heat-map visualization of gas chromatography-mass ...heat-map visualization of gas...
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Heat-Map Visualization of GasChromatography-Mass Spectrometry BasedQuantitative Signatures on Steroid Metabolism
Ju-Yeon Moon,a,b Hyun-Jin Jung,a,b Myeong Hee Moon,b
Bong Chul Chung,a and Man Ho Choiaa Life Sciences Division, Korea Institute of Science and Technology, Seoul, Koreab Department of Chemistry, Yonsei University, Seoul, Korea
Abnormalities in steroid hormones are responsible for the development and prevention ofendocrine diseases. Due to their biochemical roles in endocrine system, the quantitativeevaluation of steroid hormones is needed to elucidate altered expression of steroids. Gaschromatographic-mass spectrometric (GC-MS) profiling of 70 urinary steroids, containing 22androgens, 18 estrogens, 15 corticoids, 13 progestins, and 2 sterols, were validated and itsquantitative data were visualized using hierarchically clustered heat maps to allow “steroidsignatures”. The devised method provided a good linearity (r2 � 0.994) with the exception ofcholesterol (r2 � 0.983). Precisions (% CV) and accuracies (% bias) ranged from 0.9% to 11.2%and from 92% to 119%, respectively, for most steroids tested. To evaluate metabolic changes,this method was applied to urine samples obtained from 59 patients with benign prostatichyperplasia (BPH) versus 41 healthy male subjects. Altered concentrations of urinary steroidsfound and heat maps produced during this 70-compound study showed also differencesbetween the ratios of steroid precursors and their metabolites (representing enzyme activity).Heat maps showed that oxidoreductases clustered (5�-reductase, 3�-HSD, 3�-HSD, and17�-HSD, except for 20�-HSD). These results support that data transformation is valid, since5�-reductase is a marker of BPH and 17�-HSD is positively expressed in prostate cells.Multitargeted profiling analysis of steroids generated quantitative results that help to explaincorrelations between enzyme activities. The data transformation and visualization describedmay to be found in the integration with the mining biomarkers of hormone-dependentdiseases. (J Am Soc Mass Spectrom 2009, 20, 1626–1637) © 2009 American Society for MassSpectrometry
Mass spectrometry based metabolite profilingreveals the metabolic states of biological sys-tems and provides comprehensive insights by
allowing comparisons between many metabolites si-multaneously present in cells, tissues, or organisms [1,2]. This technique promotes the establishment of rela-tionships between phenotypes and metabolisms byproviding descriptions of the distributions of metabo-lites and their biological functions. In fact, quantitativeanalyses of sets of metabolites in biochemical pathwayshave been used for physiological monitoring, toxicolog-ical evaluations, and clinical diagnosis [3–6].Many naturally occurring steroids with similar
chemical structures could yield biological information[7]. Endogenous steroids are divided into five groups,namely, androgens, estrogens, corticoids, progestins,and sterols, which are generally synthesized from cho-lesterol in the adrenal cortex, ovaries, and testes(Scheme 1). In biosynthetic pathways of steroid hor-
mone, two major types of enzymes are involved, cyto-chrome P450 and steroid oxidoreductase. Abnormalities ofthese enzymes often lead to hormonal imbalances thathave serious consequences, and which are responsiblefor the development of hormone-dependent diseases(see Supplementary Table 1, which can be found in theelectronic version of this article). For example, concen-trations of corticoids and their metabolic ratios providediagnostic evidence of apparent mineralocorticoid ex-cesses caused by 11�-HSD deficiency [8] and congenitaladrenal hyperplasia, which are caused by deficienciesof enzymes like hydroxylase (at C-11, 17, and 21) or3�-HSD [9]. In addition, enhanced androgen activitygenerated by the conversion of testosterone to dihy-drotestosterone (DHT) by 5�-reductase was utilized toallow early therapeutic intervention in young men [10].Enzyme activity profiles can be used to describe the
functional diversities of biological systems, which aredriven by genetic diversity. Although enzyme activitieshave been monitored by following reactions betweentargeted enzymes and substrate molecules, over-estimations by radioimmunoassay (RIA) and enzymeimmunoassay (EIA), because of cross reacting antibod-
Address reprint requests to Dr. M. H. Choi, Life Sciences Division, KoreaInstitute of Science and Technology, 39-1 Hawolkok-dong, Seongbuk-ku,Seoul 136-791, Korea. E-mail: [email protected]
Published online May 5, 2009© 2009 American Society for Mass Spectrometry. Published by Elsevier Inc. Received February 7, 20091044-0305/09/$32.00 Revised April 25, 2009doi:10.1016/j.jasms.2009.04.020 Accepted April 28, 2009
ies, limit the applicability of these assays, and further-more, only single enzymes can be estimated at a time[11–14]. In contrast to conventional enzyme assays, gaschromatography-mass spectrometry (GC-MS)-basedtechniques have better quantitative reproducibility [15,16]. For these reasons, GC-MS profiling has been widelyused for steroid analysis [17–20], and offers the basis fortechniques that can be applied to large-scale clinicalstudies [21].Clinical significances are generally expressed in ta-
bles or bar graphs that show changes in analytes acrossgroups of interest. For studies involving few com-pounds, these visualizations are enough to differentiateclasses showing metabolic differences. However, quan-titative datasets of multiple compounds are much moredifficult to represent visually. Statistical clustering of-fers one such approach, and has been utilized to sup-port genomic and proteomic studies [22–24]. In a simi-lar fashion, quantitative results obtained by metaboliteprofiling can be directly compared between samplesand utilized as metabolic biomarkers. In recent, MS-based quantitative data generated by hierarchical clus-tering analysis (HCA) has been subjected to patternanalysis for metabolite profiling [2, 25]. The concept of“metabolite signature” is a result of this process, andsuch signatures are useful for measuring and visualiz-ing the relative analyte concentrations. Although many
groups have used GC-MS based steroid analysis formining biomarkers, technical improvements that moreeffectively allow the visualization of steroid metabolitesare required [26]. However, no studies have reportedMS-based steroid signatures generated by HCA to date.Here, we introduce the GC-MS quantitative profiling
of 70 urinary steroids, including 22 androgens, 18estrogens, 15 corticoids, 13 progestins, and 2 sterols,generated by HCA to evaluate metabolic changes andenzyme reactions in steroid analysis. The aim of thisstudy was to validate a GC-MS profiling method and amethod that allows the quantitative visualization ofmultiple urinary steroids. To visualize quantitative re-sults, a microarray map (a type of heat map) wasdesigned to present the urine sample results of 59patients with benign prostatic hyperplasia (BPH) and 41healthy male subjects; BPH was chosen because steroidmetabolism is known to play a role in the progress ofprostate diseases [27–29]. This study focused on illus-trating the usefulness of steroid signatures for explain-ing both the concentrations of individual steroids andthe activities of enzymes correlated global steroidogen-esis in BPH, and suggest that enzyme activity profilingmay be a useful diagnostic tool and provide a means ofidentifying mining biomarkers in hormone-dependentdiseases.
Progestins, Sterols Androgens
EstrogensCorticoids
HO
O
H
OH
HO
O
HOH
DHEA
ααααββββββββ-diol
An
5α-reductase 17β-HSD3α-HSD
3β-HSD
17β-HSD
aromatase
5αααα−−−−dione
O
O
17β-HSD
3α-HSD
O
HOH
Epi-An
3β-HSD5α-reductase
O
Epi-T
OH
17α-HSD
17αααα-OH-PregPreg
Chol
17α-hydroxylase
H
HOH
O
Etio
OH
ββββααααββββ-diol
HOH
ββββαααααααα-diolHO
H
OH
16αααα-OH-DHEA
24S-OH-CholHO
OH
HO
O
OH
HO
O
HO
O
H
OH
17αααα-OH-ProgProg
3β-HSD 3β-HSD
O
O
O
OH
O
20,22-desmolase
11-DeoxyB 11-DeoxyF
21-hydroxylase 21-hydroxylase
O
OH
O
11β-hydroxylase 11β-hydroxylase
Cortisol (F)O
OHHO OH
O
O
OHOH
O
O
O
HO OH
THF / allo-THF, allo-DHF5β- / 5α-reductase
3β-HSD
11-DehydroB
17α-hydroxylase11β-hydroxylase
O
O
HO
11ββββ-OH-Prog
HO
O
HOH
HO
O
OHOOH
O
11β-hydroxylase
11β-HSD
Cortisone (E)
O
O
OHO
O
OH
HOH
HOOH
O
O OH
HOH
OH
O
HOH
OH
THDOC
THE
5β- / 5α-reductase3β-HSD
H
HO OH
O
O
allo-DHB
20αααα-OH-progH
O
O
5αααα-DHP
HOH
O
P-oneP-diol
21β-hydroxylase
5β-reductase3β-HSD
5α-reductase
17,20-lyase
17,20-lyase
3β-HSD
A-dione
O
O
HO
OH
A-diol
17β-HSD
O
OH3β-HSD
O
OH
HDHT
HOH
OH
ααααααααββββ-diol
5ββββ−−−−dione
O
OH
5β-reductase
HO
O
HO
OH
E1 17ββββ-E2
2-OH-E1HO
O
HO
aromatase
2-OH-E2
2-MeO-E2
2-MeO-E1HO
OH
HO
HO
OH
H3CO
HO
O
H3CO
4-OH-E1
4-OH-E2
4-MeO-E2
4-MeO-E1
16αααα-OH-E1 Estriol 16-keto-E2
16-Epi-E317-Epi-E3
HO
O
OH
HO
OH
O
HO
OH
OH
HO
OH
OCH3
HO
O
OCH3
HO
OH
OH
HO
OH
OH
HO
OH
O
HO
OH
OH
17β-HSD
methyltransferase
methyltransferase methyltransferase
methyltransferase
2-hydroxylase
17β-HSDO
O
HO OH
21-DeoxyF
5α-reductase
3α-HSD 17β-HSD
17α-HSD
HO
20α-HSD 3α-HSD
11β-HSD
20α-HSD
16α-hydroxylase
4-hydroxylase 16-hydroxylase
B
T
Scheme 1. General scheme for steroid metabolism in man. See Supplementary Table 1 for the fullnames of steroid hormones.
1627J Am Soc Mass Spectrom 2009, 20, 1626–1637 QUANTITATIVE STEROID SIGNATURES BY GC-MS
Experimental
Chemicals and Materials
Reference standards of the 70 steroids examined in thisstudy (Table 1) were obtained from Sigma (St. Louis, MO,USA), Steraloids (Newport, RI, USA), or NARL (Pumble,Australia). The internal standards used were, 16,16,17-d3-testosterone and methyltestosterone for 22 androgens,2,4,16,16-d4-estradiol for 18 estrogens, 9,11,12,12-d4-cortisolfor 15 corticoids, 2,2,4,6,6,17�,21,21,21-d9-progesteroneand 2,2,4,6,6,21,21,21-d8-17�-hydroxyprogesterone for 13progestins, and 2,2,3,4,4,6-d6-cholesterol for 2 sterols werepurchased from NARL and C/D/N isotopes (Pointe-Claire, Quebec, Canada). For solid-phase extraction (SPE),Oasis HLB cartridge (3 mL, 60 mg; Waters, Milford, MA,USA) was preconditioned with 3 mL of methanol fol-lowed by 3 mL of deionized water. Sodium acetate (re-agent grade), acetic acid (glacial, 99.99�%) and L-ascorbicacid (reagent grade) were obtained from Sigma (St. Louis,MO, USA). A solution of �-glucuronidase/arylsulfatasefromHelix pomatiawas purchased fromRoche DiagnosticsGmbH (Mannheim, Germany). The trimethylsilylating(TMS) agents, N-methyl-N-trifluorotrimethylsilyl acet-amide (MSTFA), ammonium iodide (NH4I), and dithio-erythritol (DTE) were purchased from Sigma. All organicsolvents used were of analytical or HPLC grade and werepurchased from Burdick and Jackson (Muskegan, MI,USA). Deionized water was prepared using the Milli-Qpurification system (Millipore, Billerica, MA, USA).
Standard Solutions and Quality-Control Samples
Stock solutions of all reference standards were preparedat a concentration of 1000 �g/mL in methanol andworking solutions were made up with methanol atconcentrations in the range 0.1 to 10 �g/mL. L-Ascorbicacid (1 mg/mL) was added to prevent the oxidations oflabile steroid metabolites. All standard solutions werestored at �20 °C until required and all were stable for aminimum of 3 mo. The urine samples used for calibra-tion and quality-control (QC) purposes were preparedin house from steroid-free urine [30]. Steroids-free urinesamples were prepared by percolating urine samplesthrough Serdolit PAD-1 (0.1–0.2 mm analytical grade;Serva, Heidelberg, Germany). In this way, urinary ste-roids and other potential interfering compounds areretained in the cartridges and the eluates were collected.After checking for endogenous steroids with negativeresult following the solvent extraction procedure, theywere used as matrix for steroid profiling.
Subjects and Sample Collection
First-morning urine samples were collected from 59BPH patients (age: 65.3 � 8.2 y male) and 41 healthymale subjects (age: 56.7 � 7.1 y) in the Department ofUrology at Severance Hospital (Seoul, Korea). All pa-tients underwent a transrectal ultrasound-guided oc-
tant biopsy and had either a suspicious finding bydigitorectal examination or an elevated level of serumprostate-specific antigen (PSA). The age-matched nor-mal controls showed no evidence of serum PSA levelelevation or of BPH. Steroid levels in urine were nor-malized versus urinary creatinine values using Jaffemethod [31].
Sample Preparation
Quantitative metabolite profiling of urinary steroidswas based on previous reports [4, 8, 32]. Briefly, urinesamples (2 mL) spiked with 20 �L of the 7 internalstandards (d3-testosterone and d4-estradiol; 1 �g/mL,d4-cortisol and d8-17�-hydroxyprogesterone; 5 �g/mL,methyltestosterone, d9-progesterone, and d6-cholesterolto 10 �g/mL) were extracted with Oasis HLB SPEcartridges coupled to a peristaltic pump. After loadinga sample onto a cartridge, the cartridge was washedwith 2 mL water and eluted twice with 2 mL ofmethanol. Combined methanol eluates were evapo-rated under a stream of nitrogen and then 1 mL of 0.2 Macetate buffer (pH 5.2), 100 �L of aqueous 0.2% ascorbicacid, and 50 �L of �-glucuronidase/arylsulfatase werewas added. After incubation at 55 °C for 3 h, thesolution was extracted twice with 2.5 mL of ethylacetate: n-hexane (2:3, vol/vol). Combined organic sol-vents were evaporated using a N2 evaporator at 40 °Cand further dried in a vacuum desiccator over P2O5-KOH for at least 30 min. Finally, the dried residue wasderivatized with MSTFA/NH4I/DTE (40 �L; 500:4:2,vol/wt/wt) at 60 °C for 20 min, and 2 �L of theresulting mixture was subjected to GC-MS in selected-ion monitoring (SIM) mode. To maximize extractionefficiencies, two organic solvents, tetrahydrofuran(THF) and ethyl acetate, were evaluated in the pH range5 to 9. In addition, the potential uses of diethyl ether,methyl tert-butyl ether, and n-hexane were investigatedfor promoting the partition of water-miscible THF andethyl acetate.
Instrumental Conditions
GC-MS was performed with an Agilent 6890 Plus gaschromatograph interfaced with a single-quadrupoleAgilent 5975 MSD at an electron energy of 70 eV and anion source temperature of 230 °C. Each sample (2 �L)was injected in split mode (10:1) at 280 °C and separatedthrough an Ultra-1 capillary column (25 m � 0.2 mmi.d., 0.33 �m film thickness; Agilent Technologies; PaloAlto, CA, USA). The GC oven temperature was initiallyset at 215 °C, then ramped to 260 °C at 1 °C/min, andfinally increased to 320 °C at 15 °C/min and held for 1min. The carrier gas was helium at a column headpressure of 210.3 kPa (column flow: 1.0 mL/min at oventemperature of 215 °C). For quantitative analysis, char-acteristic ions of each steroid were determined as theirTMS derivatives. Peak identifications were achieved by
1628 MOON ET AL. J Am Soc Mass Spectrom 2009, 20, 1626–1637
Tab
le1.
TheGC-MSinformationforquantitativeanalysisofsteroidsstudied
Co
mp
ou
nd
s(t
rivi
aln
ame)
Ab
bre
viat
ion
Ion
sele
cted
a
Ret
enti
on
tim
e(m
in)
Co
mp
ou
nd
s(t
rivi
aln
ame)
Ab
bre
viat
ion
Ion
sele
cted
Ret
enti
on
tim
e(m
in)
An
dro
gen
sE
stro
gen
s5�
-an
dro
stan
-3�
,17�
-dio
l�
��
-dio
l25
612
.12
17�
-est
rad
iol
17�
-E2
416
18.6
05�
-an
dro
stan
-3�
,17�
-dio
l�
��
-dio
l25
612
.87
Est
ron
eE
141
419
.12
An
dro
ster
on
eA
n43
415
.27
17�
-est
rad
iol
17�
-E2
416
19.9
8E
tio
cho
lan
olo
ne
Eti
o43
415
.44
2-m
eth
oxy
-17�
-est
rad
iol-
3-m
eth
ylet
her
2-M
eO-E
2-3-
met
hyl
eth
er38
823
.40
5�-a
nd
rost
an-3
�,1
7�-d
iol
��
�-d
iol
241
16.0
05 �
-an
dro
stan
-3�
,17�
-dio
l�
��
-dio
l25
616
.07
4-m
eth
oxy
-17�
-est
rad
iol
4-M
eO-E
244
623
.73
5�-a
nd
rost
an-3
�,1
7�-d
iol
��
�-d
iol
241
17.0
42-
met
ho
xyes
tro
ne
2-M
eO-E
144
424
.57
Ep
idih
ydro
test
ost
ero
ne
Ep
i-D
HT
434
17.4
62-
hyd
roxy
-17�
-est
rad
iol-
3-m
eth
ylet
her
2-O
H-E
2-3-
met
hyl
eth
er44
625
.06
11-k
eto
-an
dro
ster
on
e11
-ket
o-A
n52
017
.55
11-k
eto
-eti
och
ola
no
lon
e11
-ket
o-E
tio
520
17.6
02-
met
ho
xy-1
7�-e
stra
dio
l2-
MeO
-E2
446
25.5
3D
ehyd
roep
ian
dro
ster
on
eD
HE
A43
217
.85
2-h
ydro
xyes
tro
ne
2-O
H-E
150
225
.92
Ep
ian
dro
ster
on
eE
pi-
An
419
18.1
02-
hyd
roxy
-17 �
-est
rad
iol
2-O
H-E
250
426
.75
An
dro
sten
edio
lA
-dio
l43
418
.58
4-h
ydro
xyes
tro
ne
4-O
H-E
150
227
.34
5�-A
nd
rost
aned
ion
e5�
-dio
ne
432
18.6
04-
hyd
roxy
-17�
-est
rad
iol
4-O
H-E
250
428
.42
Ep
ites
tost
ero
ne
Ep
i-T
432
18.7
717
-ep
iest
rio
l17
-ep
i-E
350
429
.19
5 �-a
nd
rost
an-3
�,1
7�-d
iol
��
�-d
iol
241
18.8
3E
stri
ol
E3
504
29.8
2D
ihyd
rote
sto
ster
on
eD
HT
434
19.3
416
-ket
o-1
7�-e
stra
dio
l16
-ket
o-E
248
730
.06
An
dro
sten
edio
ne
A-d
ion
e43
019
.80
16a-
hyd
roxy
estr
on
e16
�-O
H-E
148
730
.06
Tes
tost
ero
ne
T43
220
.52
16-e
pie
stri
ol
16-e
pi-
E3
504
31.1
611
�-h
ydro
xyan
dro
ster
on
e11
�-O
H-A
n52
220
.73
2-h
ydro
xyes
trio
l2-
OH
-E3
592
37.3
011
�-
hyd
roxy
etio
cho
lan
olo
ne
11�
-OH
-Eti
o52
221
.05
d4-
17�
-est
rad
iolb
d4-
E2
420
19.8
8
16�
-hyd
roxy
-DH
EA
16�
-OH
-DH
EA
505
28.4
9d
3-te
sto
ster
on
ebd
3-T
435
20.4
4M
eth
ylte
sto
ster
on
ebM
eth
yl-T
446
24.2
1C
ort
ico
ids
Pro
ges
tin
sT
etra
hyd
rod
eoxy
cort
iso
lT
HS
548
34.9
85 �
-dih
ydro
pro
ges
tero
ne
5�-D
HP
445
20.0
1T
etra
hyd
rod
eoxy
cort
ico
ster
on
eTH
DO
C55
036
.26
Ep
ipre
gn
ano
lon
eE
pi-
P-o
ne
447
23.3
3T
etra
hyd
roco
rtis
on
eT
HE
634
38.6
6P
reg
nan
olo
ne
P-o
ne
447
23.6
2T
etra
hyd
roco
rtis
ol
TH
F63
641
.30
Allo
pre
gn
ano
lon
eA
llo-P
-on
e44
723
.97
Dih
ydro
deo
xyco
rtic
ost
ero
ne
DH
DO
C54
842
.03
Pre
gn
aned
iol
P-d
iol
269
25.0
3A
llote
trah
ydro
cort
iso
lA
llo-T
HF
636
42.3
9P
reg
nan
etri
ol
P-t
rio
l43
526
.34
21-d
eoxy
cort
iso
l21
-deo
xyF
634
42.5
5P
reg
nen
olo
ne
Pre
g44
527
.36
11-d
eoxy
cort
iso
l11
-deo
xyF
544
42.7
65 �
-dih
ydro
pro
ges
tero
ne
5�-D
HP
445
28.5
711
-deo
xyco
rtic
ost
ero
ne
11-d
eoxy
B54
643
.51
Pro
ges
tero
ne
Pro
g45
829
.90
Co
rtis
on
eE
615
46.0
320
�-h
ydro
pro
ges
tero
ne
20�
-DH
P44
530
.20
11-d
ehyd
roco
rtic
ost
ero
ne
11-d
ehyd
roB
617
46.8
017
�-h
ydro
xyp
reg
nen
olo
ne
17�
-OH
-Pre
g54
832
.68
Allo
dih
ydro
cort
ico
ster
on
eA
llo-D
HB
636
46.8
717
�-h
ydro
xyp
rog
este
ron
e17
�-O
H-P
rog
546
35.7
0A
llod
ihyd
roco
rtis
ol
Allo
-DH
F63
447
.01
11�
-hyd
roxy
pro
ges
tero
ne
11�
-OH
-Pro
g53
141
.32
1629J Am Soc Mass Spectrom 2009, 20, 1626–1637 QUANTITATIVE STEROID SIGNATURES BY GC-MS
comparing retention times and matching the heightratios of characteristic ions (Table 1).
Method Validation
QC samples containing all 70 analytes were quantifiedusing MS peak height ratios versus the IS. Calibrationsamples were made up at 15 different concentrations,which depended on the sensitivity and reference valuesof the urinary steroids. Least-squares regression analy-sis was performed on peak height ratios at increasinganalyte levels to obtain calibration linearity. Limits ofdetection (LOD) and quantification (LOQ) were definedas the lowest concentration with a signal-to-noise (S/N)ratio � 3 for LOD and of S/N ratio � 10 for LOQ.Precisions are expressed as coefficients of variation (%CV) and accuracies as percent relative errors (% bias),and were determined using QC samples at three differ-ent concentrations (low; 2 � 50 ng/mL, medium; 20 �200 ng/mL, and high; 100 � 2000 ng/mL) dependingon the sensitivity and reference values of the urinarysteroids. To determine within-day repeatabilities, fourreplicates were analyzed, whereas day-to-day repro-ducibility was measured by running samples on 5different days.Extraction recoveries were determined using QC
samples at three concentration levels in triplicate foreach steroid by adding known amounts of mixed work-ing solutions to steroid-free urine samples. Absoluterecoveries were calculated by comparing peak heightratios of extracted samples versus those of their nonex-tracted counterparts, using the IS added just before thederivatization step.
Statistical Analysis and Steroid Signatures
Data manipulation was performed using Excel 2007spreadsheets (Microsoft Corp., Seattle, WA, USA), Sig-maplot (SYSTAT Software Inc., San Jose, CA, USA), andSIMCA software (Umetrics Inc., Umeå, Sweden). Quan-titative results are expressed as means � SD, and groupcomparisons are made using the unpaired two-tailedStudent’s t-test. Statistical significance was consideredat P 0.01.To visualize differences between the steroid signa-
tures of BPH patients and healthy subjects, a supervisedhierarchical clustering algorithm based on Pearson’scorrelation coefficient was used with a TIBCO SpotfireDecisionSite Browser (TIBCO Spotfire, Inc., Somerville,MA, USA). Concentrations of steroids and ratios ofmetabolites to precursors (an indicator of enzyme ac-tivity) in BPH patients and healthy subjects were com-pared using the Student’s t-test, and statistically sig-nificant variables were selected and processed. Forclustering analysis, all prefiltered quantitative results ofsteroids measured and their ratios were log trans-formed and normalized using z-scores by subtractingpopulation means from individual raw scores and di-viding the result by the population standard deviation.T
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1630 MOON ET AL. J Am Soc Mass Spectrom 2009, 20, 1626–1637
Z-score transformation [z � (observed value – baselinemedian)/baseline standard variation] ensures that eachanalyte in the subject population has a median value of0 and a standard deviation of 1. In the heat mapgenerated using HCA, color coding in maps indicatingauto range by difference of concentration in each com-pound was gradated at three point; red indicates z-scores � 0, blue z-scores 0, and white z-scores 0 ofa row (subjects) across all columns (urinary steroids).
Results and Discussion
Urinary Steroid Profiling
Steroid hormones of significance under different biolog-ical conditions fall into several distinct groups, and arefrequently used to evaluate endocrine functions. Com-prehensive extraction methods for GC-MS based ste-roid analysis mainly focus on specific steroid metabo-lites which have the same biological function andchemical structures [15–17, 19]. Due to the chemical andphysical diversities within androgens, estrogens, corti-coids, progestins, and sterols, the described profilingtechnique was devised to simultaneously quantify ste-roid analytes as diverse as lipophilic cholesterol andhydrophilic corticoids in a single extract.In SPE experiment, urinary steroids are purified
using a unique copolymer sorbent, Oasis HLB, whichallows high and reproducible results to be obtained [8,30, 32, 33]. In general, SPE absorbent retains steroidsbased on hydrophobic interactions with free and con-jugated steroids. The following two extractions meth-ods were therefore investigated: (1) 2 mL of urine wasprocessed with a SPE cartridge and the sample obtainedwas hydrolyzed, and (2) urine was first hydrolyzed andthen processed in SPE. However, difficulties in loadingsamples into SPE cartridges after hydrolyzing themwith �-glucuronidase/arylsulfatases, due to an increasein the viscosity of urinary solution hydrolyzed, wereobserved. This result was not observed if �-glucuronidaseonly was present in the enzyme solution [6]. Therefore,SPE procedure was processed first in sample prepara-tion steps.Although catechol estrogens, such as 2-OH-E1, 2-OH-
E2, 4-OH-E1, 4-OH-E2, and 2-OH-E3, are degraded whenexposed to light or to a pH higher than 9.5 [34], 0.2%aqueous L-ascorbic acid was added to prevent oxidativedecomposition before enzymatic hydrolysis. After enzy-matic hydrolysis, deconjugated steroids were extractedwith an ethyl acetate: n-hexane (2:3, vol/vol) mix. Inextraction, THF and ethyl acetate were primarily investi-gated, and diethyl ether, t-butyl methyl ether, and n-hexane were added to expedite THF and ethyl acetatepartitioning. When relatively polar organic solvents, suchas diethyl ether and t-butyl methyl ether, were used,chromatographic interference was encountered. Althoughboth THF and ethyl acetate had high extraction efficien-cies, ethyl acetate was finally selected because of theobjectionable smell and high polarity of THF.
Overall extraction efficiencies were not signifi-cantly different for all steroids studied at pH valuesof 5 to 7. The recoveries of catechol estrogens (10.4%� 48.9%) were poor at pH 9 because they are oxidizedto quinones at this pH [35]. In addition, differentratios of ethyl acetate to n-hexane were examined anda 2:3 (vol/vol) mix was chosen having consideredextraction yield and chromatographic properties. Us-ing optimized conditions, all urinary steroids studiedwere extracted in good yields, except 2-OH-E3 and24S-OH-Chol, which are still detectable in urine afterextraction (Figure 1).
Gas Chromatography-Mass Spectrometry
Using the described GC-SIM/MS conditions, 70 steroidhormones were analyzed as their TMS derivatives andpeak identification was straightforward using retentiontimes, characteristic ions, chromatograms, and massspectra, the latter were compared with those of refer-ence standards. The GC oven program used resulted inwell separated, good peak shapes for most steroids withretention times from 12.12 min for ���-diol to 48.99 minfor 24S-OH-Chol. On the other hand, 11-keto-An and11-keto-Etio, and 16-keto-E2 and 16�-OH-E1 were co-eluted and estimated totally in quantification (Figure 2).However, some partial-overlapped compounds (e.g.,5�-dione and 17�-E2, 2-OH-E2-3-methylether and P-diol, 4-OH-E1 and Preg) were differentiated by SIMusing their different characteristic ions (Table 1).Most steroids were monitored using their molecular
ions as base peaks, except: ���-diol, ���-diol, ���-diol,which had an abundant [M-180; M-2OTMS]� ion at m/z256; ���-diol, ���-diol, ���-diol with an [M-195;M-2OTMS-CH3]
� ion at m/z 241; 5�-DHP, 5�-DHP,Preg with an [M-15; M-CH3]
� ion at m/z 445; Epi-P-one,P-one, and Allo-P-one with an [M-15]� at m/z 447;16-keto-E2, 16�-OH-E1 with an [M-15]� ion at m/z 487;THS with an [M-90; M-OTMS]� ion atm/z 548; THE andAllo-DHF with an [M-90]� ion at m/z 634; THF andAllo-THF with an [M-90]� ion at m/z 636; 11-deoxyFwith an [M-90]� ion at m/z 544; cortisone (E) with an[M-90-15; M-OTMS-CH3]
� ion at m/z 615; and 11-dehydroB with an [M-15]� at m/z 617. In the cases ofP-diol, P-triol, and 11�-OH-Prog, less intense fragmentsat m/z 269, 435 and 531, respectively, were chosen toimprove selectivity rather than most intense peaks (m/z117, 255, and 546); this was attributed to urinary inter-ference. Regarding the TMS ethers of P-diol and P-triol,the characteristic ions at m/z 269 and 435 were moni-tored, which are attributed to [M-195; M-2OTMS-CH3]
�
and [M-117; M-CH[OSi(CH3)3]CH3 side-chain]� ions.
The base peak of P-diol is m/z 117 and other importantfragments are m/z 269 [M-90-90-15]�, m/z 284 [M-90-90]�, m/z 347 [M-117]�, and m/z 449 [M-15]�. Amongthese fragments, m/z 269 instead of m/z 117 was chosento improve selectivity from urinary backgrounds. Alsothe P-triol has m/z 255 [M-117-90-90]�, m/z 345 [M-117-90]�, and m/z 435 [M-117]� as major fragments formed
1631J Am Soc Mass Spectrom 2009, 20, 1626–1637 QUANTITATIVE STEROID SIGNATURES BY GC-MS
by the loss of 117 mass units, butm/z 435 was monitoredto improve selectivity. In addition, 11�-OH-Prog elutesTHF at the similar retention time (41.30 min), but atypical loss of 90 Da (-OTMS) from the THF (m/z 636)would interfere the detection of 11�-OH-Prog in case ofusing m/z 546, the molecular ion. Therefore, m/z 531[M-90-15]�, which rarely did not exist in THF, waschosen instead of m/z 546 (see Supplementary Figure 1).
Method Validation
Method validation requires the evaluations of linearity,LOD, LOQ, precision, and accuracy using calibrationsamples prepared from in-house steroid-free urine [30].Calibration curves were generated for all analytes usingQC samples fortified with all reference standards at
different concentrations. The devised method wasfound to be linear (correlation coefficient, r2 � 0.994) forall analytes, except for cholesterol (r2 � 0.983). Mostcompounds had an LOQ in the 0.05� 2.0 ng/mL range,while those of DHEA, Epi-An, 5�-dione, ���-diol,11-dehydroB, 17�-OH-Preg, and 11�-OH-Prog rangedbetween 5.0 and 50 ng/mL (Table 2).Assay precisions and accuracies were determined by
analyzing three QC samples at different concentrationsof the individual steroids (5, 20, 100, 200, 500, and 2000ng/mL). Intra-day (n � 4) precisions (expressed as %CV) ranged from 0.9% to 11.2%, whereas accuracies(expressed as % bias) ranged from 95.8 to 119.1%, andinter-day (n � 5) precisions (% CV) and accuracies (%bias) ranged from 1.6% to 10.5% and from 91.6% to115.5%, respectively (Table 2). Especially, the accuracy
Figure 1. Extraction recoveries of 70 urinary steroids analyzed using the described method. Absoluterecoveries were calculated by comparing peak height ratios of extracted samples versus theirnon-extracted counterparts.
15.00 20.00 25.00 30.00 35.00 40.00 45.00Time (min)
Abu
ndan
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Androsterone Etiocholanolone
THF
Allo-THF
THS 17α-OH-preg
THE
Cortisone
Cortisol
P-diol
P-triol
5 -androstan-3 ,17 -diol
11-keto-androsterone11-keto-etiocholanolone
16-keto-17 -estradiol16 -hydroxyestrone
24S-hydroxycholesterol
Figure 2. A representative total ion chromatogram obtained from a healthy male subject fordetection of 70 urinary steroids.
1632 MOON ET AL. J Am Soc Mass Spectrom 2009, 20, 1626–1637
Table 2. The validation results of overall method with intra- and inter-day assays
Compounds (trivial name)LODa
(ng/mL)LOQb
(ng/mL)Calibration
range (ng/mL)Linearity
(r2)
intra-day (n � 4) inter-day (n � 5)
CVc
(%)Accuracyc
(%)CV(%)
Accuracy(%)
Androgens���-diol 0.5 1.0 1–200 0.998 5.9 104.0 3.8 97.9���-diol 0.2 0.5 0.5–200 0.998 5.7 107.8 3.1 105.0An 0.1 0.5 0.5–3000 0.996 3.2 119.1 3.5 108.8Etio 0.1 0.5 0.5–3000 0.998 2.5 106.1 2.2 109.7���-diol 0.5 1.0 1–200 0.998 6.8 111.4 3.3 109.6���-diol 0.2 0.5 0.5–200 0.998 4.4 106.2 3.0 109.1���-diol 1.0 2.0 2–200 0.995 5.2 107.5 3.4 103.4Epi-DHT 0.1 0.2 0.2–200 0.994 8.0 106.0 3.4 108.911-keto-An & Etio 0.1 0.5 0.5–1000 0.996 3.7 108.4 3.4 112.3DHEA 5.0 50.0 50–3000 0.997 3.5 106.6 3.3 108.2Epi-An 2.0 5.0 5–1000 0.994 2.5 98.0 2.1 109.5A-diol 0.5 2.0 2–200 0.996 7.4 116.3 10.5 97.25�-dione 0.5 5.0 10–200 0.995 4.8 106.2 2.2 111.8Epi-T 0.05 0.1 0.1–200 0.997 3.8 100.7 1.6 100.8���-diol 10.0 20.0 20–500 0.998 6.9 104.0 3.0 104.0DHT 0.1 0.2 0.2–200 0.998 4.7 109.6 2.4 102.7A-dione 0.05 0.1 0.1–200 0.999 5.7 103.4 2.4 101.7T 0.05 0.1 0.1–200 0.998 4.7 106.1 1.9 102.511�-OH-An 0.2 0.5 0.5–3000 0.997 3.4 104.6 5.8 112.911�–OH-Etio 0.2 0.5 0.5–3000 0.998 2.7 101.3 4.1 113.416�-OH-DHEA 0.1 0.2 0.2–1000 0.996 4.0 104.3 1.7 105.8
Estrogens17�-E2 0.05 0.1 0.1–200 0.998 3.9 98.6 2.6 96.3E1 0.1 0.2 0.2–200 0.998 2.9 99.0 2.0 97.317�-E2 0.05 0.1 0.1–200 0.997 3.5 99.8 2.3 97.22-MeO-E2-3-methylether 0.1 0.2 0.2–200 0.998 2.9 97.3 2.1 96.44-MeO-E2 0.2 0.5 0.5–200 0.998 2.1 98.7 1.8 95.62-MeO-E1 0.05 0.1 0.1–200 0.998 1.9 99.0 1.8 95.82-OH-E2-3-methylether 0.1 0.2 0.2–200 0.998 4.2 101.3 2.4 97.62-MeO-E2 0.05 0.1 0.1–200 0.998 4.3 100.2 2.2 97.12-OH-E1 0.1 0.2 0.2–200 0.998 4.9 104.7 3.7 99.52-OH-E2 0.1 0.2 0.2–200 0.998 6.1 106.4 3.4 99.34-OH-E1 0.1 0.2 0.2–200 0.998 2.9 103.2 2.5 98.84-OH-E2 0.1 0.2 0.2–200 0.998 4.6 100.1 4.2 97.317-epi-E3 0.5 1.0 1–200 0.997 2.4 106.7 2.4 100.3E3 0.2 0.5 0.5–200 0.997 2.7 101.6 2.8 99.716-keto-E2 and 16�-OH-E1 0.1 0.2 0.2–500 0.998 2.7 98.7 8.8 92.516-epi-E3 0.5 1.0 1–200 0.997 3.5 103.2 2.3 100.52-OH-E3 0.5 1.0 1–100 0.997 5.0 107.4 5.3 101.0
CorticoidsTHS 0.1 0.2 0.2–200 0.997 0.9 99.2 3.0 98.4THDOC 0.2 0.5 0.5–200 0.996 7.1 100.4 4.1 100.0THE 1.0 2.0 2–500 0.997 7.6 151.4 9.9 151.3THF 0.2 0.5 0.5–200 0.998 6.6 106.1 4.9 104.0DHDOC 0.5 1.0 1–200 0.997 4.2 101.2 4.1 104.9Allo-THF 0.2 0.5 0.5–500 0.996 4.8 103.9 2.6 102.621-deoxyF 0.5 1.0 1–200 0.997 7.3 108.5 4.8 109.311-deoxyF 0.2 0.5 0.5–200 0.998 2.9 98.5 3.5 91.611-deoxyB 0.5 1.0 1–200 0.997 6.9 100.3 2.9 105.1Cortisone (E) 0.2 0.5 0.5–500 0.998 3.2 101.2 2.7 99.811-dehydroB 0.2 5.0 5–200 0.994 2.1 101.8 2.7 100.4Allo-DHB 0.5 1.0 1–200 0.997 6.9 113.1 5.3 108.0Allo-DHF 1.0 2.0 2–200 0.997 2.3 97.5 2.9 107.3Corticosterone (B) 0.2 0.5 0.5–200 0.997 3.3 99.0 3.3 100.3Cortisol (F) 0.1 0.2 0.2–200 0.998 3.0 100.5 3.5 98.0
Progestins5�-DHP 0.1 0.2 0.2–100 0.997 9.9 109.2 3.5 110.5Epi-P-one 1.0 2.0 2–200 0.995 4.1 106.0 3.0 105.8P-one 1.0 2.0 2–200 0.997 7.4 110.1 3.3 115.5Allo-P-one 0.2 0.5 0.5–200 0.994 2.9 109.9 2.2 103.7
1633J Am Soc Mass Spectrom 2009, 20, 1626–1637 QUANTITATIVE STEROID SIGNATURES BY GC-MS
of THE resulted in abnormal values, and it might beproduced by low calibration slope because of poorGC-MS properties.
Quantitative Results of Benign ProstaticHyperplasia
The validated quantitative profiling method was ap-plied to measure 70 endogenous steroids in urinesamples obtained from 59 BPH patients and 41 age-matched healthy male subjects. All quantitative results,corrected by urinary creatinine levels, were compared,and differences between patients and healthy subjectswere evaluated using the Student’s t-test. Although itwas not the purpose of this study to elucidate clinicalimplications, some features were notable, and signifi-cant differences were found between patients andhealthy subjects (see Supplementary Figure 2).In patients, urinary levels of T, Epi-T, ���-diol,
���-diol, ���-diol, 17�-E2, 11�-OH-Prog, and 16�-OH-DHEA were significantly decreased (P � 4.52 � 10–4 �2.77 � 10–13), and those of 11�-OH-Etio, ���-diol,2-OH-E3, 17�-OH-Prog, and 11-deoxyF were signifi-cantly increased (P � 4.56 � 10–7 � 9.42 � 10–18). Someother urinary steroids quantified were also significantlydifferent in patients and controls (P 0.01). Changes inthe urinary levels of ���-diol and ���-diol were inaccord with previous findings [36, 37], but other steroidchanges observed in this study have not been reportedto date. In particular, urinary 17�-E2 and 2-OH-E3showed remarkable changes with P values of 2.77 �10–13 and 4.25 � 10–9, which might be associated withthe different biochemical roles of estrogen receptor �(ER�) and � (ER�) in various types of prostate cells [28, 38,39]. The involvements of other urinary steroids needs tofuture study.
Steroid Signatures by Hierarchical ClusteringAnalysis
The present MS-based steroid profiling has become anessential clinical tool and has produced many results inBPH, but it is difficult to identify critical differencesbetween patients and controls because of the largenumber of results. Hierarchical clustering, which in-volves calculating the distance matrices of data objectsand then merging objects that are close to each other toform sub-clusters, has been utilized in biomedical stud-ies to interpret the expressions of biomolecules [2,22–25]. In the present study, after determining therelative levels of each steroid, all data were z-scoretransformed to produce a heat map using a supervisedHCA based on Pearson’s correlation coefficient. Theraw data were the relative concentrations of the 70urinary steroids, and these were filtered by statisticalsignificance (P 0.01) using the Student’s t-test. Theclustering method and similarity measure were setunweighted average and Euclidean distance, respec-tively. Urinary concentrations were represented by col-ors in the heat map, and each steroid was representedby a single row of colored boxes, whereas columnsrepresented different subjects. Heat maps were com-pared with respect to individual quantitative results,and indicated the effectiveness of steroid signatures.Figure 3 illustrates in a heat map showing altered
concentrations of urinary steroids in BPH patients andhealthy subjects. The heat map readily shows changes inthe concentrations of urinary steroids. Increased urinaryexcretion patterns of several steroids, from Epi-DHTdown to 11-deoxyF, were detected in patients, while othersteroid levels were significantly reduced. In addition,visual inspections of steroid signatures complementedquantitative statistics. Although 2-OH-E3 was present at asignificantly higher level in patients (P � 4.25 � 10–9; seeSupplementary Figure 2), these increases were only ob-
Table 2. Continued
Compounds (trivial name)LODa
(ng/mL)LOQb
(ng/mL)Calibration
range (ng/mL)Linearity
(r2)
intra-day (n � 4) inter-day (n � 5)
CVc
(%)Accuracy
c (%)CV(%)
Accuracy(%)
P-diol 0.5 1.0 1–500 0.997 6.2 105.6 3.6 107.5P-triol 0.2 0.5 0.5–500 0.999 6.0 102.8 2.3 105.5Preg 1.0 2.0 20–200 0.995 8.8 104.1 3.5 98.55�-DHP 0.2 0.5 0.5–200 0.995 7.0 99.2 3.8 104.0Prog 0.5 1.0 1–100 0.998 4.8 96.0 2.5 98.620�-DHP 0.2 0.5 0.5–100 0.997 9.1 101.7 4.9 103.817�-OH-Preg 5.0 10.0 20–500 0.998 3.6 98.7 3.0 102.917�-OH-Prog 0.2 0.5 0.5–200 0.996 3.1 95.8 2.3 96.111�-OH-Prog 2.0 5.0 5–500 0.996 11.2 103.9 7.3 94.3
SterolsChol 1.0 2.0 50–1000 0.983 7.3 113.0 7.8 115.024S-OH-Chol 0.5 2.0 2–200 0.994 6.5 96.3 4.1 100.9
aThe limit of detection was measured S/N ratio � 3.bThe limit of quantification was measured S/N ratio � 10.cPrecision and accuracy were expressed as the mean values of data obtained from three different concentrations for each analyte.
1634 MOON ET AL. J Am Soc Mass Spectrom 2009, 20, 1626–1637
served in some patients in the heat map. The levels ofother steroids, 11�-OH-Etio and 11-deoxyF, were alsoinconsistency different in patients (Figure 3).To illustrate further the usefulness of a steroid sig-
nature, the ratio of steroid metabolite to precursor,which reflects enzyme activity (Scheme 1), was exam-ined. The cluster and heat maps of all analyzed sam-ples in this 70 compound study showed differencesbetween groups in these ratios (Figure 4). A dendro-gram of ratios revealed that the oxidoreductasesformed a cluster (5�-reductase, 3�-HSD, 3�-HSD, and17�-HSD, except for 20�-HSD; see SupplementaryTable 1 for full enzyme names), which are differenti-ated with a cytochrome P450 enzyme, 11�-hydroxy-lase. These results support the validity of the datatransformation, since 5�-reductase is a marker of
BPH [27–29], and 17�-HSD is positively expressed inprostate cells [40, 41]. Other up-regulated enzymes inthe map might be biomarkers of BPH. Furthermore,the method can be used to visualize quantitativesteroid data in a single graphic using a hierarchicallyclustered heat map. The need for this type of visual-ization arises from the complexity of large experi-mental datasets. One important advantage of using aheat map is that it can be used to visualize clinicaldata across multiple subjects for many analytes,which allows patterns to be easily identified.
Conclusions
Due to the clinical requirement to quantify trace levelsof urinary endogenous steroids, we devised an analyt-
Healthy BPH
Figure 3. Hierarchically clustered heat map of the urinary steroids levels of 59 BPH patients and 41healthy male subjects. Differences between steroid levels in controls and patients were examinedusing Student’s t-test, and only those that were significantly different at the P 0.01 level wereselected. Row represents subjects and column urinary concentration of individual steroids. Cells arecolored based on concentrations in urinary samples. Red represents highly excreted into urine andblue showed a concentration in urine.
Healthy BPH
Figure 4. A heat map for measuring enzyme activities related to steroid metabolism. The ratio ofprecursor to metabolite for each steroid was calculated, and only steroids with level differencessignificant at the P 0.01 level were selected. Rows represent subjects and column metabolic ratio.Red represents a high ratio and blue a low ratio.
1635J Am Soc Mass Spectrom 2009, 20, 1626–1637 QUANTITATIVE STEROID SIGNATURES BY GC-MS
ical method to measure the individual concentrations of70 urinary steroids and several enzyme activities basedon steroid signatures using a single assay, which sub-stantially reduces analytical time and sample size. Incontrast to classical biochemical approaches using RIAand EIA that mainly focus on single enzymes, singlemetabolic reactions, and kinetic properties, profilinganalysis involves the collation of quantitative results fora broad series of metabolites to gain an overall under-standing of metabolism.Steroid signatures as represented by hierarchically
clustered heat maps use color to communicate under-lying quantitative results, which are much harder toappreciate when presented numerically. This method issimple to implement and maintains the biological in-tegrity of data. Using this technique, inter-relationshipsbetween absolute concentrations and enzyme activitiesin samples from different sources can be recognized.The combined GC-MS profiling technique describedhas adequate sensitivity that could be used for highthroughput analysis, and could be adopted to enablethe quantifications of urinary steroids and indicatemetabolic alterations at biologically relevant levels.
AcknowledgmentsThe authors acknowledge support for this work by an intramuralgrant from the Korean Institute of Science and Technology (KIST),and by grants from the National R and D Program of the KoreanMinistry of Education, Science, and Technology (MEST), and theKorean Science and Engineering Foundation (KOSEF).
Appendix ASupplementary Material
Supplementary material associated with this articlemay be found in the online version at doi:10.1016/j.jasms.2009.04.020.
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