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Tissue metabolites in diffuse glioma and their modulations by IDH1 mutation, histology, and treatment
Christoph Trautwein, Laimdota Zizmare, Irina Mäurer, Benjamin Bender, Björn Bayer, Ulrike Ernemann, Marcos Tatagiba, Stefan J. Grau, Bernd J. Pichler, Marco Skardelly, Ghazaleh Tabatabai
Christoph Trautwein, Laimdota Zizmare, Irina Mäurer, Benjamin Bender, Björn Bayer, Ulrike Ernemann, Marcos Tatagiba, Stefan J. Grau, Bernd J. Pichler, Marco Skardelly, Ghazaleh Tabatabai
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Resource and Technical Advance Oncology

Tissue metabolites in diffuse glioma and their modulations by IDH1 mutation, histology, and treatment

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Abstract

The discovery of the oncometabolite 2-hydroxyglutarate in isocitrate dehydrogenase 1–mutated (IDH1-mutated) tumor entities affirmed the role of metabolism in cancer. However, large databases with tissue metabolites that are modulated by IDH1 mutation remain an area of development. Here, we present an unprecedented and valuable resource for tissue metabolites in diffuse glioma and their modulations by IDH1 mutation, histology, and tumor treatments in 101 tissue samples from 73 diffuse glioma patients (24 astrocytoma, 17 oligodendroglioma, 32 glioblastoma), investigated by NMR-based metabolomics and supported by RNA-Seq. We discovered comparison-specific metabolites and pathways modulated by IDH1 (IDH1 mutation status cohort) and tumor entity. The Longitudinal investigation cohort provides metabolic profiles of untreated and corresponding treated glioma samples at first progression. Most interestingly, univariate and multivariate cox regressions and Kaplan-Meier analyses revealed that tissue metabolites correlate with progression-free and overall survival. Thus, this study introduces potentially novel candidate prognostic and surrogate metabolite biomarkers for future prospective clinical studies, aiming at further refining patient stratification in diffuse glioma. Furthermore, our data will facilitate the generation of so-far–unanticipated hypotheses for experimental studies to advance our molecular understanding of glioma biology.

Authors

Christoph Trautwein, Laimdota Zizmare, Irina Mäurer, Benjamin Bender, Björn Bayer, Ulrike Ernemann, Marcos Tatagiba, Stefan J. Grau, Bernd J. Pichler, Marco Skardelly, Ghazaleh Tabatabai

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Figure 7

Longitudinal investigation cohort comparisons VIII and IX.

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Longitudinal investigation cohort comparisons VIII and IX.
(A) Multivari...
(A) Multivariate principal component analysis (PCA) of untreated (n = 8) patients (comparison VIII) shows no general separation of samples from first (T0) and second (T1) surgery time point. (B) The partial least squares–discriminant analysis (PLS-DA) identifies 11 metabolites (on top of dashed blue line) with variable importance in projection (VIP) scores > 1 that contribute significantly to the PLS-DA model (blue box, low metabolite concentration in the respective group; red, high concentration). (C) By contrast, PCA of treated (n = 7) astrocytoma (RCT Astro) patients (comparison IX) shows 5 samples (samples 4218, 3071, 1774, 2581, T04) outside the main cluster. From those, we identified 4 sample pairs with specific metabolite changes between T0 and T1; while patient 3071/4218 showed decreased hypotaurine levels and higher OS (73 months) and PFS (66 months), patient 1534/1774 showed the opposite, with an increase in hypotaurine and a very short OS (18 months) and PFS (14 months). The patient sample pairs 2252/2581 (OS 18 months, PFS 16 months) and patient T03/T04 (OS > 72 months, PFS 10 months) showed a strong increase in glucose with decreased lactate. However, a reduced OS in patient 2252/2581 was additionally associated with increased glycine levels between the 2 resections. (D) The PLS-DA identified 12 further metabolites (on top of dashed blue line) with variable importance in projection (VIP) scores > 1 that contribute significantly to the PLS-DA model. m, months.

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