Exploring the differences in metabolic behavior of astrocyte and glioblastoma: a flux balance analysis approach

Metabolic reprogramming and signalling cross-talks in tumour-immune interaction: a system-level exploration

Tumour-immune microenvironment (TIME) is pivotal in tumour progression and immunoediting. Within TIME, immune cells undergo metabolic adjustments impacting nutrient supply and the anti-tumour immune response. Metabolic reprogramming emerges as a promising approach to revert the immune response towards a pro-inflammatory state and conquer tumour dominance. This study proposes immunomodulatory mechanisms based on metabolic reprogramming and employs the regulatory flux balance analysis modelling approach, which integrates signalling, metabolism and regulatory processes. For the first time, a comprehensive system-level model is constructed to capture signalling and metabolic cross-talks during tumour-immune interaction and regulatory constraints are incorporated by considering the time lag between them. The model analysis identifies novel features to enhance the immune response while suppressing tumour activity. Particularly, altering the exchange of succinate and oxaloacetate between glioma and macrophage enhances the pro-inflammatory response of immune cells. Inhibition of glutamate uptake in T-cells disrupts the antioxidant mechanism of glioma and reprograms metabolism. Metabolic reprogramming through adenosine monophosphate (AMP)-activated protein kinase (AMPK), coupled with glutamate uptake inhibition, was identified as the most impactful combination to restore T-cell function. A comprehensive understanding of metabolism and gene regulation represents a favourable approach to promote immune cell recovery from tumour dominance.

The "Superoncogene" Myc at the Crossroad between Metabolism and Gene Expression in Glioblastoma Multiforme

The concept of the Myc (c-myc, n-myc, l-myc) oncogene as a canonical, DNA-bound transcription factor has consistently changed over the past few years. Indeed, Myc controls gene expression programs at multiple levels: directly binding chromatin and recruiting transcriptional coregulators; modulating the activity of RNA polymerases (RNAPs); and drawing chromatin topology. Therefore, it is evident that Myc deregulation in cancer is a dramatic event. Glioblastoma multiforme (GBM) is the most lethal, still incurable, brain cancer in adults, and it is characterized in most cases by Myc deregulation. Metabolic rewiring typically occurs in cancer cells, and GBM undergoes profound metabolic changes to supply increased energy demand. In nontransformed cells, Myc tightly controls metabolic pathways to maintain cellular homeostasis. Consistently, in Myc-overexpressing cancer cells, including GBM cells, these highly controlled metabolic routes are affected by enhanced Myc activity and show substantial alterations. On the other hand, deregulated cancer metabolism impacts Myc expression and function, placing Myc at the intersection between metabolic pathway activation and gene expression. In this review paper, we summarize the available information on GBM metabolism with a specific focus on the control of the Myc oncogene that, in turn, rules the activation of metabolic signals, ensuring GBM growth.

Identification of potential microRNAs regulating metabolic plasticity and cellular phenotypes in glioblastoma

MicroRNAs (miRNAs) play important role in regulating cellular metabolism, and are currently being explored in cancer. As metabolic reprogramming in cancer is a major mediator of phenotypic plasticity, understanding miRNA-regulated metabolism will provide opportunities to identify miRNA targets that can regulate oncogenic phenotypes by taking control of cellular metabolism. In the present work, we studied the effect of differentially expressed miRNAs on metabolism, and associated oncogenic phenotypes in glioblastoma (GBM) using patient-derived data. Networks of differentially expressed miRNAs and metabolic genes were created and analyzed to identify important miRNAs that regulate major metabolism in GBM. Graph network-based approaches like network diffusion, backbone extraction, and different centrality measures were used to analyze these networks for identification of potential miRNA targets. Important metabolic processes and cellular phenotypes were annotated to trace the functional responses associated with these miRNA-regulated metabolic genes and associated phenotype networks. miRNA-regulated metabolic gene subnetworks of cellular phenotypes were extracted, and important miRNAs regulating these phenotypes were identified. The most important outcome of the study is the target miRNA combinations predicted for five different oncogenic phenotypes that can be tested experimentally for miRNA-based therapeutic design in GBM. Strategies implemented in the study can be used to generate testable hypotheses in other cancer types as well, and design context-specific miRNA-based therapy for individual patient. Their usability can be further extended to other gene regulatory networks in cancer and other genetic diseases.

Metabolic Rewiring in Glioblastoma Cancer: EGFR, IDH and Beyond

Glioblastoma multiforme (GBM), a highly invasive and incurable tumor, is the humans’ foremost, commonest, and deadliest brain cancer. As in other cancers, distinct combinations of genetic alterations (GA) in GBM induce a diversity of metabolic phenotypes resulting in enhanced malignancy and altered sensitivity to current therapies. Furthermore, GA as a hallmark of cancer, dysregulated cell metabolism in GBM has been recently linked to the acquired GA. Indeed, Numerous point mutations and copy number variations have been shown to drive glioma cells’ metabolic state, affecting tumor growth and patient outcomes. Among the most common, IDH mutations, EGFR amplification, mutation, PTEN loss, and MGMT promoter mutation have emerged as key patterns associated with upregulated glycolysis and OXPHOS glutamine addiction and altered lipid metabolism in GBM. Therefore, current Advances in cancer genetic and metabolic profiling have yielded mechanistic insights into the metabolism rewiring of GBM and provided potential avenues for improved therapeutic modalities. Accordingly, actionable metabolic dependencies are currently used to design new treatments for patients with glioblastoma. Herein, we capture the current knowledge of genetic alterations in GBM, provide a detailed understanding of the alterations in metabolic pathways, and discuss their relevance in GBM therapy.

The Glioblastoma Microenvironment: Morphology, Metabolism, and Molecular Signature of Glial Dynamics to Discover Metabolic Rewiring Sequence

Different functional states determine glioblastoma (GBM) heterogeneity. Brain cancer cells coexist with the glial cells in a functional syncytium based on a continuous metabolic rewiring. However, standard glioma therapies do not account for the effects of the glial cells within the tumor microenvironment. This may be a possible reason for the lack of improvements in patients with high-grade gliomas therapies. Cell metabolism and bioenergetic fitness depend on the availability of nutrients and interactions in the microenvironment. It is strictly related to the cell location in the tumor mass, proximity to blood vessels, biochemical gradients, and tumor evolution, underlying the influence of the context and the timeline in anti-tumor therapeutic approaches. Besides the cancer metabolic strategies, here we review the modifications found in the GBM-associated glia, focusing on morphological, molecular, and metabolic features. We propose to analyze the GBM metabolic rewiring processes from a systems biology perspective. We aim at defining the crosstalk between GBM and the glial cells as modules. The complex networking may be expressed by metabolic modules corresponding to the GBM growth and spreading phases. Variation in the oxidative phosphorylation (OXPHOS) rate and regulation appears to be the most important part of the metabolic and functional heterogeneity, correlating with glycolysis and response to hypoxia. Integrated metabolic modules along with molecular and morphological features could allow the identification of key factors for controlling the GBM-stroma metabolism in multi-targeted, time-dependent therapies.

Differential suitability of reactive oxygen species and the role of glutathione in regulating paradoxical behavior in gliomas: A mathematical perspective

Manipulative strategies of ROS in cancer are often exhibited as changes in the redox and thiol ratio of the cells. Cellular responses to oxidative insults are generated in response to these changes which are triggered due to the rerouting of the metabolic framework to maintain survival under stress. However, mechanisms of these metabolic re-routing are not clearly understood and remained debatable. In the present work, we have designed a context-based dynamic metabolic model to establish that the coordinated functioning of glutathione peroxidase (GTHP), glutathione oxidoreductase (GTHO) and NADPH oxidase (NOX) is crucial in determining cancerous transformation, specifically in gliomas. Further, we propose that the puzzling duality of ROS (represented by changes in h₂o₂ in the present model) in exhibiting varying cellular fates can be determined by considering simultaneous changes in nadph/nadp⁺ and gsh/gssg that occur during the reprogramming of metabolic reactions. This will be helpful in determining the pro-apoptotic or anti-apoptotic fate of gliomas and can be useful in designing effective pro-oxidant and/or anti-oxidant therapeutic approaches against gliomas.

Peptidylarginine Deiminase Isozyme-Specific PAD2, PAD3 and PAD4 Inhibitors Differentially Modulate Extracellular Vesicle Signatures and Cell Invasion in Two Glioblastoma Multiforme Cell Lines

Glioblastoma multiforme (GBM) is an aggressive adult brain tumour with poor prognosis. Roles for peptidylarginine deiminases (PADs) in GBM have recently been highlighted. Here, two GBM cell lines were treated with PAD2, PAD3 and PAD4 isozyme-specific inhibitors. Effects were assessed on extracellular vesicle (EV) signatures, including EV-microRNA cargo (miR21, miR126 and miR210), and on changes in cellular protein expression relevant for mitochondrial housekeeping (prohibitin (PHB)) and cancer progression (stromal interaction molecule 1 (STIM-1) and moesin), as well as assessing cell invasion. Overall, GBM cell-line specific differences for the three PAD isozyme-specific inhibitors were observed on modulation of EV-signatures, PHB, STIM-1 and moesin protein levels, as well as on cell invasion. The PAD3 inhibitor was most effective in modulating EVs to anti-oncogenic signatures (reduced miR21 and miR210, and elevated miR126), to reduce cell invasion and to modulate protein expression of pro-GBM proteins in LN229 cells, while the PAD2 and PAD4 inhibitors were more effective in LN18 cells. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways for deiminated proteins relating to cancer, metabolism and inflammation differed between the two GBM cell lines. Our findings highlight roles for the different PAD isozymes in the heterogeneity of GBM tumours and the potential for tailored PAD-isozyme specific treatment.

Multiple Pathways Involved in Palmitic Acid-Induced Toxicity: A System Biology Approach

Inflammation is a complex biological response to injuries, metabolic disorders or infections. In the brain, astrocytes play an important role in the inflammatory processes during neurodegenerative diseases. Recent studies have shown that the increase of free saturated fatty acids such as palmitic acid produces a metabolic inflammatory response in astrocytes generally associated with damaging mechanisms such as oxidative stress, endoplasmic reticulum stress, and autophagic defects. In this aspect, the synthetic neurosteroid tibolone has shown to exert protective functions against inflammation in neuronal experimental models without the tumorigenic effects exerted by sexual hormones such as estradiol and progesterone. However, there is little information regarding the specific mechanisms of tibolone in astrocytes during inflammatory insults. In the present study, we performed a genome-scale metabolic reconstruction of astrocytes that was used to study astrocytic response during an inflammatory insult by palmitate through Flux Balance Analysis methods and data mining. In this aspect, we assessed the metabolic fluxes of human astrocytes under three different scenarios: healthy (normal conditions), induced inflammation by palmitate, and tibolone treatment under palmitate inflammation. Our results suggest that tibolone reduces the L-glutamate-mediated neurotoxicity in astrocytes through the modulation of several metabolic pathways involved in glutamate uptake. We also identified a set of reactions associated with the protective effects of tibolone, including the upregulation of taurine metabolism, gluconeogenesis, cPPAR and the modulation of calcium signaling pathways. In conclusion, the different scenarios studied in our model allowed us to identify several metabolic fluxes perturbed under an inflammatory response and the protective mechanisms exerted by tibolone.

Reconstructed Metabolic Network Models Predict Flux-Level Metabolic Reprogramming in Glioblastoma

Developments in genome scale metabolic modeling techniques and omics technologies have enabled the reconstruction of context-specific metabolic models. In this study, glioblastoma multiforme (GBM), one of the most common and aggressive malignant brain tumors, is investigated by mapping GBM gene expression data on the growth-implemented brain specific genome-scale metabolic network, and GBM-specific models are generated. The models are used to calculate metabolic flux distributions in the tumor cells. Metabolic phenotypes predicted by the GBM-specific metabolic models reconstructed in this work reflect the general metabolic reprogramming of GBM, reported both in in-vitro and in-vivo experiments. The computed flux profiles quantitatively predict that major sources of the acetyl-CoA and oxaloacetic acid pool used in TCA cycle are pyruvate dehydrogenase from glycolysis and anaplerotic flux from glutaminolysis, respectively. Also, our results, in accordance with recent studies, predict a contribution of oxidative phosphorylation to ATP pool via a slightly active TCA cycle in addition to the major contributor aerobic glycolysis. We verified our results by using different computational methods that incorporate transcriptome data with genome-scale models and by using different transcriptome datasets. Correct predictions of flux distributions in glycolysis, glutaminolysis, TCA cycle and lipid precursor metabolism validate the reconstructed models for further use in future to simulate more specific metabolic patterns for GBM.