogen related compounds measured from ten breast tissue samples are presented in Table 1. Overall presence of all major classes of steroids, viz., androgens, corticosteroids, progestogens, and estrogens, was detected in breast tissue (Table 1 and Figure 3). From the metabolic profile, it appears that estrogens are further metabolized to various classes of derivatives, such as glucuronates, hydroxyestrogens, methoxyestrogens, conjugates, and adducts. Endogenous steroids and their derivatives have long been of interest as biomarkers of various diseases resulting from steroid imbalances and have been used in clinical and preclinical studies.44−46 Recently, steroid metabolite profiling has been used to examine potential biomarkers indicating the activity of nonfunctioning adrenal incidentalomas,47 adrenal disorders and adrenal tumors,48 and the influence of gestational age on the preterm labor.49 Furthermore, steroid profiling was also applied in search of biomarkers of breast cancer,18,19 prostate cancer,37 non-Hodgkin lymphoma,36 Parkinsons disease,38 urogenital tract cancer diseases (bladder, kidney, prostate, and testis),50 and stress and depressive disorders51 and for diagnosing genetic defects in newborns.52 The ability to detect more than a hundred steroids in a single run in less than 15 min will likely prove to be very useful in a number of clinical, toxicological, and nutritional investigations. In summary, this UPLC-MS/MS assay method provides analysis of wide range of indigenous steroids (#1−79) as well as exogenous steroid esters (#80−101) in 12 min. The limit of detection and linear range suggests that it is possible to detect and quantify steroids in tissue samples to investigate fluxes in their metabolic pathway. This method could be employed in large sample size investigations with high throughput demands.

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REFERENCES

(1) Gruber, C.; Tschugguel, W.; Schneeberger, C.; Huber, J. N. Engl. J. Med. 2002, 346, 340−352. (2) Clemons, M.; Goss, P. N. Engl. J .Med. 2001, 344, 276−285. (3) Bulun, S.; et al. J. Steroid Biochem. Mol. Biol. 2007, 106, 81−96. (4) Carruba, G. Ann. N.Y. Acad. Sci. 2006, 1089, 201−217. (5) Shang, Y. Nat. Rev. Cancer 2010, 6, 360−368. (6) Khosla, S. J. Clin. Endocrinol. Metabol. 2010, 95, 3569−3577. (7) Chakraborti, A.; Gulati, K.; Ray, A. Rev. Neurosci. 2010, 18, 395− 416. (8) Bechlioulis, A.; et al. Curr. Vasc. Pharmacol. 2010, 8, 249−258. (9) Mayes, J.; Watson, G. Obes. Rev. 2004, 5, 197−216. (10) Persson, I. J. Steroid Biochem. Mol. Biol. 2000, 74, 357−364. (11) Feigelson, H.; Henderson, B. Carcinogenesis 1996, 17, 2279− 2284. (12) Simpson, E.; Brown, K. Exp. Rev. Endocrinol. Metabol. 2011, 6, 383−395. (13) Cleary, M.; Grossmann, M. Endocrinology 2009, 6, 2537−2542. (14) Liehr, J. G.; Fang, W. R.; Sirbasku, D. A.; Ari-Ulubelen, A. J. Steroid Biochem. 1986, 24, 353−356. (15) Li, J. J.; Li, S. A. Fed. Proc. 1987, 46, 1858−1863. (16) Newbold, R. R.; Liehr, J. G. Cancer Res. 2000, 60, 235−237. (17) Yager, J.; Davidson, N. N. Engl. J. Med. 2006, 354, 270−282. (18) Gaikwad, N. W.; Yang, L.; Muti, P.; Meza, J. L.; Pruthi, S.; Ingle, J. N.; Rogan, E. G.; Cavalieri, E. L. Int. J. Cancer 2008, 122, 1949− 1957. (19) Gaikwad, N. W.; Yang, L.; Pruthi, S.; Ingle, J. N.; Sandhu, N.; Rogan, E.; Cavalieri, E. Breast Cancer: Basic Clin. Res. 2009, 3, 1−8. (20) Andrew, R. Best Pract. Res., Clin. Endocrinol. Metab. 2001, 15, 1− 16. (21) Hoffmann, P.; Hartmann, M. F.; Remer, T.; Zimmer, K. P.; Wudy, S. A. Steroids 2010, 75, 1067−1074. (22) Sadanalaa, K. C.; Leea, J.; Chunga, B. C.; Choi, M. H. Mass Spectrom. Lett. 2012, 3, 4−9. (23) Hauser, B.; Deschner, T.; Boesch, C. J. Chromatogr., B 2008, 862, 100−112. (24) Kuehnbaum, N. L.; Britz-McKibbin, P. Anal. Chem. 2011, 83, 8063−8068. (25) Wudy, S. A.; Wachter, U. A.; Homoki, J.; Teller, W. M. Pediatr. Res. 1995, 38, 76−80. (26) Tate, J.; Ward, G. Clin. Biochem. Rev. 2004, 25, 105−120. (27) Zhou, Y. Q.; Wang, Z. J.; Jia, N. J. Environ. Sci. (China) 2007, 19, 879−884. (28) Flores-Valverde, A. M.; Hill, E. M. Anal. Chem. 2008, 80, 8771− 8779. (29) Dai, W.; Huang, Q.; Yin, P.; Li, J.; Zhou, J.; Kong, H.; Zhao, C.; Lu, X.; Xu, G. Anal. Chem. 2012, 84, 10245−10251. (30) Carvalho, V. M.; Nakamura, O. H.; Vieira, J. G. H. J. Chromatogr., B 2008, 872, 154−161. (31) Mitamura, K.; Yatera, M.; Shimada, K. Analyst 2000, 125, 811− 814. (32) Xu, X.; Ziegler, R. G.; Waterhouse, D. J.; Saavedra, J. E.; Keefer, L. K. J. Chromatogr., B 2002, 780, 315−330. (33) Vanhaecke, L.; Bussche, J.; Wille, K.; Bekaert, K.; De Brabander, H. Anal. Chim. Acta 2011, 700, 70−77. (34) Hintikkaa, L.; Haapalaa, M.; Franssilab, S.; Kuurannec, T.; Leinonenc, A.; Kostiainena, R. J. Chromatogr., A 2010, 1217, 8290− 8297. (35) Ahonen, L.; Haapala, M.; Saarela, V.; Franssila, S.; Kotiaho, T.; Kostiainen, R. Rapid Commun. Mass Spectrom. 2010, 24, 958−964. (36) Gaikwad, N.; Yang, L.; Vose, J.; Rogan, E.; Cavalieri, E. Biomarkers 2009, 14, 502−512. (37) Yang, L.; Gaikwad, N.; Meza, J.; Cavalieri, E.; Mutti, P.; Trock, B.; Rogan, E. Prostate 2009, 69, 41−48. (38) Gaikwad, N.; Murman, D.; Beseler, C.; Rogan, E.; Cavalieri, E. Biomarkers 2011, 16, 434−444.

AUTHOR INFORMATION

Corresponding Author

*Address: Departments of Nutrition and Environmental Toxicology, University of California, One Sheilds Ave, Davis, CA 95616. Phone: (530) 752-5255. Fax: (530)-752-8966. Email: [email protected]. Notes

The author declares no competing financial interest.

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ACKNOWLEDGMENTS This research was supported by a grant from Center for Health & Nutrition Research (CHNR), Department of Nutrition, University of California, Davis, NIFA. USDA grant #CA-DNTR-2104-H and a Fellowship grant from the Hellman Foundation. The author thanks UC Davis Cancer Center’s 4959



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(39) Li, K. M.; Todorovic, R.; Devanesan, P.; Higginbotham, S.; Kofeler, H.; Ramanathan, R.; Gross, M. L.; Rogan, E. G.; Cavalieri, E. L. Carcinogenesis 2004, 25, 289−297. (40) Cao, K.; Stack, D. E.; Ramanathan, R.; Gross, M. L.; Rogan, E. G.; Cavalieri, E. L. Chem. Res. Toxicol. 1998, 11, 909−916. (41) Gaikwad, N. W. PLoS One 2013, in press. (42) Rangiah, K.; Shah, S. J.; Vachani, A.; Ciccimaro, E.; Blair, I. Rapid Commun. Mass Spectrom. 2011, 25, 1297−1307. (43) Xu, X.; Roman, J. M.; Issaq, H. J.; Keefer, L. K.; Veenstra, T. D.; Ziegler, R. G. Anal. Chem. 2007, 79, 7813−7821. (44) Findling, J. W.; Raff, H. J. Clin. Endocrinol. Metab. 2006, 91, 3746−3753. (45) Nomura, S.; Fujitaka, M.; Jinno, K.; Sakura, N.; Ueda, K. Clin. Chim. Acta 1996, 256, 1−11. (46) Lee, S. H.; Yang, Y. J.; Kim, K. M.; Chung, B. C. Cancer Lett. 2003, 201, 121−131. (47) Kotłowska, A.; Maliński, E.; Sworczak, K.; Kumirska, J.; Stepnowski, P. Clin. Biochem. 2009, 42, 448−454. (48) Arlt, W.; Biehl, M.; Taylor, A. E.; Hahner, S.; Libé, R.; Hughes, B. A.; Schneider, P.; Smith, D. J.; Stiekema, H.; Krone, N.; et al. J. Clin. Endocrinol. Metab. 2011, 96, 3775−3784. (49) Hill, M.; Parízek, A.; Kancheva, R.; Dusková, M.; Velíková, M.; Kríz, L.; Klímková, M.; Pasková, A.; Zizka, Z.; Matucha, P.; et al. J. Steroid Biochem. Mol. Biol. 2010, 121, 594−610. (50) Konieczna, L.; Baczek, T.; Belka, M.; Fel, A.; Markuszewski, M.; Struck, W.; Markuszewski, M.; Kaliszan, R. J. Pharm. Biomed. Anal. 2013, 73, 108−115. (51) Plenis, A.; Konieczna, L.; Olȩdzka, I.; Kowalski, P.; Ba̧czek, T. Mol. Biosyst. 2011, 7, 1487−1500. (52) Homma, K.; Hasegawa, T.; Takeshita, E.; Watanabe, K.; Anzo, M.; Toyoura, T.; Jinno, K.; Ohashi, T.; Hamajima, T.; Takahashi, Y.; et al. J. Clin. Endocrinol. Metab. 2004, 89, 6087−6091.

4960


Ultra Performance Liquid Chromatography-Tandem Mass

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