Altered lipid metabolism marks glioblastoma stem and non-stem cells in separate tumor niches

Metabolism: an important player in glioma survival and development

Gliomas are malignant tumors originating from both neuroglial cells and neural stem cells. The involvement of neural stem cells contributes to the tumor's heterogeneity, affecting its metabolic features, development, and response to therapy. This review provides a brief introduction to the importance of metabolism in gliomas before systematically categorizing them into specific groups based on their histological and molecular genetic markers. Metabolism plays a critical role in glioma biology, as tumor cells rely heavily on altered metabolic pathways to support their rapid growth, survival, and progression. Dysregulated metabolic processes, involving carbohydrates, lipids, and amino acids not only fuel tumor development but also contribute to therapy resistance and metastatic potential. By understanding these metabolic changes, key intervention points, such as mutations in genes like RTK, EGFR, RAS, and IDH can be identified, paving the way for novel therapeutic strategies. This review emphasizes the connection between metabolic pathways and clinical challenges, offering actionable insights for future research and therapeutic development in gliomas.

Analyzing research trends in glioblastoma metabolism: a bibliometric review

Background

A bibliometric and visual analysis of articles related to glioblastoma metabolism was conducted to reveal the dynamics of scientific development and to assist researchers in gaining a global perspective when exploring hotspots and trends.

Methods

The Web of Science Core Collection (WoSCC) was employed to search, screen, and download articles about glioblastoma metabolism published between 2014 and 2024. The relevant literature was analyzed using CiteSpace, VOSviewer and Microsoft Excel.

Results

A total of 729 articles were included for bibliometric analysis between 2014 and 2024, and the number of articles published each year showed an overall increasing trend, except for a decrease in the number of articles published in 2018 compared to 2017. Collaboration network analysis showed that the United States, Germany and China are influential countries in this field, with a high number of articles published, citations and collaborations with other countries. The journal with the largest number of published articles is the International Journal of Molecular Sciences. Mischel PS is the most prolific author with 14 articles, and Guo DL received the most citations with 104 citations. Keyword analysis of the literature showed that the "Warburg effect" achieved the highest burst intensity, and "central nervous system", "classification" and "fatty acids" showed stronger citation bursts in 2024, indicating that they are still popular topics so far.

Conclusion

This article elucidates the research trends and focal points in the field of glioblastoma metabolism, furnishes invaluable insights into the historical and contemporary status of this field, and offers guidance for future research. Further research into glioblastoma metabolism will undoubtedly yield new insights that will inform the diagnosis and treatment of this disease.

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.

Metabolomic characterization of human glioblastomas and patient plasma: a pilot study

Background

Glioblastoma (GBM) is a clinically challenging primary brain tumor with poor survival outcome despite surgical resection and intensive chemoradiation. The metabolic heterogeneity of GBM can become biomarkers for treatment response, resistance, and outcome prediction. The aim of the study is to investigate metabolic distinctions between primary and recurrent GBM tissue and patient plasma to establish feasibility for metabolic profiling.

Methods

A single-center cohort study analyzed tissue and blood samples from 15 patients with GBM using untargeted metabolomic/lipidomic assays. Metabolomic, lipidomic, and biogenic amine analyses were conducted on GBM tissue and patient plasma at diagnosis and recurrence using untargeted mass spectrometry. The study utilized a small but longitudinally collected cohort to evaluate alteration in metabolites, lipids, and biogenic amines between specimens at diagnosis and recurrence.

Results

Exploratory analysis revealed significant alteration in metabolites, lipids, and biogenic amines between diagnostic and recurrent states in both tumor and plasma specimens. Notable metabolites differed at recurrence, including N-alpha-methylhistamine, glycerol-3-phosphate, phosphocholine, and succinic acid in tissue, and indole-3-acetate, and urea in plasma. Principal component analysis revealed distinct metabolomic profiles between tumor tissue and patient plasma. Distinct metabolic profiles were observed in GBM tissue and patient plasma at recurrence, demonstrating the feasibility of using metabolomic methodologies for longitudinal studies. One patient exhibited a unique tumor resistance signature at diagnosis, possibly indicating a high-risk metabolomic phenotype.

Conclusions

In this small cohort, the findings suggest the potential of metabolomic signatures of GBM tissue and patient plasma for risk stratification, outcome prediction, and the development of novel adjuvant metabolic-targeting therapies. The findings suggest metabolic discrepancies at diagnosis and recurrence in tissue and plasma, highlighting potential implications for evaluation of clinical response. The identification of significant changes in metabolite abundance emphasizes the need for larger studies using targeted metabolomics to validate and further explore these profiles.

Metformin and its potential influence on cell fate decision between apoptosis and senescence in cancer, with a special emphasis on glioblastoma

Despite reaching enormous achievements in therapeutic approaches worldwide, GBM still remains the most incurable malignancy among various cancers. It emphasizes the necessity of adjuvant therapies from the perspectives of both patients and healthcare providers. Therefore, most emerging studies have focused on various complementary and adjuvant therapies. Among them, metabolic therapy has received special attention, and metformin has been considered as a treatment in various types of cancer, including GBM. It is clearly evident that reaching efficient approaches without a comprehensive evaluation of the key mechanisms is not possible. Among the studied mechanisms, one of the more challenging ones is the effect of metformin on apoptosis and senescence. Moreover, metformin is well known as an insulin sensitizer. However, if insulin signaling is facilitated in the tumor microenvironment, it may result in tumor growth. Therefore, to partially resolve some paradoxical issues, we conducted a narrative review of related studies to address the following questions as comprehensively as possible: 1) Does the improvement of cellular insulin function resulting from metformin have detrimental or beneficial effects on GBM cells? 2) If these effects are detrimental to GBM cells, which is more important: apoptosis or senescence? 3) What determines the cellular decision between apoptosis and senescence?

MYC-Mediated Inhibition of ARNT2 Uncovers a Key Tumor Suppressor in Glioblastoma

Tumor initiation and progression rely on intricate cellular pathways that promote proliferation while suppressing differentiation, yet the importance of pathways inhibiting differentiation in cancer remains incompletely understood. Here, we reveal a novel mechanism centered on the repression of the neuronal-specific transcription factor ARNT2 by the MYC oncogene that governs the balance between proliferation and differentiation. We found that MYC coordinates the transcriptional repression of ARNT2 through the activity of polycomb repressive complex 2 (PRC2). Notably, ARNT2, highly and specifically expressed in the central nervous system, is diminished in glioblastoma, inversely correlating with patient survival. Utilizing in vitro and in vivo models, we demonstrate that ARNT2 knockout (KO) exerts no discernible effect on the in vitro proliferation of glioblastoma cells, but significantly enhances the growth of glioblastoma cells in vivo. Conversely, ARNT2 overexpression severely dampens the growth of fully transformed glioblastoma cells subcutaneously or orthotopically xenografted in mice. Mechanistically, ARNT2 depletion diminishes differentiation and enhances stemness of glioblastoma cells. Our findings provide new insights into the complex mechanisms used by oncogenes to limit differentiation in cancer cells and define ARNT2 as a tumor suppressor in glioblastoma.

SCD1 promotes the stemness of gastric cancer stem cells by inhibiting ferroptosis through the SQLE/cholesterol/mTOR signalling pathway

Cancer stem cells (CSCs) play a substantial role in cancer onset and recurrence. Anomalous iron and lipid metabolism have been documented in CSCs, suggesting that ferroptosis, a recently discovered form of regulated cell death characterised by lipid peroxidation, could potentially exert a significant influence on CSCs. However, the precise role of ferroptosis in gastric cancer stem cells (GCSCs) remains unknown. To address this gap, we screened ferroptosis-related genes in GCSCs using The Cancer Genome Atlas and corroborated our findings through quantitative polymerase chain reaction and western blotting. These results indicate that stearoyl-CoA desaturase (SCD1) is a key player in the regulation of ferroptosis in GCSCs. This study provides evidence that SCD1 positively regulates the transcription of squalene epoxidase (SQLE) by eliminating transcriptional inhibition of P53. This mechanism increases the cholesterol content and the elevated cholesterol regulated by SCD1 inhibits ferroptosis via the mTOR signalling pathway. Furthermore, our in vivo studies showed that SCD1 knockdown or regulation of cholesterol intake affects the stemness of GCSCs and their sensitivity to ferroptosis inducers. Thus, targeting the SCD1/squalene epoxidase/cholesterol signalling axis in conjunction with ferroptosis inducers may represent a promising therapeutic approach for the treatment of gastric cancer based on GCSCs.

Expression and prognostic significance of microsomal triglyceride transfer protein in brain tumors: a retrospective cohort study

Background

Glioblastoma (GBM) is the most common malignant brain tumor and has poor survival. An elevated cholesterol level is involved occurrence and progression of brain tumors. Microsomal triglyceride transfer protein (MTTP) is a target for lowering lipids, and its inhibition helps to improve hyperlipidemia. However, whether the altered expression of MTTP affects the development and prognosis of brain tumors is currently unidentified. The purpose of this study is to determine MTTP as a prognostic marker for brain tumors.

Methods

Data for patients with brain cancers and control brain tissue were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The datasets were analyzed using Mann-Whitney U-test or t-test to compare the expression of MTTP in normal and brain tumor tissues. To examine whether MTTP affected the prognosis of patients with brain tumors, log-rank test and multivariable Cox proportional hazard regression were conducted.

Results

The expression of MTTP was significantly upregulated in brain tumors and was correlated with age, tumor stage, and isocitrate dehydrogenase (IDH) mutation. Importantly, increased MTTP expression in brain tumors is associated with poor patient survival.

Conclusions

High MTTP expression is associated with brain tumor development, tumor stage, and prognosis. Therefore, MTTP is an independent prognostic indicator for brain tumors, which can serve as one of the possible targets for adjuvant treatment of GBM.

Application of the Hydrophilic Interaction Liquid Chromatography (HILIC-MS) Novel Protocol to Study the Metabolic Heterogeneity of Glioblastoma Cells

Glioblastoma is a highly malignant brain tumor consisting of a heterogeneous cellular population. The transformed metabolism of glioblastoma cells supports their growth and division on the background of their milieu. One might hypothesize that the transformed metabolism of a primary glioblastoma could be well adapted to limitations in the variety and number of substrates imported into the brain parenchyma and present it their microenvironment. Additionally, the phenotypic heterogeneity of cancer cells could promote the variations among their metabolic capabilities regarding the utilization of available substrates and release of metabolic intermediates. With the aim to identify the putative metabolic footprint of different types of glioblastoma cells, we exploited the possibility for separation of polar and ionic molecules present in culture media or cell lysates by hydrophilic interaction liquid chromatography (HILIC). The mass spectrometry (MS) was then used to identify and quantify the eluted compounds. The introduced method allows the detection and quantification of more than 150 polar and ionic metabolites in a single run, which may be present either in culture media or cell lysates and provide data for polaromic studies within metabolomics. The method was applied to analyze the culture media and cell lysates derived from two types of glioblastoma cells, T98G and U118. The analysis revealed that even both types of glioblastoma cells share several common metabolic aspects, and they also exhibit differences in their metabolic capability. This finding agrees with the hypothesis about metabolic heterogeneity of glioblastoma cells. Furthermore, the combination of both analytical methods, HILIC-MS, provides a valuable tool for metabolomic studies based on the simultaneous identification and quantification of a wide range of polar and ionic metabolites-polaromics.

WITHDRAWN: LonP1 Drives Proneural Mesenchymal Transition in IDH1-R132H Diffuse Glioma

The authors have withdrawn their manuscript owing to massive revision and data validation. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

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.

Hsa_circ_0021205 enhances lipolysis via regulating miR-195-5p/HSL axis and drives malignant progression of glioblastoma

Abnormal lipid metabolism is an essential hallmark of glioblastoma. Hormone sensitive lipase (HSL), an important rate-limiting enzyme contributed to lipolysis, which was involved in aberrant lipolysis of glioblastoma, however, its definite roles and the relevant regulatory pathway have not been fully elucidated. Our investigations disclosed high expression of HSL in glioblastoma. Knock-down of HSL restrained proliferation, migration, and invasion of glioblastoma cells while adding to FAs could significantly rescue the inhibitory effect of si-HSL on tumor cells. Overexpression of HSL further promoted tumor cell proliferation and invasion. Bioinformatics analysis and dual-luciferase reporter assay were performed to predict and verify the regulatory role of ncRNAs on HSL. Mechanistically, hsa_circ_0021205 regulated HSL expression by sponging miR-195-5p, which further promoted lipolysis and drove the malignant progression of glioblastoma. Besides, hsa_circ_0021205/miR-195-5p/HSL axis activated the epithelial-mesenchymal transition (EMT) signaling pathway. These findings suggested that hsa_circ_0021205 promoted tumorigenesis of glioblastoma through regulation of HSL, and targeting hsa_circ_0021205/miR-195-5p/HSL axis can serve as a promising new strategy against glioblastoma.

Should I stay or should I go? Transsulfuration influences invasion and growth in glioblastoma

A major challenge in treating patients with glioblastoma is the inability to eliminate highly invasive cells with chemotherapy, radiation, or surgical resection. As cancer cells face the issue of replicating or invading neighboring tissue, they rewire their metabolism in a concerted effort to support necessary cellular processes and account for altered nutrient abundance. In this issue of the JCI, Garcia et al. compared an innovative 3D hydrogel-based invasion device to regional patient biopsies through a comprehensive multiomics-based approach paired with a CRISPR knockout screen. Their findings elucidate a role for cystathionine γ-lyase (CTH), an enzyme in the transsulfuration pathway, as a means of regulating the cellular response to oxidative stress. CTH-mediated conversion of cystathionine to cysteine was necessary for regulating reactive oxygen species to support invasion. Meanwhile, inhibition of CTH suppressed the invasive glioblastoma phenotype. However, inhibiting CTH resulted in a larger overall tumor mass. These findings suggest that targeting the transsulfuration pathway may serve as a means of redirecting glioblastoma to proliferate or invade.

CD36 as a double-edged sword in cancer

The membrane protein CD36 is a lipid transporter, scavenger receptor, and receptor for the antiangiogenic protein thrombospondin 1 (TSP1). CD36 is expressed by cancer cells and by many associated cells including various cancer-infiltrating immune cell types. Thereby, CD36 plays critical roles in cancer, and it has been reported to affect cancer growth, metastasis, angiogenesis, and drug resistance. However, these roles are partly contradictory, as CD36 has been both reported to promote and inhibit cancer progression. Moreover, the mechanisms are also partly contradictory, because CD36 has been shown to exert opposite cellular effects such as cell division, senescence and cell death. This review provides an overview of the diverse effects of CD36 on tumor progression, aiming to shed light on its diverse pro- and anti-cancer roles, and the implications for therapeutic targeting.

Emerging Lipid Targets in Glioblastoma

GBM accounts for most of the fatal brain cancer cases, making it one of the deadliest tumor types. GBM is characterized by severe progression and poor prognosis with a short survival upon conventional chemo- and radiotherapy. In order to improve therapeutic efficiency, considerable efforts have been made to target various features of GBM. One of the targetable features of GBM is the rewired lipid metabolism that contributes to the tumor's aggressive growth and penetration into the surrounding brain tissue. Lipid reprogramming allows GBM to acquire survival, proliferation, and invasion benefits as well as supportive modulation of the tumor microenvironment. Several attempts have been made to find novel therapeutic approaches by exploiting the lipid metabolic reprogramming in GBM. In recent studies, various components of de novo lipogenesis, fatty acid oxidation, lipid uptake, and prostaglandin synthesis have been considered promising targets in GBM. Emerging data also suggest a significant role hence therapeutic potential of the endocannabinoid metabolic pathway in GBM. Here we review the lipid-related GBM characteristics in detail and highlight specific targets with their potential therapeutic use in novel antitumor approaches.

Investigating the Metabolic Heterogeneity of Cancer Cells Using Functional Single-Cell Selection and nLC Combined with Multinozzle Emitter Mass Spectrometry

Tumor metastasis and cancer recurrence are often a result of cell heterogeneity, where specific subpopulations of tumor cells may be resistant to radio- or chemotherapy. To investigate this physiological and phenotypic diversity, single-cell metabolomics provides a powerful approach at the chemical level, where distinct lipid profiles can be found in different tumor cells. Here, we established a highly sensitive platform using nanoflow liquid chromatography (nLC) combined with multinozzle emitter electrospray ionization mass spectrometry for more in-depth metabolomics profiling. Our platform identified 15 and 17 lipids from individual osteosarcoma (U2OS) and glioblastoma (GBM) cells when analyzing single-cell samples. Additionally, we used the functional single-cell selection (fSCS) pipeline to analyze the subpopulations of cells with a DNA damage response (DDR) in U2OS cells and fast migration in GBM cells. Specifically, we observed a down-regulation of polyunsaturated fatty acids (PUFAs) in U2OS cells undergoing DDR, such as fatty acids FA 20:3; O2 and FA 17:4; O3. Furthermore, ceramides (Cer 38:0; O3) and triglycerides (TG 36:0) were found to be down-regulated in fast-migrating GBM cells compared to the slow-migrating subpopulation. These findings suggest the potential roles of these metabolites and/or lipids in the cellular behavior of the subpopulations.

Metabolic heterogeneity in cancer

Cancer cells rewire their metabolism to survive during cancer progression. In this context, tumour metabolic heterogeneity arises and develops in response to diverse environmental factors. This metabolic heterogeneity contributes to cancer aggressiveness and impacts therapeutic opportunities. In recent years, technical advances allowed direct characterisation of metabolic heterogeneity in tumours. In addition to the metabolic heterogeneity observed in primary tumours, metabolic heterogeneity temporally evolves along with tumour progression. In this Review, we summarize the mechanisms of environment-induced metabolic heterogeneity. In addition, we discuss how cancer metabolism and the key metabolites and enzymes temporally and functionally evolve during the metastatic cascade and treatment.

Targeting lipid metabolism in cancer metastasis

This review delves into the most recent research on the metabolic adaptability of cancer cells and examines how their metabolic functions can impact their progression into metastatic forms. We emphasize the growing significance of lipid metabolism and dietary lipids within the tumor microenvironment, underscoring their influence on tumor progression. Additionally, we present an outline of the interplay between metabolic processes and the epigenome of cancer cells, underscoring the importance regarding the metastatic process. Lastly, we examine the potential of targeting metabolism as a therapeutic approach in combating cancer progression, shedding light on innovative drugs/targets currently undergoing preclinical evaluation.

Stationary-to-migratory transition in glioblastoma stem-like cells driven by a fatty acid-binding protein 7-RXRα neurogenic pathway

BACKGROUND

Glioblastoma (GBM) stem-like cells (GSCs) are crucial drivers of treatment resistance and tumor recurrence. While the concept of "migrating" cancer stem cells was proposed a decade ago, the roles and underlying mechanisms of the heterogeneous populations of GSCs remain poorly defined.

METHODS

Cell migration using GBM cell lines and patient-derived GSCs was examined using Transwell inserts and the scratch assay. Single-cell RNA sequencing data analysis were used to map GSC drivers to specific GBM cell populations. Xenografted mice were used to model the role of brain-type fatty acid-binding protein 7 (FABP7) in GBM infiltration and expansion. The mechanism by which FABP7 and its fatty acid ligands promote GSC migration was examined by gel shift and luciferase gene reporter assays.

RESULTS

A subpopulation of FABP7-expressing migratory GSCs was identified, with FABP7 upregulating SOX2, a key modulator for GBM stemness and plasticity, and ZEB1, a prominent factor in GBM epithelial-mesenchymal transition and invasiveness. Our data indicate that GSC migration is driven by nuclear FABP7 through activation of RXRα, a nuclear receptor activated by polyunsaturated fatty acids (PUFAs).

CONCLUSION

Infiltrative progression in GBM is driven by migratory GSCs through activation of a PUFA-FABP7-RXRα neurogenic pathway.

Metabolic Profiles of Cancer Stem Cells and Normal Stem Cells and Their Therapeutic Significance

Cancer stem cells (CSCs) are a rare cancer cell population, responsible for the facilitation, progression, and resistance of tumors to therapeutic interventions. This subset of cancer cells with stemness and tumorigenic properties is organized in niches within the tumor microenvironment (TME) and presents altered regulation in a variety of metabolic pathways, including glycolysis, oxidative phosphorylation (OXPHOS), as well as lipid, amino acid, and iron metabolism. CSCs exhibit similarities as well as differences when comparedto normal stem cells, but also possess the ability of metabolic plasticity. In this review, we summarize the metabolic characteristics of normal, non-cancerous stem cells and CSCs. We also highlight the significance and implications of interventions targeting CSC metabolism to potentially achieve more robust clinical responses in the future.

Rapid, label-free classification of glioblastoma differentiation status combining confocal Raman spectroscopy and machine learning

Label-free identification of tumor cells using spectroscopic assays has emerged as a technological innovation with a proven ability for rapid implementation in clinical care. Machine learning facilitates the optimization of processing and interpretation of extensive data, such as various spectroscopy data obtained from surgical samples. The here-described preclinical work investigates the potential of machine learning algorithms combining confocal Raman spectroscopy to distinguish non-differentiated glioblastoma cells and their respective isogenic differentiated phenotype by means of confocal ultra-rapid measurements. For this purpose, we measured and correlated modalities of 1146 intracellular single-point measurements and sustainingly clustered cell components to predict tumor stem cell existence. By further narrowing a few selected peaks, we found indicative evidence that using our computational imaging technology is a powerful approach to detect tumor stem cells in vitro with an accuracy of 91.7% in distinct cell compartments, mainly because of greater lipid content and putative different protein structures. We also demonstrate that the presented technology can overcome intra- and intertumoral cellular heterogeneity of our disease models, verifying the elevated physiological relevance of our applied disease modeling technology despite intracellular noise limitations for future translational evaluation.

Tumor cell-derived spermidine promotes a pro-tumorigenic immune microenvironment in glioblastoma via CD8+ T cell inhibition

The glioblastoma microenvironment is enriched in immunosuppressive factors that potently interfere with the function of cytotoxic T lymphocytes. Cancer cells can directly impact the immune system, but the mechanisms driving these interactions are not completely clear. Here we demonstrate that the polyamine metabolite spermidine is elevated in the glioblastoma tumor microenvironment. Exogenous administration of spermidine drives tumor aggressiveness in an immune-dependent manner in pre-clinical mouse models via reduction of CD8+ T cell frequency and phenotype. Knockdown of ornithine decarboxylase, the rate-limiting enzyme in spermidine synthesis, did not impact cancer cell growth in vitro but did result in extended survival. Furthermore, glioblastoma patients with a more favorable outcome had a significant reduction in spermidine compared to patients with a poor prognosis. Our results demonstrate that spermidine functions as a cancer cell-derived metabolite that drives tumor progression by reducing CD8+T cell number and function.

Glioblastomas: Hijacking Metabolism to Build a Flexible Shield for Therapy Resistance

Significance: Glioblastomas (GBMs) are among the most lethal tumors despite the almost exclusive localization to the brain. This is largely due to therapeutic resistance. Radiation and chemotherapy significantly increase the survival for GBM patients, however, GBMs always recur, and the median overall survival is just over a year. Proposed reasons for such intractable resistance to therapy are numerous and include tumor metabolism, in particular, the ability of tumor cells to reconfigure metabolic fluxes on demand (metabolic plasticity). Understanding how the hard-wired, oncogene-driven metabolic tendencies of GBMs intersect with flexible, context-induced metabolic rewiring promises to reveal novel approaches for combating therapy resistance. Recent Advances: Personalized genome-scale metabolic flux models have recently provided evidence that metabolic flexibility promotes radiation resistance in cancer and identified tumor redox metabolism as a major predictor for resistance to radiation therapy (RT). It was demonstrated that radioresistant tumors, including GBM, reroute metabolic fluxes to boost the levels of reducing factors of the cell, thus enhancing clearance of reactive oxygen species that are generated during RT and promoting survival. Critical Issues: The current body of knowledge from published studies strongly supports the notion that robust metabolic plasticity can act as a (flexible) shield against the cytotoxic effects of standard GBM therapies, thus driving therapy resistance. The limited understanding of the critical drivers of such metabolic plasticity hampers the rational design of effective combination therapies. Future Directions: Identifying and targeting regulators of metabolic plasticity, rather than specific metabolic pathways, in combination with standard-of-care treatments have the potential to improve therapeutic outcomes in GBM. Antioxid. Redox Signal. 39, 957-979.

Self-Functionalized Superlattice Nanosensor Enables Glioblastoma Diagnosis Using Liquid Biopsy

Glioblastoma (GBM), the most aggressive and lethal brain cancer, is detected only in the advanced stage, resulting in a median survival rate of 15 months. Therefore, there is an urgent need to establish GBM diagnosis tools to identify the tumor accurately. The clinical relevance of the current liquid biopsy techniques for GBM diagnosis remains mostly undetermined, owing to the challenges posed by the blood-brain barrier (BBB) that restricts biomarkers entering the circulation, resulting in the unavailability of clinically validated circulating GBM markers. GBM-specific liquid biopsy for diagnosis and prognosis of GBM has not yet been developed. Here, we introduce extracellular vesicles of GBM cancer stem cells (GBM CSC-EVs) as a previously unattempted, stand-alone GBM diagnosis modality. As GBM CSCs are fundamental building blocks of tumor initiation and recurrence, it is desirable to investigate these reliable signals of malignancy in circulation for accurate GBM diagnosis. So far, there are no clinically validated circulating biomarkers available for GBM. Therefore, a marker-free approach was essential since conventional liquid biopsy relying on isolation methodology was not viable. Additionally, a mechanism capable of trace-level detection was crucial to detecting the rare GBM CSC-EVs from the complex environment in circulation. To break these barriers, we applied an ultrasensitive superlattice sensor, self-functionalized for surface-enhanced Raman scattering (SERS), to obtain holistic molecular profiling of GBM CSC-EVs with a marker-free approach. The superlattice sensor exhibited substantial SERS enhancement and ultralow limit of detection (LOD of attomolar 10-18 M concentration) essential for trace-level detection of invisible GBM CSC-EVs directly from patient serum (without isolation). We detected as low as 5 EVs in 5 μL of solution, achieving the lowest LOD compared to existing SERS-based studies. We have experimentally demonstrated the crucial role of the signals of GBM CSC-EVs in the precise detection of glioblastoma. This was evident from the unique molecular profiles of GBM CSC-EVs demonstrating significant variation compared to noncancer EVs and EVs of GBM cancer cells, thus adding more clarity to the current understanding of GBM CSC-EVs. Preliminary validation of our approach was undertaken with a small amount of peripheral blood (5 μL) derived from GBM patients with 100% sensitivity and 97% specificity. Identification of the signals of GBM CSC-EV in clinical sera specimens demonstrated that our technology could be used for accurate GBM detection. Our technology has the potential to improve GBM liquid biopsy, including real-time surveillance of GBM evolution in patients upon clinical validation. This demonstration of liquid biopsy with GBM CSC-EV provides an opportunity to introduce a paradigm potentially impacting the current landscape of GBM diagnosis.

Applications of organoid technology to brain tumors

Lacking appropriate model impedes basic and preclinical researches of brain tumors. Organoids technology applying on brain tumors enables great recapitulation of the original tumors. Here, we compared brain tumor organoids (BTOs) with common models including cell lines, tumor spheroids, and patient-derived xenografts. Different BTOs can be customized to research objectives and particular brain tumor features. We systematically introduce the establishments and strengths of four different BTOs. BTOs derived from patient somatic cells are suitable for mimicking brain tumors caused by germline mutations and abnormal neurodevelopment, such as the tuberous sclerosis complex. BTOs derived from human pluripotent stem cells with genetic manipulations endow for identifying and understanding the roles of oncogenes and processes of oncogenesis. Brain tumoroids are the most clinically applicable BTOs, which could be generated within clinically relevant timescale and applied for drug screening, immunotherapy testing, biobanking, and investigating brain tumor mechanisms, such as cancer stem cells and therapy resistance. Brain organoids co-cultured with brain tumors (BO-BTs) own the greatest recapitulation of brain tumors. Tumor invasion and interactions between tumor cells and brain components could be greatly explored in this model. BO-BTs also offer a humanized platform for testing the therapeutic efficacy and side effects on neurons in preclinical trials. We also introduce the BTOs establishment fused with other advanced techniques, such as 3D bioprinting. So far, over 11 brain tumor types of BTOs have been established, especially for glioblastoma. We conclude BTOs could be a reliable model to understand brain tumors and develop targeted therapies.

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.

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.

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.

Biosynthesis and Significance of Fatty Acids, Glycerophospholipids, and Triacylglycerol in the Processes of Glioblastoma Tumorigenesis

One area of glioblastoma research is the metabolism of tumor cells and detecting differences between tumor and healthy brain tissue metabolism. Here, we review differences in fatty acid metabolism, with a particular focus on the biosynthesis of saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), and polyunsaturated fatty acids (PUFA) by fatty acid synthase (FASN), elongases, and desaturases. We also describe the significance of individual fatty acids in glioblastoma tumorigenesis, as well as the importance of glycerophospholipid and triacylglycerol synthesis in this process. Specifically, we show the significance and function of various isoforms of glycerol-3-phosphate acyltransferases (GPAT), 1-acylglycerol-3-phosphate O-acyltransferases (AGPAT), lipins, as well as enzymes involved in the synthesis of phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS), phosphatidylinositol (PI), and cardiolipin (CL). This review also highlights the involvement of diacylglycerol O-acyltransferase (DGAT) in triacylglycerol biosynthesis. Due to significant gaps in knowledge, the GEPIA database was utilized to demonstrate the significance of individual enzymes in glioblastoma tumorigenesis. Finally, we also describe the significance of lipid droplets in glioblastoma and the impact of fatty acid synthesis, particularly docosahexaenoic acid (DHA), on cell membrane fluidity and signal transduction from the epidermal growth factor receptor (EGFR).

The utility of 3D models to study cholesterol in cancer: Insights and future perspectives

Cholesterol remains a vital molecule required for life; however, increasing evidence exists implicating cholesterol in cancer development and progression. Numerous studies investigating the relationship between cholesterol and cancer in 2-dimensional (2D) culture settings exist, however these models display inherent limitations highlighting the incipient need to develop better models to study disease pathogenesis. Due to the multifaceted role cholesterol plays in the cell, researchers have begun utilizing 3-dimensional (3D) culture systems, namely, spheroids and organoids to recapitulate cellular architecture and function. This review aims to describe current studies exploring the relationship between cancer and cholesterol in a variety of cancer types using 3D culture systems. We briefly discuss cholesterol dyshomeostasis in cancer and introduce 3D in-vitro culture systems. Following this, we discuss studies performed in cancerous spheroid and organoid models that focused on cholesterol, highlighting the dynamic role cholesterol plays in various cancer types. Finally, we attempt to provide potential gaps in research that should be explored in this rapidly evolving field of study.

A pilot study on metabolomic characterization of human glioblastomas and patient plasma

Purpose

To determine whether recurrent GBMs are metabolically distinct from primary GBM, and whether patient plasma can be used as a liquid biopsy to reflect this difference.

Methods

In a single center cohort study, tissue and blood samples from 15 patients with glioblastoma (9 glioblastoma tissues at diagnosis, 3 pairs of tissue, and 6 pairs of plasma specimens at diagnosis and at recurrence) were analyzed.

Results

Several metabolites had significant alternations in both tumor and plasma specimens. In the tissue, the following representative metabolites had a significant increase in peak intensity at recurrence compared to diagnosis: N-alpha-methylhistamine (p = 0.037), glycerol-3-phosphate (p = 0.029), phosphocholine (p = 0.045), and succinic acid (p = 0.025). In patient plasma, metabolites that significantly increased at recurrence included: 2,4-difluorotoluene (p = 0.031), diatrizoic acid (p = 0.032), indole-3-acetate with (p = 0.029), urea (P = 0.025), pseudouridine (p = 0.042), and maltose (p = 0.035). Metabolites that significantly decreased in plasma at recurrence were: eicosenoic acid (p = 0.017), glucose-1-phosphate (p = 0.017), FA 18:2 (linoleic acid) (p = 0.017), arginine (p = 0.036), fatty acids 20:3 (homo-gamma-linolenic acid (p = 0.036), galactosamine (p = 0.007), and FA 18:3 (linolenic acid) (P = 0.012). Principal component analysis showed that the metabolomic profiles differ between tumor tissue and patient plasma.

Conclusions

Our data suggest that metabolomic profiles of human GBM tissue and patient plasma differ at diagnosis and at recurrence. Many metabolites involved in tumorigenesis and metabolomic flexibility were identified. A larger study using targeted metabolomic assay is warranted to measure the levels of these metabolites, which will help identify the metabolomic signatures in both GBM tissue and patient plasma for risk stratification, clinical outcome prediction, and development of new adjuvant metabolomic-targeting therapy.

Modeling nervous system tumors with human stem cells and organoids

Nervous system cancers are the 10th leading cause of death worldwide, many of which are difficult to diagnose and exhibit varying degrees of treatment resistance. The limitations of existing cancer models, such as patient-derived xenograft (PDX) models and genetically engineered mouse (GEM) models, call for the development of novel preclinical cancer models to more faithfully mimic the patient's cancer and offer additional insights. Recent advances in human stem cell biology, organoid, and genome-editing techniques allow us to model nervous system tumors in three types of next-generation tumor models: cell-of-origin models, tumor organoids, and 3D multicellular coculture models. In this review, we introduced and compared different human stem cell/organoid-derived models, and comprehensively summarized and discussed the recently developed models for various primary tumors in the central and peripheral nervous systems, including glioblastoma (GBM), H3K27M-mutant Diffuse Midline Glioma (DMG) and H3G34R-mutant High-grade Glioma (HGG), Low-grade Glioma (LGG), Neurofibromatosis Type 1 (NF1), Neurofibromatosis Type 2 (NF2), Medulloblastoma (MB), Atypical Teratoid/rhabdoid Tumor (AT/RT), and meningioma. We further compared these models with PDX and GEM models, and discussed the opportunities and challenges of precision nervous cancer modeling with human stem cells and organoids.

Metabolic Barriers to Glioblastoma Immunotherapy

Glioblastoma (GBM) is the most common primary brain tumor with a poor prognosis with the current standard of care treatment. To address the need for novel therapeutic options in GBM, immunotherapies which target cancer cells through stimulating an anti-tumoral immune response have been investigated in GBM. However, immunotherapies in GBM have not met with anywhere near the level of success they have encountered in other cancers. The immunosuppressive tumor microenvironment in GBM is thought to contribute significantly to resistance to immunotherapy. Metabolic alterations employed by cancer cells to promote their own growth and proliferation have been shown to impact the distribution and function of immune cells in the tumor microenvironment. More recently, the diminished function of anti-tumoral effector immune cells and promotion of immunosuppressive populations resulting from metabolic alterations have been investigated as contributory to therapeutic resistance. The GBM tumor cell metabolism of four nutrients (glucose, glutamine, tryptophan, and lipids) has recently been described as contributory to an immunosuppressive tumor microenvironment and immunotherapy resistance. Understanding metabolic mechanisms of resistance to immunotherapy in GBM can provide insight into future directions targeting the anti-tumor immune response in combination with tumor metabolism.

Synthesis and Significance of Arachidonic Acid, a Substrate for Cyclooxygenases, Lipoxygenases, and Cytochrome P450 Pathways in the Tumorigenesis of Glioblastoma Multiforme, Including a Pan-Cancer Comparative Analysis

Glioblastoma multiforme (GBM) is one of the most aggressive gliomas. New and more effective therapeutic approaches are being sought based on studies of the various mechanisms of GBM tumorigenesis, including the synthesis and metabolism of arachidonic acid (ARA), an omega-6 polyunsaturated fatty acid (PUFA). PubMed, GEPIA, and the transcriptomics analysis carried out by Seifert et al. were used in writing this paper. In this paper, we discuss in detail the biosynthesis of this acid in GBM tumors, with a special focus on certain enzymes: fatty acid desaturase (FADS)1, FADS2, and elongation of long-chain fatty acids family member 5 (ELOVL5). We also discuss ARA metabolism, particularly its release from cell membrane phospholipids by phospholipase A₂ (cPLA₂, iPLA₂, and sPLA₂) and its processing by cyclooxygenases (COX-1 and COX-2), lipoxygenases (5-LOX, 12-LOX, 15-LOX-1, and 15-LOX-2), and cytochrome P450. Next, we discuss the significance of lipid mediators synthesized from ARA in GBM cancer processes, including prostaglandins (PGE₂, PGD₂, and 15-deoxy-Δ^12,14-PGJ₂ (15d-PGJ₂)), thromboxane A₂ (TxA₂), oxo-eicosatetraenoic acids, leukotrienes (LTB₄, LTC₄, LTD₄, and LTE₄), lipoxins, and many others. These lipid mediators can increase the proliferation of GBM cancer cells, cause angiogenesis, inhibit the anti-tumor response of the immune system, and be responsible for resistance to treatment.

WDR5 represents a therapeutically exploitable target for cancer stem cells in glioblastoma

Glioblastomas (GBMs) are heterogeneous, treatment-resistant tumors driven by populations of cancer stem cells (CSCs). However, few molecular mechanisms critical for CSC population maintenance have been exploited for therapeutic development. We developed a spatially resolved loss-of-function screen in GBM patient-derived organoids to identify essential epigenetic regulators in the SOX2-enriched, therapy-resistant niche and identified WDR5 as indispensable for this population. WDR5 is a component of the WRAD complex, which promotes SET1 family-mediated Lys4 methylation of histone H3 (H3K4me), associated with positive regulation of transcription. In GBM CSCs, WDR5 inhibitors blocked WRAD complex assembly and reduced H3K4 trimethylation and expression of genes involved in CSC-relevant oncogenic pathways. H3K4me3 peaks lost with WDR5 inhibitor treatment occurred disproportionally on POU transcription factor motifs, including the POU5F1(OCT4)::SOX2 motif. Use of a SOX2/OCT4 reporter demonstrated that WDR5 inhibitor treatment diminished cells with high reporter activity. Furthermore, WDR5 inhibitor treatment and WDR5 knockdown altered the stem cell state, disrupting CSC in vitro growth and self-renewal, as well as in vivo tumor growth. These findings highlight the role of WDR5 and the WRAD complex in maintaining the CSC state and provide a rationale for therapeutic development of WDR5 inhibitors for GBM and other advanced cancers.

Antibody Profiling and In Silico Functional Analysis of Differentially Reactive Antibody Signatures of Glioblastomas and Meningiomas

Studies on tumor-associated antigens in brain tumors are sparse. There is scope for enhancing our understanding of molecular pathology, in order to improve on existing forms, and discover new forms, of treatment, which could be particularly relevant to immuno-oncological strategies. To elucidate immunological differences, and to provide another level of biological information, we performed antibody profiling, based on a high-density protein array (containing 8173 human transcripts), using IgG isolated from the sera of n = 12 preoperative and n = 16 postoperative glioblastomas, n = 26 preoperative and n = 29 postoperative meningiomas, and n = 27 healthy, cancer-free controls. Differentially reactive antigens were compared to gene expression data from an alternate public GBM data set from OncoDB, and were analyzed using the Reactome pathway browser. Protein array analysis identified approximately 350-800 differentially reactive antigens, and revealed different antigen profiles in the glioblastomas and meningiomas, with approximately 20-30%-similar and 10-15%-similar antigens in preoperative and postoperative sera, respectively. Seroreactivity did not correlate with OncoDB-derived gene expression. Antigens in the preoperative glioblastoma sera were enriched for signaling pathways, such as signaling by Rho-GTPases, COPI-mediated anterograde transport and vesicle-mediated transport, while the infectious disease, SRP-dependent membrane targeting cotranslational proteins were enriched in the meningiomas. The pre-vs. postoperative seroreactivity in the glioblastomas was enriched for antigens, e.g., platelet degranulation and metabolism of lipid pathways; in the meningiomas, the antigens were enriched in infectious diseases, metabolism of amino acids and derivatives, and cell cycle. Antibody profiling in both tumor entities elucidated several hundred antigens and characteristic signaling pathways that may provide new insights into molecular pathology and may be of interest for the development of new treatment strategies.

Targeting fatty acid metabolism in glioblastoma

Glioblastoma (GBM) is a primary tumor of the brain defined by its uniform lethality and resistance to conventional therapies. There have been considerable efforts to untangle the metabolic underpinnings of this disease to find novel therapeutic avenues for treatment. An emerging focus in this field is fatty acid (FA) metabolism, which is critical for numerous diverse biological processes involved in GBM pathogenesis. These processes can be classified into four broad fates: anabolism, catabolism, regulation of ferroptosis, and the generation of signaling molecules. Each fate provides a unique perspective by which we can inspect GBM biology and gives us a road map to understanding this complicated field. This Review discusses the basic, translational, and clinical insights into each of these fates to provide a contemporary understanding of FA biology in GBM. It is clear, based on the literature, that there are far more questions than answers in the field of FA metabolism in GBM, and substantial efforts should be made to untangle these complex processes in this intractable disease.

Lipid metabolism-related gene signature predicts prognosis and depicts tumor microenvironment immune landscape in gliomas

Background

Glioma is the most common primary brain tumor in adults and accounts for more than 70% of brain malignancies. Lipids are crucial components of biological membranes and other structures in cells. Accumulating evidence has supported the role of lipid metabolism in reshaping the tumor immune microenvironment (TME). However, the relationship between the immune TME of glioma and lipid metabolism remain poorly described.

Materials and methods

The RNA-seq data and clinicopathological information of primary glioma patients were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). An independent RNA-seq dataset from the West China Hospital (WCH) also included in the study. Univariate Cox regression and LASSO Cox regression model was first to determine the prognostic gene signature from lipid metabolism-related genes (LMRGs). Then a risk score named LMRGs-related risk score (LRS) was established and patients were stratified into high and low risk groups according to LRS. The prognostic value of the LRS was further demonstrated by construction of a glioma risk nomogram. ESTIMATE and CIBERSORTx were used to depicted the TME immune landscape. Tumor Immune Dysfunction and Exclusion (TIDE) was utilized to predict the therapeutic response of immune checkpoint blockades (ICB) among glioma patients.

Results

A total of 144 LMRGs were differentially expressed between gliomas and brain tissue. Finally, 11 prognostic LMRGs were included in the construction of LRS. The LRS was demonstrated to be an independent prognostic predictor for glioma patients, and a nomogram consisting of the LRS, IDH mutational status, WHO grade, and radiotherapy showed a C-index of 0.852. LRS values were significantly associated with stromal score, immune score, and ESTIMATE score. CIBERSORTx indicated remarkable differences in the abundance of TME immune cells between patients with high and low LRS risk levels. Based on the results of TIDE algorithm, we speculated that the high-risk group had a greater chance of benefiting from immunotherapy.

Conclusion

The risk model based upon LMRGs could effectively predict prognosis in patients with glioma. Risk score also divided glioma patients into different groups with distinct TME immune characteristics. Immunotherapy is potentially beneficial to glioma patients with certain lipid metabolism profiles.

Lipid Alterations in Glioma: A Systematic Review

Gliomas are highly lethal tumours characterised by heterogeneous molecular features, producing various metabolic phenotypes leading to therapeutic resistance. Lipid metabolism reprogramming is predominant and has contributed to the metabolic plasticity in glioma. This systematic review aims to discover lipids alteration and their biological roles in glioma and the identification of potential lipids biomarker. This systematic review was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Extensive research articles search for the last 10 years, from 2011 to 2021, were conducted using four electronic databases, including PubMed, Web of Science, CINAHL and ScienceDirect. A total of 158 research articles were included in this study. All studies reported significant lipid alteration between glioma and control groups, impacting glioma cell growth, proliferation, drug resistance, patients' survival and metastasis. Different lipids demonstrated different biological roles, either beneficial or detrimental effects on glioma. Notably, prostaglandin (PGE2), triacylglycerol (TG), phosphatidylcholine (PC), and sphingosine-1-phosphate play significant roles in glioma development. Conversely, the most prominent anti-carcinogenic lipids include docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and vitamin D3 have been reported to have detrimental effects on glioma cells. Furthermore, high lipid signals were detected at 0.9 and 1.3 ppm in high-grade glioma relative to low-grade glioma. This evidence shows that lipid metabolisms were significantly dysregulated in glioma. Concurrent with this knowledge, the discovery of specific lipid classes altered in glioma will accelerate the development of potential lipid biomarkers and enhance future glioma therapeutics.

Lipid droplets and ferroptosis as new players in brain cancer glioblastoma progression and therapeutic resistance

A primary brain tumor glioblastoma is the most lethal of all cancers and remains an extremely challenging disease. Apparent oncogenic signaling in glioblastoma is genetically complex and raised at any stage of the disease's progression. Many clinical trials have shown that anticancer drugs for any specific oncogene aberrantly expressed in glioblastoma show very limited activity. Recent discoveries have highlighted that alterations in tumor metabolism also contribute to disease progression and resistance to current therapeutics for glioblastoma, implicating an alternative avenue to improve outcomes in glioblastoma patients. The roles of glucose, glutamine and tryptophan metabolism in glioblastoma pathogenesis have previously been described. This article provides an overview of the metabolic network and regulatory changes associated with lipid droplets that suppress ferroptosis. Ferroptosis is a newly discovered type of nonapoptotic programmed cell death induced by excessive lipid peroxidation. Although few studies have focused on potential correlations between tumor progression and lipid droplet abundance, there has recently been increasing interest in identifying key players in lipid droplet biology that suppress ferroptosis and whether these dependencies can be effectively exploited in cancer treatment. This article discusses how lipid droplet metabolism, including lipid synthesis, storage, and use modulates ferroptosis sensitivity or tolerance in different cancer models, focusing on glioblastoma.

Metabolic signatures associated with oncolytic myxoma viral infections

Oncolytic viral therapy is a recent advance in cancer treatment, demonstrating promise as a primary treatment option. To date, the secondary metabolic effects of viral infection in cancer cells has not been extensively studied. In this work, we have analyzed early-stage metabolic changes in cancer cells associated with oncolytic myxoma virus infection. Using GC–MS based metabolomics, we characterized the myxoma virus infection induced metabolic changes in three cancer cell lines—small cell (H446) and non-small cell (A549) lung cancers, and glioblastoma (SFxL). We show that even at an early stage (6 and 12 h) myxoma infection causes profound changes in cancer cell metabolism spanning several important pathways such as the citric acid cycle, fatty acid metabolism, and amino acid metabolism. In general, the metabolic effects of viral infection across cell lines are not conserved. However, we have identified several candidate metabolites that can potentially serve as biomarkers for monitoring oncolytic viral action in general.

Targeting Oncogenic Rewiring of Lipid Metabolism for Glioblastoma Treatment

Glioblastoma (GBM) is the most malignant primary brain tumor. Despite increasing research on GBM treatment, the overall survival rate has not significantly improved over the last two decades. Although recent studies have focused on aberrant metabolism in GBM, there have been few advances in clinical application. Thus, it is important to understand the systemic metabolism to eradicate GBM. Together with the Warburg effect, lipid metabolism has emerged as necessary for GBM progression. GBM cells utilize lipid metabolism to acquire energy, membrane components, and signaling molecules for proliferation, survival, and response to the tumor microenvironment. In this review, we discuss fundamental cholesterol, fatty acid, and sphingolipid metabolism in the brain and the distinct metabolic alterations in GBM. In addition, we summarize various studies on the regulation of factors involved in lipid metabolism in GBM therapy. Focusing on the rewiring of lipid metabolism will be an alternative and effective therapeutic strategy for GBM treatment.

Therapy-induced shaping of the glioblastoma microenvironment: Macrophages at play

The intricate cross-talks between tumor cells and their microenvironment play a key role in cancer progression and resistance to treatment. In recent years, targeting pro-tumorigenic components of the tumor microenvironment (TME) has emerged as a tantalizing strategy to improve the efficacy of standard-of-care (SOC) treatments, particularly for hard-to-treat cancers such as glioblastoma. In this review, we explore how the distinct microenvironmental niches characteristic of the glioblastoma TME shape response to therapy. In particular, we delve into the interplay between tumor-associated macrophages (TAM) and glioblastoma cells within angiogenic and hypoxic niches, and interrogate their dynamic co-evolution upon SOC therapies that fuels malignancy. Resolving the complexity of therapy-induced alterations in the glioblastoma TME and their impact on disease relapse is a stepping stone to identify targetable pro-tumorigenic pathways and TAM subsets, and may open the way to efficient combination therapies that will improve clinical outcomes.

Heterogeneity of glioblastoma stem cells in the context of the immune microenvironment and geospatial organization

Glioblastoma (GBM) is an extremely aggressive and incurable primary brain tumor with a 10-year survival of just 0.71%. Cancer stem cells (CSCs) are thought to seed GBM's inevitable recurrence by evading standard of care treatment, which combines surgical resection, radiotherapy, and chemotherapy, contributing to this grim prognosis. Effective targeting of CSCs could result in insights into GBM treatment resistance and development of novel treatment paradigms. There is a major ongoing effort to characterize CSCs, understand their interactions with the tumor microenvironment, and identify ways to eliminate them. This review discusses the diversity of CSC lineages present in GBM and how this glioma stem cell (GSC) mosaicism drives global intratumoral heterogeneity constituted by complex and spatially distinct local microenvironments. We review how a tumor's diverse CSC populations orchestrate and interact with the environment, especially the immune landscape. We also discuss how to map this intricate GBM ecosystem through the lens of metabolism and immunology to find vulnerabilities and new ways to disrupt the equilibrium of the system to achieve improved disease outcome.

LC–MS Based Lipidomics Depict Phosphatidylethanolamine as Biomarkers of TNBC MDA-MB-231 over nTNBC MCF-7 Cells

Breast cancer (BC) is the first malignant neoplasm in women, with a high death rate despite early diagnoses and treatment advances. Significant differences exist between the most common BC and triple-negative breast cancer (TNBC). TNBC presents molecular differences such as lacking expression of the estrogen receptor (ER), progesterone receptor (PR), and HER2 proteins, making this cancer have a poor clinical prognostic and lack clear strategies for its treatment. However, growing evidence points to metabolic dysregulation as another differential process between stages and types of BC. Therefore, the study of this crucial hallmark could identify new therapeutic targets to treat this aggressive form of BC. These differences induce an in vitro exploration of the metabolic behavior of the MCF7 cells (nTNBC) and MDA-MB-231 (TNBC) cells under lipidomic based LC–MS. The results show more significant differences in lipid regulation (phosphatidylethanolamine) that could be associated with the aggressiveness and difficulties of the treatment of TNBC.

Molecular Crosstalk between T Cells and Tumor Uncovers GBM-Specific T Cell Signatures in Blood: Noninvasive GBM Diagnosis Using Immunosensors

Glioblastoma (GBM) is the most common and aggressive stage IV brain cancer with a poor prognosis and survival rate. The blood-brain barrier (BBB) in GBM prevents the entry and exit of biomarkers, limiting its treatment options. Hence, GBM diagnosis is pivotal for timely clinical management. Currently, there exists no clinically validated biomarker for GBM diagnosis. T cells exhibit the potential to escape a leaky BBB in GBM patients. These T cells infiltrating the GBM interact with the heterogeneous population of tumor cells, display a symbiotic interaction resulting in intertwined molecular crosstalk, and display a GBM-associated signature while entering the peripheral circulation. Therefore, we hypothesize that studying these distinct molecular changes is critical to enable T cells to be a diagnostic marker for accurate detection of GBM from patient blood. We demonstrated this by utilizing the phenotypic and immunological landscape changes in T cells associated with glioblastoma tumors. GBM exhibits a high level of heterogeneity with diverse subtypes of cells within the tumor, enabling immune infiltration and different degrees of interactions with the tumor. To accurately detect these subtle molecular differences in T cells, we designed an immunosensor with a high detection sensitivity and repeatability. Hence in this study, we investigated the characteristic behavior of T cells to establish two preclinically validated biomarkers: GBM-associated T cells (GBMAT) and GBM stem cell-associated T cells (GSCAT). A comprehensive investigation was conducted by mimicking the tumor microenvironment in vitro by coculturing T cells with cancer cells and cancer stem cells to study the distinct variation in GBMAT and GSCAT. Preclinical investigation of T cells from GBM patient blood shows similar characteristics to our established biomarkers (GBMAT, GSCAT). Further evaluating the relative attributes of T cells in patient blood and tissue biopsy confirms the infiltrating ability of T cells across the BBB. A pilot validation using a SERS-based machine learning algorithm was accomplished by training the model with GBMAT and GSCAT as diagnostic markers. Using GBMAT as a biomarker, we achieved a sensitivity and specificity of 93.3% and 97.4%, respectively, whereas applying GSCAT yielded a sensitivity and specificity of 100% and 98.7%, respectively. We also validated this diagnostic methodology by using conventional biological assays to study the change in expression levels of T cell surface markers (CD4 and CD8) and cytokine levels in T cells (IL6, IL10, TNFα, INFγ) from GBM patients. This study introduces T cells as GBM-specific immune biomarkers to diagnose GBM using patient liquid biopsy. This preclinical validation study presents a better translatability into clinical reality that will enable rapid and noninvasive glioblastoma detection from patient blood.

Exploring glioblastoma stem cell heterogeneity: Immune microenvironment modulation and therapeutic opportunities

Despite its growing use in cancer treatment, immunotherapy has been virtually ineffective in clinical trials for gliomas. The inherently cold tumor immune microenvironment (TIME) in gliomas, characterized by a high ratio of pro-tumor to anti-tumor immune cell infiltrates, acts as a seemingly insurmountable barrier to immunotherapy. Glioma stem cells (GSCs) within these tumors are key contributors to this cold TIME, often functioning indirectly through activation and recruitment of pro-tumor immune cell types. Furthermore, drivers of GSC plasticity and heterogeneity (e.g., reprogramming transcription factors, epigenetic modifications) are associated with induction of immunosuppressive cell states. Recent studies have identified GSC-intrinsic mechanisms, including functional mimicry of immune suppressive cell types, as key determinants of anti-tumor immune escape. In this review, we cover recent advancements in our understanding of GSC-intrinsic mechanisms that modulate GSC-TIME interactions and discuss cutting-edge techniques and bioinformatics platforms available to study immune modulation at high cellular resolution with exploration of both malignant (i.e., GSC) and non-malignant (i.e., immune) cell fractions. Finally, we provide insight into the therapeutic opportunities for targeting immunomodulatory GSC-intrinsic mechanisms to potentiate immunotherapy response in gliomas.

An update on the molecular biology of glioblastoma, with clinical implications and progress in its treatment

Glioblastoma multiforme (GBM) is the most aggressive and common malignant primary brain tumor. Patients with GBM often have poor prognoses, with a median survival of ∼15 months. Enhanced understanding of the molecular biology of central nervous system tumors has led to modifications in their classifications, the most recent of which classified these tumors into new categories and made some changes in their nomenclature and grading system. This review aims to give a panoramic view of the last 3 years' findings in glioblastoma characterization, its heterogeneity, and current advances in its treatment. Several molecular parameters have been used to achieve an accurate and personalized characterization of glioblastoma in patients, including epigenetic, genetic, transcriptomic and metabolic features, as well as age- and sex-related patterns and the involvement of several noncoding RNAs in glioblastoma progression. Astrocyte-like neural stem cells and outer radial glial-like cells from the subventricular zone have been proposed as agents involved in GBM of IDH-wildtype origin, but this remains controversial. Glioblastoma metabolism is characterized by upregulation of the PI3K/Akt/mTOR signaling pathway, promotion of the glycolytic flux, maintenance of lipid storage, and other features. This metabolism also contributes to glioblastoma's resistance to conventional therapies. Tumor heterogeneity, a hallmark of GBM, has been shown to affect the genetic expression, modulation of metabolic pathways, and immune system evasion. GBM's aggressive invasion potential is modulated by cell-to-cell crosstalk within the tumor microenvironment and altered expressions of specific genes, such as ANXA2, GBP2, FN1, PHIP, and GLUT3. Nevertheless, the rising number of active clinical trials illustrates the efforts to identify new targets and drugs to treat this malignancy. Immunotherapy is still relevant for research purposes, given the amount of ongoing clinical trials based on this strategy to treat GBM, and neoantigen and nucleic acid-based vaccines are gaining importance due to their antitumoral activity by inducing the immune response. Furthermore, there are clinical trials focused on the PI3K/Akt/mTOR axis, angiogenesis, and tumor heterogeneity for developing molecular-targeted therapies against GBM. Other strategies, such as nanodelivery and computational models, may improve the drug pharmacokinetics and the prognosis of patients with GBM.

Targeting the Sphingolipid Rheostat in Gliomas

Gliomas are highly aggressive cancer types that are in urgent need of novel drugs and targeted therapies. Treatment protocols have not improved in over a decade, and glioma patient survival remains among the worst of all cancer types. As a result, cancer metabolism research has served as an innovative approach to identifying novel glioma targets and improving our understanding of brain tumors. Recent research has uncovered a unique metabolic vulnerability in the sphingolipid pathways of gliomas that possess the IDH1 mutation. Sphingolipids are a family of lipid signaling molecules that play a variety of second messenger functions in cellular regulation. The two primary metabolites, sphingosine-1-phosphate (S1P) and ceramide, maintain a rheostat balance and play opposing roles in cell survival and proliferation. Altering the rheostat such that the pro-apoptotic signaling of the ceramides outweighs the pro-survival S1P signaling in glioma cells diminishes the hallmarks of cancer and enhances tumor cell death. Throughout this review, we discuss the sphingolipid pathway and identify the enzymes that can be most effectively targeted to alter the sphingolipid rheostat and enhance apoptosis in gliomas. We discuss each pathway’s steps based on their site of occurrence in the organelles and postulate novel targets that can effectively exploit this vulnerability.