Hi h h h d b li fili i hHigh throughput non targeted metabolic profiling withHigh-throughput non-targeted metabolic profiling withHigh-throughput non-targeted metabolic profiling withHigh throughput non targeted metabolic profiling withg g p g p gl d Q TOF MS i hco pled to Q TOF MS in cancer researchcoupled to Q-TOF-MS in cancer researchcoupled to Q-TOF-MS in cancer researchcoupled to Q TOF MS in cancer researchp Q

H Ji J 1 2 M H Ch i1 K Mi Ki 1 W Y L 2 B Ch l ChHyun-Jin Jung1, 2 Man Ho Choi1 Kyung Mi Kim1 Won-Yong Lee2 Bong Chul ChuHyun-Jin Jung , , Man Ho Choi , Kyung Mi Kim , Won-Yong Lee , Bong Chul Chuy g , , y g , g , g1 Lif S i Di i i KIST S l 136 791 K 2 D t t f Ch i t Y i U1 Life Sciences Division KIST Seoul 136-791 Korea; 2 Department of Chemistry Yonsei UnLife Sciences Division, KIST, Seoul 136 791, Korea; Department of Chemistry, Yonsei Un, , , ; p y,

I d i E i l dIntroduction Experimental proceduresIntroduction Experimental proceduresp p

S l i iSample pretreatment steps Instrumental conditionsetabolomics is a suitable approach in monitoring early changesMM Sample pretreatment steps Instrumental conditionsetabolomics is a suitable approach in monitoring early changes MM pp g y gf b li h d h b li b iMM of metabolic pathways and these metabolic perturbationsMM of metabolic pathways and these metabolic perturbations

200200 L U iL U i LC parametersLC parameterst bi k f hi h i f hi hl l 200200 μμL UrineL Urine LC parametersLC parametersrepresent a biomarker of cancer, which is one of highly complex 200 200 μμL UrineL Urine ppep ese t a b o a e o ca ce , w c s o e o g y co p eInstrument: ACQUITYTM Ultra Pdiseases Although gas chromatography mass spectrometry based Instrument: ACQUITYTM Ultra Pdiseases. Although gas chromatography-mass spectrometry based Liquid Chromatograpg g g p y p y

h h b i il d i b l i diffi l i iLiquid Chromatograp

approaches have been primarily used in metabolomics difficulties in Column: Cadenza HS-C18approaches have been primarily used in metabolomics, difficulties in FilterationFilterationColumn: Cadenza HS C18

d t ti f l d ith hi h l l i htFilterationFilteration (2.0 × 100 mm, 3 μm)detection of polar compounds with high molecular weight or (2.0 100 mm, 3 μm)

Fl t 0 4 L/ idetection of polar compounds with high molecular weight or Flow rate: 0.4 mL/minhydrophilicity limit this technique In contrast targeted analysis non I j ti l 5 Lhydrophilicity limit this technique. In contrast targeted analysis, non- Injection volume: 5 µLy p y q g y , j µ

Column temperature: 40 ºCtargeted metabolic profiling involves a large number of different Column temperature: 40 ºCtargeted metabolic profiling involves a large number of different Mobile phase:b li i h h bj i f id if i ifi b li

Mobile phase: metabolites with the objective of identifying a specific metabolite A: 0 1 % formic acid in 5metabolites with the objective of identifying a specific metabolite A: 0.1 % formic acid in 5

responsible for biological changes A rapid and reprod cible sample B: 0.1 % formic acid in 9responsible for biological changes. A rapid and reproducible sample B: 0.1 % formic acid in 9G di

p g g p p pGradient:

preparation is necessary in non targeted metabolomics because it mayG

10 min 2preparation is necessary in non-targeted metabolomics because it may 100 % A (4 i ) 10 % A

10 min 2 p p y g yff d ibili l f h h i f b li

100 % A (4 min) 10 % A affect reproducibility as a result of the heterogeneity of metabolites

( )affect reproducibility as a result of the heterogeneity of metabolites d i d f ll l ti H i t d t t d Inject 5Inject 5 μμL into QL into Q--TOFTOF--MSMSderived from cell populations. Here, we introduce a non-targeted Inject 5 Inject 5 μμL into QL into Q--TOFTOF--MSMSderived from cell populations. Here, we introduce a non targeted metabolic profiling technique using hybrid stationary phase LC columnmetabolic profiling technique using hybrid stationary phase LC column p g q g y y pcoupled to a quadrupole-time-of-flight mass spectrometer (Q-TOF-MS)coupled to a quadrupole-time-of-flight mass spectrometer (Q-TOF-MS) t id tif lt d t b lit d t fi d t ti l bi k hi hto identify altered metabolites and to find potential biomarkers, whichto identify altered metabolites and to find potential biomarkers, which

S i i l l imay indicate progress of cervical and prostate cancers Statistical analysismay indicate progress of cervical and prostate cancers. Statistical analysisy p g p y

PLS DA score plotPLS-DA score plotMetabolomic approaches

pMetabolomic approachesMetabolomic approaches

PatientPatient C t lC t lPatientPatientC t lC t l ControlControlControlControl PatientPatientPatientPatient

7654321RT 7654321RT

NN t t d filit t d filiTargeted profilingTargeted profiling NonNon--targeted profilingtargeted profilingTargeted profilingTargeted profiling NonNon targeted profilingtargeted profilingTargeted profilingTargeted profiling

Hi hi l l t i l iHierarchical clustering analysisHierarchical clustering analysis4 06 7 084.06 7.08

High LowHigh Low

C i i4.30 8 39Ceatinine4.30 8.39 AgeAgeStage

4 91 CIN I CIN II CIN III CIS06 326 89224

g4.91

8.50 CIN I CIN II CIN III CIS.07_240.9592.06_326.8922

44

8.50.06 132.9892.05_227.9358

44

76 552 9694

.06_318.8910

.06_132.9892

5

44

5 77 9 11 .79_344.0033.76_552.9694

55

5.77 9.1161 547 9635

.76_415.9882_

55

.50_415.9881

.61_547.963555

53 344 0034.51_552.9693

55

5 82 10 38 .30_415.9880.53_344.0034

55

5.82 10.3847 415 9882

.25_547.9637

6

5

DHT-A 64_206.1184.47_415.9882

5.6

DHT A.98 547.9635.65_358.2000

45

6 25 23 310 2021

.99_415.9881

.98_547.9635

7

44

6.2512 43 .77_385.0109

.23_310.20216712.43

99 547 9700.62_579.9425

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67

.43_593.9189

.99_547.970066

2 3 4 5 6 7 8 5 6 7 8 9 1011121314 64 337 165099_318.2077

75.

2 3 4 5 6 7 8 5 6 7 8 9 1011121314 .65_319.1561.64_337.1650

77

Time (min) Time (min) 66 393 1323.67_377.1584

77

Time (min) Time (min)4 11

.65_179.1432

.66_393.1323

7

7

.99 300.2173

.64_277.116257

42 310 2015

.26_358.2601

.99_300.2173

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75

.26_310.2019

.42_310.201566

47 295 2026.00_310.2013

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67

.96_177.0551

.47_295.202656

High Low50 355 1752.41_251.1289

78 High Low.43_342.1744.50_355.1752

87

.12 170.0601

.11_245.093088

Metabolic profilingMetabolic profiling.12_170.06018

Metabolic profilingMetabolic profiling ControlsControls PPatientsatientsp gp g ControlsControls PPatientsatients

h h b id i h LC lh hybrid stationary phase LC columnh hybrid stationary phase LC columnh hybrid stationary phase LC columnh hybrid stationary phase LC columny y p

1ng1nggi it S l 120 749 Kiversity Seoul 120-749 Koreaiversity, Seoul 120 749, Koreay, ,

Procedure for Non targeted profilingProcedure for Non-targeted profiling ocedu e fo o ta geted p ofili g

SamplingSamplingSamplingSamplingp gp gMS tMS tMS parametersMS parameters S lid h t tipp

● Solid-phase extractionInstrument: Waters Q TOF micro MSPerformance

pLi id li id t tiInstrument: Waters Q-TOF micro MSPerformance ● Liquid-liquid extraction

Ionization: ESI+ ion modesphy systemq q

Column switchingIonization: ESI ion modes phy system ● Column switchingAcquisition mode: Scan (m/z 50-1 200)

gAcquisition mode: Scan (m/z 50 1,200)Nebulization gas: 600 L/hNebulization gas: 600 L/hC 60 L/hCone gas: 60 L/hgS t t 105 ºCSource temperature: 105 ºCpCapillary voltage: 3 100Capillary voltage: 3,100 Cone voltage: 40 VCone voltage: 40 V

5 % ACN5 % ACNC lC l i hii hi95 % ACN GCGC Ms or LCMs or LC MS analysisMS analysisColumnColumn switchingswitching95 % ACN GCGC--Ms or LCMs or LC--MS analysisMS analysisColumnColumn switchingswitching yy

min100 % A

minCLC 100 % A LCLC

11 22 QTOF-MS11 22 QTOF-MS

wastewaste

Identification of potent biomarkerIdentification of potent biomarker Statistical analysisStatistical analysisf f p Statistical analysisStatistical analysisyy● PLS-DA with SIMCA-P®

C t lC t l● PLS-DA with SIMCA-P

1 TOF MS ES+7 67ControlControl PatientPatient1 TOF MS ES+ ● Hierarchical clustering

1001: TOF MS ES+

393 1327.67PatientPatient

100 1: TOF MS ES+ 393 1327.69

● Hierarchical clustering ®100 393.132

2 23 3393.132103

7.69 with Decision Site ®2.23e3103 with Decision Site

% %%

001 00 3 00 5 00 7 00 9 00 11 00 13 001 00 3 00 5 00 7 00 9 00 11 00 13 00

0OH

Time1.00 3.00 5.00 7.00 9.00 11.00 13.001.00 3.00 5.00 7.00 9.00 11.00 13.00

Time TimeTimec e rv ic a l c a n c e r 7 Database searchDatabase searchc e rv ic a l c a n c e r 7c c _ 0 7 3 6 6 (7 .6 6 9 ) 1 : T O F M S E S +

2 4 9 33 5 8 2 6 0 8Database searchDatabase searchO

1 0 0 2 .4 9 e 33 5 8 .2 6 0 82 4 9 0 OH

3 9 3 1 3 3 5

OH3 9 3 .1 3 3 5

2 0 9 1

3 1 4 2 3 3 93 1 4 .2 3 3 91 7 4 9 1 1 0 7 4 3 6 8 H1 1 0 7 .4 3 6 8

1 6 2 3

% 1 1 0 8 .4 3 9 1 Potent biomarkerPotent biomarkerH H

% 1 1 0 8 .4 3 9 11 0 9 7 Potent biomarkerPotent biomarker

HOH

OHH

2 7 7 1 0 8 11 7 9 1 4 3 91 4 1 0 1 9 7 3 9 4 1 3 7 11 1 0 9 .4 4 2 7

5 4 22 7 7 .1 0 8 15 0 6

1 7 9 .1 4 3 94 8 7

1 4 1 .0 1 9 74 4 0

3 9 4 .1 3 7 14 2 0 7 3 1 .3 3 1 6

3 9 0 1 0 8 7 4 7 9 2

5 4 2

1 3 7 0 9 7 21 9 9 .0 2 2 8

3 1 7

3 9 05 5 1 .2 3 3 32 8 24 9 5 1 9 6 5 7 2 8 3 1 7 9

1 0 8 7 .4 7 9 22 6 59 3 1 .3 9 7 5

2 4 51 1 1 0 .4 4 6 9

1 3 7 .0 9 7 22 2 9

3 1 7 2 8 24 9 5 .1 9 6 52 6 6

7 2 8 .3 1 7 92 7 05 8 5 .1 2 8 4

7 12 4 5

7 5 3 .2 6 8 71 8 9 ! ;9 2 9 .3 0 1 3 ;9 4 9 3 3 .4 1 1 6 ;6 2

1 6 0

m /z0

1 8 9 9 3 3 .4 1 1 6 ;6 2

m /z1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0 7 0 0 8 0 0 9 0 0 1 0 0 0 1 1 0 0

0

“Targeted metabolic profiling”“Targeted metabolic profiling”“Targeted metabolic profiling”“Targeted metabolic profiling”g p f gg p f g

319 1561319 1561

C l i319.1561319.1561

ConclusionE i lUbi iUbi i Q2Q2 M l i Conclusion● Epipregnanolone●● UbiquinoneUbiquinone Q2Q2 ● Melanin● Alloepipregnanolone●● LeukotrieneLeukotriene A4A4 Alloepipregnanolone

Allopregnanolone●● LeukotrieneLeukotriene A4A4

5 HEPE5 HEPE ● Allopregnanolone●● 5 HEPE5 HEPE

377 1584377 1584377.1584377.1584

Using the present non targeted metabolic profilingResolvin D1 ● 7a-OH-5b-cholanic acid Isolithocholic acid Using the present non-targeted metabolic profiling● Resolvin D1 ● 7a-OH-5b-cholanic acid12b OH 5b h l i id

● Isolithocholic acid Using the present non targeted metabolic profiling ● Resolvin D2 ● 12b-OH-5b-cholanic acid ● Isoallolithocholic acid t h i bi d ith h b id t ti h LC● 18-Oxocortisol ● Lithocholic aicd ● Allolithocholic acid technique combined with hybrid stationary phase LC● 18 Oxocortisol ● Lithocholic aicd ● Allolithocholic acid technique combined with hybrid stationary phase LC

column two potential biomarkers which may indicate393.1323393.1323 column, two potential biomarkers which may indicate 393.1323393.1323 , p y● Allodeoxycholic acid ● 3a,7a-Dihydroxycholanoic acid ● Allochenodeoxycholic acid f i l d l i id tifi d d thodeo yc o c c d● Isodeoxycholic acid

3a,7a Dihydroxycholanoic acid3b 7a Dihydroxy 5b cholanoic acid

Allochenodeoxycholic acidChenodeoxycholic acid progress of cervical dysplasia was identified and they● Isodeoxycholic acid

D h li id● 3b,7a-Dihydroxy-5b-cholanoic acid ● Chenodeoxycholic acid progress of cervical dysplasia was identified and they

● Deoxycholic acid ● 3b,12a-Dihydroxy-5b-cholanoic acid ● Isoursodeoxycholic acidi h b l d i h li id b li

y● Ursodeoxycholic acid

y y● 3a,12b-Dihydroxy-5b-cholanoic acid

y● Isohyodeoxycholic acid might be correlated with lipid or energy metabolism● Ursodeoxycholic acid

Murocholic aicd● 3a,12b Dihydroxy 5b cholanoic acid

3b 12 Dih d 5 h l i id● Isohyodeoxycholic acid

7b 12 Dih d h l i idmight be correlated with lipid or energy metabolism.

● Murocholic aicd ● 3b,12a-Dihydroxy-5a-cholanoic acid ● 7b,12a-Dihydroxycholanoic acidg p gy

● Hyodeoxycholic aicd ● 3b,12b-Dihydroxy-5b-cholanoic aicdy y , y y