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This study utilizes Metabolomic analysis with NMR spectroscopy to identify biomarkers and metabolic pathways in hepatocellular carcinoma, aiming to improve early detection and therapeutic targeting of this deadly disease. Results show alterations in metabolic profiles between healthy and tumoral tissues, emphasizing the potential of metabolomics in understanding cancer progression.
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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
Diagnostic of Hepatocarcinoma(HCC) • MarkerSerique • 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 • 1H Spectra • 31P Spectra
Spectral Treatments • Software : MestReNova • Reference : creatine 3,035 ppm
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
Ten patients underwent liver resection for tumor Comparative metabolic profile from tumoral tissue versus adjacent tissue from the same patient by 1H-NMR Biopsies of both tumor and non-tumoral tissues were obtained from these patients
Results: Identification of Metabolites Publications HMDB
Results : Spectrum difference Healthy Tissue Pathological Tissue Difference PT / HT PT/HT lactate alanine glutamate glutathione
ascorbic acid Results : Spectrum difference PT/HT Healthy Tissue Pathological Tissu Difference PT / HT glucose glucose / glycogen
Analysis of Relative Concentrations( Univariate data analysis) Mann-Whitney test a = 5%
Results from Principal Component Analysis (PCA) Glycolysis is predominant: Warburg effect Ros increased Ros increased Ros increased Differentiation Differentiation Differentiation Anaerobic creatine system / phosphocreatine is predominant • Allow to describe the information from a set of data (linear combinations of variables) The 2 dimension analysis represents 51% of totalvariance Correlation circle
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
Conclusion • 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) Metabolomic study represents an good way of generating experimental data for metabolic modeling in integrative biology Transfer to in vivo studies using Magnetic Resonance Imaging (MRI)
INRA Anne Fages Daniel Morvan Pascale Rio Georges Stepien MNR/MS Team Guy Bielicki Jean Pierre Renou Estelle Pujos Hospital Team Armand Abergel Emmanuel Buc Denis Pezet