Métabolomique : application à la recherche de transfert dans le cancer. Olivier Trédan, Elodie Jobard, Bénédicte Elena

Transcription

1 Métabolomique : application à la recherche de transfert dans le cancer Olivier Trédan, Elodie Jobard, Bénédicte Elena

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3 Preuve du concept En projetant en aveugle le set de données spectrales : sensibilité : 9 % spécificité : 8 % E. Jobard, et al. Cancer Lett. 213

4 Preuve du concept Mise en évidence de métabolites liées à la consommation énergétique : 9 validés dans les 2 cohortes 5 métabolites non définis E. Jobard, et al. Cancer Lett. 213

5 Application pharmacodynamique?

6 Application pharmacodynamique?

7 RADHER metabolomic study Evaluate the contribution of adding Everolimus to treatment with Trastuzumab in patients with non-metastatic breast cancer overexpressing HER-2 and accessible to surgery 75 women patients with HER-2 positive breast cancer A series of serum samples were collected under fasting conditions : 247 serum samples Trastuzumab drip (every week / 6 cures) Arm A Trastuzumab drip + Everolimus (2 pills daily / 6 weeks) Arm B T REAT M EN T SU RGERY Week (W) Week 2 (W2) Week 4 (W4) Week 8 (W8) 2 Quality Controls serum samples (to evaluate NMR reproducibility) NMR analysis conducted at 8 MHz 5 identified metabolites (with 1D & 2D) H Chemical Shift (ppm) 5 Citrate Citrate Glutamine Succinate, 3-hydroxybutyrate Glutamate, Proline 3-hydroxybutyrate Acetone, FAs Methionine Glutamate, Glutamine Glutamate, Glutamine, Proline Proline, FAs Lysine Acetate FAs, Lysine, Leucine FAs (mainly VLDL) Lysine Ethanol 3-hydroxybutyrate Isoleucine Isoleucine Alanine Valine FAs, Leucine NAC 2 NAC 1 Lactate FAs (mainly LDL) b-galactose Lactose Glycerophosphocholine 3-hydroxybutyrate Proline Lactate Choline, Glyceryl of lipids Creatinine Histidine, Phenylalanine Creatine Valine Methanol Proline Myo-inositol Betaine Lysine Creatine Creatinine Albumin lysyl FAs Aspartate Glycerophosphocholine Glycine Glycerol Choline Glycerophosphocholine FAs, FAs (mainly LDL & VLDL) FAs (mainly VLDL) Formate Histidine Phenylalanine Tyrosine Histidine Tyrosine Urea FAs Glyceryol backbone of PGLYs & TAGs Mannose H Chemical Shift (ppm) Overview of 1 H NMR CPMG mean spectrum for HER-2 positive breast cancer

8 Discrimination between pre- & on-treatment serum samples Treatment A Treatment B W W2 R 2 Y =.51 Q 2 =.759 W W2 R 2 Y =.73 Q 2 =.452 W vs W Significative & validated discrimination.4 No significant discrimination n = n = 66 W vs W4 W W4 R 2 Y =.334 Q 2 = Significative & validated discrimination W W4 R 2 Y =.63 Q 2 = No significant discrimination n = n = 65 No significant separation between pre- & after-treatment samples, on-treatment samples, on- & after-treatment samples for both treatments Discrimination only for Treatment B between pre- & on-treatment samples It is associated to the presence of the Trastuzumab + Everolimus combination W: Week W2: Week 2 W4: Week 4 W8: Week 8

9 A metabolic signature associated with the use of targeted therapies Metabolic signature are identified only for Treatment B between pre- & on-treatment samples Absence of metabolic signature for treatment A is coherent with the nature and the action mechanism of Trastuzumab Metabolic signature are associated with administration of targeted therapy and more precisely of the combination of trastuzumab & everolimus Presumably the metabolic pattern results to the presence of everolimus in the treatment B

10 Comparison of the metabolic serum changes between therapies Treatment A vs Treatment B No significant separation at W and W8 between both treatments Discrimination between the two groups only during treatment ( at W2 and at W4) As the two arms contain Trastuzumab, one can hypothesize that the metabolic pattern characterizes the presence of everolimus a mtor inhibitor in the treatment B

11 Evaluate the effectiveness and safety of Bevacizumab and Temsirolimus in first-line treatment for mrcc compared with two other standard therapies 121 patients with metastatic renal cell carcinoma TORAVA metabolomic study A series of serum samples were collected without fasting conditions : 35 serum samples Arm A : Intraveinous Temsirolimus (25 mg weekly) Intraveinous Bevacizumab (1 mg/kg every 2 weeks) Arm B : Oral Sunitinib (5 mg/day for 4 weeks) OFF Arm C : Intraveinous Bevacizumab (1 mg/kg every 2 weeks) Subcateneous Interferon (9mlU 3 times per week)... NMR Analysis Week (W) Week 2 (W2) Blood sample Week 5 or 6 (W5-6) NMR analysis conducted at 8 MHz 49 identified metabolites (with 1D & 2D) H Chemical shift (ppm) Overview of 1 H NMR NOESY spectrum of TORAVA serum samples

12 Longitudinal discrimination of serum metabolic profiles 1 W W vs. W2 W vs. W5-6 W2 R 2 Y =.581 Q 2 =.376 W W5-6 R 2 Y =.65 Q 2 = W: Week W2: Week 2 W5-6: Week n = 111 n = 15 R 2 Y Q W W2 R 2 Y =.147 Q 2 = W W5-6 R 2 Y =.149 Q 2 = R 2 Y and Q Correlation coefficient between original and permuted Y matrix n = 48.4 n = W W2 R 2 Y =.124 Q 2 =.55 W W5-6 R 2 Y =.319 Q 2 = Correlation coefficient between original and permuted Y matrix Correlation 1 coefficient between original and permuted Y matrix -1 A clear & validated discrimination between W & W2 and W & W n = 55 n = Treatment A Bevacizumab + Temsirolimus 1 R 2 Y Q 2 1 R 2 Y Q No significant separation.4 Treatment B.4 R 2 Y and Q 2 between W & W2 Significative separation 96 between W & W5-6 No significant discrimination between W & W2 and W & W5-6 R 2 Y and Q 2 Sunitinib Treatment C Bevacizumab + Interferon-α Discrimination only between pre- and on-treatment serum samples for treatments A&C Treatment A drove changes quicker

13 Metabolic signatures associated with the use of targeted therapies Metabolic signatures for arm A & C are quite similar and mainly due to alterations of lipid and carbohydrate metabolism No metabolic side effects with bevacizumab while temsirolimus induces hyperglycemia & hyperlipidemia Metabolic signature for arm A seems to mainly reflects the effect of the inhibition of mtor by temsirolimus treatment Metabolites identified for arm C are consistent with side effect of interferon-α (hypertriglyceridemia)

14 Comparison of the metabolic changes between 3 therapies Temsirolimus & Bevacizumab vs. Interferon-α & W5-6 A B R 2 Y =.355 Q 2 = n = 69 Significant & validated discrimination A significant discrimination is only observed between arm A & B after several weeks of treatment These 2 therapies are very different regarding the type of molecules used and their action mechanisms The observed metabolic fingerprint here is mainly due to the presence of temsirolimus in the arm A No significant separation between arm A & C, not due to the common presence of bevacizumab but rather to respective presence of temsirolimus & interferon-α that produce similar side effects

15 Identification of the metabolic pathways associated with targeted therapies Using various analysis and visualisation of metabolic pathways tools (MetPA, ipath, Metexplore) 4 metabolic pathways are highlighted by MetPA analysis Metabolite signature - concentrated at W2/W Synthesis and degradation of ketone bodies + concentrated at W2/W Significative metabolite - concentrated at W2/W + concentrated at W2/W Global vizualisation of metabolic pathways involved - using ipath Correlating these different information with what is known in the literature on the mtor inhibition

16 Acknoledgments Elodie Jobard Sylvie Négrier Ellen Blanc Thomas Bachelot Bernard Escudier Gwenaëlle Gravis Christine Chevreau Mario Campone Bénédicte Elena-Herrmann