Metabolomic analysis of Human Hepatocellular Carcinoma by proton NMR spectroscopy

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

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Metabolomic analysis of Human Hepatocellular Carcinoma by proton NMR spectroscopy. Aicha Demidem INRA, Theix. Colloquium LIX, Ecole Polytechnique. . Palaiseau november 2010. Context. Hepatocarcinoma – HCC Deadly disease : 3rd position (WHO) Diagnostic Relatively late. - PowerPoint PPT Presentation

Transcript of Metabolomic analysis of Human Hepatocellular Carcinoma by proton NMR spectroscopy

Page 1: Metabolomic analysis of Human Hepatocellular  Carcinoma by proton NMR spectroscopy

Metabolomic analysis of Human Hepatocellular

Carcinoma by proton NMR spectroscopy

Palaiseau november 2010

Aicha DemidemINRA, Theix

Colloquium LIX, Ecole Polytechnique.

Page 2: Metabolomic analysis of Human Hepatocellular  Carcinoma by proton NMR spectroscopy

Context

• Hepatocarcinoma – HCC– Deadly disease: 3rd position (WHO)

• Diagnostic– Relatively late

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Diagnostic of Hepatocarcinoma(HCC)

– Marker Serique• AFP (α-fœto protein) weak sensibility

– Anatomo-pathologie, mutation of β-catenin after hepatic resection

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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

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Method

• Metabolomic : approach without a priori * Nuclear Magnetic Resonance (NMR)* Mass Spectroscopy (SM)

– Identification and quantification of metabolites from tissues and biological fluids

• Literature dataMetabonomic studies of human hepatocellular carcinoma using 1H NMR spectroscopy

Yang et al., J of Proteome Res, 2007

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Material & Method: NMR

• Spectral acquisition

– NMR 400 MHz– 1H Spectra– 31P Spectra

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• Software : MestReNova

• Reference : creatine 3,035 ppm

Spectral Treatments

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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

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Comparative metabolic profile from tumoral tissue versus adjacent tissue from the same patient by 1H-NMR

Ten patients underwent liver resection for tumor

Biopsies of both tumor and non-tumoral tissues were obtained from these patients

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Clinical MaterialAge and

sexesNon tumoral tissue Tumoral tissue Serum

Patient 1 F61 years

healthy Endocrine carcinoma yes

Patient 2 M52 years

healthy Neuroendocrine carcinoma yes

Patient 3 M67 years

healthy non

Patient 4 M78 years

Cirrhosis post-hepatitis B HCC grade III Edmonson and Steinert

yes

Patient 5 M72 years

Non cirrhoticSteatose 25% of hepatocytes

HCC grade III Edmonson and Steinert

yes

Patient 6 M 72 years

Cirrhoses macro-nodular and hepatic steatose

HCC grade II Edmonson and Steinert

yes

Patient 7 M73 years

Cirrhosis alcoholic HCC grade II Edmonson and Steinert

yes

Patient 8 M77 years

Steatosis 30% of hepatocytes Benin Hemangiome yes

Patient 9 M67 years

Fibrosis and excess in iron HCC grade II Edmonson and Steinert

yes

Patient 10 F70 years

Steatosis 10% of hepatocytes HCC grade II Edmonson and Steinert

yes

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Results: Identification of Metabolites

PublicationsHMDB

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Results: Identification of Metabolites

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Results: 2D spectral to identify metabolites

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Results : Spectrum difference

Patient 7 TP/TS

-3000

-2000

-1000

0

1000

2000

3000

4000

5000

6000

7000

11.21.41.61.822.22.42.62.83

lactate

alanine

glutathione

Healthy Tissue

Pathological Tissue

Difference PT / HT

glutamate

PT/HT

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Results : Spectrum difference

patient 7 TP/TS

-3500

-1500

500

2500

4500

6500

33,23,43,63,844,24,44,6

glucose glucose / glycogen

ascorbic acid

Healthy Tissue

Pathological Tissu

Difference PT / HT

PT/HT

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Analysis of Relative Concentrations( Univariate data analysis)

Non-Tumoral Group Tumoral Group

meanStandard deviation mean

Standard deviation p-value

hydroxybutyrate 0,0015 0,0013 0,0023 0,0019 0,2226

lactate 0,0910 0,0140 0,1372 0,0610 0,02564 *

alanine 0,0162 0,0033 0,0214 0,0087 0,0507 *

acetate 0,0034 0,0059 0,0014 0,0007 0,4178

glutamate 0,0083 0,0043 0,0144 0,0060 0,002331 **

succinate 0,0065 0,0033 0,0035 0,0025 0,03671 *

glutamine 0,0062 0,0052 0,0142 0,0112 0,01748 *

glutathione 0,0008 0,0006 0,0038 0,0020 0,004662 **

ascorbic acid 0,0012 0,0004 0,0035 0,0020 0,00407 **

PE 0,0017 0,0010 0,0055 0,0026 0,00058 ***

Mann-Whitney test = 5%

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Cho 0,0018 0,0010 0,0014 0,0010 0,2226

lactate CH 0,0288 0,0052 0,0401 0,0186 0,1474

GPC 0,0066 0,0027 0,0065 0,0078 0,1474

signal 4.35 0,0010 0,0006 0,0019 0,0011 0,0507 *

signal 4.43 0,0015 0,0004 0,0013 0,0008 0,4726

creatine 0,0101 0,0009 0,0119 0,0045 0,4178

β-glucose 0,0305 0,0055 0,0198 0,00470,00058

28 ***

α-glucose 0,0223 0,0043 0,0155 0,0041 0,02005 *

glycogen 0,0023 0,0030 0,0006 0,0007 0,02673 *

fumarate 0,0003 0,0001 0,0003 0,0002 0,2669

Non TumoralGroup Tumoral Group

mean SD mean SD p-value

Analysis of relative concentrations

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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 increasedDifferentiation Ros increasedDifferentiation Ros increasedDifferentiation

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

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Interpretation1- 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

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Conclusion

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

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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

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Hospital TeamArmand AbergelEmmanuel BucDenis Pezet

INRAAnne FagesDaniel MorvanPascale RioGeorges Stepien

MNR/MS TeamGuy Bielicki Jean Pierre RenouEstelle Pujos