Glutamine Metabolism in Brain Tumors

Role of Glutamate Excitotoxicity in Glioblastoma Growth and Its Implications in Treatment

Glioblastoma is a highly malignant and invasive type of primary brain tumor that originates from astrocytes. Glutamate, a neurotransmitter in the brain plays a crucial role in excitotoxic cell death. Excessive glutamate triggers a pathological process known as glutamate excitotoxicity, leading to neuronal damage. This excitotoxicity contributes to neuronal death and tumor necrosis in glioblastoma, resulting in seizures and symptoms such as difficulty in concentrating, low energy, depression, and insomnia. Glioblastoma cells, derived from astrocytes, fail to maintain glutamate-glutamine homeostasis, releasing excess glutamate into the extracellular space. This glutamate activates ionotropic N-methyl-D-aspartate (NMDA) receptors and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors on nearby neurons, causing hyperexcitability and triggering apoptosis through caspase activation. Additionally, glioblastoma cells possess calcium-permeable AMPA receptors, which are activated by glutamate in an autocrine manner. This activation increases intracellular calcium levels, triggering various signaling pathways. Alkylating agent temozolomide has been used to counteract glutamate excitotoxicity, but its efficacy in directly combating excitotoxicity is limited due to the development of resistance in glioblastoma cells. There is an unmet need for alternative biochemical agents that can have the greatest impact on reducing glutamate excitotoxicity in glioblastoma. In this review, we discuss the mechanism and various signaling pathways involved in glutamate excitotoxicity in glioblastoma cells. We also examine the roles of various receptor and transporter proteins, in glutamate excitotoxicity and highlight biochemical agents that can mitigate glutamate excitotoxicity in glioblastoma and serve as potential therapeutic agents.

Lactate-coated polyurea-siRNA dendriplex: a gene therapy-directed and metabolism-based strategy to impair glioblastoma (GBM)

Glioblastoma (GBM) is a highly lethal disease with limited treatment options due to its infiltrative nature and the lack of efficient therapy able to cross the protective blood-brain barrier (BBB). GBMs are metabolically characterized by increased glycolysis and glutamine dependence. This study explores a novel metabolism-based therapeutic approach using a polyurea generation 4 dendrimer (PUREG4) surface functionalized with lactate (LA) (PUREG4-LA24), to take advantage of glucose-dependent monocarboxylate transporters (MCTs) overexpression, loaded with selenium-chrysin (SeChry) and temozolomide (TMZ) or complexed with anti-glutaminase (GLS1) siRNAs to abrogate glutamine dependence. The nanoparticles (PUREG4-LA24) were efficient vehicles for cytotoxic compounds delivery, since SeChry@PUREG4-LA24 and TMZ@PUREG4-LA24 induced significant cell death in GBM cell lines, particularly in U251, which exhibits higher MCT1 expression. The anti-GLS1 siRNA-dendriplex with PUREG4-LA12 (PUREG4-LA12-anti-GLS1-siRNA) knocked down GLS1 in the GBM cell lines. In two in vitro BBB models, these dendriplexes successfully crossed the BBB, decreased GLS1 expression and altered the exometabolome of GBM cell lines, concomitantly with autophagy activation. Our findings highlight the potential of targeting glucose and glutamine pathways in GBM using dendrimer-based nanocarriers, overcoming the BBB and disrupting key metabolic processes in GBM cells. PUREG4-LA12-anti-GLS1-siRNA dendriplexes cross the blood-brain barrier (BBB) and impair glioblastoma (GBM) metabolism. The BBB is formed by a thin monolayer of specialized brain microvascular endothelial cells joined together by tight junctions that selectively control the passage of substances from the blood to the brain. It is a major obstacle in the treatment of GBM, since many chemotherapeutic drugs are unable to penetrate the brain. Therefore, we developed a strategy to overcome this obstacle: a lactate-coated polyurea dendrimer generation 4 (PUREG4) able to cross the BBB in vitro, that act as a nanocarrier of drugs and siRNA to the GBM cells. PUREG4-LA12 are nanoparticles functionalized with lactate (LA) to target MCT1, a lactate transporter highly expressed by GBM cells. Moreover, a complex of this nanoparticle with anti-GLS1 (glutaminase) siRNA (PUREG4-LA12-anti-GLS1-siRNA) was made, to target glutamine metabolism. It efficiently knocked down GLS1. Moreover, PUREG4-LA24 loaded with SeChry led to BBB disruption.

Optimized Long-TE 1H sLASER MR Spectroscopic Imaging at 3T for Separate Quantification of Glutamate and Glutamine in Glioma

BACKGROUND

Glutamate and glutamine are critical metabolites in gliomas, each serving distinct roles in tumor biology. Separate quantification of these metabolites using in vivo MR spectroscopy (MRS) at clinical field strengths (≤ 3T) is hindered by their molecular similarity, resulting in overlapping, hence indistinguishable, spectral peaks.

PURPOSE

To develop an MRS imaging (MRSI) protocol to map glutamate and glutamine separately at 3T within clinically feasible time, using J-modulation to enhance spectral differentiation, demonstrate its reliability/reproducibility, and quantify the metabolites in glioma subregions.

STUDY TYPE

Prospective.

POPULATION

Phantoms, 5 healthy subjects, and 30 patients with suspected glioma. IDH wild-type glioblastoma cases were evaluated to establish a uniform group.

FIELD STRENGTH/SEQUENCE

3T, Research protocol: 2D 1H sLASER MRSI (40 and 120 ms TE) with water reference, 3D T1-weighted and 2D T2-weighted. Trial-screening process: T1-weighted, T1-weighted contrast-enhanced, T2-weighted, FLAIR.

ASSESSMENT

Spectral simulations and phantom measurements were performed to design and validate the protocol. Spectral quality/fitting parameters for scan-rescan measurements were obtained using LCModel. The proposed long-TE data were compared with short-TE data. BraTS Toolkit was employed for fully automated tumor segmentation.

STATISTICAL TESTS

Scan-rescan comparison was performed using Bland-Altman analysis. LCModel coefficient of modeling covariance (CMC) between glutamate and glutamine was mapped to evaluate their model interactions for each spectral fitting. Metabolite levels in tumor subregions were compared using one-way ANOVA and Kruskal-Wallis. A p value < 0.05 was considered statistically significant.

RESULTS

Spectral quality/fitting parameters and metabolite levels were highly consistent between scan-rescan measurements. A negative association between glutamate and glutamine models at short TE (CMC = -0.16 ± 0.06) was eliminated at long TE (0.01 ± 0.05). Low glutamate in tumor subregions (non-enhancing-tumor-core: 5.35 ± 4.45 mM, surrounding-non-enhancing-FLAIR-hyperintensity: 7.39 ± 2.62 mM, and enhancing-tumor: 7.60 ± 4.16 mM) was found compared to contralateral (10.84 ± 2.94 mM), whereas glutamine was higher in surrounding-non-enhancing-FLAIR-hyperintensity (9.17 ± 6.84 mM) and enhancing-tumor (7.20 ± 4.42 mM), but not in non-enhancing-tumor-core (4.92 ± 3.38 mM, p = 0.18) compared to contralateral (2.94 ± 1.35 mM).

DATA CONCLUSION

The proposed MRSI protocol (~12 min) enables separate mapping of glutamate and glutamine reliably along with other MRS-detectable standard metabolites in glioma subregions at 3T.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 3.

Alzheimer's disease: an integrative bioinformatics and machine learning analysis reveals glutamine metabolism-associated gene biomarkers

BACKGROUND

Alzheimer's disease (AD), a hallmark of age-related cognitive decline, is defined by its unique neuropathology. Metabolic dysregulation, particularly involving glutamine (Gln) metabolism, has emerged as a critical but underexplored aspect of AD pathophysiology, representing a significant gap in our current understanding of the disease.

METHODS

To investigate the involvement of GlnMgs in AD, we conducted a comprehensive bioinformatic analysis. We began by identifying differentially expressed GlnMgs from a curated list of 34 candidate genes. Subsequently, we employed GSEA and GSVA to assess the biological significance of these GlnMgs. Advanced techniques such as Lasso regression and SVM-RFE were utilized to identify key hub genes and evaluate the diagnostic potential of 14 central GlnMgs in AD. Additionally, we examined their correlations with clinical parameters and validated their expression across multiple independent AD cohorts (GSE5281, GSE37263, GSE106241, GSE132903, GSE63060).

RESULTS

Our rigorous analysis identified 14 GlnMgs-GLS2, GLS, GLUD2, GLUL, GOT1, HAL, AADAT, PFAS, ASNSD1, PPAT, NIT2, ALDH5A1, ASRGL1, and ATCAY-as potential contributors to AD pathogenesis. These genes were implicated in vital biological processes, including lipid transport and the metabolism of purine-containing compounds, in response to nutrient availability. Notably, these GlnMgs demonstrated significant diagnostic potential, highlighting their utility as both diagnostic and prognostic biomarkers for AD.

CONCLUSIONS

Our study uncovers 14 GlnMgs with potential links to AD, expanding our understanding of the disease's molecular underpinnings and offering promising avenues for biomarker development. These findings not only enhance the molecular landscape of AD but also pave the way for future diagnostic and therapeutic innovations, potentially reshaping AD diagnostics and patient care.

Metabolic shifts in glioblastoma: unraveling altered pathways and exploring novel therapeutic avenues

Metabolic reprogramming stands out as a defining characteristic of cancer, including glioblastoma (GB), enabling tumor cells to overcome growth and survival challenges in adverse conditions. The dysregulation of metabolic processes in GB is crucial to its pathogenesis, influencing both tumorigenesis and the disease's invasive tendencies. This altered metabolism supplies essential energy substrates for uncontrolled cell proliferation and also creates an immunosuppressive microenvironment, complicating conventional therapies. A comprehensive understanding of the complexities of metabolic dysregulation in carbohydrate, amino acid, lipid and nucleotide pathways in GB holds promise for effective therapeutic interventions. Key metabolic enzymes, transporters, and signaling pathways and mitochondrial metabolism have been examined for their roles in GB pathology and their possible therapeutic potential. Addressing these metabolic targets has shown efficacy in preclinical models and is currently being evaluated in clinical trials. Combination therapies that exploit metabolic vulnerabilities alongside conventional treatments hold the promise of improving patient outcomes. This review explores the dynamic interplay between glioblastoma's aggressiveness and altered metabolism, offering insights into potential therapeutic strategies. Moreover, this review discusses the recent advancements in drug development aimed at targeting these dysregulated metabolic pathways.

Reciprocal links between methionine metabolism, DNA repair and therapy resistance in glioblastoma

Glioblastoma (GBM) is uniformly lethal due to profound treatment resistance. Altered cellular metabolism is a key mediator of GBM treatment resistance. Uptake of the essential sulfur-containing amino acid methionine is drastically elevated in GBMs compared to normal cells, however, it is not known how this methionine is utilized or whether it relates to GBM treatment resistance. Here, we find that radiation acutely increases the levels of methionine-related metabolites in a variety of treatment-resistant GBM models. Stable isotope tracing studies further revealed that radiation acutely activates methionine to S-adenosyl methionine (SAM) conversion through an active signaling event mediated by the kinases of the DNA damage response. In vivo tumor SAM synthesis increases after radiation, while normal brain SAM production remains unchanged, indicating a tumor- specific metabolic alteration to radiation. Pharmacological and dietary strategies to block methionine to SAM conversion slowed DNA damage response and increased cell death following radiation in vitro. Mechanistically, these effects are due to depletion of DNA repair proteins and are reversed by SAM supplementation. These effects are selective to GBMs lacking the methionine salvage enzyme methylthioadenosine phosphorylase. Pharmacological inhibition of SAM synthesis hindered tumor growth in flank and orthotopic in vivo GBM models when combined with radiation. By contrast, methionine depletion does not reduce tumor SAM levels and fails to radiosensitize intracranial models, indicating depleting SAM, as opposed to simply lowering methionine, is critical for hindering tumor growth in intracranial models of GBM. These results highlight a new signaling link between DNA damage and SAM synthesis and define the metabolic fates of methionine in GBM in vivo . Inhibiting radiation-induced SAM synthesis slows DNA repair and augments radiation efficacy in GBM. Using MAT2A inhibitors to deplete SAM may selectively overcome treatment resistance in GBMs with defective methionine salvage while sparing normal brain.

Glutaminolysis is associated with mitochondrial pathway activation and can be therapeutically targeted in glioblastoma

BACKGROUND

Glioblastoma is an aggressive cancer that originates from abnormal cell growth in the brain and requires metabolic reprogramming to support tumor growth. Metabolic reprogramming involves the upregulation of various metabolic pathways. Although the activation of specific metabolic pathways in glioblastoma cell lines has been documented, the comprehensive profile of metabolic reprogramming and the role of each pathway in glioblastoma tissues in patients remain elusive.

METHODS

We analyzed 38 glioblastoma tissues. As a test set, we examined 20 tissues from Kyushu University Hospital, focusing on proteins related to several metabolic pathways, including glycolysis, the one-carbon cycle, glutaminolysis, and the mitochondrial tricarboxylic acid cycle. Subsequently, we analyzed an additional 18 glioblastoma tissues from Kagoshima University Hospital as a validation set. We also validated our findings using six cell lines, including U87, LN229, U373, T98G, and two patient-derived cells.

RESULTS

The levels of mitochondria-related proteins (COX1, COX2, and DRP1) were correlated with each other and with glutaminolysis-related proteins (GLDH and GLS1). Conversely, their expression was inversely correlated with that of glycolytic proteins. Notably, inhibiting the glutaminolysis pathway in cell lines with high GLDH and GLS1 expression proved effective in suppressing tumor growth.

CONCLUSIONS

Our findings confirm that glioblastoma tissues can be categorized into glycolytic-dominant and mitochondrial-dominant types, as previously reported. The mitochondrial-dominant type is also glutaminolysis-dominant. Therefore, inhibiting the glutaminolysis pathway may be an effective treatment for mitochondrial-dominant glioblastoma.

Circadian Alterations in Brain Metabolism Linked to Cognitive Deficits During Hepatic Ischemia-Reperfusion Injury Using [1H-13C]-NMR Metabolomics

Background: Hepatic ischemia-reperfusion injury (HIRI) is known to affect cognitive functions, with particular concern for its impact on brain metabolic dynamics. Circadian rhythms, as a crucial mechanism for internal time regulation within organisms, significantly influence metabolic processes in the brain. This study aims to explore how HIRI affects hippocampal metabolism and its circadian rhythm differences in mice, and to analyze how these changes are associated with cognitive impairments. Methods: A C57BL/6 male mouse model was used, simulating HIRI through hepatic ischemia-reperfusion surgery, with a sham operation conducted for the control group. Cognitive functions were evaluated using open field tests, Y-maze tests, and novel object recognition tests. Magnetic resonance spectroscopic imaging (MRSI) technology, combined with intravenous injection of [2-13C]-acetate and [1-13C]-glucose, was utilized to analyze metabolic changes in the hippocampus of HIRI mice at different circadian time points (Zeitgeber Time ZT0, 8:00 and ZT12, 20:00). Circadian rhythms regulate behavioral, physiological, and metabolic rhythms through transcriptional feedback loops, with ZT0 at dawn (lights on) and ZT12 at dusk (lights off). Results: HIRI mice exhibited significant cognitive impairments in behavioral tests, particularly in spatial memory and learning abilities. MRSI analysis revealed significant circadian rhythm differences in the concentration of metabolites in the hippocampus, with the enrichment concentrations of lactate, alanine, glutamate, and taurine showing different trends at ZT0 compared to ZT12, highlighting the important influence of circadian rhythms on metabolic dysregulation induced by HIRI. Conclusions: This study highlights the significant impact of HIRI on brain metabolic dynamics in mice, especially in the hippocampal area, and for the first time reveals the differences in these effects within circadian rhythms. These findings not only emphasize the association between HIRI-induced cognitive impairments and changes in brain metabolism but also point out the crucial role of circadian rhythms in this process, offering new metabolic targets and timing considerations for therapeutic strategies against HIRI-related cognitive disorders.

Unveiling the Molecular Mechanisms of Glioblastoma through an Integrated Network-Based Approach

Background/Objectives: Despite current treatments extending the lifespan of Glioblastoma (GBM) patients, the average survival time is around 15-18 months, underscoring the fatality of GBM. This study aims to investigate the impact of sample heterogeneity on gene expression in GBM, identify key metabolic pathways and gene modules, and explore potential therapeutic targets. Methods: In this study, we analysed GBM transcriptome data derived from The Cancer Genome Atlas (TCGA) using genome-scale metabolic models (GEMs) and co-expression networks. We examine transcriptome data incorporating tumour purity scores (TPSs), allowing us to assess the impact of sample heterogeneity on gene expression profiles. We analysed the metabolic profile of GBM by generating condition-specific GEMs based on the TPS group. Results: Our findings revealed that over 90% of genes showing brain and glioma specificity in RNA expression demonstrate a high positive correlation, underscoring their expression is dominated by glioma cells. Conversely, negatively correlated genes are strongly associated with immune responses, indicating a complex interaction between glioma and immune pathways and non-tumorigenic cell dominance on gene expression. TPS-based metabolic profile analysis was supported by reporter metabolite analysis, highlighting several metabolic pathways, including arachidonic acid, kynurenine and NAD pathway. Through co-expression network analysis, we identified modules that significantly overlap with TPS-correlated genes. Notably, SOX11 and GSX1 are upregulated in High TPS, show a high correlation with TPS, and emerged as promising therapeutic targets. Additionally, NCAM1 exhibits a high centrality score within the co-expression module, which shows a positive correlation with TPS. Moreover, LILRB4, an immune-related gene expressed in the brain, showed a negative correlation and upregulated in Low TPS, highlighting the importance of modulating immune responses in the GBM mechanism. Conclusions: Our study uncovers sample heterogeneity's impact on gene expression and the molecular mechanisms driving GBM, and it identifies potential therapeutic targets for developing effective treatments for GBM patients.

Metabolic vulnerabilities in cancer: A new therapeutic strategy

Cancer metabolism is now a key area for therapeutic intervention, targeting unique metabolic reprogramming crucial for tumor growth and survival. This article reviews the therapeutic potential of addressing metabolic vulnerabilities through glycolysis and glutaminase inhibitors, which disrupt cancer cell metabolism. Challenges such as tumor heterogeneity and adaptive resistance are discussed, with strategies including personalized medicine and predictive biomarkers to enhance treatment efficacy. Additionally, integrating diet and lifestyle changes with metabolic targeting underscores a holistic approach to improving therapy outcomes. The article also examines the benefits of incorporating these strategies into standard care, highlighting the potential for more tailored, safer treatments. In conclusion, exploiting metabolic vulnerabilities promises a new era in oncology, positioning metabolic targeting at the forefront of personalized cancer therapy and transforming patient care.

A glutamatergic biomarker panel enables differentiating Grade 4 gliomas/astrocytomas from brain metastases

Background

The differentiation of high-grade glioma and brain tumors of an extracranial origin is eminent for the decision on subsequent treatment regimens. While in high-grade glioma, a surgical resection of the tumor mass is a fundamental part of current standard regimens, in brain metastasis, the burden of the primary tumor must be considered. However, without a cancer history, the differentiation remains challenging in the imaging. Hence, biopsies are common that may help to identify the tumor origin. An additional tool to support the differentiation may be of great help. For this purpose, we aimed to identify a biomarker panel based on the expression analysis of a small sample of tissue to support the pathological analysis of surgery resection specimens. Given that an aberrant glutamate signaling was identified to drive glioblastoma progression, we focused on glutamate receptors and key players of glutamate homeostasis.

Methods

Based on surgically resected samples from 55 brain tumors, the expression of ionotropic and metabotropic glutamate receptors and key players of glutamate homeostasis were analyzed by RT-PCR. Subsequently, a receiver operating characteristic (ROC) analysis was performed to identify genes whose expression levels may be associated with either glioblastoma or brain metastasis.

Results

Out of a total of 29 glutamatergic genes analyzed, nine genes presented a significantly different expression level between high-grade gliomas and brain metastases. Of those, seven were identified as potential biomarker candidates including genes encoding for AMPA receptors GRIA1, GRIA2, kainate receptors GRIK1 and GRIK4, metabotropic receptor GRM3, transaminase BCAT1 and the glutamine synthetase (encoded by GLUL). Overall, the biomarker panel achieved an accuracy of 88% (95% CI: 87.1, 90.8) in predicting the tumor entity. Gene expression data, however, could not discriminate between patients with seizures from those without.

Conclusion

We have identified a panel of seven genes whose expression may serve as a biomarker panel to discriminate glioblastomas and brain metastases at the molecular level. After further validation, our biomarker signatures could be of great use in the decision making on subsequent treatment regimens after diagnosis.

Upregulated ECM genes and increased synaptic activity in Parkinson's human DA neurons with PINK1/ PRKN mutations

Parkinson's disease (PD) is the second most prevalent neurodegenerative disease. Primary symptoms of PD arise with the loss of dopaminergic (DA) neurons in the Substantia Nigra Pars Compacta, but PD also affects the hippocampus and cortex, usually in its later stage. Approximately 15% of PD cases are familial with a genetic mutation. Two of the most associated genes with autosomal recessive (AR) early-onset familial PD are PINK1 and PRKN. In vitro studies of these genetic mutations are needed to understand the neurophysiological changes in patients' neurons that may contribute to neurodegeneration. In this work, we generated and differentiated DA and hippocampal neurons from human induced pluripotent stem cells (hiPSCs) derived from two patients with a double mutation in their PINK1 and PRKN (one homozygous and one heterozygous) genes and assessed their neurophysiology compared to two healthy controls. We showed that the synaptic activity of PD neurons generated from patients with the PINK1 and PRKN mutations is impaired in the hippocampus and dopaminergic neurons. Mutant dopaminergic neurons had enhanced excitatory post-synaptic activity. In addition, DA neurons with the homozygous mutation of PINK1 exhibited more pronounced electrophysiological differences compared to the control neurons. Signaling network analysis of RNA sequencing results revealed that Focal adhesion and ECM receptor pathway were the top two upregulated pathways in the mutant PD neurons. Our findings reveal that the phenotypes linked to PINK1 and PRKN mutations differ from those from other PD mutations, suggesting a unique interplay between these two mutations that drives different PD mechanisms.

Therapeutic resurgence of 6-diazo-5-oxo-l-norleucine (DON) through tissue-targeted prodrugs

The recognition that rapidly proliferating cancer cells rely heavily on glutamine for their survival and growth has renewed interest in the development of glutamine antagonists for cancer therapy. Glutamine plays a pivotal role as a carbon source for synthesizing lipids and metabolites through the TCA cycle, as well as a nitrogen source for synthesis of amino acid and nucleotides. Numerous studies have explored the significance of glutamine metabolism in cancer, providing a robust rationale for targeting this metabolic pathway in cancer treatment. The glutamine antagonist 6-diazo-5-oxo-l-norleucine (DON) has been explored as an anticancer therapeutic for nearly six decades. Initial investigations revealed remarkable efficacy in preclinical studies and promising outcomes in early clinical trials. However, further advancement of DON was hindered due to dose-limiting gastrointestinal (GI) toxicities as the GI system is highly dependent on glutamine for regulating growth and repair. In an effort to repurpose DON and mitigate gastrointestinal (GI) toxicity concerns, prodrug strategies were utilized. These strategies aimed to enhance the delivery of DON to specific target tissues, such as tumors and the central nervous system (CNS), while sparing DON delivery to normal tissues, particularly the GI tract. When administered at low daily doses, optimized for metabolic inhibition, these prodrugs exhibit remarkable effectiveness without inducing significant toxicity to normal tissues. This approach holds promise for overcoming past challenges associated with DON, offering an avenue for its successful utilization in cancer treatment.

Glutamine metabolism, a double agent combating or fuelling hepatocellular carcinoma

The reprogramming of glutamine metabolism is a key event in cancer more generally and in hepatocellular carcinoma (HCC) in particular. Glutamine consumption supplies tumours with ATP and metabolites through anaplerosis of the tricarboxylic acid cycle, while glutamine production can be enhanced by the overexpression of glutamine synthetase. In HCC, increased glutamine production is driven by activating mutations in the CTNNB1 gene encoding β-catenin. Increased glutamine synthesis or utilisation impacts tumour epigenetics, oxidative stress, autophagy, immunity and associated pathways, such as the mTOR (mammalian target of rapamycin) pathway. In this review, we will discuss studies which emphasise the pro-tumoral or tumour-suppressive effect of glutamine overproduction. It is clear that more comprehensive studies are needed as a foundation from which to develop suitable therapies targeting glutamine metabolic pathways, depending on the predicted pro- or anti-tumour role of dysregulated glutamine metabolism in distinct genetic contexts.

Regulation of Hypoxia Dependent Reprogramming of Cancer Metabolism: Role of HIF-1 and Its Potential Therapeutic Implications in Leukemia

Metabolic reprogramming occurs to meet cancer cells' high energy demand. Its function is essential to the survival of malignancies. Comparing cancer cells to non-malignant cells has revealed that cancer cells have altered metabolism. Several pathways, particularly mTOR, Akt, PI3K, and HIF-1 (hypoxia-inducible factor-1) modulate the metabolism of cancer. Among other aspects of cancer biology, gene expression in metabolism, survival, invasion, proliferation, and angiogenesis of cells are controlled by HIF-1, a vital controller of cellular responsiveness to hypoxia. This article examines various cancer cell metabolisms, metabolic alterations that can take place in cancer cells, metabolic pathways, and molecular aspects of metabolic alteration in cancer cells placing special attention on the consequences of hypoxia-inducible factor and summarising some of their novel targets in the treatment of cancer including leukemia. A brief description of HIF-1α's role and target in a few common types of hematological malignancies (leukemia) is also elucidated in the present article.

MALDI-MSI-LC-MS/MS Workflow for Single-Section Single Step Combined Proteomics and Quantitative Lipidomics

We introduce a novel approach for comprehensive molecular profiling in biological samples. Our single-section methodology combines quantitative mass spectrometry imaging (Q-MSI) and a single step extraction protocol enabling lipidomic and proteomic liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis on the same tissue area. The integration of spatially correlated lipidomic and proteomic data on a single tissue section allows for a comprehensive interpretation of the molecular landscape. Comparing Q-MSI and Q-LC-MS/MS quantification results sheds new light on the effect of MSI and related sample preparation. Performing MSI before Q-LC-MS on the same tissue section led to fewer protein identifications and a lower correlation between lipid quantification results. Also, the critical role and influence of internal standards in Q-MSI for accurate quantification is highlighted. Testing various slide types and the evaluation of different workflows for single-section spatial multiomics analysis emphasized the need for critical evaluation of Q-MSI data. These findings highlight the necessity for robust quantification methods comparable to current gold-standard LC-MS/MS techniques. The spatial information from MSI allowed region-specific insights within heterogeneous tissues, as demonstrated for glioblastoma multiforme. Additionally, our workflow demonstrated the efficiency of a single step extraction for lipidomic and proteomic analyses on the same tissue area, enabling the examination of significantly altered proteins and lipids within distinct regions of a single section. The integration of these insights into a lipid-protein interaction network expands the biological information attainable from a tissue section, highlighting the potential of this comprehensive approach for advancing spatial multiomics research.

Glioblastoma Therapy: Past, Present and Future

Glioblastoma (GB) stands out as the most prevalent and lethal form of brain cancer. Although great efforts have been made by clinicians and researchers, no significant improvement in survival has been achieved since the Stupp protocol became the standard of care (SOC) in 2005. Despite multimodality treatments, recurrence is almost universal with survival rates under 2 years after diagnosis. Here, we discuss the recent progress in our understanding of GB pathophysiology, in particular, the importance of glioma stem cells (GSCs), the tumor microenvironment conditions, and epigenetic mechanisms involved in GB growth, aggressiveness and recurrence. The discussion on therapeutic strategies first covers the SOC treatment and targeted therapies that have been shown to interfere with different signaling pathways (pRB/CDK4/RB1/P16ink4, TP53/MDM2/P14arf, PI3k/Akt-PTEN, RAS/RAF/MEK, PARP) involved in GB tumorigenesis, pathophysiology, and treatment resistance acquisition. Below, we analyze several immunotherapeutic approaches (i.e., checkpoint inhibitors, vaccines, CAR-modified NK or T cells, oncolytic virotherapy) that have been used in an attempt to enhance the immune response against GB, and thereby avoid recidivism or increase survival of GB patients. Finally, we present treatment attempts made using nanotherapies (nanometric structures having active anti-GB agents such as antibodies, chemotherapeutic/anti-angiogenic drugs or sensitizers, radionuclides, and molecules that target GB cellular receptors or open the blood-brain barrier) and non-ionizing energies (laser interstitial thermal therapy, high/low intensity focused ultrasounds, photodynamic/sonodynamic therapies and electroporation). The aim of this review is to discuss the advances and limitations of the current therapies and to present novel approaches that are under development or following clinical trials.

The role of glutamate and glutamine metabolism and related transporters in nerve cells

BACKGROUND

Glutamate and glutamine are the most abundant amino acids in the blood and play a crucial role in cell survival in the nervous system. Various transporters found in cell and mitochondrial membranes, such as the solute carriers (SLCs) superfamily, are responsible for maintaining the balance of glutamate and glutamine in the synaptic cleft and within cells. This balance affects the metabolism of glutamate and glutamine as non-essential amino acids.

AIMS

This review aims to provide an overview of the transporters and enzymes associated with glutamate and glutamine in neuronal cells.

DISCUSSION

We delve into the function of glutamate and glutamine in the nervous system by discussing the transporters involved in the glutamate-glutamine cycle and the key enzymes responsible for their mutual conversion. Additionally, we highlight the role of glutamate and glutamine as carbon and nitrogen donors, as well as their significance as precursors for the synthesis of reduced glutathione (GSH).

CONCLUSION

Glutamate and glutamine play a crucial role in the brain due to their special effects. It is essential to focus on understanding glutamate and glutamine metabolism to comprehend the physiological behavior of nerve cells and to treat nervous system disorders and cancer.

A novel diabetic foot ulcer diagnostic model: identification and analysis of genes related to glutamine metabolism and immune infiltration

BACKGROUND

Diabetic foot ulcer (DFU) is one of the most common and severe complications of diabetes, with vascular changes, neuropathy, and infections being the primary pathological mechanisms. Glutamine (Gln) metabolism has been found to play a crucial role in diabetes complications. This study aims to identify and validate potential Gln metabolism biomarkers associated with DFU through bioinformatics and machine learning analysis.

METHODS

We downloaded two microarray datasets related to DFU patients from the Gene Expression Omnibus (GEO) database, namely GSE134431, GSE68183, and GSE80178. From the GSE134431 dataset, we obtained differentially expressed Gln-metabolism related genes (deGlnMRGs) between DFU and normal controls. We analyzed the correlation between deGlnMRGs and immune cell infiltration status. We also explored the relationship between GlnMRGs molecular clusters and immune cell infiltration status. Notably, WGCNA to identify differentially expressed genes (DEGs) within specific clusters. Additionally, we conducted GSVA to annotate enriched genes. Subsequently, we constructed and screened the best machine learning model. Finally, we validated the predictions' accuracy using a nomogram, calibration curves, decision curve analysis (DCA), and the GSE134431, GSE68183, and GSE80178 dataset.

RESULTS

In both the DFU and normal control groups, we confirmed the presence of deGlnMRGs and an activated immune response. From the GSE134431 dataset, we obtained 20 deGlnMRGs, including CTPS1, NAGS, SLC7A11, GGT1, GCLM, RIMKLA, ARG2, ASL, ASNS, ASNSD1, PPAT, GLS2, GLUD1, MECP2, ASS1, PRODH, CTPS2, ALDH5A1, DGLUCY, and SLC25A12. Furthermore, two clusters were identified in DFU. Immune infiltration analysis indicated the presence of immune heterogeneity in these two clusters. Additionally, we established a Support Vector Machine (SVM) model based on 5 genes (R3HCC1, ZNF562, MFN1, DRAM1, and PTGDS), which exhibited excellent performance on the external validation datasetGSE134431, GSE68183, and GSE80178 (AUC = 0.929).

CONCLUSION

This study has identified five Gln metabolism genes associated with DFU, revealing potential novel biomarkers and therapeutic targets for DFU. Additionally, the infiltration of immune-inflammatory cells plays a crucial role in the progression of DFU.

Glutamine metabolism-related genes and immunotherapy in nonspecific orbital inflammation were validated using bioinformatics and machine learning

BACKGROUND

Nonspecific orbital inflammation (NSOI) is an idiopathic, persistent, and proliferative inflammatory condition affecting the orbit, characterized by polymorphous lymphoid infiltration. Its pathogenesis and progression have been linked to imbalances in tumor metabolic pathways, with glutamine (Gln) metabolism emerging as a critical aspect in cancer. Metabolic reprogramming is known to influence clinical outcomes in various malignancies. However, comprehensive research on glutamine metabolism's significance in NSOI is lacking.

METHODS

This study conducted a bioinformatics analysis to identify and validate potential glutamine-related molecules (GlnMgs) associated with NSOI. The discovery of GlnMgs involved the intersection of differential expression analysis with a set of 42 candidate GlnMgs. The biological functions and pathways of the identified GlnMgs were analyzed using GSEA and GSVA. Lasso regression and SVM-RFE methods identified hub genes and assessed the diagnostic efficacy of fourteen GlnMgs in NSOI. The correlation between hub GlnMgs and clinical characteristics was also examined. The expression levels of the fourteen GlnMgs were validated using datasets GSE58331 and GSE105149.

RESULTS

Fourteen GlnMgs related to NSOI were identified, including FTCD, CPS1, CTPS1, NAGS, DDAH2, PHGDH, GGT1, GCLM, GLUD1, ART4, AADAT, ASNSD1, SLC38A1, and GFPT2. Biological function analysis indicated their involvement in responses to extracellular stimulus, mitochondrial matrix, and lipid transport. The diagnostic performance of these GlnMgs in distinguishing NSOI showed promising results.

CONCLUSIONS

This study successfully identified fourteen GlnMgs associated with NSOI, providing insights into potential novel biomarkers for NSOI and avenues for monitoring disease progression.

Mechanisms of Intracellular Communication in Cancer and Pathogen Spreading

Cell-to-cell interactions are essential for proper development, homeostasis, and complex syncytia/organ formation and function. Intercellular communication are mediated by multiple mechanisms including soluble mediators, adhesion molecules and specific mechanisms of cell to cell communication such as Gap junctions (GJ), tunneling nanotubes (TNT), and exosomes. Only recently, has been discovered that TNTs and exosomes enable the exchange of large signaling molecules, RNA, viral products, antigens, and organelles opening new avenues of research and therapeutic approaches. The focus of this review is to summarize these recent findings in physiologic and pathologic conditions.

Role of Glycolytic and Glutamine Metabolism Reprogramming on the Proliferation, Invasion, and Apoptosis Resistance through Modulation of Signaling Pathways in Glioblastoma

Glioma cells exhibit genetic and metabolic alterations that affect the deregulation of several cellular signal transduction pathways, including those related to glucose metabolism. Moreover, oncogenic signaling pathways induce the expression of metabolic genes, increasing the metabolic enzyme activities and thus the critical biosynthetic pathways to generate nucleotides, amino acids, and fatty acids, which provide energy and metabolic intermediates that are essential to accomplish the biosynthetic needs of glioma cells. In this review, we aim to explore how dysregulated metabolic enzymes and their metabolites from primary metabolism pathways in glioblastoma (GBM) such as glycolysis and glutaminolysis modulate anabolic and catabolic metabolic pathways as well as pro-oncogenic signaling and contribute to the formation, survival, growth, and malignancy of glioma cells. Also, we discuss promising therapeutic strategies by targeting the key players in metabolic regulation. Therefore, the knowledge of metabolic reprogramming is necessary to fully understand the biology of malignant gliomas to improve patient survival significantly.

Carbonized polymer dots derived from metformin and L-arginine for tumor cell membrane- and mitochondria-dual targeting therapy

Metformin has demonstrated antitumor potential in clinical studies; however, achieving optimal antitumor effects requires administering an extremely safe medication dose. To enhance the efficacy and reduce dosage requirements, we propose the creation of large-molecule drugs through the combination of small-molecule drugs. In this study, we developed novel polymer dots, referred to as MA-dots, with sizes of approximately 5 nm, featuring dual targeting capabilities for tumor cell membranes and mitochondria. MA-dots were synthesized using metformin and L-arginine via a rapid microwave-assisted method. Notably, the resulting MA-dots (with a half maximal inhibitory concentration (IC50) of 93.60 μg mL-1) exhibited more than a 12-fold increase in antitumor activity compared to the raw metformin material (IC50 = 1159.00 μg mL-1) over a 24-hour period. In addition, our MA-dots outperformed most metformin-derived nanodrugs in terms of antitumor efficacy. Furthermore, oral gavage treatment with MA-dots led to the suppression of A549 (lung cancer cell lines) tumor growth in vivo. Mechanistic investigations revealed that MA-dots bound to the large neutral amino acid transporter 1 (LAT1) proteins, which are overexpressed in malignant tumor cell membranes. Moreover, these MA-dots accumulated within the mitochondria, leading to increased production of reactive oxygen species (ROS), mitochondrial damage, and disruption of energy metabolism by modulating the 5'-adenosine monophosphate-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR) pathway in tumor cells. This cascade of events triggers cell-cycle arrest and apoptosis. In summary, this study presented a rapid method for fabricating a novel nanoderivative, MA-dots, capable of both tumor targeting and exerting tumor-suppressive effects.

An adult Drosophila glioma model to highlight metabolic dysfunctions and evaluate the role of the serotonin 5-HT7 receptor as a potential therapeutic target

Gliomas account for 50% of brain cancers and are therefore the most common brain tumors. Molecular alterations involved in adult gliomas have been identified and mainly affect tyrosine kinase receptors with amplification and/or mutation of the epidermal growth factor receptor (EGFR) and its associated signaling pathways. Several targeted therapies have been developed, but current treatments remain ineffective for glioblastomas, the most severe forms. Thus, it is a priority to identify new pharmacological targets. Drosophila glioma models established in larvae and adults are useful to identify new genes and signaling pathways involved in glioma progression. Here, we used a Drosophila glioma model in adults, to characterize metabolic disturbances associated with glioma and assess the consequences of 5-HT7 R expression on glioma development. First, by using in vivo magnetic resonance imaging, we have shown that expression of the constitutively active forms of EGFR and PI3K in adult glial cells induces brain enlargement. Then, we explored altered cellular metabolism by using high-resolution magic angle spinning NMR and 1 H-13 C heteronuclear single quantum coherence solution states. Discriminant metabolites identified highlight the rewiring of metabolic pathways in glioma and associated cachexia phenotypes. Finally, the expression of 5-HT7 R in this adult model attenuates phenotypes associated with glioma development. Collectively, this whole-animal approach in Drosophila allowed us to provide several rapid and robust phenotype readouts, such as enlarged brain volume and glioma-associated cachexia, as well as to determine the metabolic pathways involved in glioma genesis and finally to confirm the interest of the 5-HT7 R in the treatment of glioma.

Metabolic control of cancer metastasis: role of amino acids at secondary organ sites

Most cancer-related deaths are caused by the metastases, which commonly develop at multiple organ sites including the brain, bone, and lungs. Despite longstanding observations that the spread of cancer is not random, our understanding of the mechanisms that underlie metastatic spread to specific organs remains limited. However, metabolism has recently emerged as an important contributor to metastasis. Amino acids are a significant nutrient source to cancer cells and their metabolism which can serve to fuel biosynthetic pathways capable of facilitating cell survival and tumor expansion while also defending against oxidative stress. Compared to the primary tumor, each of the common metastatic sites exhibit vastly different nutrient compositions and environmental stressors, necessitating the need of cancer cells to metabolically thrive in their new environment during colonization and outgrowth. This review seeks to summarize the current literature on amino acid metabolism pathways that support metastasis to common secondary sites, including impacts on immune responses. Understanding the role of amino acids in secondary organ sites may offer opportunities for therapeutic inhibition of cancer metastasis.

Alpha-Ketoglutarate Regulates Tnfrsf12a/Fn14 Expression via Histone Modification and Prevents Cancer-Induced Cachexia

Previous studies have shown that inhibition of TNF family member FN14 (gene: TNFRSF12A) in colon tumors decreases inflammatory cytokine expression and mitigates cancer-induced cachexia. However, the molecular mechanisms underlying the regulation of FN14 expression remain unclear. Tumor microenvironments are often devoid of nutrients and oxygen, yet how the cachexic response relates to the tumor microenvironment and, importantly, nutrient stress is unknown. Here, we looked at the connections between metabolic stress and FN14 expression. We found that TNFRSF12A expression was transcriptionally induced during glutamine deprivation in cancer cell lines. We also show that the downstream glutaminolysis metabolite, alpha-ketoglutarate (aKG), is sufficient to rescue glutamine-deprivation-promoted TNFRSF12A induction. As aKG is a co-factor for histone de-methylase, we looked at histone methylation and found that histone H3K4me3 at the Tnfrsf12a promoter is increased under glutamine-deprived conditions and rescued via DM-aKG supplementation. Finally, expression of Tnfrsf12a and cachexia-induced weight loss can be inhibited in vivo by DM-aKG in a mouse cancer cachexia model. These findings highlight a connection between metabolic stress and cancer cachexia development.

Bioinformatics and machine learning were used to validate glutamine metabolism-related genes and immunotherapy in osteoporosis patients

BACKGROUND

Osteoporosis (OP), often referred to as the "silent disease of the twenty-first century," poses a significant public health concern due to its severity, chronic nature, and progressive course, predominantly affecting postmenopausal women and elderly individuals. The pathogenesis and progression of this disease have been associated with dysregulation in tumor metabolic pathways. Notably, the metabolic utilization of glutamine has emerged as a critical player in cancer biology. While metabolic reprogramming has been extensively studied in various malignancies and linked to clinical outcomes, its comprehensive investigation within the context of OP remains lacking.

METHODS

This study aimed to identify and validate potential glutamine metabolism genes (GlnMgs) associated with OP through comprehensive bioinformatics analysis. The identification of GlnMgs was achieved by integrating the weighted gene co-expression network analysis and a set of 28 candidate GlnMgs. Subsequently, the putative biological functions and pathways associated with GlnMgs were elucidated using gene set variation analysis. The LASSO method was employed to identify key hub genes, and the diagnostic efficacy of five selected GlnMgs in OP detection was assessed. Additionally, the relationship between hub GlnMgs and clinical characteristics was investigated. Finally, the expression levels of the five GlnMgs were validated using independent datasets (GSE2208, GSE7158, GSE56815, and GSE35956).

RESULTS

Five GlnMgs, namely IGKC, TMEM187, RPS11, IGLL3P, and GOLGA8N, were identified in this study. To gain insights into their biological functions, particular emphasis was placed on synaptic transmission GABAergic, inward rectifier potassium channel activity, and the cytoplasmic side of the lysosomal membrane. Furthermore, the diagnostic potential of these five GlnMgs in distinguishing individuals with OP yielded promising results, indicating their efficacy as discriminative markers for OP.

CONCLUSIONS

This study discovered five GlnMgs that are linked to OP. They shed light on potential new biomarkers for OP and tracking its progression.

Metabolic partitioning in the brain and its hijacking by glioblastoma

The different cell types in the brain have highly specialized roles with unique metabolic requirements. Normal brain function requires the coordinated partitioning of metabolic pathways between these cells, such as in the neuron-astrocyte glutamate-glutamine cycle. An emerging theme in glioblastoma (GBM) biology is that malignant cells integrate into or "hijack" brain metabolism, co-opting neurons and glia for the supply of nutrients and recycling of waste products. Moreover, GBM cells communicate via signaling metabolites in the tumor microenvironment to promote tumor growth and induce immune suppression. Recent findings in this field point toward new therapeutic strategies to target the metabolic exchange processes that fuel tumorigenesis and suppress the anticancer immune response in GBM. Here, we provide an overview of the intercellular division of metabolic labor that occurs in both the normal brain and the GBM tumor microenvironment and then discuss the implications of these interactions for GBM therapy.

Glutamine metabolism genes prognostic signature for stomach adenocarcinoma and immune infiltration: potential biomarkers for predicting overall survival

Background

Stomach adenocarcinoma (STAD), caused by mutations in stomach cells, is characterized by poor overall survival. Chemotherapy is commonly administered for stomach cancer patients following surgical resection. An imbalance in tumor metabolic pathways is connected to tumor genesis and growth. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. Metabolic reprogramming is associated with clinical prognosis in various cancers. However, the role of glutamine metabolism genes (GlnMgs) in the fight against STAD remains poorly understood.

Methods

GlnMgs were determined in STAD samples from the TCGA and GEO datasets. The TCGA and GEO databases provide information on stemness indices (mRNAsi), gene mutations, copy number variations (CNV), tumor mutation burden (TMB), and clinical characteristics. Lasso regression was performed to build the prediction model. The relationship between gene expression and Gln metabolism was investigated using co-expression analysis.

Results

GlnMgs, found to be overexpressed in the high-risk group even in the absence of any symptomatology, demonstrated strong predictive potential for STAD outcomes. GSEA highlighted immunological and tumor-related pathways in the high-risk group. Immune function and m6a gene expression differed significantly between the low- and high-risk groups. AFP, CST6, CGB5, and ELANE may be linked to the oncology process in STAD patients. The prognostic model, CNVs, single nucleotide polymorphism (SNP), and medication sensitivity all revealed a strong link to the gene.

Conclusion

GlnMgs are connected to the genesis and development of STAD. These corresponding prognostic models aid in predicting the prognosis of STAD GlnMgs and immune cell infiltration in the tumor microenvironment (TME) may be possible therapeutic targets in STAD. Furthermore, the glutamine metabolism gene signature presents a credible alternative for predicting STAD outcomes, suggesting that these GlnMgs could open a new field of study for STAD-focused therapy Additional trials are needed to validate the results of the current study.

The role of tunneling nanotubes during early stages of HIV infection and reactivation: implications in HIV cure

Tunneling nanotubes (TNTs), also called cytonemes or tumor microtubes, correspond to cellular processes that enable long-range communication. TNTs are plasma membrane extensions that form tubular processes that connect the cytoplasm of two or more cells. TNTs are mostly expressed during the early stages of development and poorly expressed in adulthood. However, in disease conditions such as stroke, cancer, and viral infections such as HIV, TNTs proliferate, but their role is poorly understood. TNTs function has been associated with signaling coordination, organelle sharing, and the transfer of infectious agents such as HIV. Here, we describe the critical role and function of TNTs during HIV infection and reactivation, as well as the use of TNTs for cure strategies.

Glioblastoma Metabolism: Insights and Therapeutic Strategies

Tumor metabolism is emerging as a potential target for cancer therapies. This new approach holds particular promise for the treatment of glioblastoma, a highly lethal brain tumor that is resistant to conventional treatments, for which improving therapeutic strategies is a major challenge. The presence of glioma stem cells is a critical factor in therapy resistance, thus making it essential to eliminate these cells for the long-term survival of cancer patients. Recent advancements in our understanding of cancer metabolism have shown that glioblastoma metabolism is highly heterogeneous, and that cancer stem cells exhibit specific metabolic traits that support their unique functionality. The objective of this review is to examine the metabolic changes in glioblastoma and investigate the role of specific metabolic processes in tumorigenesis, as well as associated therapeutic approaches, with a particular focus on glioma stem cell populations.

Single-Voxel MR Spectroscopy of Gliomas with s-LASER at 7T

BACKGROUND AND PURPOSE

Magnetic resonance spectroscopy (MRS)-a method of analysing metabolites in vivo-has been utilized in several studies of brain glioma biomarkers at lower field strengths. At ultra-high field strengths, MRS provides an improved signal-to-noise-ratio and spectral resolution, but 7T studies on patients with gliomas are sparse. The purpose of this exploratory study was to evaluate the potential clinical implication of the use of single-voxel MRS at 7T to assess metabolic information on lesions in a pilot cohort of patients with grade II and III gliomas.

METHODS

We scanned seven patients and seven healthy controls using the semi-localization by adiabatic-selective refocusing sequence on a Philips Achieva 7T system with a standard dual-transmit head coil. The metabolic ratios were calculated relative to water and total creatine. Additionally, 2-hydroxyglutarate (2-HG) MRS was carried out in four of the patients, and the 2-HG concentration was calculated relative to water.

RESULTS

When comparing the tumour data to control regions in both patients and healthy controls, we found that the choline/creatine and myo-inositol/creatine ratios were significantly increased and that the N-acetylaspartate/creatine and the neurotransmitter glutamate/creatine ratios were significantly decreased. The N-acetylaspartate/water and glutamate/water ratios were also significantly decreased. The lactate/water and lactate/creatine ratios showed increases, although not significant. The GABA/water ratio was significantly decreased, but the GABA/creatine ratio was not. MRS spectra showed the presence of 2-HG in three of the four patients studied. Three of the patients, including the MRS 2-HG-negative patient, were operated on, and all of them had the IDH mutation.

CONCLUSION

Our findings were consistent with the existing literature on 3T and 7T MRS.

Identification of Some Glutamic Acid Derivatives with Biological Potential by Computational Methods

Glutamic acid is a non-essential amino acid involved in multiple metabolic pathways. Of high importance is its relationship with glutamine, an essential fuel for cancer cell development. Compounds that can modify glutamine or glutamic acid behaviour in cancer cells have resulted in attractive anticancer therapeutic alternatives. Based on this idea, we theoretically formulated 123 glutamic acid derivatives using Biovia Draw. Suitable candidates for our research were selected among them. For this, online platforms and programs were used to describe specific properties and their behaviour in the human organism. Nine compounds proved to have suitable or easy to optimise properties. The selected compounds showed cytotoxicity against breast adenocarcinoma, lung cancer cell lines, colon carcinoma, and T cells from acute leukaemia. Compound 2Ba5 exhibited the lowest toxicity, and derivative 4Db6 exhibited the most intense bioactivity. Molecular docking studies were also performed. The binding site of the 4Db6 compound in the glutamine synthetase structure was determined, with the D subunit and cluster 1 being the most promising. In conclusion, glutamic acid is an amino acid that can be manipulated very easily. Therefore, molecules derived from its structure have great potential to become innovative drugs, and further research on these will be conducted.

A novel Alzheimer's disease prognostic signature: identification and analysis of glutamine metabolism genes in immunogenicity and immunotherapy efficacy

Alzheimer's disease (AD) is characterized as a distinct onset and progression of cognitive and functional decline associated with age, as well as a specific neuropathology. It has been discovered that glutamine (Gln) metabolism plays a crucial role in cancer. However, a full investigation of its role in Alzheimer's disease is still missing. This study intended to find and confirm potential Gln-related genes associated with AD using bioinformatics analysis. The discovery of GlnMgs was made possible by the intersection of the WGCNA test and 26 Gln-metabolism genes (GlnMgs). GlnMgs' putative biological functions and pathways were identified using GSVA. The LASSO method was then used to identify the hub genes as well as the diagnostic efficiency of the four GlnMgs in identifying AD. The association between hub GlnMgs and clinical characteristics was also studied. Finally, the GSE63060 was utilized to confirm the levels of expression of the four GlnMgs. Four GlnMgs were discovered (ATP5H, NDUFAB1, PFN2, and SPHKAP). For biological function analysis, cell fate specification, atrioventricular canal development, and neuron fate specification were emphasized. The diagnostic ability of the four GlnMgs in differentiating AD exhibited a good value. This study discovered four GlnMgs that are linked to AD. They shed light on potential new biomarkers for AD and tracking its progression.

Perampanel in Brain Tumor-Related Epilepsy: A Systematic Review

Brain tumor-related epilepsy (BTRE) is a common comorbidity in patients with brain neoplasms and it may be either the first symptom or develop after the tumor diagnosis. Increasing evidence suggests that brain tumors and BTRE share common pathophysiological mechanisms. Glutamatergic mechanisms can play a central role in promoting both primary brain tumor growth and epileptogenesis. Perampanel (PER), which acts as a selective antagonist of glutamate α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors, may play a role both in the reduction in tumor growth and the control of epileptiform activity. This systematic review aimed to summarize the pre-clinical and clinical evidence about the antitumor properties, antiseizure effects and tolerability of PER in BTRE. Eight pre-clinical and eight clinical studies were identified. The currently available evidence suggests that PER can be an effective and generally well-tolerated therapeutic option in patients with BTRE. In vitro studies demonstrated promising antitumor activity of PER, while no role in slowing tumor progression has been demonstrated in rat models; clinical data on the potential antitumor activity of PER are scarce. Additional studies are needed to explore further the effects of PER on tumor progression and fully characterize its potentialities in patients with BTRE.

The Interleukin-11/IL-11 Receptor Promotes Glioblastoma Survival and Invasion under Glucose-Starved Conditions through Enhanced Glutaminolysis

Glioblastoma cells adapt to changes in glucose availability through metabolic plasticity allowing for cell survival and continued progression in low-glucose concentrations. However, the regulatory cytokine networks that govern the ability to survive in glucose-starved conditions are not fully defined. In the present study, we define a critical role for the IL-11/IL-11Rα signalling axis in glioblastoma survival, proliferation and invasion when cells are starved of glucose. We identified enhanced IL-11/IL-11Rα expression correlated with reduced overall survival in glioblastoma patients. Glioblastoma cell lines over-expressing IL-11Rα displayed greater survival, proliferation, migration and invasion in glucose-free conditions compared to their low-IL-11Rα-expressing counterparts, while knockdown of IL-11Rα reversed these pro-tumorigenic characteristics. In addition, these IL-11Rα-over-expressing cells displayed enhanced glutamine oxidation and glutamate production compared to their low-IL-11Rα-expressing counterparts, while knockdown of IL-11Rα or the pharmacological inhibition of several members of the glutaminolysis pathway resulted in reduced survival (enhanced apoptosis) and reduced migration and invasion. Furthermore, IL-11Rα expression in glioblastoma patient samples correlated with enhanced gene expression of the glutaminolysis pathway genes GLUD1, GSS and c-Myc. Overall, our study identified that the IL-11/IL-11Rα pathway promotes glioblastoma cell survival and enhances cell migration and invasion in environments of glucose starvation via glutaminolysis.

Epigenetics and Metabolism Reprogramming Interplay into Glioblastoma: Novel Insights on Immunosuppressive Mechanisms

The central nervous system represents a complex environment in which glioblastoma adapts skillfully, unleashing a series of mechanisms suitable for its efficient development and diffusion. In particular, changes in gene expression and mutational events that fall within the domain of epigenetics interact complexly with metabolic reprogramming and stress responses enacted in the tumor microenvironment, which in turn fuel genomic instability by providing substrates for DNA modifications. The aim of this review is to analyze this complex interaction that consolidates several conditions that confer a state of immunosuppression and immunoevasion, making glioblastoma capable of escaping attack and elimination by immune cells and therefore invincible against current therapies. The progressive knowledge of the cellular mechanisms that underlie the resistance of the glioblastoma represents, in fact, the only weapon to unmask its weak points to be exploited to plan successful therapeutic strategies.

Mechanical and metabolic interplay in the brain metastatic microenvironment

In this Perspective, we provide our insights and opinions about the contribution-and potential co-regulation-of mechanics and metabolism in incurable breast cancer brain metastasis. Altered metabolic activity can affect cancer metastasis as high glucose supply and demand in the brain microenvironment favors aerobic glycolysis. Similarly, the altered mechanical properties of disseminating cancer cells facilitate migration to and metastatic seeding of the brain, where local metabolites support their progression. Cancer cells in the brain and the brain tumor microenvironment often possess opposing mechanical and metabolic properties compared to extracranial cancer cells and their microenvironment, which inhibit the ease of extravasation and metastasis of these cells outside the central nervous system. We posit that the brain provides a metabolic microenvironment that mechanically reinforces the cellular structure of cancer cells and supports their metastatic growth while restricting their spread from the brain to external organs.

Review of Current Human Genome-Scale Metabolic Models for Brain Cancer and Neurodegenerative Diseases

Brain disorders represent 32% of the global disease burden, with 169 million Europeans affected. Constraint-based metabolic modelling and other approaches have been applied to predict new treatments for these and other diseases. Many recent studies focused on enhancing, among others, drug predictions by generating generic metabolic models of brain cells and on the contextualisation of the genome-scale metabolic models with expression data. Experimental flux rates were primarily used to constrain or validate the model inputs. Bi-cellular models were reconstructed to study the interaction between different cell types. This review highlights the evolution of genome-scale models for neurodegenerative diseases and glioma. We discuss the advantages and drawbacks of each approach and propose improvements, such as building bi-cellular models, tailoring the biomass formulations for glioma and refinement of the cerebrospinal fluid composition.

CD133-Functionalized Gold Nanoparticles as a Carrier Platform for Telaglenastat (CB-839) against Tumor Stem Cells

The failure of a long-lasting curative therapeutic benefit of currently applied chemotherapies against malignant cancers is suggested to be caused by the ineffectiveness of such interventions on cancer stem cells (CSCs). CD133/AC133 is a cell surface protein previously shown to have potential to identify CSCs in various tumors, including brain tumors. Moreover, an increase in the rate of cellular metabolism of glutamine and glucose are contributors to the fast cellular proliferation of some high-grade malignancies. Inhibition of glutaminolysis by utilizing pharmacological inhibitors of the enzyme glutaminase 1 (GLS1) can be an effective anti-CSC strategy. In this study, the clinical-stage GLS1 inhibitor Telaglenastat (CB-839) was loaded into PEGylated gold nanoparticles equipped with the covalently conjugated CD133 aptamer (Au-PEG-CD133-CB-839) and exposed to a collection of CD133-positive brain tumor models in vitro. Our results show that Au-PEG-CD133-CB-839 significantly decreased the viability of CD133-postive cancer cells in a dose-dependent manner, which was higher as compared to the effects of treatment of the cells with the individual components of the assembled nanodrug. Interestingly, the treatment effect was observed in glioblastoma stem cells modeling different transcriptomic subtypes of the disease. The presented platform is the fundament for subsequent target specificity characterization and in vivo application.

Correlation between amino acid metabolism and self-renewal of cancer stem cells: Perspectives in cancer therapy

Cancer stem cells (CSCs) possess self-renewal and differentiation potential, which may be related to recurrence, metastasis, and radiochemotherapy resistance during tumor treatment. Understanding the mechanisms via which CSCs maintain self-renewal may reveal new therapeutic targets for attenuating CSC resistance and extending patient life-span. Recent studies have shown that amino acid metabolism plays an important role in maintaining the self-renewal of CSCs and is involved in regulating their tumorigenicity characteristics. This review summarizes the relationship between CSCs and amino acid metabolism, and discusses the possible mechanisms by which amino acid metabolism regulates CSC characteristics particularly self-renewal, survival and stemness. The ultimate goal is to identify new targets and research directions for elimination of CSCs.

Emerging MR Imaging and Spectroscopic Methods to Study Brain Tumor Metabolism

Proton magnetic resonance spectroscopy (1H-MRS) provides a non-invasive biochemical profile of brain tumors. The conventional 1H-MRS methods present a few challenges mainly related to limited spatial coverage and low spatial and spectral resolutions. In the recent past, the advent and development of more sophisticated metabolic imaging and spectroscopic sequences have revolutionized the field of neuro-oncologic metabolomics. In this review article, we will briefly describe the scientific premises of three-dimensional echoplanar spectroscopic imaging (3D-EPSI), two-dimensional correlation spectroscopy (2D-COSY), and chemical exchange saturation technique (CEST) MRI techniques. Several published studies have shown how these emerging techniques can significantly impact the management of patients with glioma by determining histologic grades, molecular profiles, planning treatment strategies, and assessing the therapeutic responses. The purpose of this review article is to summarize the potential clinical applications of these techniques in studying brain tumor metabolism.

Cascade-activatable NO release based on GSH-detonated "nanobomb" for multi-pathways cancer therapy

Therapeutic approaches of combining conventional photodynamic therapy (PDT) with other adjuvant treatments to sensitize PDT represent an appealing strategy. Herein, a novel synergetic "nanobomb" strategy based on glutathione (GSH)-responsive biodegradation was proposed to effectively destroy tumors expeditiously and accurately. This "nanobomb" was rationally constructed via the simultaneous encapsulation of methylene blue (MB) and l-arginine (L-Arg) into polyethylene glycol (PEG) modified mesoporous organosilicon nanoparticles (MON). The resulting L-Arg/MB@MP initially exhibited prolonged blood circulation, improved bioavailability, and enhanced tumor accumulation in mice after tail vein injection according to the pharmacokinetic investigations, before the nanoparticles were entirely excreted. Under laser irradiation, L-Arg/MB@MP produced remarkable reactive oxygen species (ROS) directly for PDT therapy, while a portion of ROS may oxidize L-Arg to generate nitric oxide (NO) not only for gas therapy (GT) but also serve as a biological messenger to regulate vasodilation to alleviate the tumor hypoxia. Subsequently, the rapidly released NO was further oxidized to reactive nitrogen species, which together with ROS promote immunogenic cell death by inducing G2/M cell-cycle arrest and apoptosis in cancer cells, and eventually resulting in enhanced anti-tumor immune responses. Moreover, the GSH depletion in tumor tissues induced by L-Arg/MB@MP biodegradation can cooperate with GT to amplify the therapeutic effect of PDT. These results demonstrate that this "nanobomb" provides new ideas for clinical translation to treat tumor patients in terms of synergistic PDT-GT nanotherapy in hypoxic-solid tumors.

The expression of glutamate metabolism modulators in the intracranial tumors and glioblastoma cell line

BACKGROUND

The accumulation of excess glutamate in the synapse leads to excitotoxicity, which is the underlying reason of neuronal death in intracranial tumors.

METHODS AND RESULTS

We identified the expression levels of glutamate dehydrogenase, glutamine synthetase and sirtuin 4 in U87 cell line and various intracranial tumors. mRNA expressions of glutamate dehydrogenase (GDH), glutamine synthetase (GS) and sirtuin 4 (SIRT4) were analyzed in various intracranial tumors using qPCR. GDH, GS and SIRT4 protein expressions were analyzed in glioblastoma (U87) and glial (IHA-immortalized human astrocytes) cell lines via western blotting. The protein expressions of SIRT4 and GS were shown to be elevated and GDH protein expression was reduced in U87 cells in comparison to IHA cells. All types of intracranial tumors displayed lower GS mRNA expressions compared to controls. SIRT4 mRNA expressions were also shown to be lower in all the tumors and grades, although not significantly. GDH mRNA expression was found to be similar in all groups.

CONCLUSION

The molecular mechanisms of glutamate metabolism and excitotoxicity should be discovered to develop therapies against intracranial tumors.

The Neglected Liaison: Targeting Cancer Cell Metabolic Reprogramming Modifies the Composition of Non-Malignant Populations of the Tumor Microenvironment

Metabolic reprogramming is a well-known hallmark of cancer, whereby the development of drugs that target cancer cell metabolism is gaining momentum. However, when establishing preclinical studies and clinical trials, it is often neglected that a tumor mass is a complex system in which cancer cells coexist and interact with several types of microenvironment populations, including endothelial cells, fibroblasts and immune cells. We are just starting to understand how such populations are affected by the metabolic changes occurring in a transformed cell and little is known about the impact of metabolism-targeting drugs on the non-malignant tumor components. Here we provide a general overview of the links between cancer cell metabolism and tumor microenvironment (TME), particularly focusing on the emerging literature reporting TME-specific effects of metabolic therapies.

Dysregulated Alanine as a Potential Predictive Marker of Glioma-An Insight from Untargeted HRMAS-NMR and Machine Learning Data

Metabolic alterations play a crucial role in glioma development and progression and can be detected even before the appearance of the fatal phenotype. We have compared the circulating metabolic fingerprints of glioma patients versus healthy controls, for the first time, in a quest to identify a panel of small, dysregulated metabolites with potential to serve as a predictive and/or diagnostic marker in the clinical settings. High-resolution magic angle spinning nuclear magnetic resonance spectroscopy (HRMAS-NMR) was used for untargeted metabolomics and data acquisition followed by a machine learning (ML) approach for the analyses of large metabolic datasets. Cross-validation of ML predicted NMR spectral features was done by statistical methods (Wilcoxon-test) using JMP-pro16 software. Alanine was identified as the most critical metabolite with potential to detect glioma with precision of 1.0, recall of 0.96, and F1 measure of 0.98. The top 10 metabolites identified for glioma detection included alanine, glutamine, valine, methionine, N-acetylaspartate (NAA), γ-aminobutyric acid (GABA), serine, α-glucose, lactate, and arginine. We achieved 100% accuracy for the detection of glioma using ML algorithms, extra tree classifier, and random forest, and 98% accuracy with logistic regression. Classification of glioma in low and high grades was done with 86% accuracy using logistic regression model, and with 83% and 79% accuracy using extra tree classifier and random forest, respectively. The predictive accuracy of our ML model is superior to any of the previously reported algorithms, used in tissue- or liquid biopsy-based metabolic studies. The identified top metabolites can be targeted to develop early diagnostic methods as well as to plan personalized treatment strategies.

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.

Metabolic Drivers of Invasion in Glioblastoma

Glioblastoma is a primary malignant brain tumor with a median survival under 2 years. The poor prognosis glioblastoma caries is largely due to cellular invasion, which enables escape from resection, and drives inevitable recurrence. While most studies to date have focused on pathways that enhance the invasiveness of tumor cells in the brain microenvironment as the primary driving forces behind GBM’s ability to invade adjacent tissues, more recent studies have identified a role for adaptations in cellular metabolism in GBM invasion. Metabolic reprogramming allows invasive cells to generate the energy necessary for colonizing surrounding brain tissue and adapt to new microenvironments with unique nutrient and oxygen availability. Historically, enhanced glycolysis, even in the presence of oxygen (the Warburg effect) has dominated glioblastoma research with respect to tumor metabolism. More recent global profiling experiments, however, have identified roles for lipid, amino acid, and nucleotide metabolism in tumor growth and invasion. A thorough understanding of the metabolic traits that define invasive GBM cells may provide novel therapeutic targets for this devastating disease. In this review, we focus on metabolic alterations that have been characterized in glioblastoma, the dynamic nature of tumor metabolism and how it is shaped by interaction with the brain microenvironment, and how metabolic reprogramming generates vulnerabilities that may be ripe for exploitation.

Altered Metabolism in Glioblastoma: Myeloid-Derived Suppressor Cell (MDSC) Fitness and Tumor-Infiltrating Lymphocyte (TIL) Dysfunction

The metabolism of glioblastoma (GBM), the most aggressive and lethal primary brain tumor, is flexible and adaptable to different adverse conditions, such as nutrient deprivation. Beyond glycolysis, altered lipid metabolism is implicated in GBM progression. Indeed, metabolic subtypes were recently identified based on divergent glucose and lipid metabolism. GBM is also characterized by an immunosuppressive microenvironment in which myeloid-derived suppressor cells (MDSCs) are a powerful ally of tumor cells. Increasing evidence supports the interconnection between GBM and MDSC metabolic pathways. GBM cells exert a crucial contribution to MDSC recruitment and maturation within the tumor microenvironment, where the needs of tumor-infiltrating lymphocytes (TILs) with antitumor function are completely neglected. In this review, we will discuss the unique or alternative source of energy exploited by GBM and MDSCs, exploring how deprivation of specific nutrients and accumulation of toxic byproducts can induce T-cell dysfunction. Understanding the metabolic programs of these cell components and how they impact fitness or dysfunction will be useful to improve treatment modalities, including immunotherapeutic strategies.

MR-Guided Radiotherapy for Brain and Spine Tumors

MRI is the standard modality to assess anatomy and response to treatment in brain and spine tumors given its superb anatomic soft tissue contrast (e.g., T1 and T2) and numerous additional intrinsic contrast mechanisms that can be used to investigate physiology (e.g., diffusion, perfusion, spectroscopy). As such, hybrid MRI and radiotherapy (RT) devices hold unique promise for Magnetic Resonance guided Radiation Therapy (MRgRT). In the brain, MRgRT provides daily visualizations of evolving tumors that are not seen with cone beam CT guidance and cannot be fully characterized with occasional standalone MRI scans. Significant evolving anatomic changes during radiotherapy can be observed in patients with glioblastoma during the 6-week fractionated MRIgRT course. In this review, a case of rapidly changing symptomatic tumor is demonstrated for possible therapy adaptation. For stereotactic body RT of the spine, MRgRT acquires clear isotropic images of tumor in relation to spinal cord, cerebral spinal fluid, and nearby moving organs at risk such as bowel. This visualization allows for setup reassurance and the possibility of adaptive radiotherapy based on anatomy in difficult cases. A review of the literature for MR relaxometry, diffusion, perfusion, and spectroscopy during RT is also presented. These techniques are known to correlate with physiologic changes in the tumor such as cellularity, necrosis, and metabolism, and serve as early biomarkers of chemotherapy and RT response correlating with patient survival. While physiologic tumor investigations during RT have been limited by the feasibility and cost of obtaining frequent standalone MRIs, MRIgRT systems have enabled daily and widespread physiologic measurements. We demonstrate an example case of a poorly responding tumor on the 0.35 T MRIgRT system with relaxometry and diffusion measured several times per week. Future studies must elucidate which changes in MR-based physiologic metrics and at which timepoints best predict patient outcomes. This will lead to early treatment intensification for tumors identified to have the worst physiologic responses during RT in efforts to improve glioblastoma survival.