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    Inter nat ional Jour nal of Chem ical And Ph ar ma ceutical Resea rch

    Volume 1, Issue 1 , July 20 12 .

    Glor igin Lifesciences Pr ivate Limited.

    Research Article

    1

    Keywords: Metabonomics, Nuclear Magnet ic Resonance, NMR, Spectroscopy, Hepatocel lular

    Car cinom a, Chr on ic Liver Disea se, Diagn ost ic Tool.

    Cor re spon d ing Auth or : Rake sh N Pillai, Clinical Epidem iology Reso ur ce & Tra inin g Cen tre, Med ical

    College, Trivandr um 6 50 01 1 em ail address: p illai60 48 @gma il.com

    Author Affiliations: 1 Cl inical Epidemiology Resource & Training Centre , Medical College,

    Tr i vandr um, 2Vice Prinicpal, Medical College, Trivandrum, 3 Sr. Scientist , IISR, Papanamcode,

    Trivandrum, 4 Consultant, Trivandrum

    IJPCR VOL. 1 (1 ) JULY 2 01 2 w w w.ijp cr.n et 8

    1H NMR BASED METABONOMICS AS A DIAGNOSTIC TOOL

    TO HARACTERIZE PATIENTS WITH HEPATOCELLULAR

    CARCINOMA

    Rakes h N Pillai1*, Har ikum aran Nair 1, Vinay Kumar 2, Luxm i Var m a 3, Nisha Nair4

    Abstract

    The qu ant i ta t ive measu rem ent of dynamic mu lt i -param et r ic me tabol ic response of liv ing

    systems to physiological stimuli or genetic modifications is known as Metabonomics and is

    indicated to extract biochem ical inform ation with re spo nse to a biological even t. It encom pas ses

    the com preh ensive and systema tic lis t ing of metabol ites and their concentrat ions in the t issue

    or b iofluids. Therefore this technique sum mar izes the tem poral changes in th e wh ole or ganism,

    both beneficial and adverse, through the effects of diet, l ifestyle, environment, genetics, and

    ph arm aceut icals. Thus a m etabolic profile is gener ated by th e study of biofluids or tissue s an d

    this data is being interp reted using chemom etr ics techniques. The technique a nalyses the ent i re

    pool of metabol ite sum ma ry in a biofluid close to i ts ph enotype, thereby p rom ising a pow erful

    diagn ostic tool in futur e.

    In t l. J Ch em Ph a rm Re s 2 0 1 2 ;1(1 ) : 8 1 9

    Clinical Research

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    1. INTRODUCTION

    Metabonomics is formally defined as The

    q u a n t ita t i ve m e a s u r e m e n t o f d y n a m i c

    mul t i - pa r ame t r i c me t abo l i c r e sponse o f

    l iving system s to physiological s t im uli orgene tic m od ifications. [1] This is the m ost

    re cen t tech no logy in th e wo rld of Om ics,

    which is indicated to extract biochemical

    information with response to a biological

    event . I t encomp asses the comp rehe nsive

    and systematic l is t ing of metabol i tes and

    t h e i r c o n c e n t r a t i o n s i n t h e t i s s u e o r

    b i o f l u i d s . T h e r e f o r e t h i s t e c h n i q u e

    summ ar i zes t he t em por a l changes i n t he

    w h o l e o r g a n i s m , b o t h b e n e f i c i a l a n dadve rs e, th ro ugh th e effects of d iet, lifestyle,

    e n v i r o n m e n t , g e n e t i c s , a n d

    ph arm aceut icals. Thu s a m etabolic profile is

    gener ated by the study of biofluids or tissues

    and t h i s da t a i s be i ng i n t e r p r e t ed us i ng

    c h e m o m e t r ic s t e c h n i q u e s .[ 2 ] I n s h o r t

    Metabonomics analyses the ent i re pool of

    me tabolite sum m ary in a biofluid close t o its

    phen otype , thereby prom ising a power ful

    diagnost ic tool in future. There are many

    techniques u sed in Metabonom ic studies in

    w h i c h N M R s p e c t r o s c o p y h a v e c e r t a i n

    advantages over oth er w hich is summ arized

    in Table 1 .

    1.1 NMR based Metabonom ics

    N uc l ea r magne t i c r e sonance ( N MR ) i s a

    p o w e r f u l a n a l y t i c a l t o o l f o r t h e

    c h a r a c t e r i z a t io n o f m o le c u la r s t r u c tu r e ,

    qu ant itative analysis, and the exam ination ofdynam ic processes in b ioflu ids or t i s sues .

    T h i s t e c h n i q u e e x p l o i t s t h e m a g n e t i c

    p r o p e r t i e s o f c e r t a i n a t o m i c n u c l e i

    (esp ecially atom s like Hydrogen and Carb on)

    depending upon the i r chemica l s t ruc ture .

    This atomic nucleus in a static magnetic field

    absor bs electrom agnet ic radiation of specific

    f r equency depend i ng on t he i r angu l a r

    momentum,

    which is recorded a s i tsresona nce pea ks on

    X axis. The r eson ance pea ks takes car e of

    c h e m i c a l s h i f t s w h i c h i s m a r k e d i n a

    continuou s scale ran ging from 0-10 par ts per

    million (PPM). The Y axis corresponds to

    the inte nsity of each p eak w hich is directlyprop ort ional to the concentrat ion of those

    me tabolites in the biological fluid or tissue .

    Thus NMR spectroscopy wil l summarizes

    t h e l i s t o f m e t a b o l i t e s a t d i f f e r e n t

    c o n c e n t r a t i o n b o t h o b j e c t i v e l y a n d

    subjectively.

    Metabono mics based on NMR spectroscopy

    have r ising ap plications in differen t are nas

    of health like d iagnosis an d classification ofd i seases , to moni tor t ime-course d i sease

    pr ogres sion, to iden tify new b iomar kers, to

    learn pathological mechanisms, to monitor

    efficiency and toxicity of diseases etc. This

    i s a l s o u s e d t o g e n e r a t e m e t a b o l o m e

    database s and in dru g designing.

    1.2 Hepatocellular Carcinom a

    Est imates f rom var ious cancer regi s t r i es

    indicate that l iver cancer re mains the fi fthmost common mal ignancy in m en and the

    eighth in w om en wo rldw ide. Hepa tocellular

    C a r c i n o m a ( H C C ) i s t h e m o s t c o m m o n

    primary l iver cancer and about 90% of al l

    l iver can cer con stitutes to be HCC. The a ge

    standardized incidence rates , ranges from

    less than 10 cases p er 1 00,000 po pulat ions,

    i n p a r ts o f No r t h Am e r i c a a n d W e s t e r n

    Europ e as w ell as in Ind ia, Iran an d Iraq. The

    standard m ortality rate is from 50 150 case sper 100,000 populations in parts of Africa

    and Asia. In high-risk countries, HCC can

    arise before the a ge of 20 years , whe reas in

    coun tries at low risk, HCC is rar e b efore th e

    age of 50 year s. Rates of liver can cer in m en

    are typica l ly 2 to 4 t imes h igher than in

    women.[3,4] .

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    The i nc i dence o f p r i mar y l ive r can ce r i s

    increasing in several developed countr ies ,

    includ ing the United States and t he incre ase

    is likely to cont inue for som e decades. The

    trend is a resu lt of a cohor t effect re lated to

    infection w ith hep atitis B an d C viruses , theincidence of which peaked in th e 19 50s to

    19 80 s. In selected are as of some developin g

    count r ies , the inc idence of pr imary l iver

    cancer has decreas ed, pos sibly as a res ult of

    the introdu ction of hepa titis B virus vaccine

    T h e a t t r i b u t a b l e r i s k e s t i m a t e s f o r t h e

    comb ined effect of this infection a ccount for

    over 8 0% of liver can cer cases w orldw ide.[ 5]

    T h e m a j o r e t i o l o g i e s o f h e p a t o c e l l u l a r

    carcinoma are l is ted in table 2. There is a

    p o s i t i v e a s s o c i a t i o n o f h e p a t o c e l l u l a r

    carc inoma wi th fac tors l ike a ge , e leva ted

    bod y mas s index, (esp ecially in men ) as w ell

    as d iabetes m elli tus. 6 As for most types of

    cancer , hepatocel lular carcinogenesis is a

    mu ltistep p rocess involving differen t gene tic

    altera tions th at ultimate ly lead to m alignan t

    transforma tion of the hepato cytes.

    1.3 Rationa le of th e study

    The rat ionale for th is study wa s based on th e

    concept that , populat ions at high r isk for

    l iver cancer , such a s tho se w ith cirr hosis ,

    have to be ident ified ea rly. Studies sh ow tha t

    a r ound 20 t o 5 0% of pa t i en ts p r e sen t i ng

    w i t h h e p a t o c e l l u l a r c a r c i n o m a h a d

    previously undiagnosed cirrh osis . [7] The

    curr ent m odalities pote nt ially available for

    screening include serum alpha-fetoprotein( A F P ) a n d U l t r a s o n o g r a p h y ( U S G ) .

    Moreover uncharac ter i s t ic screening m ay

    l e a d t o m o r e i n v a s i v e c o n f i r m a t o r y

    techn iques like liver b iopsy. Com plications

    o f live r b i opsy a r e r e por t ed i n 0 .06% t o

    0.32% of pat ients, and typically occur within

    the first few hou rs after t he b iopsy. For this

    reason, we were a iming a t new screening

    strategies an d

    1.4 Risk of hepa tocellular carcinom a

    in chronic liver d isease

    M a n y s t u d i e s s h o w i n c r e a s e d r i s k o f

    hepatocel lular carcinoma in pat ients with

    l iver c i r r hos i s depen ding o n t he ac t iv ity,

    dura t ion and the e t io logy of the d i sease .

    Clinical markers such as Alpha fetoprotein

    (AFP) , Des carb oxy pr othr om bin (DCP) ,

    biological var iables s uch as Hb s-Ag, an ti-HCV

    a n d p l a t e l e t c o u n t s e t c a l l o w s f u r t h e r

    classification of cirr hot ic patien ts w ith h igh

    risk ofhepa tocellular carcinom a. Child pu gh

    scor e and MELD scor e a r e ca lcu la t ed t o

    m o n i t o r t h e p r o g r e s s i o n o f c i r r h o s i s .

    Relative risk of liver can cer is incre ased with

    coexistence of etiologies, such as hepatitis

    B ( H BV) , he pa t i t i s C ( H CV) i n f ec t i on s ,

    aflatoxins, [8,9] HBV, HCV infection and

    alcohol or diab etes m ell itus, [10 ] ,11 HCV

    i n f e c t i o n a n d l i v e r s t e a t o s i s . [ 1 0 ]

    Coexistence of oth er en vironm en tal factor s

    l ike a lcohol , [8 ,12 ,13] d iabetes mel l i tus ,

    o b e s i t y a n d t o b a c c o a ls o i n c r e a s e s t h e

    relat ive r isk of HCC development . [12,14]

    Ther e is also incre ased risk w ith occult HBV

    i n f e c t i o n . [ 1 5 ] I n t e r e s t i n g l y , c o f f e e

    consumpt i on appea r s t o r educe t he H C C

    risk.[16] In general, ther e are evidences th at

    HBV an d HCV un der certain circum stances

    play an a dd itiona l direct r ole in th e m olecular

    pathogenesis of HCC. Aflatoxins have been

    s h o w n t o i n d u c e m u t a t i o n s o f t h e p 5 3

    tum our su ppr essor gene , thus p oint ing to

    the contr ibut ion of an environm ental factor

    to th e tum our developm ent at th e m olecular

    level.

    char acterization tools to find the vulne rab le

    p a t i e n t s e f f e c t i v e l y w h e n p r e v e n t i v e

    treatment is helpful. Metabonomics based

    on 1H NMR, is very sen sitive instrum ent and

    c a n b e d e v e l o p e d f o r s c r e e n i n g a n d

    sur veillance of hep atocellular carcinom a. Itcan efficien t ly extra ct detai led m olecu lar

    i n f o r m a t i o n o n a l a r g e n u m b e r o f

    m etabolites in d iffere nt bio fluids.

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    1.5 Gold stan dard in the d iagn osis of

    hepa tocellular carcinom a

    Standards recom m ended b y EASL (Europ ean

    a s s o c i a t i o n o f s t u d i e s o n l i v e r ) i n t h e

    diagnosis of liver cancer depen d o n th e size

    of nodules in the liver. In the case of nodulesize not exceed ing 2 cm, biopsy of the no dule

    i s r e c o m m e n d e d s i n c e t h e i m a g i n g

    techn iques do not have su fficient accur acy to

    dist inguish hepatocel lular carcinoma from

    other ben ign or malignant condi t ions and the

    AFP concentration will usually re ma in w ithin

    n o r m a l v a l u e s o r b e s l i g h t l y e l e v a t e d .

    Pathological confirmations are obtained by

    cytology or h istology, bu t th e com binat ion of

    both techniques offers the highest d iagnost ic

    accuracy. In the case of no dules a bove 2 cm,

    imaging techniques along with ap prop riate

    s e r o l o g y c a n c o n f i d e n t l y e s t a b l i s h t h e

    diagnosis without need ing confirmat ion with

    a pos i t i ve b i op sy .[ 17 ] . The EASL, ha s

    stressed that the biopsy of small lesions m ay

    not be rel iable due to 3 r easons,

    In the case of small lesions needle

    placeme nt may b e d ifficul t and one

    cannot be cer tain that the samp le was

    drawn from the lesion.

    There is a d ispar i ty between

    pathologists in sort ing out dysplasia

    and HCC, and this disagreement occurs

    more frequently as the size of the

    lesion decreases.

    It may b e d ifficult to dist inguish we ll-

    d i f f e r e n t i a t e d h e p a t o m a f r o m

    normal l iver on b iopsy, where the

    archi tectural features of l iver cel ls

    such a s w idened plates m ight be lost .

    the d iagnosis of l iver cancer. The pr imar y

    objective was to identify and characterize

    the distribution o f significant me tabolites in

    s e r u m o f p a t i e n t s w i t h h e p a t o c e l lu la r

    c a r c i n o m a a n d p a t i e n t s w i t h o u t

    hep atocellular car cinom a, from a bas ket ofm e t a b o l o m e l i b r a r y . T h e s e c o n d a r y

    ob jective wa s to der ive an o pt imal cut-off for

    each m e t abo l it e w h i ch can d i ffe r en t i a t e

    be tween these two cond i t ions . Since we

    w er e us i ng t he p r i nc i p l e s o f d i agnos t i c

    test ing in th e ana lysis, the sa m ple size was

    ca lcu la t e d accor d i ng l y, u s i ng n - ma s t e r .

    Keep ing sens i t iv ity of new tes t as 9 5 % ,

    pre cision of pop ulat ion param eter as 1 0 % ,

    a n d ( 1 - a ) a t 9 5 % , t h e n t h e s a m p le s i zerequ ired was 18 p osi t ive cases.

    2. MATERIALS AND METHODS

    T h i s s t u d y w a s a v e n t u r e t o a d o p t

    ep idem iological pr inciples into b asic science

    resea rch an d is a sole attemp t to highlight the

    use of Nuclear ma gnet ic reson ance (NMR)

    spe ctroscop y and Metabo nom ics pr inciple in

    2.1 Sam ple Collection

    The patients were selected from Gastroen-

    t e r o l ogy depa r t men t , Med i ca l C o l l ege ,

    Trivandrum, which is a ren owne d ter t iary

    care centre for liver related ailm ents. Seru m

    ana lysis using NMR spectroscop y, was car -

    r ied out w ith the help and guidance from

    NIST (Nationa l inst itut e of science an d tech -nology), Trivandrum, which is one among

    the recognized CSIR labs in India. All sus-

    pected cases of chronic liver disease con-

    secu tively adm itted to Gastro en ter ology de-

    pa rtm en t in Med ical College, with r esu lts of

    u ltra soun d examinat ion and approp r ia te

    serology tests were included in the study.

    Patients not giving consent as we ll as th ose

    without o r n ot w ill ing for fur th er tests wer e

    excluded. For ROC ana lysis gold stan dar d

    considered were ul t ra sound examinat ion

    along w ith app ropriate ser ology and expert

    opinions . Appr oval from hum an e th ica l

    commit tee was ob tained and th e data were

    col lec ted us ing Per forma af te r informed

    consen t which was com pleted by ph ysician

    at tending the pat ient .

    Blo o d sa m p le s w e r e co lle ct e d an d

    r o u t i n e b i o c h e m i c a l p a r a m e t e r s

    were m easured.

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    and at tent ion. The m ost impor tant facet of

    a n y f i t t i n g t e c h n i q u e i s a p p l y i n g i t

    consisten tly to all spe ctra in a dataset.

    F i r s t s t e p w a s t o i d e n t i f y a l i s t o f

    metabolites (targeted profile) from a pool

    of comp oun ds available in the Chen om x

    l i b r a r y . L a t e r t h i s c o m p o u n d s e t w a s

    ma tched an d qu ant i fi ed uni form ly in a l l

    e x p e r i m e n t a l s p e c t r u m s . I n t h i s s t u d y

    p r o f il in g w a s r e s t r ic t e d t o c o m p o u n d s

    reson at ing their peaks in the re gion 0- 4.5

    pp m. There are two w indows in th is region,

    wh ich const itute s lipopr otein lipids (LIPO)

    w i t h compl ex b r oad spec t r ums o f l i p i d

    m o l e c u l e s a n d l o w m o l e c u l a r w e i g h t

    molecules (LMWM) like glucose.[ 1 9]

    Init ially 2 50 me tabol i tes wer e considered

    from the CHENOMX libra ry an d pr ofiling

    was done on 137 metabol i tes . The others

    w e r e e x clu d e d b e c a u s e o f s u s p e c t e d

    overlaps with water peaks. Quantification

    was b ased on the intensi ty of peaks, in th e

    e x p e r im e n t a l s p e c tr u m m a t c h e d w i t h

    reference peaks . Prof i l ed compounds as

    wel l as i ts po tent ia l concent ra t ion w ere

    e x p o r t e d t o E x c e l s h e e t f o r s t a t i s t i c a l

    analysis.

    2.21

    H NMR Spectroscop y

    The serum was d i luted by D2O (Deuter ium

    oxide) a t a ra t io of 1 : 4 l concent ra t ion .

    500 l of samp le is transferred into a 5 m m-

    outer -diameter NMR tubes an d was pr ocessed

    p r o c e s s e d i n a B r u k e r s p e c t r o m e t e r

    o p e r a t i n g a t 5 0 0 M H Z . F o r a c q u i r i n g

    quan t i ta t i ve mea su r em en t s t he s equence

    was re pea ted 4 0 time s each with a total delay

    of 5.8s and an a cquisition time 1 .7s, which

    g a ve r e a s o n a b le s i g n a l t o n o i s e ( S / N )

    ratio.[18].

    The la rge water p eaks was sup pressed by

    ap plying a s econda ry irra diat ion field at i ts

    resonance f requency. The procedure was

    repe ated in al l sam ples un iform ly to br ing

    intern al val idi ty in data pr ocessing. Phase

    angle and base l ine correct ions w ere done

    a n d t h e s p e c t r u m i s t r a n s f e r r e d i n t o

    C h e n o m x p l a t f o r m f o r t a r g e t p r o f i l i n g .

    Targeted pr ofiling involves fit t ing a se ries o f

    compounds to an exper imenta l spec t rum.

    Practically, targeted profiling includes the

    two tasks of ident i fy ing compounds , and

    f i t t i n g t h e i n d i v i d u a l c l u s t e r s o f e a c h

    compou nd to th eir respect ive regions of the

    spe ctru m . Fitting individua l com pou nds in a

    region of the spe ctrum requ ires some care

    Serology for Alfa fe toprotein and Ultra

    s o n o gr a m w e r e m e a s u r e d o n a l l

    p a t i e n ts . CT a n d M R I w e r e u s e d

    wherever required.

    Ch ild P u gh s co r e we r e r eco r de d a s a

    sum mar y index in the progression of liver cirrh osis.

    Th e pa t ie n ts w e r e g r o up e d, a s

    h e p a t o c e llu la r c a r c in o m a a n d n o

    hepatocellular carcinoma, according

    to th e re sults from gold stan dards.

    Th e se r um s am p le s w e re se n t fo r

    N u c l e a r M a g n e t i c R e s o n a n c e

    Spectroscopy.

    2.3 ROC an alysis

    Di agnos t i c pe r fo r m ance o f a t e s t o r

    accuracy of a test to d iscr iminate d iseased

    cases from non diseased is evaluated using

    Receiver Operat ing Character is t ic (ROC)

    curve a na lysis. [20] ROC curves can a lso b e

    u s e d t o c o m p a r e t h e d i a g n o s t i c

    per form ance of two or mor e labora tory or

    d i a g n o s t i c t e s t s . [ 2 1 ] R O C ana l yses a r e

    comm only used in me dical decision m aking,

    a n d i n r e c e n t y e a r s h a v e b e e n u s e d

    increasingly in machine learning and data

    mining research. For a cont inuous ou tcome,

    as s een in th is s tudy, differen t th res holds

    (cut offs or criterion value) ar e ap plied to

    pred ict class me mb ersh ips.

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    T h i s i s a n e s t i m a t e o f e a c h m e t a b o l i t e s

    pr oba bility to wh ich indepen dent class t hey

    be lon gs to, at t ha t cut o ff [22 ].

    T o t a l 1 3 7 m e t a b o l i t e s i n t h e

    m e t a b o l o m e w e r e c o n s i d e r e d a s 1 3 7indepe ndent te sts an d con tingen cy table for

    each m etabolites an d th ere se nsitivity as well

    as false p ositive r ates, at ea ch cut offs w ere

    ca l cu l a t ed . R O C cur ve p l o t t ed and t he i r

    corresponding area under the ROC (AUC)

    wer e com pu ted. AUC gives the pr oba bility

    that , when presen ted w ith a ran domly chosen

    pat ient w ith disease and a ran domly chosen

    pat ient withou t disease, the resu lts of the te st

    will rank the p at ient w ith disease as havinghigher chance for d isease than the pa t ient

    w i t h o u t d i s e a s e . T h e r e fo r e t h o s e

    M e t a b o l i t e s w i t h h i g h e r A U C c a n b e

    c o n s i d e r e d a s t h e b e s t m a r k e r s t o

    d iscriminate hep atocellular carcinom a from

    no ca r c i nom a . Op t i ma l cu t -o f fs f o r e ach

    me tabol it e can be read d i rec t ly f rom ROC

    curves.Several comb ination s of m etabolites

    whe re t r ied so that , those m etabol ites wh en

    compared paral lel , ( i .e . , i f any one test isp o s i t i v e i s c o n s i d e r e d a s t e s t p o s i t i v e )

    improves th e sen si t ivity at minimal cost of

    specificity.

    be tween 41 - 50 age groups .Biochemical

    par am eter s sh owing th e elevated levels of

    liver en zyme s and CHILD-Pugh scor es for all

    pat ients, wh ich ar e sum m arized in Table, 3.

    ROC curve was plotted for each m etabolite

    a t d i ffe ren t concen t ra t ions a nd AUC wascalculated (Table 4). Metabolite, which had

    significant AUC (> 0.70) were selected for

    furth er analysis . Out of 137 me tabol i tes 7 3

    w e r e f o u n d t o h a v e AUC a b o v e 0 .7 0 a s

    shown in the table. An optimal cut-off from

    ROC curve was obtained and the pat ients

    wer e classified into binar y group s as having,

    h e p a t o c e l l u l a r c a r c i n o m a o r N o

    h e p a t o c e l lu la r c a r c i n o m a . M e a s u r e o f

    d i a g n o s t i c a c c u r a c y l i k e S e n s i t i v i t y ,S p e c i f i c i t y a n d L i k e l i h o o d r a t i o s f o r

    hepa tocellular carcinom a w ere compu ted.

    The op timal cut-off was s elected at th e po int

    w her e , t he r e w as a r ea sonab l e t r ade - o f f

    betwee n sen sitivity an d s pe cificity. Here the

    investigator pr eferred b etter sen sitivity for

    selecting cut off values , un like in t he case o f

    tumor markers where specif ici ty is given

    more importance. This strategy is adopteda t t h i s s t a g e k e e p i n g i n m i n d t h a t , a

    scree ning tool is essen tial for th e detect ion

    of ea r l y hepa t oce l l u l a r ca r c i noma f r om

    cirr hot ic patients. The final m etabolom e wa s

    d r a w n fr o m t h e t a b le , w h i ch h a v e h i g h

    l ike l ihood pos i t ive va lues (> 3) and less

    likelihood negat ive values (Table 5). These

    are th e m etabolit es in th e an a lys is wh ich

    have the highest l ikel ihood to d iscr iminate

    hep atoce l lu lar carc inom a. Many par a l le lcombinat ions where t r i ed on the bas i s of

    their l ikel ihood rat ios. Those with higher

    l ikel ihood posi t ive values were pooled to

    check the improvement in sens i t iv i ty . In

    par a l le l comb inat ions (Table 6 ) th e t e s ts

    were considered positive if any one of the

    me tabol i tes in the combinat ion is posi t ive.

    3. RESULTS

    There wer e 68 pat ients part icipated

    in th e stud y. On the bas is of resu lts from gold

    s tandards , 20 pa t ients w here grouped in to

    hep atocellular carcinom a, 28 as chr onic liver

    disease with cirrh osis and 2 0 as appar ent lynor ma l liver. Therefore th e en t i re da tase t

    obtaine d h ad, 13 7 m etabolites X 68 pa tien ts.

    Mean age distribution am on g hep atoce llular

    carcinom a pat ients was 5 0.21 (45.81-54.61)

    and that of pat ients group ed as Chron ic liver

    disease w as 5 0.79 (46.86-54.71) . Mean age

    distr ibut ion among people with apparent ly

    nor ma l liver wa s 40.15 (36 .81 -43.49 ). 52 .6%

    of hep atocellular carcinom a pat ients wer e

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    IJPCR VOL. 1 (1 ) JULY 20 12 w w w.ijp cr.n e t 14

    9 . Min g , L., e t a l. D o m i n a n t r o le o f

    hep atitis B virus an d cofactor r ole of

    aflatoxin in he pa tocarcinogen esis in

    Qidon g, Chin a. Hep a to logy 36 , 121 4-

    1220 ( 2002) .

    1 0 . Hassan , M.M., e t a l. Risk factors forhep atocellular carcinom a: syner gism

    of a lcohol w i th v i ra l hep at i t i s and

    d i abe t e s me l l i t u s . H e p a t o lo g y 36 ,

    1206- 1213 ( 2002) .

    11 . Ohata , K., e t a l. Hepat ic stea tosis is a

    r i s k f a c t o r f o r h e p a t o c e l l u l a r

    carcinoma in pat ients with chronic

    hep atitis C virus infection. Cancer97 ,

    3036- 3043 ( 2003) .

    1 2 . Mar re r o , J.A., e t a l. Alcohol, tobaccoa n d o b e s i t y a r e s y n e r g i s t i c r i s k

    factor s for h ep atocellular car cinom a.

    J He p a to l42 , 218-224 (2 005) .

    13 . Mor gan , T.R., Mandayam, S. & Jama l,

    M. M. A l coho l and hepa t oce l l u l a r

    c a r c i n o m a . G a s t r o e n t e r o lo g y 1 27 ,

    S87-96 (200 4) .

    14 . El-Serag, H.B., Tran , T. & Everhar t, J.E.

    Diabete s increases th e risk of chron ic

    l iv e r d i s e a s e a n d h e p a t o c e l lu la r

    c a r c i n o m a . G a s t r o e n t e r o lo g y 1 26 ,

    460- 468 ( 2004) .

    1 5 . Pollicin o , T., e t a l. Hepatitis B virus

    m a i n t a i n s i t s p r o - o n c o g e n i c

    pro per ties in the case of occult HBV

    infection. Gastroenterology126 , 102 -

    110 ( 2004) .

    16 . Gela tt i, U., e t a l. Coffee consumption

    reduces the r i sk of hepatoce l lu lar

    c a r c i n o m a i n d e p e n d e n t l y o f i t s

    ae t i o l ogy : a ca se - con t r o l s t udy . J

    Hep a tol42 , 528-534 (2 005) .

    17 . Br u ix, J., e t a l. Clinical management

    o f h e p a t o c e l l u l a r c a r c i n o m a .

    Conclusions of the Barcelona-200 0

    E A S L c o n f e r e n c e . E u r o p e a n

    Asso ciation for t he Stud y of th e Liver.

    J He p a to l35 , 421-430 (2 001) .

    4. REFERENCES

    1 . N icho lson , J.K., Conne l ly, J., Lindon ,

    J.C. & Holmes, E. Metabonomics: a

    platform for studying drug toxicity

    a n d g e n e f u n c t i o n . N a t Re v Dr u gDisco v 1 , 153-161 (2 002) .

    2 . Nicholson , J.K., Lindon , J.C. & Holmes ,

    E. Metabonomics: understanding

    t he me t abo l ic r e sp onses o f liv ing

    s y s t e m s t o p a t h o p h y s i o l o g i c a l

    s t imu l i via m ul t ivar ia te s ta t i s t i ca l

    ana l ys i s o f b i o l og i ca l N MR

    spe ctroscop ic data. Xe n o b io t ic a 29 ,

    1181- 1189 ( 1999) .

    3 . She r man , M. & Kle in , A. AASLD s ingle -t o p i c r e s e a r c h c o n f e r e n c e o n

    h e p a t o c e l l u l a r c a r c i n o m a :

    Conference proceed ings.Hep a t o logy

    40 , 1465 -1473 (2004) .

    4 . Br u ix, J. & Sh er m an , M. Ma na ge m en t

    o f h e p a t o c e l l u l a r c a r c i n o m a .

    Hep a to logy 42 , 1208-1236 (2 005) .

    5 . Bo s ch , F.X., Rib e s , J., Dia z , M. &

    C l e r i e s , R . P r i mar y l i ve r cance r :

    w o r l d w i d e i n c i d e n c e a n d t r e n d s .

    Gastroe nte rology 127 , S5-S16 (20 04 ).

    6 . Blu m , H.E. He p at oce llu la r ca r cin o m a

    - G l oba l bu r den and r i sk f ac t o r s .

    SUPLEMENT O IATREIA VOL 20 , S11 -

    14 ( 2007) .

    7 . Za m a n , S.N., Jo h n so n , P.J. & W illia m s ,

    R. Silen t ci rrh osis in p at ients with

    h e p a t o c e l l u l a r c a r c i n o m a .

    Implicat ions for screening in h igh-

    incidence and low-incidence areas.

    Cancer65 , 1607-1610 (1990) .

    8 . Yu , M.C. & Yu a n , J.M. En vir o n m e n ta l

    factors and r isk for hepatocel lular

    c a r c i n o m a . Gastro en tero logy 1 27 ,

    S72-78 (200 4) .

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    IJPCR VOL. 1 (1 ) JULY 2 01 2 w w w.ijp cr.n e t 1 5

    1 8. Nich olson , J.K., e t a l. Proton-nuclear-

    m a g n e t i c - r e s o n a n c e s t u d i e s o f

    s e r u m , p l a s m a a n d u r i n e f r o m

    fast ing nor ma l and diabet ic subjects .

    B io ch em J217 , 365-375 (1 984) .

    19 . Ma kin en , V.P., e t a l. 1H N MRm e t a b o n o m i c s a p p r o a c h t o t h e

    d i s e a s e c o n t i n u u m o f d i a b e t i c

    complicat ions and p rem ature death.

    Mol S yst Bio l4 , 167 (2 008) .

    2 0 . Me tz , C.E. Ba s ic p r in c ip le s o f ROC

    analysis. Semin N uc l Med 8 , 283 -298

    ( 1978) .

    21 . Gr iner, P.F., Mayewski , R.J., Mushl in ,

    A.I. & Greenland, P. Selection and

    interp retation of diagnostic tests an d

    p r o c e d u r e s . P r i n c i p l e s a n d

    app l i ca t i ons . An n In te r n M e d 94 ,

    557- 592 ( 1981) .2 2 . To m , F. ROC gr ap h s w it h in s ta n ce -

    varying costs. Pattern Recogn. Let t .

    27 , 882-891 (2 006) .

    Table 2, lists out the major etiological factors of hepatocellular carcinoma worldwide, as cited in

    the art icle by Blum et.al in r eference 6 .

    Table 2, Major etiologies of hepa tocellular carcinom a

    Tab le 1, Advan tages of NMR sp ectr osco py

    Table 1, l ists s om e distinguishing feature s o f Nuclear Magnetic Resonan ce (NMR) s pectroscopyover other comm on techn iques in Metabonomic studies.

    ! Cirrho sis due to Chronic Hepat itis B, C and D

    ! Cirr ho sis du e to Toxins ( e.g., alcoh ol, to ba cco, aflato xins )

    ! Autoimm une hepa t i t is

    ! Hered itary m etabolic liver d iseases

    (e.g., her ed itar y hem ochrom atosis, 1-antitrypsin deficien cy)

    ! States of ins ulin re sistance

    Overw eight in ma les

    Diabe tes me llitus

    Non-alcoholic steatohepatitis (NASH)

    Non-alcoholic fatty liver disease (NAFLD)

    ! Dire ct an alysis of com plex biological sam ples

    ! Non selective an d simu ltaneou s detection o f en dogen ous m etabolites

    ! Quan ti tat ive at minimu m of 10 M concentrat ion

    ! Rapid, approximately 10 minute s

    ! Sam ples ar e no n destructive

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    Table 3, shows t he biochem ical par am eter s of 68 pat ients in the s tudy who w ere groupe d as HCC, CLD and

    normal l iver. Abbrevations for, AST (aspartate transferase), ALT (alkaline transferase), ALP(alkaline

    pho spatase). IU/ L is the intern ational unit per l it re and m g/ dl is mill igram p er desili tre.

    Tab le 4 , List of me tabolit es w ith significant AUC

    IJPCR VOL. 1 (1 ) JULY 20 12 w w w.ijp cr.n e t 16

    Table 3, Biochem ical pa ra me ter s of th e t otal sam ples

    Cha ra cter ist ics HCC grou pn =20 No HCC grou pn =28

    (Mean , 95% C.I) (Mean , 95 % C.I)

    AST (IU/ L) 180 (134 .02-225 .98) 104 .07(8 0.71-12 7.43)

    ALT (IU/ L) 80 .68 (70 .18 -91.19) 58 .21 (45 .49 -70.93)

    ALP (IU/ L) 284 .26(1 83.43-385.10) 165 .04(1 36.04-194.03)

    Bil irub in (mg/ dl) 4.068 (2.067 -6.069 ) 2.636 (1.950 -3.322 )

    CHILD-Pugh 11 (10 .26 -11.74) 8.75(7 .90 -9.60 )

    Ar ea 95% Confidence

    Sl no un der P va lue In ter va l

    curve

    1 . Galactar ate 0 .8 57 0 .0 00 0 .7 65 0 .9 49

    2 . Ace toace tate 0 .8 50 0 .0 00 0 .7 60 0 .9 40

    3 . Methylam in e 0 .846 0 .00 0 0 .75 5 0 .9 364 . 1 ,3 -Dihydr oxyace tone 0 .8 35 0 .0 00 0 .7 41 0 .9 30

    5 . 2 -Hydr oxyglu tarate 0 .835 0 .000 0 .7 34 0 .93 6

    6 . S-Su lfocyste in e 0 .83 0 0 .0 00 0 .73 1 0 .9 30

    7 . 3 -Hydr oxy-3 -Methylglu tar ate 0 .8 28 0 .0 00 0 .7 31 0 .9 25

    8 . Bu tan on e 0 .827 0 .000 0 .72 8 0 .92 7

    9 . Citr ate 0 .821 0 .0 00 0 .7 20 0.9 22

    10 . Tar tr ate 0 .82 1 0 .00 0 0 .721 0 .92 1

    11 . Glu tara te 0 .82 0 0 .00 0 0 .717 0 .92 3

    12 . Glu tam ate 0 .81 8 0 .00 0 0 .70 5 0 .93 0

    13 . Levu lina te 0 .8 18 0 .0 00 0 .71 4 0 .92 1

    14 . Succin ate 0 .816 0 .000 0 .713 0 .91815 . Malate 0 .811 0 .000 0 .707 0 .91 6

    16 . Suber ate 0 .810 0 .000 0 .702 0 .91 9

    17 . 2 -Am inoad ipa te 0 .809 0 .000 0 .695 0 .92 4

    18 . Glycin e 0 .80 8 0 .00 0 0 .70 5 0 .91 2

    19 . Dim e thylam ine 0 .807 0 .000 0 .70 4 0 .91 1

    20 . 2 -Oxovalera te 0 .805 0 .00 0 0 .69 9 0 .9 11

    21 . Prop ionate 0 .804 0 .000 0 .69 8 0 .91 1

    22 . Pyr uvate 0 .80 4 0 .00 0 0 .69 9 0 .91 0

    23 . Ace ton e 0 .80 3 0 .00 0 0 .70 0 0 .90 6

    24 . Glucar ate 0 .80 2 0 .00 0 0 .691 0 .91 4

    25 . O-Phosphoser ine 0 .7 98 0 .000 0 .683 0 .91 3

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    IJPCR VOL. 1 (1 ) JULY 2 012 w w w.ijp cr.n e t 17

    Ar ea 95% Con fiden ce

    Sl no un der P va lue In ter va l

    curve

    26 . 1 ,6 -An hydr o- -d-glucose 0 .796 0 .00 0 0 .66 1 0 .9 31

    27 . Propylene glycol 0 .794 0 .0 00 0 .6 88 0 .89 9

    28 . Glycolate 0 .79 2 0 .00 0 0 .67 8 0 .9 05

    29 . -Alan ine 0 .78 6 0 .00 0 0 .67 5 0 .89 83 0 . Sar cosin e 0 .785 0 .000 0 .6 70 0 .9 01

    31 . Thr eonate 0 .78 5 0 .00 0 0 .67 1 0 .9 00

    32 . Tran s-4 -hydr oxy-l-p rolin e 0 .7 84 0 .0 00 0 .67 1 0 .8 98

    33 . Pim ela te 0 .783 0 .000 0 .656 0 .91 1

    34 . Cysta th ion ine 0 .7 81 0 .00 0 0 .66 8 0 .89 4

    35 . Alan in e 0 .779 0 .0 00 0 .6 64 0 .89 4

    36 . Succinylace ton e 0 .777 0 .000 0 .661 0 .89 3

    37 . Tr im ethylam ine n -oxide 0 .77 7 0 .000 0 .659 0 .8 95

    38 . 2 -Oxocapr oate 0 .776 0 .000 0 .65 9 0 .8 93

    39 . Ser in e 0 .7 76 0 .0 00 0 .6 54 0 .8 98

    40 . 2 -Methylglu tar a te 0 .77 5 0 .00 0 0 .66 0 0 .8 90

    41 . Meth ion ine 0 .768 0 .001 0 .64 3 0 .8 92

    42 . Glycylp roline 0 .7 67 0 .0 01 0 .6 48 0 .8 86

    43 . 5 -Am in olevu lina te 0 .765 0 .001 0 .650 0 .87 9

    44 . 2 -Phosp hoglycer ate 0 .76 3 0 .00 1 0 .64 4 0 .8 81

    45 . 2 -Oxobu tyra te 0 .75 6 0 .00 1 0 .63 4 0 .87 8

    4 6 . Glutaric acid monomethyl ester 0 .756 0 .001 0 .6 34 0 .8 78

    47 . 1 ,3 -Dim e thylu rate 0 .75 5 0 .00 1 0 .63 9 0 .8 71

    48 . 3 -Methylglu tar a te 0 .75 4 0 .00 1 0 .62 8 0 .8 80

    49 . Fr uctose 0 .7 53 0 .0 01 0 .6 21 0 .8 85

    50 . Ascorbate 0 .750 0 .00 1 0 .62 1 0 .8 79

    51 . Ethylene glycol 0 .748 0 .0 01 0 .62 3 0 .87 3

    52 . Asp ar tate 0 .74 7 0 .00 1 0 .62 2 0 .87 253 . Galacton ate 0 .7 43 0 .0 02 0 .61 5 0 .8 70

    54 . Methylsuccin ate 0 .739 0 .002 0 .611 0 .86 6

    55 . Xylose 0 .7 36 0 .0 02 0 .6 06 0 .8 67

    56 . Prolin e 0 .73 3 0 .00 3 0 .61 2 0 .8 55

    57 . Isocitrate 0 .732 0 .00 3 0 .60 4 0 .8 60

    58 . N-Car bam oylasp ar tate 0 .731 0 .003 0 .590 0 .87 3

    59 . 2 -Ethylacr yla te 0 .729 0 .003 0 .59 3 0 .8 65

    60 . 2 -Oxoisocapr oate 0 .724 0 .00 4 0 .58 3 0 .865

    61 . Sucrose 0 .72 4 0 .0 04 0 .5 73 0 .8 75

    62 . Glucose 0 .722 0 .00 4 0 .59 5 0 .8 49

    63 . 4 -Hydroxybu tyrate 0 .720 0 .005 0 .5 89 0 .85 164 . N-Car bam oyl- -a lan in e 0 .720 0 .004 0 .578 0 .86 2

    65 . Valine 0 .72 0 0 .00 5 0 .58 0 0 .8 59

    66 . Galact itol 0 .71 9 0 .00 5 0 .58 9 0 .8 48

    67 . Man n itol 0 .710 0 .007 0 .5 67 0 .8 53

    68 . Tr im e thylam in e 0 .710 0 .00 7 0 .57 1 0 .8 50

    69 . Isobu tyrate 0 .70 4 0 .00 8 0 .57 3 0 .8 36

    70 . N,N-d im e thylglycin e 0 .70 3 0 .00 9 0 .55 9 0 .84 7

    71 . Methylguan id ine 0 .70 1 0 .00 9 0 .561 0 .84 2

    7 2 . Hom oser in e 0 .7 00 0 .0 10 0 .5 57 0 .8 43

    Table: 4, show s m etabolite at th eir 95 % con fidence inte rval, the ir are a un der t he ROC curve w hich is above

    0.70 along w ith the p values.

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    Table 5, Final Metabolome with highest degrees of accuracy

    Table 5. Lists the final me tabolom e w ith highest degrees of accura cy to discrimina te h ep a-

    tocellular carcinom a from th ose pa tients with chron ic l iver d isease or ap pare ntly norm al

    liver

    Table 6, Metabolites a nd their mea sure s of accuracy on pa rallel combinations

    IJPCR VOL. 1 (1 ) JULY 20 12 w w w.ijp cr.n e t 18

    Table 6 , show s th e p arallel comb ination of metabolites in table 4 . On p arallel combina tions s om e of

    the me tabolites sh ow im pro ved sen sitivity and spe cificity.

    Sl n o Me tabolites Cu t offs Sen sit ivity Sp ecificity LR LR

    (+) ( -)

    1 . 1 ,6 -An hydr o- -D-glucose 4 .5 6 52 8 0 .0 0 8 5 .42 5 .4 9 0 .2 3

    2 . Galacta r ate 4 .8 22 3 90 .00 79 .17 4 .3 2 0 .1 33 . 1 ,3 -Dihydr oxyaceton e 1 .4 6 28 7 0 .0 0 8 3 .33 4 .2 0 0 .3 6

    4 . 2 - Bu tan on e 5 .5 89 8 8 5 .0 0 7 7 .0 8 3 .7 1 0 .1 9

    5 . 2 -Hydr oxyglu tarate 24 .71 7 9 0 .0 0 7 5 .0 0 3 .6 0 0 .1 3

    6 . 2 -Oxoisocap r oate 3 .50 5 6 0 .0 0 8 3 .3 3 3 .6 0 0 .4 8

    7 . Citr a te 6 .9 83 5 8 5 .0 0 7 5 .0 0 3 .4 0 0 .2 0

    8 . Cystath ion in e 8 .0 30 4 70 .00 79 .1 7 3 .3 6 0 .3 8

    9 . Acetoace ta te 3 .0 80 8 95 .00 70 .83 3 .2 6 0 .0 7

    10 . Succin a te 1 .7 02 7 80 .00 75 .00 3 .2 0 0 .2 7

    11 . Tar tar ate 5 .83 7 6 85 .00 72 .92 3 .1 4 0 .2 1

    1 2 . Tr im ethylam in e N-oxide 5 .8 37 6 8 5 .0 0 7 2 .9 2 3 .1 4 0 .2 1

    13 . Pyr uvate 2 .9 39 75 .00 75 .00 3 .0 0 0 .3 3

    Sl no Metabolite Combinat ions Sensit ivity Specificity LR+ LR-

    1 . Ser in e an d 2 -Ethylacr ylate 100 68 .75 3 .20 0

    2 . Glycylp roline an d Methylam in e 100 64 .58 2 .82 0

    3 . Methylam in e and Galactarate 100 64 .5 8 2 .82 04 . Methylam ine and Prop ion ate 1 00 5 0 2 .0 0

    5 . 2 -Oxocap roate and Methylam ine 100 50 2 .0 0

    6 . 2 -Hydr oxyglu tarate and Galactarate 9 5 70 .83 3 .2 6 0 .07

    7 . Guan idoacetate and 1,6-Anhydro --D-glucose 9 5 68 .75 3 .05 0 .07

    8 . 2-Methylglutarate and 1,6-Anhydro--D-glucose 9 5 66 .67 2 .85 0 .08

    9 . Ace ton e an d cysta th ion ine 9 5 62 .5 0 2 .53 0 .0 6

    10 . 1 ,6 -An hydr o- -D-glucose an d Ethylen e glycol 9 5 60 .42 2 .4 0 0 .08

    11 . Ace tone an d 2 ethylacr ylate 9 5 50 1 .90 0 .10

    12 . Galactorate and Cysta th ion in e 90 75 3 .6 0 0 .13

    13 . 2 hydroxyglu tar ate and p im e late 9 0 66 .6 7 2 .7 0 0 .15

    14 . Galactarate and Tr im e thylam in e N-oxide 90 6 4 .58 2 .5 4 0 .1115 . Succin ate an d Cystath ion in e 85 75 3 .40 0 .2 0

    16 . Bu tan one an d pyr uvate 85 70 .83 2 .9 1 0 .21

    17 . 3 hydr oxy-3 -m e thylglu tar ate an d Succin ate 8 5 70 .83 2 .9 1 0 .21

    18 . Pim e late and Cysta th ion in e 8 5 66 .6 7 2 .55 0 .2 3

    19 . Alan in e an d Pim elate 85 64 .58 2 .40 0 .23

    20 . 2 -m e thylglu tarate and guan idoacetate 8 5 60 .42 2 .1 5 0 .17

    21 . Pyr uvate an d Cysta th ion ine 80 75 3 .2 0 0 .27

    22 . Cysta th ion ine an d Succinylace ton e 75 7 0 .83 2 .57 0 .3 5

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    Figure 1, Exper imen tal spectru m after p rofiling

    Figure 1; shows an experimental spectrum after profiling. The green line corresponds to the ex-

    perimen tal spectral line of serum, under wh ich som e of the reference comp ounds are m atched in

    correspon ding colors .

    Figur e 2 , Sam ple ROC cur ve p lotte d for 1 ,6Anhydr o -D-Glucose

    Figure 2, show s a s am ple ROC cur ve plotted for 1,6Anhydro -D-Glucose an d its op tim al

    cut off along w ith its m eas ur es of diagno stic accuracy.

    ,

    IJPCR VOL. 1 (1 ) JULY 20 12 w w w.ijp cr.n e t 19