Metabolomic analysis of Human Hepatocellular Carcinoma by proton NMR spectroscopy Palaiseau november 2010 Aicha Demidem INRA, Theix Colloquium LIX, Ecole Polytechnique.

Context Hepatocarcinoma – HCC –Deadly disease: 3rd position (WHO) Diagnostic –Relatively late

Diagnostic of Hepatocarcinoma (HCC) –Marker Serique AFP (α-fœto protein) weak sensibility –Anatomo-pathologie, mutation of β-catenin after hepatic resection

AIMS OF STUDY Identify new biomarkers from tissues and sera (from patients having hepatocarcinoma) to improve the early detection of this deadly disease Identify metabolic pathway of cellular transformation in the aim to determine new therapeutic targets

Method Metabolomic : approach without a priori * Nuclear Magnetic Resonance (NMR) * Mass Spectroscopy (SM) –Identification and quantification of metabolites from tissues and biological fluids Literature data Metabonomic studies of human hepatocellular carcinoma using 1H NMR spectroscopy Yang et al., J of Proteome Res, 2007

Material & Method: NMR Spectral acquisition –NMR 400 MHz – 1 H Spectra – 31 P Spectra

Software : MestReNova Reference : creatine 3,035 ppm Spectral Treatments

Materials and methods: Experimental protocol Collection of liver tissues (+ 4°C) Collection of blood (serum sample) Preparation of tissues for extract and acquisition of NMR spectra Histology report Prelevement of pathological and healthy tissues

Comparative metabolic profile from tumoral tissue versus adjacent tissue from the same patient by 1 H-NMR Ten patients underwent liver resection for tumor Biopsies of both tumor and non-tumoral tissues were obtained from these patients

Clinical Material Age and sexes Non tumoral tissueTumoral tissueSerum Patient 1F 61 years healthy Endocrine carcinomayes Patient 2M 52 years healthy Neuroendocrine carcinomayes Patient 3M 67 years healthy non Patient 4M 78 years Cirrhosis post-hepatitis B HCC grade III Edmonson and Steinert yes Patient 5M 72 years Non cirrhotic Steatose 25% of hepatocytes HCC grade III Edmonson and Steinert yes Patient 6M 72 years Cirrhoses macro-nodular and hepatic steatose HCC grade II Edmonson and Steinert yes Patient 7M 73 years Cirrhosis alcoholic HCC grade II Edmonson and Steinert yes Patient 8M 77 years Steatosis 30% of hepatocytes Benin Hemangiomeyes Patient 9M 67 years Fibrosis and excess in iron HCC grade II Edmonson and Steinert yes Patient 10F 70 years Steatosis 10% of hepatocytes HCC grade II Edmonson and Steinert yes

Results: Identification of Metabolites Publications HMDB

Results: Identification of Metabolites

Results: 2D spectral to identify metabolites

Results : Spectrum difference lactate alanine glutathione Healthy Tissue Pathological Tissue Difference PT / HT glutamate PT/HT

Results : Spectrum difference glucoseglucose / glycogen ascorbic acid Healthy Tissue Pathological Tissu Difference PT / HT PT/HT

Analysis of Relative Concentrations ( Univariate data analysis) Non-Tumoral GroupTumoral Group mean Standard deviationmean Standard deviation p-value hydroxybutyrate0,00150,00130,00230,00190,2226 lactate 0,09100,01400,13720,06100,02564* alanine 0,01620,00330,02140,00870,0507* acetate0,00340,00590,00140,00070,4178 glutamate 0,00830,00430,01440,00600,002331** succinate 0,00650,00330,00350,00250,03671* glutamine 0,00620,00520,01420,01120,01748* glutathione 0,00080,00060,00380,00200,004662** ascorbic acid 0,00120,00040,00350,00200,00407** PE 0,00170,00100,00550,00260,00058*** Mann-Whitney test  = 5%

Cho0,00180,00100,00140,00100,2226 lactate CH0,02880,00520,04010,01860,1474 GPC0,00660,00270,00650,00780,1474 signal ,00100,00060,00190,00110,0507* signal 4.430,00150,00040,00130,00080,4726 creatine0,01010,00090,01190,00450,4178 β-glucose 0,03050,00550,01980,0047 0, *** α-glucose 0,02230,00430,01550,00410,02005* glycogen 0,00230,00300,00060,00070,02673* fumarate0,00030,00010,00030,00020,2669 Non Tumoral GroupTumoral Group meanSDmeanSD p-value Analysis of relative concentrations

Glycolysis is predominant: Warburg effect Anaerobic creatine system / phosphocreatine is predominant Results from Principal Component Analysis (PCA) Allow to describe the information from a set of data (linear combinations of variables) The 2 dimension analysis represents 51% of total variance Correlation circle Ros increased Differentiation Ros increased Differentiation Ros increased Differentiation

Correlation between the grade of HCC and the increase of glycolysis?

Interpretation 1- Increase of lactate and alanine content (final products of glycolysis) Biomarkers of Warburg effect : correlation with progression/stage of disease 2- Increase of glutamate (aggressive form) and glutamine level (less aggressive form ) : Promoters of the tumoral progression Actual target: Glutaminase Inhibitors Convert an aggressive form to an non aggressive form 3 -Decrease of glucose and glycogen level : Result from the conversion of glucose to lactate: hyperactive glycoysis Phenomena common to tumor cells

Conclusion Comparative metabolomic analysis of healthy hepatic tissue and HCC allowed generating assumptions on the redox status and bioenergetics of HCC

Metabolomic analysis of HCC allows to propose : - Metabolic tumoral biomarker (s ) as candidate HCC - Hypothesis (ses) on the metabolic pathways implicated in HCC pathological evolution (aerobic glycolysis, glutamine and creatine system) Conclusion Transfer to in vivo studies using Magnetic Resonance Imaging (MRI) Metabolomic study represents an good way of generating experimental data for metabolic modeling in integrative biology

Hospital Team Armand Abergel Emmanuel Buc Denis Pezet INRA Anne Fages Daniel Morvan Pascale Rio Georges Stepien MNR/MS Team Guy Bielicki Jean Pierre Renou Estelle Pujos