Myoinositol as a Biomarker in Recurrent Glioblastoma Treated with Bevacizumab: A 1H-Magnetic Resonance Spectroscopy Study

PPAR-γ agonists reactivate the ALDOC-NR2F1 axis to enhance sensitivity to temozolomide and suppress glioblastoma progression

Glioblastoma (GBM) is a type of brain cancer categorized as a high-grade glioma. GBM is characterized by limited treatment options, low patient survival rates, and abnormal serotonin metabolism. Previous studies have investigated the tumor suppressor function of aldolase C (ALDOC), a glycolytic enzyme in GBM. However, it is unclear how ALDOC regulates production of serotonin and its associated receptors, HTRs. In this study, we analyzed ALDOC mRNA levels and methylation status using sequencing data and in silico datasets. Furthermore, we investigated pathways, phenotypes, and drug effects using cell and mouse models. Our results suggest that loss of ALDOC function in GBM promotes tumor cell invasion and migration. We observed that hypermethylation, which results in loss of ALDOC expression, is associated with serotonin hypersecretion and the inhibition of PPAR-γ signaling. Using several omics datasets, we present evidence that ALDOC regulates serotonin levels and safeguards PPAR-γ against serotonin metabolism mediated by 5-HT, which leads to a reduction in PPAR-γ expression. PPAR-γ activation inhibits serotonin release by HTR and diminishes GBM tumor growth in our cellular and animal models. Importantly, research has demonstrated that PPAR-γ agonists prolong animal survival rates and increase the efficacy of temozolomide in an orthotopic brain model of GBM. The relationship and function of the ALDOC-PPAR-γ axis could serve as a potential prognostic indicator. Furthermore, PPAR-γ agonists offer a new treatment alternative for glioblastoma multiforme (GBM).

Integrative Magnetic Resonance Imaging and Metabolomic Characterization of a Glioblastoma Rat Model

Glioblastoma (GBM) stands as the most prevalent and lethal malignant brain tumor, characterized by its highly infiltrative nature. This study aimed to identify additional MRI and metabolomic biomarkers of GBM and its impact on healthy tissue using an advanced-stage C6 glioma rat model. Wistar rats underwent a stereotactic injection of C6 cells (GBM group, n = 10) or cell medium (sham group, n = 4). A multiparametric MRI, including anatomical T2W and T1W images, relaxometry maps (T2, T2*, and T1), the magnetization transfer ratio (MTR), and diffusion tensor imaging (DTI), was performed. Additionally, ex vivo magnetic resonance spectroscopy (MRS) HRMAS spectra were acquired. The MRI analysis revealed significant differences in the T2 maps, T1 maps, MTR, and mean diffusivity parameters between the GBM tumor and the rest of the studied regions, which were the contralateral areas of the GBM rats and both regions of the sham rats (the ipsilateral and contralateral). The ex vivo spectra revealed markers of neuronal loss, apoptosis, and higher glucose uptake by the tumor. Notably, the myo-inositol and phosphocholine levels were elevated in both the tumor and the contralateral regions of the GBM rats compared to the sham rats, suggesting the effects of the tumor on the healthy tissue. The MRI parameters related to inflammation, cellularity, and tissue integrity, along with MRS-detected metabolites, serve as potential biomarkers for the tumor evolution, treatment response, and impact on healthy tissue. These techniques can be potent tools for evaluating new drugs and treatment targets.

Advances in Neuro-Oncological Imaging: An Update on Diagnostic Approach to Brain Tumors

This study delineates the pivotal role of imaging within the field of neurology, emphasizing its significance in the diagnosis, prognostication, and evaluation of treatment responses for central nervous system (CNS) tumors. A comprehensive understanding of both the capabilities and limitations inherent in emerging imaging technologies is imperative for delivering a heightened level of personalized care to individuals with neuro-oncological conditions. Ongoing research in neuro-oncological imaging endeavors to rectify some limitations of radiological modalities, aiming to augment accuracy and efficacy in the management of brain tumors. This review is dedicated to the comparison and critical examination of the latest advancements in diverse imaging modalities employed in neuro-oncology. The objective is to investigate their respective impacts on diagnosis, cancer staging, prognosis, and post-treatment monitoring. By providing a comprehensive analysis of these modalities, this review aims to contribute to the collective knowledge in the field, fostering an informed approach to neuro-oncological care. In conclusion, the outlook for neuro-oncological imaging appears promising, and sustained exploration in this domain is anticipated to yield further breakthroughs, ultimately enhancing outcomes for individuals grappling with CNS tumors.

Tracking Therapy Response in Glioblastoma Using 1D Convolutional Neural Networks

BACKGROUND

Glioblastoma (GB) is a malignant brain tumour that is challenging to treat, often relapsing even after aggressive therapy. Evaluating therapy response relies on magnetic resonance imaging (MRI) following the Response Assessment in Neuro-Oncology (RANO) criteria. However, early assessment is hindered by phenomena such as pseudoprogression and pseudoresponse. Magnetic resonance spectroscopy (MRS/MRSI) provides metabolomics information but is underutilised due to a lack of familiarity and standardisation.

METHODS

This study explores the potential of spectroscopic imaging (MRSI) in combination with several machine learning approaches, including one-dimensional convolutional neural networks (1D-CNNs), to improve therapy response assessment. Preclinical GB (GL261-bearing mice) were studied for method optimisation and validation.

RESULTS

The proposed 1D-CNN models successfully identify different regions of tumours sampled by MRSI, i.e., normal brain (N), control/unresponsive tumour (T), and tumour responding to treatment (R). Class activation maps using Grad-CAM enabled the study of the key areas relevant to the models, providing model explainability. The generated colour-coded maps showing the N, T and R regions were highly accurate (according to Dice scores) when compared against ground truth and outperformed our previous method.

CONCLUSIONS

The proposed methodology may provide new and better opportunities for therapy response assessment, potentially providing earlier hints of tumour relapsing stages.

Dysregulated lipid metabolism in TMZ-resistant glioblastoma: pathways, proteins, metabolites and therapeutic opportunities

Glioblastoma (GBM) is a highly aggressive and lethal brain tumor with limited treatment options, such as the chemotherapeutic agent, temozolomide (TMZ). However, many GBM tumors develop resistance to TMZ, which is a major obstacle to effective therapy. Recently, dysregulated lipid metabolism has emerged as an important factor contributing to TMZ resistance in GBM. The dysregulation of lipid metabolism is a hallmark of cancer and alterations in lipid metabolism have been linked to multiple aspects of tumor biology, including proliferation, migration, and resistance to therapy. In this review, we aimed to summarize current knowledge on lipid metabolism in TMZ-resistant GBM, including key metabolites and proteins involved in lipid synthesis, uptake, and utilization, and recent advances in the application of metabolomics to study lipid metabolism in GBM. We also discussed the potential of lipid metabolism as a target for novel therapeutic interventions. Finally, we highlighted the challenges and opportunities associated with developing these interventions for clinical use, and the need for further research to fully understand the role of lipid metabolism in TMZ resistance in GBM. Our review suggests that targeting dysregulated lipid metabolism may be a promising approach to overcome TMZ resistance and improve outcomes in patients with GBM.

Glucose and Inositol Transporters, SLC5A1 and SLC5A3, in Glioblastoma Cell Migration

(1) Background: The recurrence of glioblastoma multiforme (GBM) is mainly due to invasion of the surrounding brain tissue, where organic solutes, including glucose and inositol, are abundant. Invasive cell migration has been linked to the aberrant expression of transmembrane solute-linked carriers (SLC). Here, we explore the role of glucose (SLC5A1) and inositol transporters (SLC5A3) in GBM cell migration. (2) Methods: Using immunofluorescence microscopy, we visualized the subcellular localization of SLC5A1 and SLC5A3 in two highly motile human GBM cell lines. We also employed wound-healing assays to examine the effect of SLC inhibition on GBM cell migration and examined the chemotactic potential of inositol. (3) Results: While GBM cell migration was significantly increased by extracellular inositol and glucose, it was strongly impaired by SLC transporter inhibition. In the GBM cell monolayers, both SLCs were exclusively detected in the migrating cells at the monolayer edge. In single GBM cells, both transporters were primarily localized at the leading edge of the lamellipodium. Interestingly, in GBM cells migrating via blebbing, SLC5A1 and SLC5A3 were predominantly detected in nascent and mature blebs, respectively. (4) Conclusion: We provide several lines of evidence for the involvement of SLC5A1 and SLC5A3 in GBM cell migration, thereby complementing the migration-associated transportome. Our findings suggest that SLC inhibition is a promising approach to GBM treatment.

Conventional and Advanced Imaging Techniques in Post-treatment Glioma Imaging

Despite decades of advancement in the diagnosis and therapy of gliomas, the most malignant primary brain tumors, the overall survival rate is still dismal, and their post-treatment imaging appearance remains very challenging to interpret. Since the limitations of conventional magnetic resonance imaging (MRI) in the distinction between recurrence and treatment effect have been recognized, a variety of advanced MR and functional imaging techniques including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), perfusion-weighted imaging (PWI), MR spectroscopy (MRS), as well as a variety of radiotracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) have been investigated for this indication along with voxel-based and more quantitative analytical methods in recent years. Machine learning and radiomics approaches in recent years have shown promise in distinguishing between recurrence and treatment effect as well as improving prognostication in a malignancy with a very short life expectancy. This review provides a comprehensive overview of the conventional and advanced imaging techniques with the potential to differentiate recurrence from treatment effect and includes updates in the state-of-the-art in advanced imaging with a brief overview of emerging experimental techniques. A series of representative cases are provided to illustrate the synthesis of conventional and advanced imaging with the clinical context which informs the radiologic evaluation of gliomas in the post-treatment setting.

Congress of Neurological Surgeons systematic review and evidence-based guidelines update on the role of imaging in the management of progressive glioblastoma in adults

TARGET POPULATION

These recommendations apply to adults with glioblastoma who have been previously treated with first-line radiation or chemoradiotherapy and who are suspected of experiencing tumor progression.

QUESTION

In patients with previously treated glioblastoma, is standard contrast-enhanced magnetic resonance imaging including diffusion weighted imaging useful for diagnosing tumor progression and differentiating progression from treatment-related changes?

LEVEL II

Magnetic resonance imaging with and without gadolinium enhancement including diffusion weighted imaging is recommended as the imaging surveillance method to detect the progression of previously diagnosed glioblastoma.

QUESTION

In patients with previously treated glioblastoma, does magnetic resonance spectroscopy add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement?

LEVEL II

Magnetic resonance spectroscopy is recommended as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma.

QUESTION

In patients with previously treated glioblastoma, does magnetic resonance perfusion add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement?

LEVEL III

Magnetic resonance perfusion is suggested as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma.

QUESTION

In patients with previously treated glioblastoma, does the addition of single-photon emission computed tomography (SPECT) provide additional useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement?

LEVEL III

Single-photon emission computed tomography imaging is suggested as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma.

QUESTION

In patients with previously treated glioblastoma, does 18F-fluorodeoxyglucose positron emission tomography add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement?

LEVEL III

The routine use of 18F-fluorodeoxyglucose positron emission tomography to identify progression of glioblastoma is not recommended.

QUESTION

In patients with previously treated glioblastoma, does positron emission tomography with amino acid agents add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement?

LEVEL III

It is suggested that amino acid positron emission tomography be considered to assist in the differentiation of progressive glioblastoma from treatment related changes.

Magnetic resonance spectroscopy outperforms perfusion in distinguishing between pseudoprogression and disease progression in patients with glioblastoma

Background

There is a need to establish biomarkers that distinguish between pseudoprogression (PsP) and true tumor progression in patients with glioblastoma (GBM) treated with chemoradiation.

Methods

We analyzed magnetic resonance spectroscopic imaging (MRSI) and dynamic susceptibility contrast (DSC) MR perfusion data in patients with GBM with PsP or disease progression after chemoradiation. MRSI metabolites of interest included intratumoral choline (Cho), myo-inositol (mI), glutamate + glutamine (Glx), lactate (Lac), and creatine on the contralateral hemisphere (c-Cr). Student T-tests and area under the ROC curve analyses were used to detect group differences in metabolic ratios and their ability to predict clinical status, respectively.

Results

28 subjects (63 ± 9 years, 19 men) were evaluated. Subjects with true progression (n = 20) had decreased enhancing region mI/c-Cr (P = .011), a marker for more aggressive tumors, compared to those with PsP, which predicted tumor progression (AUC: 0.84 [0.76, 0.92]). Those with true progression had elevated Lac/Glx (P = .0009), a proxy of the Warburg effect, compared to those with PsP which predicted tumor progression (AUC: 0.84 [0.75, 0.92]). Cho/c-Cr did not distinguish between PsP and true tumor progression. Despite rCBV (AUC: 0.70 [0.60, 0.80]) and rCBF (AUC: 0.75 [0.65, 0.84]) being individually predictive of tumor response, they added no additional predictive value when combined with MRSI metabolic markers.

Conclusions

Incorporating enhancing lesion MRSI measures of mI/c-Cr and Lac/Glx into brain tumor imaging protocols can distinguish between PsP and true progression and inform patient management decisions.

Magnetic resonance spectroscopic imaging for detecting metabolic changes in glioblastoma after anti-angiogenic therapy—a systematic literature review

Background

The impact of anti-angiogenic therapy (AAT) on patients with glioblastoma (GBM) is unclear due to a disconnect between radiographic findings and overall survivorship. MR spectroscopy (MRS) can provide clinically relevant information regarding tumor metabolism in response to AAT. This review explores the use of MRS to track metabolic changes in patients with GBM treated with AAT.

Methods

We conducted a systematic literature review in accordance with PRISMA guidelines to identify primary research articles that reported metabolic changes in GBMs treated with AAT. Collected variables included single or multi-voxel MRS acquisition parameters, metabolic markers, reported metabolic changes in response to AAT, and survivorship data.

Results

Thirty-five articles were retrieved in the initial query. After applying inclusion and exclusion criteria, 11 studies with 262 patients were included for qualitative synthesis with all studies performed using multi-voxel 1H MRS. Two studies utilized 31P MRS. Post-AAT initiation, shorter-term survivors had increased choline (cellular proliferation marker), increased lactate (a hypoxia marker), and decreased levels of the short echo time (TE) marker, myo-inositol (an osmoregulator and gliosis marker). MRS detected metabolic changes as soon as 1-day after AAT, and throughout the course of AAT, to predict survival. There was substantial heterogeneity in the timing of scans, which ranged from 1-day to 6–9 months after AAT initiation.

Conclusions

Multi-voxel MRS at intermediate and short TE can serve as a robust prognosticator of outcomes of patients with GBM who are treated with AAT.

Myo-Inositol Levels Measured with MR Spectroscopy Can Help Predict Failure of Antiangiogenic Treatment in Recurrent Glioblastoma

Background Patients with recurrent glioblastoma (GBM) are often treated with antiangiogenic agents, such as bevacizumab (BEV). Despite therapeutic promise, conventional MRI methods fail to help determine which patients may not benefit from this treatment. Purpose To use MR spectroscopic imaging (MRSI) with intermediate and short echo time to measure corrected myo-inositol (mI)normalized by contralateral creatine (hereafter, mI/c-Cr) in participants with recurrent GBM treated with BEV and to investigate whether such measurements can help predict survivorship before BEV initiation (baseline) and at 1 day, 4 weeks, and 8 weeks thereafter. Materials and Methods In this prospective longitudinal study (2016-2020), spectroscopic data on mI-a glial marker and osmoregulator within the brain-normalized by contralateral creatine in the intratumoral, contralateral, and peritumoral volumes of patients with recurrent GBM were evaluated. Area under the receiver operating characteristic curve (AUC) was calculated for all volumes at baseline and 1 day, 4 weeks, and 8 weeks after treatment to determine the ability of mI/c-Cr to help predict survivorship. Results Twenty-one participants (median age ± standard deviation, 62 years ± 12; 15 men) were evaluated. Lower mI/c-Cr in the tumor before and during BEV treatment was predictive of poor survivorship, with receiver operating characteristic analyses showing an AUC of 0.75 at baseline, 0.87 at 1 day after treatment, and 1 at 8 weeks after. A similar result was observed in contralateral normal-appearing tissue and the peritumoral volume, with shorter-term survivors having lower levels of mI/c-Cr. In the contralateral volume, a lower ratio of mI to creatine (hereafter, mI/Cr) predicted shorter-term survival at baseline and all other time points. Within the peritumoral volume, lower mI/c-Cr levels were predictive of shorter-term survival at baseline (AUC, 0.80), at 1 day after treatment (AUC, 0.93), and at 4 weeks after treatment (AUC, 0.68). Conclusion Lower levels of myo-inositol normalized by contralateral creatine within intratumoral, contralateral, and peritumoral volumes were predictive of poor survivorship and antiangiogenic treatment failure as early as before bevacizumab treatment. Adapting MR spectroscopic imaging alongside conventional MRI modalities conveys critical information regarding the biologic characteristics of tumors to help better treat individuals with recurrent glioblastoma. Clinical trial registration no. NCT02843230 © RSNA, 2021 Online supplemental material is available for this article.

Complementary Nuclear Magnetic Resonance-Based Metabolomics Approaches for Glioma Biomarker Identification in a Drosophila melanogaster Model

Human malignant gliomas are the most common type of primary brain tumor. Composed of glial cells and their precursors, they are aggressive and highly invasive, leading to a poor prognosis. Due to the difficulty of surgically removing tumors and their resistance to treatments, novel therapeutic approaches are needed to improve patient life expectancy and comfort. Drosophila melanogaster is a compelling genetic model to better understanding human neurological diseases owing to its high conservation in signaling pathways and cellular content of the brain. Here, glioma has been induced in Drosophila by co-activating the epidermal growth factor receptor and the phosphatidyl-inositol-3 kinase signaling pathways. Complementary nuclear magnetic resonance (NMR) techniques were used to obtain metabolic profiles in the third instar larvae brains. Fresh organs were directly studied by ¹H high resolution-magic angle spinning (HR-MAS) NMR, and brain extracts were analyzed by solution-state ¹H-NMR. Statistical analyses revealed differential metabolic signatures, impacted metabolic pathways, and glioma biomarkers. Each method was efficient to determine biomarkers. The highlighted metabolites including glucose, myo-inositol, sarcosine, glycine, alanine, and pyruvate for solution-state NMR and proline, myo-inositol, acetate, and glucose for HR-MAS show very good performances in discriminating samples according to their nature with data mining based on receiver operating characteristic curves. Combining results allows for a more complete view of induced disturbances and opens the possibility of deciphering the biochemical mechanisms of these tumors. The identified biomarkers provide a means to rebalance specific pathways through targeted metabolic therapy and to study the effects of pharmacological treatments using Drosophila as a model organism.

mTOR-Rictor-EGFR axis in oncogenesis and diagnosis of glioblastoma multiforme

Glioblastoma multiforme (GBM) is one of the aggressive brain cancers with patients having less survival period upto 12-15 months. Mammalian target of rapamycin (mTOR) is a serine/threonine kinase, belongs to the phosphatidylinositol 3-kinases (PI3K) pathway and is involved in various cellular processes of cancer cells. Cancer metabolism is regulated by mTOR and its components. mTOR forms two complexes as mTORC1 and mTORC2. Studies have identified the key component of the mTORC2 complex, Rapamycin-insensitive companion of mammalian target of rapamycin (Rictor) plays a prominent role in the regulation of cancer cell proliferation and metabolism. Apart, growth factor receptor signaling such as epidermal growth factor signaling mediated by epidermal growth factor receptor (EGFR) regulates cancer-related processes. In EGFR signaling various other signaling cascades such as phosphatidyl-inositol 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR pathway) and Ras/Raf/mitogen-activated protein kinase/ERK kinase (MEK)/extracellular-signal-regulated kinase (ERK) -dependent signaling cross-talk each other. From various studies about GBM, it is very well established that Rictor and EGFR mediated signaling pathways majorly playing a pivotal role in chemoresistance and tumor aggressiveness. Recent studies have shown that non-coding RNAs such as microRNAs (miRs) and long non-coding RNAs (lncRNAs) regulate the EGFR and Rictor and sensitize the cells towards chemotherapeutic agents. Thus, understanding of microRNA mediated regulation of EGFR and Rictor will help in cancer prevention and management as well as a future therapy.

Myoinositol to Total Choline Ratio in Glioblastomas as a Potential Prognostic Factor in Preoperative Magnetic Resonance Spectroscopy

Isocitrate dehydrogenase (IDH) wild-type diffuse astrocytic tumors tend to be pathologically diagnosed as glioblastomas (GBMs). We previously reported that myoinositol to total choline (Ins/Cho) ratio in GBMs on magnetic resonance (MR) spectroscopy was significantly lower than that in IDH-mutant gliomas. We then hypothesized that a low Ins/Cho ratio is a poor prognosis factor in patients with GBMs, IDH-wild-type. In the present study, we calculated the Ins/Cho ratios of patients with GBMs and investigated their progression-free survival (PFS) and overall survival (OS) to determine their utility as prognostic marker. We classified patients with GBMs harboring wild-type IDH (n = 27) into two groups based on the Ins/Cho ratio, and compared patient backgrounds, pathological findings, PFS, OS, and copy number aberrations between the high and low Ins/Cho groups. Patients with GBMs in the low Ins/Cho ratio group indicated shorter PFS (P = 0.021) and OS (P = 0.048) than those in the high Ins/Cho group. Multivariate analysis demonstrated that the Ins/Cho ratio was significantly correlated with PFS (hazard ratio 0.24, P = 0.028). In conclusion, the preoperative Ins/Cho ratio can be used as a novel potential prognostic factor for GBM, IDH-wild-type.

Advanced magnetic resonance imaging to support clinical drug development for malignant glioma

Even though the treatment options and survival of patients with glioblastoma multiforme (GBM), the most common type of malignant glioma, have improved over the past decade, there is still a high unmet medical need to develop novel therapies. Complexity in pathology and therapy require biomarkers to characterize tumors, to define malignant and active areas, to assess disease prognosis, and to quantify and monitor therapy response. While conventional magnetic resonance imaging (MRI) techniques have improved these assessments, limitations remain. In this review, we evaluate the role of various non-invasive biomarkers based on advanced structural and functional MRI techniques in the context of GBM drug development over the past 5 years.

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

Simple Summary

Approximately 75–80% of according to the classification of world health organization (WHO) grade II and III gliomas are characterized by a mutation of the isocitrate dehydrogenase (IDH) enzymes, which are very important in glioma cell metabolism. Patients with IDH mutated glioma have a significantly better prognosis than patients with IDH wildtype status, typically seen in glioblastoma WHO grade IV. Here we used a prospective O-(2-¹⁸F-fluoroethyl)-L-tyrosine (¹⁸F-FET) positron emission tomography guided single-voxel ¹H-magnetic resonance spectroscopy approach to predict the IDH status before surgery. Finally, 34 patients were included in this neuroimaging study, of whom eight had additionally tissue analysis. Using a machine learning technique, we predicted IDH status with an accuracy of 88.2%, a sensitivity of 95.5% and a specificity of 75.0%. It was newly recognized, that two metabolites (myo-inositol and glycine) have a particularly important role in the determination of the IDH status.

Abstract

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.

Glutamate Is a Noninvasive Metabolic Biomarker of IDH1-Mutant Glioma Response to Temozolomide Treatment

Although lower grade gliomas are driven by mutations in the isocitrate dehydrogenase 1 (IDH1) gene and are less aggressive than primary glioblastoma, they nonetheless generally recur. IDH1-mutant patients are increasingly being treated with temozolomide, but early detection of response remains a challenge and there is a need for complementary imaging methods to assess response to therapy prior to tumor shrinkage. The goal of this study was to determine the value of magnetic resonance spectroscopy (MRS)-based metabolic changes for detection of response to temozolomide in both genetically engineered and patient-derived mutant IDH1 models. Using 1H MRS in combination with chemometrics identified several metabolic alterations in temozolomide-treated cells, including a significant increase in steady-state glutamate levels. This was confirmed in vivo, where the observed 1H MRS increase in glutamate/glutamine occurred prior to tumor shrinkage. Cells labeled with [1-13C]glucose and [3-13C]glutamine, the principal sources of cellular glutamate, showed that flux to glutamate both from glucose via the tricarboxylic acid cycle and from glutamine were increased following temozolomide treatment. In line with these results, hyperpolarized [5-13C]glutamate produced from [2-13C]pyruvate and hyperpolarized [1-13C]glutamate produced from [1-13C]α-ketoglutarate were significantly higher in temozolomide-treated cells compared with controls. Collectively, our findings identify 1H MRS-detectable elevation of glutamate and hyperpolarized 13C MRS-detectable glutamate production from either pyruvate or α-ketoglutarate as potential translatable metabolic biomarkers of response to temozolomide treatment in mutant IDH1 glioma. SIGNIFICANCE: These findings show that glutamate can be used as a noninvasive, imageable metabolic marker for early assessment of tumor response to temozolomide, with the potential to improve treatment strategies for mutant IDH1 patients.

Matrix protease production, epithelial-to-mesenchymal transition marker expression and invasion of glioblastoma cells in response to osmotic or hydrostatic pressure

Both hydrostatic and osmotic pressures are altered in the tumour microenvironment. Glioblastoma (GBM) is a brain tumour with high invasiveness and poor prognosis. We hypothesized that physical and osmotic forces regulate glioblastoma (GBM) invasiveness. The osmotic pressure of GBM cell culture medium was adjusted using sodium chloride or water. Alternatively, cells were subjected to increased hydrostatic force. The proteolytic profile and epithelial–mesenchymal transition (EMT) were investigated using zymography and real-time qPCR. The EMT markers assessed were Snail-1, Snail-2, N-cadherin, Twist and vimentin. Invasion was investigated in vitro using extracellular matrix-coated Transwell inserts. In response to osmotic and mechanical pressure, GBM cell lines U87 and U251 and patient-derived neural oncospheres upregulated the expression of urokinase-type plasminogen activator (uPA) and/or matrix metalloproteinases (MMPs) as well as some of the EMT markers tested. The adherent cell lines invaded more when placed in media of increased osmolality. Therefore, GBM respond to osmotic or mechanical pressure by increasing matrix degrading enzyme production, and adopting a phenotype reminiscent of EMT. Better understanding the molecular and cellular mechanisms by which increased pressure promotes GBM invasiveness may help to develop innovative therapeutic approaches.

Assessment of Overall Survival in Glioma Patients as Predicted by Metabolomic Criteria

Objective: We assess the efficacy of the metabolomic profile from glioma biopsies in providing estimates of postsurgical Overall Survival in glioma patients.

Methods: Tumor biopsies from 46 patients bearing gliomas, obtained neurosurgically in the period 1992–1998, were analyzed by high resolution ¹H magnetic resonance spectroscopy (HR- ¹H MRS), following retrospectively individual postsurgical Overall Survival up to 720 weeks.

Results: The Overall Survival profile could be resolved in three groups; Short (shorter than 52 weeks, n = 19), Intermediate (between 53 and 364 weeks, n = 19) or Long (longer than 365 weeks, n = 8), respectively. Classical histopathological analysis assigned WHO grades II–IV to every biopsy but notably, some patients with low grade glioma depicted unexpectedly Short Overall Survival, while some patients with high grade glioma, presented unpredictably Long Overall Survival. To explore the reasons underlying these different responses, we analyzed HR-¹H MRS spectra from acid extracts of the same biopsies, to characterize the metabolite patterns associated to OS predictions. Poor prognosis was found in biopsies with higher contents of alanine, acetate, glutamate, total choline, phosphorylcholine, and glycine, while more favorable prognosis was achieved in biopsies with larger contents of total creatine, glycerol-phosphorylcholine, and myo-inositol. We then implemented a multivariate analysis to identify hierarchically the influence of metabolomic biomarkers on OS predictions, using a Classification Regression Tree (CRT) approach. The CRT based in metabolomic biomarkers grew up to three branches and split into eight nodes, predicting correctly the outcome of 94.7% of the patients in the Short Overall Survival group, 78.9% of the patients in the Intermediate Overall Survival group, and 75% of the patients in the Long Overall Survival group, respectively.

Conclusion: Present results indicate that metabolic profiling by HR-¹H MRS improves the Overall Survival predictions derived exclusively from classical histopathological gradings, thus favoring more precise therapeutic decisions.