High throughput
HighHigh-throughput
h ghp non-targeted
non targeted
g d metabolic
b li profiling
p fili g withi h hybrid
hyb id stationaryiy phasephLC columnl
co pcoupledpledl d to Q
Q-TOF-MSTOF MS ini cancer research
h11,,
2
1
1
2
1
Hy Ji JJung
Hyun-Jing , Man
M H
Ho Ch
Choii , Kyung
Ky g Mi Kim
Ki , Won-Yong
W Y g Lee
L , Bong
B g Chul
Ch l Chu
Ch ngg
1 Life2Lif S
Sciencesi
Di
Division
Division,i i , KIST
KIST,, SSeoull 136
136-791
791, Korea;
791,K; Department
D p t
t off Chemistry
ChChemistry,i t y, Yonsei
Yi Un
U iversity,
iiversity
ity, SSeoull 120
120-749
749, Korea
749,KI
Introduction
d i

E p i
Experimentall procedurespd

M

SSamplel pretreatment steps

Instrumental conditions
iiSamplingp g
200 μL Urine
U iFilteration

LC pparameters

MS parametersptPerformance
Instrument: ACQUITYTM Ultra P
phy system
Liquid Chromatograp
HS-C18
Column: Cadenza HSC18(2.0 × 100 mm, 3 μm)
Fl rate:t 0.40 4 mL/min
L/ iFlowµLIInjection
j ti volume:
l5µLColumn temperature: 40 ºC
Mobile phase:
A: 00.1
1 % formic acid in 5 % ACN
B: 0.1 % formic acid in 995 % ACN
Gradient:
Gdi10 min
2 min
100 % A
100 % A ((4 min)i )10 % A

Instrument: Waters Q-TOF
Q TOF micro MS
Ionization: ESI+ ion modes
Acquisition mode: Scan (m/z 5050-11,200)
200)
Nebulization gas: 600 L/h
Cggas: 60 L/hCone
Source ttemperature:
105 ºC
Sp t
Capillary voltage: 3,100
3 100Cone voltage: 40 Vextractiont ti● Liquid-liquid
Liq id liq id extractiont ti● Column switchinggLC

GC--Ms or LCGC
LC-MS analysis
yLCC

12QTOF-MS

Inject 5 μL into QQ-TOF
TOF--MSwaste

S i i l analysis
Statistically i

Identification
foff ppotent biomarker

PLS DA score plot
PLS-DAp

Patient

C t lControlC t lControl

1 TOF MS ES+
1:393 132
393.132
103

7.69

100

C t l
ControlStatistical analysisy● PLS-DA with SIMCA-P®

Patient00● Hierarchical clusteringwith Decision Site ®

1 TOF MS ES+
1:393 132
393.132
2 23 32.23e3

7 67
7.67

100%

Metabolomic approaches● Solid-phase
S lid phColumnswitching
C li hi%etabolomics is a suitable approachpp
in monitoringg earlyy changes
goff metabolic
b li pathways
hhb li perturbations
b iandd thesemetabolicep ese t a bi
bbiomarker
o a ke ooff ca
ce , which
which iiss oonee ofof hi
ghly cople
represent
cancer,highlycomplexdiseases Althoughg ggas chromatography-mass
chromatography
g p y mass spectrometry
py baseddiseases.
been
primarily
metabolomicsh havehbiil usedd ini metabolomics,
b l i difficulties
diffi l i iniapproaches
d t ti off polarl compounds
d withith high
hi h molecularl l weight
i ht ordetectionhydrophilicity
technique.
analysis,
nony py limit this techniqueq
In contrast targetedganalysisy , nontargeted metabolic profiling involves a large number of differentb li withi h theh objective
bj i off identifying
id if i a specificifi metaboliteb limetabolites
responsible
pfor biologicalg
changesg
A rapidp and reprod
pcible sample
pchanges.
reproducible
is necessary
targeted
ppreparationpy in nonnon-targetedgmetabolomics because it mayy
affectff reproducibility
d ibili as a result
l off theh hheterogeneity
i off metabolites
b liderivedHere, we iintroduce
a nonnon-targetedtargetedd i d ffrom cellll populations.
l ti
H
t dt
t d
metabolic pprofilingg techniqueq usingg hybrid
ystationary
y pphase LC column
coupled to a quadrupole-time-of-flight mass spectrometer (Q-TOF-MS)t idtoidentify
tif alteredlt d metabolites
t b lit andd tot findfi d potential
t ti l biomarkers,
bik
which
hi h
mayy indicate pprogress
gof cervical and pprostate cancers.
cancers

Procedure
ocedu e fo
for Non-targeted
Nono tatargeted
geted profilingp ofili g

Patient
1 00
1.00

3 00
3.00

5 00
5.00

7 00
7.00

9 00
9.00

11 00
11.00

13.00
1300
Time

1 00
1.00

3 00
3.00

5 00
5.00

7 00
7.00

9 00
9.00

11 00
11.00

OH

13 00
13.00
Timec e r v ic a l c a n c e r 7
c c _ 0 7 3 6 6 (7 .6 6 9 )100

O

1: TO F M S ES+2 .449e3

3 5 8 .2
2608
2490

Database searchOH

3 9 3 .1
1335
2091

23Targeted profiling4567

3 1 4 .22339
1749

N
t d profilingfili
Non
Non--ttargeted

2 7 7 .11081
506

1 4 1 .00 1 9 7 1 7 9 .1
1439
440
487

3 9 4 .11371
420

1 9 9 .0 2 2 8317

1 3 7 .00972
229

5 5 1 .2 3 3 3282

4 9 5 .1
1965266

7 3 1 .3 3 1 6390
7 2 8 .33179
5 8 5 .1 2 8 4270
71

1 0 8 7 .44792
9 3 1 .3 9 7 5265245
7 5 3 .2 6 8 7! ;9 2 9 .3 0 1 3 ;9 4 9 3 3 .4 1 1 6 ;6 2189m /z
100

8 39
8.39

HighLow

CIN I CIN II CIN III

CIS

200

300

400

500

600

700

800

900

1000

1100

“Targetedg
metabolic pprofiling”
f gAgeStageg06 326 .8922
8922
4 .06_
4 .07_ 240 .9592
4 .05_ 227 .9358
4 .06_.06 132 .9892
4 .06_ 318 .8910
5 .76_76 552 .9694
9694
5 .79__ 344 .0033
5 .76_ 415 .9882
5 .61_
61 547 .9635
9635
5 .50_ 415 .9881
5 .51_ 552 .9693
5 .53_
53 344 .0034
0034
5 .30_ 415 .9880
5 .25_ 547 .9637
6 .47_
47 415 .9882
9882
5. 64_ 206 .1184
5 .65_ 358 .2000
4 .98_.98 547 .9635
4 .99_ 415 .9881
23 310 .2021
2021
7 .23_
6 .77__ 385 .0109
7 .62_ 579 .9425
6 .99_
99 547 .9700
9700
6 .43_ 593 .9189
5. 99_ 318 .2077
7 .64_
64 337 .1650
1650
7 .65_ 319 .1561
7 .67_ 377 .15847 .66_66 393 .1323
1323
7 .65_ 179 .1432
4 277 .1162
117 .64_
5 .99_.99 300 .2173
7 .26_ 358 .2601
6 .42_
42 310 .2015
2015
6 .26__ 310 .2019
7 .00_ 310 .2013
6 .47_
47 295 .2026
2026
5 .96_ 177 .0551
8 .41_ 251 .1289
7 .50_
50 355 .1752
1752
8 .43_ 342 .1744
8 .11_ 245 .0930
8 .12_.12 170 .0601

8.50

577
5.77

582
5.82
625
6.25

4 5 6 7
Time (min)Potent biomarker

1 1 1 0 .4 4 6 9160

Ceatinine
C i i

491
4.91

3OH
H

7 087.08

4.30

H

1 1 0 9 .4 4 2 754202

H

1 1 0 8 .4 3 9 11097

HOHierarchicalHi
hi l clusteringl t i analysis
l i
406
4.06

H

1 1 0 7 .44368
1623%

1RT

911
9.11
1038
10.38

DHT-A
DHTA
12 43
12.43
8 5 6 7 8 9 1011121314
Time (min)Metabolic profilingpg

Controls

Patients

319 1561
319.1561● Ubiquinone
Ubi i
Q2

● Epipregnanolone
E il● Leukotriene A4● Alloepipregnanolone● 5 HEPE● Allopregnanolone● Melanin
M l i

377 1584
377.1584● Resolvin D1● Resolvin D2● 1818-Oxocortisol
Oxocortisol● 7a-OH-5b-cholanic acid● 12b-OH-5b-cholanic
12b OH 5b h l i acidid
● Lithocholic aicd

● Isolithocholic acid
● Isoallolithocholic acid
● Allolithocholic acid393.1323

HighLow● Allodeoxycholicodeo yc o c acidcd● 3a,7a3a,7a-Dihydroxycholanoic
Dihydroxycholanoic acid

● Allochenodeoxycholic acid

● Isodeoxycholic acid● 3b,7a-Dihydroxy-5b-cholanoic
3b 7a Dihydroxy 5b cholanoic acid● Chenodeoxycholic acid

● Deoxycholic
D y h li acidid● 3b,12a-Dihydroxy-5b-cholanoic
yyacid ● Isoursodeoxycholicyacid● Ursodeoxycholic acid● 3a,12b3a,12b-Dihydroxy-5b-cholanoic
Dihydroxy 5b cholanoic acid ● Isohyodeoxycholic acid

● Murocholic aicd

● 3b,12a-Dihydroxy-5a-cholanoic
3b 12 Dih d
5 h li acidid ● 7b,12a-Dihydroxycholanoic
7b 12 Dih dh li acidid

● Hyodeoxycholic
yyaicd● 3b,12b-Dihydroxy-5b-cholanoic,yyaicd

CConclusion
l i
Using the present non-targeted
non targeted metabolic profilingt h itechnique
combinedbi d withith hybrid
h b id stationary
t ti
phase
hLC
column, two potential
column,pbiomarkers which may
y indicate
progress off cervicali l dysplasia
d l i was identified
id tifi d andd theythmight
igh beb correlated
l d withi h lilipid
pid or energy
gy metabolism.
metabolism
b li