Myo-inositol concentration in MR spectroscopy for differentiating high grade glioma from primary central nervous system lymphoma

Nagashima, Hiroaki; Sasayama, Takashi; Tanaka, Kazuhiro; Kyotani, Katsusuke; Sato, Naoko; Maeyama, Masao; Kohta, Masaaki; Sakata, Junichi; Yamamoto, Yusuke; Hosoda, Kohkichi; Itoh, Tomoo; Sasaki, Ryohei; Kohmura, Eiji

doi:10.1007/s11060-017-2655-x

Cited by 30 publications

(30 citation statements)

References 38 publications

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“…This observation is consistent with an in vitro study showing a twenty percent increase in myo-Inositol level in IDH2 compared to IDH1 [25]. A recent in vivo survey supports this by demonstrating a link between myo-Inositol concentration and hypermethylation in the expression of inositol 3-phosphate synthase (ISYNA1) in brain tumors [26]. Another recent study of T-cell lymphoma has also reported significantly increased hypermethylation in ISYNA1 for IDH2 mutant samples [27].…”

Section: Discussionsupporting

confidence: 87%

A Noninvasive Comparison Study between Human Gliomas with IDH1 and IDH2 Mutations by MR Spectroscopy

Shen¹,

Voets²,

Larkin³

et al. 2018

Preprint

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The oncogenes that are expressed in gliomas reprogram particular pathways of glucose, amino acid, and fatty acid metabolism. Mutations in isocitrate dehydrogenase genes (IDH1/2) in diffuse gliomas are associated with abnormally high levels of 2-hydroxyglutarate (2-HG) levels. The aim of this study was to determine whether metabolic reprogramming associated with IDH mutant gliomas leads to additional 1H MRS-detectable differences between IDH1 and IDH2 mutations and to identify metabolites correlated with 2-HG. A total of 21 glioma patients (age= 3711, 13 males) were recruited for MRS using a Semi-localization by adiabatic selective refocusing pulse sequence at ultra-high-field (7T). Tumour mutation subtype was confirmed by immunohistochemistry and DNA sequencing. LCModel analysis was applied for metabolite quantification. A two-sample t-test was used for metabolite comparisons between IDH1 (n=15) and IDH2 (n=5) mutant gliomas. The Pearson correlation coefficients between 2-HG and associated metabolites were calculated. A Bonferroni correction was applied for multiple comparison. IDH2 mutant gliomas have a higher level of 2-HG/tCho (total choline=phosphocholine+glycerylphosphorylcholine) (2.481.01vs.0.720.38, Pc<0.001) and myo-Inositol/tCho (2.700.90vs.1.460.51, Pc=0.011) compared to IDH1 mutation gliomas. Associated metabolites, myo-Inositol and glucose+taurine were correlated with 2-HG levels. These results show improved characterization of the metabolic pathways in IDH1 and IDH2 gliomas for precision medicine.

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Section: Discussionsupporting

confidence: 87%

A Noninvasive Comparison Study between Human Gliomas with IDH1 and IDH2 Mutations by MR Spectroscopy

Shen¹,

Voets²,

Larkin³

et al. 2018

Preprint

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“…A high M-ins level in 1 H-MRS is relevant to distinguish glioma from other brain tumors, for example, primary central nervous system lymphomas [41]. Furthermore, IDH mutation seems to be a relevant factor for M-ins concentration.…”

Section: Discussionmentioning

confidence: 99%

Non-Invasive Prediction of IDH Mutation in Patients with Glioma WHO II/III/IV Based on F-18-FET PET-Guided In Vivo 1H-Magnetic Resonance Spectroscopy and Machine Learning

Bumes

Wirtz

Fellner

et al. 2020

Cancers

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Isocitrate dehydrogenase (IDH)-1 mutation is an important prognostic factor and a potential therapeutic target in glioma. Immunohistological and molecular diagnosis of IDH mutation status is invasive. To avoid tumor biopsy, dedicated spectroscopic techniques have been proposed to detect D-2-hydroxyglutarate (2-HG), the main metabolite of IDH, directly in vivo. However, these methods are technically challenging and not broadly available. Therefore, we explored the use of machine learning for the non-invasive, inexpensive and fast diagnosis of IDH status in standard 1H-magnetic resonance spectroscopy (1H-MRS). To this end, 30 of 34 consecutive patients with known or suspected glioma WHO grade II-IV were subjected to metabolic positron emission tomography (PET) imaging with O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET) for optimized voxel placement in 1H-MRS. Routine 1H-magnetic resonance (1H-MR) spectra of tumor and contralateral healthy brain regions were acquired on a 3 Tesla magnetic resonance (3T-MR) scanner, prior to surgical tumor resection and molecular analysis of IDH status. Since 2-HG spectral signals were too overlapped for reliable discrimination of IDH mutated (IDHmut) and IDH wild-type (IDHwt) glioma, we used a nested cross-validation approach, whereby we trained a linear support vector machine (SVM) on the complete spectral information of the 1H-MRS data to predict IDH status. Using this approach, we predicted IDH status with an accuracy of 88.2%, a sensitivity of 95.5% (95% CI, 77.2–99.9%) and a specificity of 75.0% (95% CI, 42.9–94.5%), respectively. The area under the curve (AUC) amounted to 0.83. Subsequent ex vivo 1H-nuclear magnetic resonance (1H-NMR) measurements performed on metabolite extracts of resected tumor material (eight specimens) revealed myo-inositol (M-ins) and glycine (Gly) to be the major discriminators of IDH status. We conclude that our approach allows a reliable, non-invasive, fast and cost-effective prediction of IDH status in a standard clinical setting.

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“…At the moment, using NMRS is possible to quantify the abundance of the glutamate and glutamine pool defined as Glx and it has been observed an increase in Glx in high grade glioma or in invasive regions [281,282]. In other studies, authors have investigated the relationship between the presence of the IDH mutation and the presence of Glx and they found an inverse correlation between the presence of the oncometabolite 2-hydroxglutarate (2HG) and a significant decrease of Glx [283,284].…”

Section: On This Basis 2-deoxy-2-[fluorine-18]fluoro-d-glucose ([ 18mentioning

confidence: 99%

Molecular and Cellular Complexity of Glioma. Focus on Tumour Microenvironment and the Use of Molecular and Imaging Biomarkers to Overcome Treatment Resistance

Valtorta

Salvatore

Rainone

et al. 2020

IJMS

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This review highlights the importance and the complexity of tumour biology and microenvironment in the progression and therapy resistance of glioma. Specific gene mutations, the possible functions of several non-coding microRNAs and the intra-tumour and inter-tumour heterogeneity of cell types contribute to limit the efficacy of the actual therapeutic options. In this scenario, identification of molecular biomarkers of response and the use of multimodal in vivo imaging and in particular the Positron Emission Tomography (PET) based molecular approach, can help identifying glioma features and the modifications occurring during therapy at a regional level. Indeed, a better understanding of tumor heterogeneity and the development of diagnostic procedures can favor the identification of a cluster of patients for personalized medicine in order to improve the survival and their quality of life.

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Myo-inositol concentration in MR spectroscopy for differentiating high grade glioma from primary central nervous system lymphoma

Cited by 30 publications

References 38 publications

A Noninvasive Comparison Study between Human Gliomas with IDH1 and IDH2 Mutations by MR Spectroscopy

A Noninvasive Comparison Study between Human Gliomas with IDH1 and IDH2 Mutations by MR Spectroscopy

Non-Invasive Prediction of IDH Mutation in Patients with Glioma WHO II/III/IV Based on F-18-FET PET-Guided In Vivo 1H-Magnetic Resonance Spectroscopy and Machine Learning

Molecular and Cellular Complexity of Glioma. Focus on Tumour Microenvironment and the Use of Molecular and Imaging Biomarkers to Overcome Treatment Resistance

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