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The three glioma rat models C6, F98 and RG2 exhibit different metabolic profiles: in vivo 1H MRS and ex vivo 1H HRMAS combined with multivariate statistics

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Abstract

Glioblastomas are the most malignant subtypes of glioma and many efforts are currently made to improve their characterization though molecular, microvascular, immunogenic and metabolomic approaches. The variability within pre-clinical tumor models may mimic glioma heterogeneity and force the development of innovative analytical methodologies. In this study, we investigate the metabolic variability within three rat models of glioma: C6, RG2 and F98, using in vivo magnetic resonance spectroscopy (1H MRS) and ex vivo high resolution magic angle spinning (1H HRMAS MRS). We used a multivariate statistic approach with orthogonal projection to latent structure-discriminant analysis (OPLS-DA) that was compared with univariate statistic. OPLS-DA reveals a clear separation between C6, RG2 and F98 tumors and, with the help of shared and unique structure plot (SUS-Plot), promotes a comprehensive view of their metabolic differences. Both in vivo and ex vivo analyses are similar but ex vivo 1H HRMAS MRS provides more robust results. In conclusion, MRS-based OPLS-DA appears sensitive enough to correctly predict the classification of tumors and to investigate the relationship between the host brain metabolism and the grafted tumor.

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Abbreviations

Ace:

Acetate

Ala:

Alanine

Asp:

Aspartate

Bet:

Betaine

Cho:

Choline

GABA:

Gamma-amino-butyric acid

Gln:

Glutamine

Glu:

Glutamate

Gly:

Glycine

GPC:

Glycerophosphocholine

Gsh:

Glutathione

Hyp:

Hypotaurine

Lac:

Lactate

M-ins:

Myo-inositol

NAA:

N-acetylaspartate

PC:

Phosphocholine

tCr:

Total creatine (phosphocreatine and creatine)

PE:

Phosphoethanolamine

S-Ins:

Scyllo-inositol

Tau:

Taurine

MM:

Macromolecules

MRS:

Magnetic resonance spectroscopy

HRMAS:

High resolution magic angle spinning

jMRUI:

Java based version of the Magnetic Resonance User Interface

OPLS-DA:

Orthogonal projection to latent structure-discriminant analysis

PCA:

Principal component analysis

SUS-plot:

Shared and unique structure plot

GBM:

Glioblastomas

PRESS:

Point RESolved spectroscopy

CPMG:

Carr-Purcell-Meiboom-Gill CPMG

CRLB:

Cramer Rao lower bounds

FID:

Free induced decay

NMR:

Nuclear magnetic resonance

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Acknowledgments

We thank the animal care facility of GIN.

Funding

This study was funded by the French Service de Santé des Armées, the Fondation ARC (“Association pour la Recherche sur le Cancer”) and ANR (“Agence Nationale pour la Recherche”) Imoxy grant. IRMaGe was partly funded by the French program “Investissement d’Avenir” run by the “Agence Nationale pour la Recherche”; grant “Infrastructure d’avenir en Biologie Santé”—ANR-11-INBS-0006.

Author information

Authors and Affiliations

  1. Inserm, U836, 38000, Grenoble, France

    Nicolas Coquery, Emmanuel L. Barbier & Chantal Rémy

  2. Univ Grenoble Alpes, Grenoble Institut des Neurosciences, 38000, Grenoble, France

    Nicolas Coquery, Emmanuel L. Barbier & Chantal Rémy

  3. Univ Grenoble Alpes, IRMaGe, 38000, Grenoble, France

    Vasile Stupar, Régine Farion & Florence Fauvelle

  4. CNRS, UMS 3552, 38000, Grenoble, France

    Vasile Stupar, Régine Farion & Florence Fauvelle

  5. Inserm, US17, 38000, Grenoble, France

    Vasile Stupar, Régine Farion & Florence Fauvelle

  6. IRBA, Brétigny Sur Orge, France

    Severine Maunoir-Regimbal & Florence Fauvelle

  7. U836 – Grenoble Institut des Neurosciences, Chemin Fortuné Ferrini, BP 217 – CHU Grenoble, 38043, Grenoble Cedex, France

    Florence Fauvelle

Authors
  1. Nicolas Coquery
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  2. Vasile Stupar
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  3. Régine Farion
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  4. Severine Maunoir-Regimbal
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  5. Emmanuel L. Barbier
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  6. Chantal Rémy
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  7. Florence Fauvelle
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Corresponding author

Correspondence to Florence Fauvelle.

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Conflict of interest

All authors declare that they have no conflict of interest.

Ethical approval

The study design was approved by the local ethical committee for animal care and use (C2EA-04: “Comité d’éthique en expérimentation animale GIN”). Experiments were performed under permits (No. 38 12 63 and B 38 516 10 008 for experimental and animal care facilities) from the French Ministry of Agriculture.

Electronic supplementary material

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Supplementary material 1 (TIFF 1409 kb)

Supplementary Table 1. Metabolite assignment

Supplementary material 2 (TIFF 2445 kb)

Supplementary Table 2. Details of statistical values presented in Table 1

Supplementary material 3 (TIFF 996 kb)

Supplementary Table 3. OPLS-DA models built with quantified 1H MRS data (in vivo) or 1H HRMAS MRS data (ex vivo) as x variables and tumor types as classes (C6, F98 and RG2). Cumulative values of R2X, R2Y and Q2 are given

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Coquery, N., Stupar, V., Farion, R. et al. The three glioma rat models C6, F98 and RG2 exhibit different metabolic profiles: in vivo 1H MRS and ex vivo 1H HRMAS combined with multivariate statistics. Metabolomics 11, 1834–1847 (2015). https://doi.org/10.1007/s11306-015-0835-2

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  • DOI: https://doi.org/10.1007/s11306-015-0835-2

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