Lipid accumulation and oxidation in glioblastoma multiforme

Lipidomics-driven drug discovery and delivery strategies in glioblastoma

With few viable treatment options, glioblastoma (GBM) is still one of the most aggressive and deadly types of brain cancer. Recent developments in lipidomics have demonstrated the potential of lipid metabolism as a therapeutic target in GBM. The thorough examination of lipids in biological systems, or lipidomics, is essential to comprehending the changed lipid profiles found in GBM, which are linked to the tumor's ability to grow, survive, and resist treatment. The use of lipidomics in drug delivery and discovery is examined in this study, focusing on how it may be used to find new biomarkers, create multi-target directed ligands, and improve drug delivery systems. We also cover the use of FDA-approved medications, clinical trials that use lipid-targeted medicines, and the integration of lipidomics with other omics technologies. This study emphasizes lipidomics as a possible tool in developing more effective treatment methods for GBM by exploring various lipid-centric techniques.

Metabolic checkpoints in glioblastomas: targets for new therapies and non-invasive detection

Glioblastoma (GBM) is a highly malignant tumor of the central nervous system that remains intractable despite advancements in current tumor treatment modalities, including immunotherapy. In recent years, metabolic checkpoints (aberrant metabolic pathways underlying the immunosuppressive tumor microenvironment) have gained attention as promising therapeutic targets and sensitive biomarkers across various cancers. Here, we briefly review the existing understanding of tumor metabolic checkpoints and their implications in the biology and management of GBM. Additionally, we discuss techniques that could evaluate metabolic checkpoints of GBM non-invasively, thereby potentially facilitating neo-adjuvant treatment and dynamic surveillance.

Prediction of intracranial electric field strength and analysis of treatment protocols in tumor electric field therapy targeting gliomas of the brain

BACKGROUND AND OBJECTIVE

Tumor Electric Field Therapy (TEFT) is a new treatment for glioblastoma cells with significant effect and few side effects. However, it is difficult to directly measure the intracranial electric field generated by TEFT, and the inability to control the electric field intensity distribution in the tumor target area also limits the clinical therapeutic effect of TEFT. It is a safe and effective way to construct an efficient and accurate prediction model of intracranial electric field intensity of TEFT by numerical simulation.

METHODS

Different from the traditional methods, in this study, the brain tissue was segmented based on the MRI data of patients with retained spatial location information, and the spatial position of the brain tissue was given the corresponding electrical parameters after segmentation. Then, a single geometric model of the head profile with the transducer array is constructed, which is assembled with an electrical parameter matrix containing tissue position information. After applying boundary conditions on the transducer, the intracranial electric field intensity could be solved in the frequency domain. The effects of transducer array mode, load voltage and voltage frequency on the intracranial electric field strength were further analyzed. Finally, planning system software was developed for optimizing TEFT treatment regimens for patients.

RESULTS

Experimental validation and comparison with existing results demonstrate the proposed method has a more efficient and pervasive modeling approach with higher computational accuracy while preserving the details of MRI brain tissue structure completely. In the optimization analysis of treatment protocols, it was found that increasing the load voltage could effectively increase the electric field intensity in the target area, while the effect of voltage frequency on the electric field intensity was very limited.

CONCLUSIONS

The results showed that adjusting the transducer array mode was the key method for making targeted treatment plans. The proposed method is capable prediction of intracranial electric field strength with high accuracy and provide guidance for the design of the TEFT therapy process. This study provides a valuable reference for the application of TEFT in clinical practice.

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.

ACAT1 Induces the Differentiation of Glioblastoma Cells by Rewiring Choline Metabolism

Abnormal differentiation of cells is a hallmark of malignancy. Induction of cancer-cell differentiation is emerging as a novel therapeutic strategy with low toxicity in hematological malignances, but whether such treatment can be used in solid tumors is not known. Here, we uncovered a novel function of acetyl coenzyme A acetyltransferase (ACAT1) in regulating the differentiation of glioblastoma (GBM) cells. Inhibition of ACAT1 promoted the differentiation of GBM cells into astrocytes but also delayed tumor growth. Mechanistically, suppression of ACAT1 restored mitochondrial function and led to metabolic "reprogramming" in GBM cells: reduction of fatty-acid oxidation and acetyl-CoA, but an increase in free fatty acids. Importantly, ACAT1 negatively regulated the choline metabolic pathway, which is crucial for the differentiation of GBM cells. Finally, we demonstrated that a naturally available substance, chlorogenic acid (CHA), could inhibit phosphorylation of ACAT1 and so delay GBM progression, CHA is a promising candidate to treat GBM because it could induce the differentiation of cancer cells.

Metabolic Reprogramming in Glioblastoma Multiforme: A Review of Pathways and Therapeutic Targets

Glioblastoma (GBM) is an aggressive and highly malignant primary brain tumor characterized by rapid growth and a poor prognosis for patients. Despite advancements in treatment, the median survival time for GBM patients remains low. One of the crucial challenges in understanding and treating GBMs involves its remarkable cellular heterogeneity and adaptability. Central to the survival and proliferation of GBM cells is their ability to undergo metabolic reprogramming. Metabolic reprogramming is a process that allows cancer cells to alter their metabolism to meet the increased demands of rapid growth and to survive in the often oxygen- and nutrient-deficient tumor microenvironment. These changes in metabolism include the Warburg effect, alterations in several key metabolic pathways including glutamine metabolism, fatty acid synthesis, and the tricarboxylic acid (TCA) cycle, increased uptake and utilization of glutamine, and more. Despite the complexity and adaptability of GBM metabolism, a deeper understanding of its metabolic reprogramming offers hope for developing more effective therapeutic interventions against GBMs.

Cannabidiol and fluorinated derivative anti-cancer properties against glioblastoma multiforme cell lines, and synergy with imidazotetrazine agents

BACKGROUND

Glioblastoma multiforme (GBM) is an aggressive cancer with poor prognosis, partly due to resistance to the standard chemotherapy treatment, temozolomide (TMZ). Phytocannabinoid cannabidiol (CBD) has exhibited anti-cancer effects against GBM, however, CBD's ability to overcome common resistance mechanisms to TMZ have not yet been investigated. 4'-Fluoro-cannabidiol (4'-F-CBD, or HUF-101/PECS-101) is a derivative of CBD, that exhibits increased activity compared to CBD during in vivo behavioural studies.

METHODS

This anti-cancer activity of cannabinoids against GBM cells sensitive to and representing major resistance mechanisms to TMZ was investigated. Cannabinoids were also studied in combination with imidazotetrazine agents, and advanced mass spectrometry with the 3D OrbiSIMS was used to investigate the mechanism of action of CBD.

RESULTS

CBD and 4'-F-CBD were found to overcome two major resistance mechanisms (methylguanine DNA-methyltransferase (MGMT) overexpression and DNA mismatch repair (MMR)-deficiency). Synergistic responses were observed when cells were exposed to cannabinoids and imidazotetrazine agents. Synergy increased with T25 and 4'-F-CBD. 3D OrbiSIMS analysis highlighted the presence of methylated-DNA, a previously unknown anti-cancer mechanism of action of CBD.

CONCLUSIONS

This work demonstrates the anti-cancer activity of 4'-F-CBD and the synergy of cannabinoids with imidazotetrazine agents for the first time and expands understanding of CBD mechanism of action.

Excessive lipid production shapes glioma tumor microenvironment

Disrupted lipid metabolism is a characteristic of gliomas. This study utilizes an ultrastructural approach to characterize the prevalence and distribution of lipids within gliomas. This study made use of tissue from IDH1 wild type (IDH1-wt) glioblastoma (n = 18) and IDH1 mutant (IDH1-mt) astrocytoma (n = 12) tumors. We uncover a prevalent and intriguing surplus of lipids. The bulk of the lipids manifested as sizable cytoplasmic inclusions and extracellular deposits in the tumor microenvironment (TME); in some tumors the lipids were stored in the classical membraneless spheroidal lipid droplets (LDs). Frequently, lipids accumulated inside mitochondria, suggesting possible dysfunction of the beta-oxidation pathway. Additionally, the tumor vasculature have lipid deposits in their lumen and vessel walls; this lipid could have shifted in from the tumor microenvironment or have been produced by the vessel-invading tumor cells. Lipid excess in gliomas stems from disrupted beta-oxidation and dysfunctional oxidative phosphorylation pathways. The implications of this lipid-driven environment include structural support for the tumor cells and protection against immune responses, non-lipophilic drugs, and free radicals.

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.

Circulating Liquid Biopsy Biomarkers in Glioblastoma: Advances and Challenges

Gliomas, particularly glioblastoma (GBM), represent the most prevalent and aggressive tumors of the central nervous system (CNS). Despite recent treatment advancements, patient survival rates remain low. The diagnosis of GBM traditionally relies on neuroimaging methods such as magnetic resonance imaging (MRI) or computed tomography (CT) scans and postoperative confirmation via histopathological and molecular analysis. Imaging techniques struggle to differentiate between tumor progression and treatment-related changes, leading to potential misinterpretation and treatment delays. Similarly, tissue biopsies, while informative, are invasive and not suitable for monitoring ongoing treatments. These challenges have led to the emergence of liquid biopsy, particularly through blood samples, as a promising alternative for GBM diagnosis and monitoring. Presently, blood and cerebrospinal fluid (CSF) sampling offers a minimally invasive means of obtaining tumor-related information to guide therapy. The idea that blood or any biofluid tests can be used to screen many cancer types has huge potential. Tumors release various components into the bloodstream or other biofluids, including cell-free nucleic acids such as microRNAs (miRNAs), circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), proteins, extracellular vesicles (EVs) or exosomes, metabolites, and other factors. These factors have been shown to cross the blood-brain barrier (BBB), presenting an opportunity for the minimally invasive monitoring of GBM as well as for the real-time assessment of distinct genetic, epigenetic, transcriptomic, proteomic, and metabolomic changes associated with brain tumors. Despite their potential, the clinical utility of liquid biopsy-based circulating biomarkers is somewhat constrained by limitations such as the absence of standardized methodologies for blood or CSF collection, analyte extraction, analysis methods, and small cohort sizes. Additionally, tissue biopsies offer more precise insights into tumor morphology and the microenvironment. Therefore, the objective of a liquid biopsy should be to complement and enhance the diagnostic accuracy and monitoring of GBM patients by providing additional information alongside traditional tissue biopsies. Moreover, utilizing a combination of diverse biomarker types may enhance clinical effectiveness compared to solely relying on one biomarker category, potentially improving diagnostic sensitivity and specificity and addressing some of the existing limitations associated with liquid biomarkers for GBM. This review presents an overview of the latest research on circulating biomarkers found in GBM blood or CSF samples, discusses their potential as diagnostic, predictive, and prognostic indicators, and discusses associated challenges and future perspectives.

Sphingolipid Signaling and Complement Activation in Glioblastoma: A Promising Avenue for Therapeutic Intervention

Glioblastoma is the most common and aggressive type of malignant brain tumor with a poor prognosis due to the lack of effective treatment options. Therefore, new treatment options are required. Sphingolipids are essential components of the cell membrane, while complement components are integral to innate immunity, and both play a critical role in regulating glioblastoma survival signaling. This review focuses on recent studies investigating the functional roles of sphingolipid metabolism and complement activation signaling in glioblastoma. It also discusses how targeting these two systems together may emerge as a novel therapeutic approach.

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.

Advancing glioblastoma treatment by targeting metabolism

Alterations in cellular metabolism are important hallmarks of glioblastoma(GBM). Metabolic reprogramming is a critical feature as it meets the higher nutritional demand of tumor cells, including proliferation, growth, and survival. Many genes, proteins, and metabolites associated with GBM metabolism reprogramming have been found to be aberrantly expressed, which may provide potential targets for cancer treatment. Therefore, it is becoming increasingly important to explore the role of internal and external factors in metabolic regulation in order to identify more precise therapeutic targets and diagnostic markers for GBM. In this review, we define the metabolic characteristics of GBM, investigate metabolic specificities such as targetable vulnerabilities and therapeutic resistance, as well as present current efforts to target GBM metabolism to improve the standard of care.

The role of BCL2L13 in glioblastoma: turning a need into a target

Glioblastoma (GBM) is the most common aggressive central nervous system cancer. GBM has a high mortality rate, with a median survival time of 12-15 months after diagnosis. A poor prognosis and a shorter life expectancy may result from resistance to standard treatments such as radiation and chemotherapy. Temozolomide has been the mainstay treatment for GBM, but unfortunately, there are high rates of resistance with GBM bypassing apoptosis. A proposed mechanism for bypassing apoptosis is decreased ceramide levels, and previous research has shown that within GBM cells, B cell lymphoma 2-like 13 (BCL2L13) can inhibit ceramide synthase. This review aims to discuss the causes of resistance in GBM cells, followed by a brief description of BCL2L13 and an explanation of its mechanism of action. Further, lipids, specifically ceramide, will be discussed concerning cancer and GBM cells, focusing on ceramide synthase and its role in developing GBM. By gathering all current information on BCL2L13 and ceramide synthase, this review seeks to enable an understanding of these pieces of GBM in the hope of finding an effective treatment for this disease.

The role of ApoE in fatty acid transport from neurons to astrocytes under ischemia/hypoxia conditions

BACKGROUND

The aim of this study was to investigate whether ischemia/hypoxia conditions induce fatty acid transport from neurons to astrocytes and whether this mechanism is affected by ApoE isoforms.

METHODS AND RESULTS

A neonatal rat model of hypoxic-ischemic brain damage was established. Excessive accumulation of lipid droplets and upregulation of ApoE expression occurred in the hippocampus and cerebral cortex after hypoxia-ischemia, which implied the occurrence of abnormal fatty acid metabolism. Lipid peroxidation was induced in an oxygen-glucose deprivation and reperfusion (OGDR) model of ApoE-/- primary neurons. The number of BODIPY 558/568 C12-positive particles (fatty acid markers) transferred from neurons to astrocytes was significantly increased with the addition of human recombinant ApoE compared with that in the OGDR group, which significantly increased the efficiency of fatty acid transport from neurons to astrocytes and neuronal viability. However, ApoE4 was found to be associated with lower efficiency in fatty acid transport and less protective effects in OGDR-induced neuronal cell death than both ApoE2 and ApoE3. COG133, an ApoE-mimetic peptide, partially compensated for the adverse effects of ApoE4. FABP5 and SOD1 gene and protein expression levels were upregulated in astrocytes treated with BODIPY 558/568 C12 particles.

CONCLUSIONS

In conclusion, ApoE plays an important role in mediating the transport of fatty acids from neurons to astrocytes under ischemia/hypoxia conditions, and this transport mechanism is ApoE isoform dependent. ApoE4 has a low transfer efficiency and may be a potential target for the clinical treatment of neonatal hypoxic-ischemic encephalopathy.

Proteomic, Metabolomic, and Fatty Acid Profiling of Small Extracellular Vesicles from Glioblastoma Stem-Like Cells and Their Role in Tumor Heterogeneity

Glioblastoma is a deadly brain tumor for which there is no cure. The presence of glioblastoma stem-like cells (GSCs) contributes to the heterogeneous nature of the disease and makes developing effective therapies challenging. Glioblastoma cells have been shown to influence their environment by releasing biological nanostructures known as extracellular vesicles (EVs). Here, we investigated the role of GSC-derived nanosized EVs (<200 nm) in glioblastoma heterogeneity, plasticity, and aggressiveness, with a particular focus on their protein, metabolite, and fatty acid content. We showed that conditioned medium and small extracellular vesicles (sEVs) derived from cells of one glioblastoma subtype induced transcriptomic and proteomic changes in cells of another subtype. We found that GSC-derived sEVs are enriched in proteins playing a role in the transmembrane transport of amino acids, carboxylic acids, and organic acids, growth factor binding, and metabolites associated with amino acid, carboxylic acid, and sugar metabolism. This suggests a dual role of GSC-derived sEVs in supplying neighboring GSCs with valuable metabolites and proteins responsible for their transport. Moreover, GSC-derived sEVs were enriched in saturated fatty acids, while their respective cells were high in unsaturated fatty acids, supporting that the loading of biological cargos into sEVs is a highly regulated process and that GSC-derived sEVs could be sources of saturated fatty acids for the maintenance of glioblastoma cell metabolism. Interestingly, sEVs isolated from GSCs of the proneural and mesenchymal subtypes are enriched in specific sets of proteins, metabolites, and fatty acids, suggesting a molecular collaboration between transcriptionally different glioblastoma cells. In summary, this study revealed the complexity of GSC-derived sEVs and unveiled their potential contribution to tumor heterogeneity and critical cellular processes commonly deregulated in glioblastoma.

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.

A positive feedback loop between ZEB2 and ACSL4 regulates lipid metabolism to promote breast cancer metastasis

Lipid metabolism plays a critical role in cancer metastasis. However, the mechanisms through which metastatic genes regulate lipid metabolism remain unclear. Here, we describe a new oncogenic-metabolic feedback loop between the epithelial-mesenchymal transition transcription factor ZEB2 and the key lipid enzyme ACSL4 (long-chain acyl-CoA synthetase 4), resulting in enhanced cellular lipid storage and fatty acid oxidation (FAO) to drive breast cancer metastasis. Functionally, depletion of ZEB2 or ACSL4 significantly reduced lipid droplets (LDs) abundance and cell migration. ACSL4 overexpression rescued the invasive capabilities of the ZEB2 knockdown cells, suggesting that ACSL4 is crucial for ZEB2-mediated metastasis. Mechanistically, ZEB2-activated ACSL4 expression by directly binding to the ACSL4 promoter. ACSL4 binds to and stabilizes ZEB2 by reducing ZEB2 ubiquitination. Notably, ACSL4 not only promotes the intracellular lipogenesis and LDs accumulation but also enhances FAO and adenosine triphosphate production by upregulating the FAO rate-limiting enzyme CPT1A (carnitine palmitoyltransferase 1 isoform A). Finally, we demonstrated that ACSL4 knockdown significantly reduced metastatic lung nodes in vivo. In conclusion, we reveal a novel positive regulatory loop between ZEB2 and ACSL4, which promotes LDs storage to meet the energy needs of breast cancer metastasis, and identify the ZEB2-ACSL4 signaling axis as an attractive therapeutic target for overcoming breast cancer metastasis.

Liquid biopsy: creating opportunities in brain space

In recent years, liquid biopsy has emerged as an alternative method to diagnose and monitor tumors. Compared to classical tissue biopsy procedures, liquid biopsy facilitates the repetitive collection of diverse cellular and acellular analytes from various biofluids in a non/minimally invasive manner. This strategy is of greater significance for high-grade brain malignancies such as glioblastoma as the quantity and accessibility of tumors are limited, and there are collateral risks of compromised life quality coupled with surgical interventions. Currently, blood and cerebrospinal fluid (CSF) are the most common biofluids used to collect circulating cells and biomolecules of tumor origin. These liquid biopsy analytes have created opportunities for real-time investigations of distinct genetic, epigenetic, transcriptomics, proteomics, and metabolomics alterations associated with brain tumors. This review describes different classes of liquid biopsy biomarkers present in the biofluids of brain tumor patients. Moreover, an overview of the liquid biopsy applications, challenges, recent technological advances, and clinical trials in the brain have also been provided.

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.

Integrative rare disease biomedical profile based network supporting drug repurposing or repositioning, a case study of glioblastoma

BACKGROUND

Glioblastoma (GBM) is the most aggressive and common malignant primary brain tumor; however, treatment remains a significant challenge. This study aims to identify drug repurposing or repositioning candidates for GBM by developing an integrative rare disease profile network containing heterogeneous types of biomedical data.

METHODS

We developed a Glioblastoma-based Biomedical Profile Network (GBPN) by extracting and integrating biomedical information pertinent to GBM-related diseases from the NCATS GARD Knowledge Graph (NGKG). We further clustered the GBPN based on modularity classes which resulted in multiple focused subgraphs, named mc_GBPN. We then identified high-influence nodes by performing network analysis over the mc_GBPN and validated those nodes that could be potential drug repurposing or repositioning candidates for GBM.

RESULTS

We developed the GBPN with 1,466 nodes and 107,423 edges and consequently the mc_GBPN with forty-one modularity classes. A list of the ten most influential nodes were identified from the mc_GBPN. These notably include Riluzole, stem cell therapy, cannabidiol, and VK-0214, with proven evidence for treating GBM.

CONCLUSION

Our GBM-targeted network analysis allowed us to effectively identify potential candidates for drug repurposing or repositioning. Further validation will be conducted by using other different types of biomedical and clinical data and biological experiments. The findings could lead to less invasive treatments for glioblastoma while significantly reducing research costs by shortening the drug development timeline. Furthermore, this workflow can be extended to other disease areas.

Antiangiogenic Action of JZL184 on Endothelial Cells via Inhibition of VEGF Expression in Hypoxic Lung Cancer Cells

JZL184, an inhibitor of monoacylglycerol lipase (MAGL) and thus of the degradation of the endocannabinoid 2-arachidonoylglycerol (2-AG), mediates various anticancer effects in preclinical studies. However, studies on the effect of this or other MAGL inhibitors under hypoxia, an important factor in tumor biology and response to cancer therapy, have not yet been performed in cancer cells. In the present study, the impact of the conditioned media (CM) of A549 and H358 lung cancer cells incubated with JZL184 under hypoxic conditions on the angiogenic properties of human umbilical vein endothelial cells (HUVECs) was investigated. Treatment of HUVECs with CM derived from cancer cells cultured for 48 h under hypoxic conditions was associated with a substantial increase in migration and tube formation compared with unconditioned medium, which was inhibited when cancer cells were incubated with JZL184. In this process, JZL184 led to a significant increase in 2-AG levels in both cell lines. Analysis of a panel of proangiogenic factors revealed inhibition of hypoxia-induced vascular endothelial growth factor (VEGF) expression by JZL184. Antiangiogenic and VEGF-lowering effects were also demonstrated for the MAGL inhibitor MJN110. Receptor antagonist experiments suggest partial involvement of the cannabinoid receptors CB1 and CB2 in the antiangiogenic and VEGF-lowering effects induced by JZL184. The functional importance of VEGF for angiogenesis in the selected system is supported by observations showing inhibition of VEGF receptor 2 (VEGFR2) phosphorylation in HUVECs by CM from hypoxic cancer cells treated with JZL184 or when hypoxic cancer cell-derived CM was spiked with a neutralizing VEGF antibody. On the other hand, JZL184 did not exert a direct effect on VEGFR2 activation induced by recombinant VEGF, so there seems to be no downstream effect on already released VEGF. In conclusion, these results reveal a novel mechanism of antiangiogenic action of JZL184 under conditions of hypoxic tumor-endothelial communication.

Radiation therapy promotes unsaturated fatty acids to maintain survival of glioblastoma

Radiation therapy (RT) is essential for the management of glioblastoma (GBM). However, GBM frequently relapses within the irradiated margins, thus suggesting that RT might stimulate mechanisms of resistance that limits its efficacy. GBM is recognized for its metabolic plasticity, but whether RT-induced resistance relies on metabolic adaptation remains unclear. Here, we show in vitro and in vivo that irradiated GBM tumors switch their metabolic program to accumulate lipids, especially unsaturated fatty acids. This resulted in an increased formation of lipid droplets to prevent endoplasmic reticulum (ER) stress. The reduction of lipid accumulation with genetic suppression and pharmacological inhibition of the fatty acid synthase (FASN), one of the main lipogenic enzymes, leads to mitochondrial dysfunction and increased apoptosis of irradiated GBM cells. Combination of FASN inhibition with focal RT improved the median survival of GBM-bearing mice. Supporting the translational value of these findings, retrospective analysis of the GLASS consortium dataset of matched GBM patients revealed an enrichment in lipid metabolism signature in recurrent GBM compared to primary. Overall, these results demonstrate that RT drives GBM resistance by generating a lipogenic environment permissive to GBM survival. Targeting lipid metabolism might be required to develop more effective anti-GBM strategies.

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.

Inhibition of Monoacylglycerol Lipase Decreases Angiogenic Features of Endothelial Cells via Release of Tissue Inhibitor of Metalloproteinase-1 from Lung Cancer Cells

Despite the well-described anticarcinogenic effects of endocannabinoids, the influence of the endocannabinoid system on tumor angiogenesis is still debated. In the present study, conditioned medium (CM) from A549 and H358 lung cancer cells treated with ascending concentrations of the monoacylglycerol lipase (MAGL) inhibitor JZL184 and 2-arachidonoylglycerol (2-AG), a prominent MAGL substrate, caused a concentration-dependent reduction in human umbilical vein endothelial cell (HUVEC) migration and tube formation compared with CM from vehicle-treated cancer cells. Comparative experiments with MAGL inhibitors JW651 and MJN110 showed the same results. On the other hand, the angiogenic properties of HUVECs were not significantly altered by direct stimulation with JZL184 or 2-AG or by exposure to CM of JZL184- or 2-AG-treated non-cancerous bronchial epithelial cells (BEAS-2B). Inhibition of HUVEC migration and tube formation by CM of JZL184- and 2-AG-treated A549 cells was abolished in the presence of the CB1 antagonist AM-251. Increased release of tissue inhibitor of metalloproteinase-1 (TIMP-1) from JZL184- or 2-AG-stimulated A549 or H358 cells was shown to exert an antiangiogenic effect on HUVECs, as confirmed by siRNA experiments. In addition, JZL184 caused a dose-dependent regression of A549 tumor xenografts in athymic nude mice, which was associated with a decreased number of CD31-positive cells and upregulation of TIMP-1-positive cells in xenograft tissue. In conclusion, our data suggest that elevation of 2-AG by MAGL inhibition leads to increased release of TIMP-1 from lung cancer cells, which mediates an antiangiogenic effect on endothelial cells.

Integrating Multi-Omics Analysis for Enhanced Diagnosis and Treatment of Glioblastoma: A Comprehensive Data-Driven Approach

The most aggressive primary malignant brain tumor in adults is glioblastoma (GBM), which has poor overall survival (OS). There is a high relapse rate among patients with GBM despite maximally safe surgery, radiation therapy, temozolomide (TMZ), and aggressive treatment. Hence, there is an urgent and unmet clinical need for new approaches to managing GBM. The current study identified modules (MYC, EGFR, PIK3CA, SUZ12, and SPRK2) involved in GBM disease through the NeDRex plugin. Furthermore, hub genes were identified in a comprehensive interaction network containing 7560 proteins related to GBM disease and 3860 proteins associated with signaling pathways involved in GBM. By integrating the results of the analyses mentioned above and again performing centrality analysis, eleven key genes involved in GBM disease were identified. ProteomicsDB and Gliovis databases were used for determining the gene expression in normal and tumor brain tissue. The NetworkAnalyst and the mGWAS-Explorer tools identified miRNAs, SNPs, and metabolites associated with these 11 genes. Moreover, a literature review of recent studies revealed other lists of metabolites related to GBM disease. The enrichment analysis of identified genes, miRNAs, and metabolites associated with GBM disease was performed using ExpressAnalyst, miEAA, and MetaboAnalyst tools. Further investigation of metabolite roles in GBM was performed using pathway, joint pathway, and network analyses. The results of this study allowed us to identify 11 genes (UBC, HDAC1, CTNNB1, TRIM28, CSNK2A1, RBBP4, TP53, APP, DAB1, PINK1, and RELN), five miRNAs (hsa-mir-221-3p, hsa-mir-30a-5p, hsa-mir-15a-5p, hsa-mir-130a-3p, and hsa-let-7b-5p), six metabolites (HDL, N6-acetyl-L-lysine, cholesterol, formate, N, N-dimethylglycine/xylose, and X2. piperidinone) and 15 distinct signaling pathways that play an indispensable role in GBM disease development. The identified top genes, miRNAs, and metabolite signatures can be targeted to establish early diagnostic methods and plan personalized GBM treatment strategies.

Distinct Cholesterol Localization in Glioblastoma Multiforme Revealed by Mass Spectrometry Imaging

Glioblastoma multiforme (GBM) is the most common and aggressive brain tumor in adults and is highly resistant to chemo- and radiotherapies. GBM has been associated with alterations in lipid contents, but lipid metabolism reprogramming in tumor cells is not fully elucidated. One of the key hurdles is to localize the lipid species that are correlated with tumor growth and invasion. A better understanding of the localization of abnormal lipid metabolism and its vulnerabilities may open up to novel therapeutic approaches. Here, we use time-of-flight secondary ion mass spectrometry (ToF-SIMS) to spatially probe the lipid composition in a GBM biopsy from two regions with different histopathologies: one region with most cells of uniform size and shape, the homogeneous part, and the other with cells showing a great variation in size and shape, the heterogeneous part. Our results reveal elevated levels of cholesterol, diacylglycerols, and some phosphatidylethanolamine in the homogeneous part, while the heterogeneous part was dominated by a variety of fatty acids, phosphatidylcholine, and phosphatidylinositol species. We also observed a high expression of cholesterol in the homogeneous tumor region to be associated with large cells but not with macrophages. Our findings suggest that ToF-SIMS can distinguish in lipid distribution between parts within a human GBM tumor, which can be linked to different molecular mechanisms.

Targeting fatty acid oxidation via Acyl-CoA binding protein hinders glioblastoma invasion

The diffuse nature of Glioblastoma (GBM) tumors poses a challenge to current therapeutic options. We have previously shown that Acyl-CoA Binding Protein (ACBP, also known as DBI) regulates lipid metabolism in GBM cells, favoring fatty acid oxidation (FAO). Here we show that ACBP downregulation results in wide transcriptional changes affecting invasion-related genes. In vivo experiments using patient-derived xenografts combined with in vitro models demonstrated that ACBP sustains GBM invasion via binding to fatty acyl-CoAs. Blocking FAO mimics ACBP^KD-induced immobility, a cellular phenotype that can be rescued by increasing FAO rates. Further investigation into ACBP-downstream pathways served to identify Integrin beta-1, a gene downregulated upon inhibition of either ACBP expression or FAO rates, as a mediator for ACBP's role in GBM invasion. Altogether, our findings highlight a role for FAO in GBM invasion and reveal ACBP as a therapeutic vulnerability to stall FAO and subsequent cell invasion in GBM tumors.

Integrative Rare Disease Biomedical Profile based Network Supporting Drug Repurposing, a case study of Glioblastoma

Background Glioblastoma (GBM) is the most aggressive and common malignant primary brain tumor; however, treatment remains a significant challenge. This study aims to identify drug repurposing candidates for GBM by developing an integrative rare disease profile network containing heterogeneous types of biomedical data. Methods We developed a Glioblastoma-based Biomedical Profile Network (GBPN) by extracting and integrating biomedical information pertinent to GBM-related diseases from the NCATS GARD Knowledge Graph (NGKG). We further clustered the GBPN based on modularity classes which resulted in multiple focused subgraphs, named mc_GBPN. We then identified high-influence nodes by performing network analysis over the mc_GBPN and validated those nodes that could be potential drug repositioning candidates for GBM. Results We developed the GBPN with 1,466 nodes and 107,423 edges and consequently the mc_GBPN with forty-one modularity classes. A list of the ten most influential nodes were identified from the mc_GBPN. These notably include Riluzole, stem cell therapy, cannabidiol, and VK-0214, with proven evidence for treating GBM. Conclusion Our GBM-targeted network analysis allowed us to effectively identify potential candidates for drug repurposing. This could lead to less invasive treatments for glioblastoma while significantly reducing research costs by shortening the drug development timeline. Furthermore, this workflow can be extended to other disease areas.

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 Potential Prognostic Marker TyG Index Predicts Time to Brain Metastasis at HER2 Positive Breast Cancer

Background

We aimed to investigate the prognostic significance of insulin resistance (IR) markers fasting triglyceride-glucose (TyG) index and triglyceride high-density lipoprotein cholesterol (TG/HDL-C) ratio in HER2-positive breast cancer (BC) patients with brain metastasis (BM).

Methods

In this single-center study, 120 patients who met the criteria were included. TyG and TG/HDL-C at the time of diagnosis were computed retrospectively. For TyG and TG/HDL-C, the median values of 9.32 and 2.95 were taken as the cut-off, respectively. TyG values <9.32 and <2.95 were considered low, and TG/HDL-C values ≥9.32 and ≥2.95 were considered high.

Results

The median overall survival (OS) was 47 months (95% CI: 40.54-53.45). Time to BM was 22 months (95% CI: 17.22-26.73). The median time to BM was 35 months (95% CI: 20.90-49.09) in the low TyG group and 15 months (95% CI: 8.92-21.07) in the high TyG group (p < 0.001). The time to BM was 27 months (95% CI: 20.49-33.50) in the low TG/HDL-C group and 20 months (95% CI: 16.76-23.23) in the high TG/HDL-C group (p=0.084). In the multivariate Cox regression analysis, the TyG index (HR: 20.98, 95% CI: 7.14-61.59, p < 0.001) was an independent risk factor for time to BM.

Conclusion

These findings suggest that the TyG index could be used as a predictive biomarker at the time of diagnosis for risk of time BM in patients with HER2-positive BC. The TyG index can be used as a standard potential marker with prospective studies confirming these data.

In vivo functional characterization of EGFR variants identifies novel drivers of glioblastoma

BACKGROUND

Glioblastoma is the most common and aggressive primary brain tumor. Large-scale sequencing initiatives have cataloged its mutational landscape in hopes of elucidating mechanisms driving this deadly disease. However, a major bottleneck in harnessing this data for new therapies is deciphering "driver" and "passenger" events amongst the vast volume of information.

METHODS

We utilized an autochthonous, in vivo screening approach to identify driver, EGFR variants. RNA-Seq identified unique molecular signatures of mouse gliomas across these variants, which only differ by a single amino acid change. In particular, we identified alterations to lipid metabolism, which we further validated through an unbiased lipidomics screen.

RESULTS

Our screen identified A289I as the most potent EGFR variant, which has previously not been characterized. One of the mechanisms through which A289I promotes gliomagenesis is to alter cellular triacylglycerides through MTTP. Knockout of Mttp in mouse gliomas, reduces gliomagenesis in multiple models.

CONCLUSIONS

EGFR variants that differ by a single amino acid residue differentially promote gliomagenesis. Among the identified mechanism that drives glioma growth include lipid metabolism through MTTP. Understanding triacylglyceride accumulation may present a prospective therapeutic pathway for this deadly disease.

Investigating the Potential of Lipids for Use as Biomarkers for Glioblastoma via an Untargeted Lipidomics Approach

OBJECTIVE

The types and functions of lipids involved in glioblastoma (GB) are not well known. Lipidomics is a new field that examines cellular lipids on a large scale and novel aplication of lipidomics in the biomedical sciences have emerged. This study aimed to investigate the potential of blood lipids for use as biomarkers for the diagnosis of GB via untargated lipidomic approach. Gaining a deeper understanding of lipid metabolism in patients with GB can contribute to the early diagnosis with GB patiens and also development of novel and better therapeutic options.

METHODS

This study was performed using blood samples collected from 14 patients (eight females and six males) and 14 controls (eight females and six males). Lipids were extracted from blood samples and quantified using phosphorus assay. Lipid profiles of between patients with GB and controls were compared via an untargeted lipidomics approach using 6530 Accurate-Mass Q-TOF LC/MS mass spectrometer.

RESULTS

According to the results obtained using the untargeted lipidomics approach, differentially regulated lipid species, including fatty acid (FA), glycerolipid (GL), glycerophospholipid (PG), saccharolipid (SL), sphingolipid (SP), and sterol lipid (ST) were identified between in patients with GB and controls.

CONCLUSION

Differentially regulated lipids were identified in patients with GB, and these lipid species were predicted as potential biomarkers for diagnosis of GB.

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.

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.

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.

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.

Characterization of fatty acid compositions in longissimus thoracis muscle and identification of candidate gene and SNPs related to polyunsaturated fatty acid in Hu sheep

Fatty acid (FA) composition contributes greatly to the quality and nutritional value of lamb meat. In the present study, FA was measured in longissimus thoracis (LT) muscles of 1,085 Hu sheep using gas chromatography. Comparative transcriptomic analysis was conducted in LT muscles to identify differentially expressed genes (DEGs) between six individuals with high polyunsaturated fatty acids (H-PUFA, 15.27% ± 0.42%) and six with low PUFA (L-PUFA, 5.22% ± 0.25%). Subsequently, the single nucleotide polymorphisms (SNPs) in a candidate gene PLIN2 were correlated with FA traits. The results showed a total of 29 FA compositions and 8 FA groups were identified, with the highest content of monounsaturated fatty acids (MUFA, 46.54%, mainly C18:1n9c), followed by saturated fatty acids (SFA, 44.32%, mainly C16:0), and PUFA (8.72%, mainly C18:2n6c), and significant correlations were observed among the most of FA traits. Transcriptomic analyses identified 110 upregulated and 302 downregulated DEGs between H-PUFA and L-PUFA groups. The functional enrichment analysis revealed three significant Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and 17 gene ontology (GO) terms, in which regulation of lipolysis in adipocytes, the AMPK signaling pathway, and the PPAR signaling pathway may play important roles in FA metabolism and biosynthesis. In addition, weighted gene co-expression network analysis (WGCNA) identified 37 module genes associated with PUFA-related traits. In general, PLIN1, LIPE, FABP4, LEP, ACACA, ADIPOQ, SCD, PCK2, FASN, PLIN2, LPL, FABP3, THRSP, and ACADVL may have a great impact on PUFA metabolism and lipid deposition. Four SNPs within PLIN2 were significantly associated with FA. Of those, SNP1 (g.287 G>A) was significantly associated with C18:1n9c and MUFA, and SNP4 (g.7807 T>C) was significantly correlated with PUFA (C18:3n3). In addition, the combined genotype of SNP1 (g.287 G>A), SNP3 (g.7664 T>C), and SNP4 (g.7807 T>C) were significantly correlated with C16:1, C17:0, C18:1C6, PUFA (C18:3n3, C22:6n3), and n-6/n-3 PUFA. These results contribute to the knowledge of the biological mechanisms and genetic markers involved in the composition of FA in Hu sheep.

Fatty acid metabolism and radiation-induced anti-tumor immunity

Fatty acid metabolic reprogramming has emerged as a major regulator of anti-tumor immune responses with large body of evidence that demonstrate its ability to impact the differentiation and function of immune cells. Therefore, depending on the metabolic cues that stem in the tumor microenvironment, the tumor fatty acid metabolism can tilt the balance of inflammatory signals to either promote or impair anti-tumor immune responses. Oxidative stressors such as reactive oxygen species generated from radiation therapy can rewire the tumor energy supply, suggesting that radiation therapy can further perturb the energy metabolism of a tumor by promoting fatty acid production. In this review, we critically discuss the network of fatty acid metabolism and how it regulates immune response especially in the context of radiation therapy.

Progress of potential drugs targeted in lipid metabolism research

Lipids are a class of complex hydrophobic molecules derived from fatty acids that not only form the structural basis of biological membranes but also regulate metabolism and maintain energy balance. The role of lipids in obesity and other metabolic diseases has recently received much attention, making lipid metabolism one of the attractive research areas. Several metabolic diseases are linked to lipid metabolism, including diabetes, obesity, and atherosclerosis. Additionally, lipid metabolism contributes to the rapid growth of cancer cells as abnormal lipid synthesis or uptake enhances the growth of cancer cells. This review introduces the potential drug targets in lipid metabolism and summarizes the important potential drug targets with recent research progress on the corresponding small molecule inhibitor drugs. The significance of this review is to provide a reference for the clinical treatment of metabolic diseases related to lipid metabolism and the treatment of tumors, hoping to deepen the understanding of lipid metabolism and health.

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.

Abnormal expression of HADH, an enzyme of fatty acid oxidation, affects tumor development and prognosis (Review)

Tumor occurrence and progression are closely associated with abnormal energy metabolism and energy metabolism associated with glucose, proteins and lipids. The reprogramming of energy metabolism is one of the hallmarks of cancer. As a form of energy metabolism, fatty acid metabolism includes fatty acid uptake, de novo synthesis and β‑oxidation. In recent years, the role of abnormal fatty acid β‑oxidation in tumors has gradually been recognized. Mitochondrial trifunctional protein (MTP) serves an important role in fatty acid β‑oxidation and HADH (two subtypes: α subunit, HADHA and β subunit, HADHB) are important subunits of MTP. HADH participates in the steps of 2, 3 and 4 fatty acid β‑oxidation. However, there is no review summarizing the specific role of HADH in tumors. Therefore, the present study focused on HADH as the main indicator to explore the changes in fatty acid β‑oxidation in several types of tumors. The present review summarized the changes in HADH in 11 organs (cerebrum, oral cavity, esophagus, liver, pancreas, stomach, colorectum, lymph, lung, breast, kidney), the effect of up‑ and downregulation and the relationship of HADH with prognosis. In summary, HADH can be either a suppressor or a promoter depending on where the tumor is located, which is closely associated with prognostic assessment. HADHA and HADHB have similar prognostic roles in known and comparable tumors.

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.

DEEP Surveillance of Brain Cancer Using Self-Functionalized 3D Nanoprobes for Noninvasive Liquid Biopsy

Brain cancers, one of the most fatal malignancies, require accurate diagnosis for guided therapeutic intervention. However, conventional methods for brain cancer prognosis (imaging and tissue biopsy) face challenges due to the complex nature and inaccessible anatomy of the brain. Therefore, deep analysis of brain cancer is necessary to (i) detect the presence of a malignant tumor, (ii) identify primary or secondary origin, and (iii) find where the tumor is housed. In order to provide a diagnostic technique with such exhaustive information here, we attempted a liquid biopsy-based deep surveillance of brain cancer using a very minimal amount of blood serum (5 μL) in real time. We hypothesize that holistic analysis of serum can act as a reliable source for deep brain cancer surveillance. To identify minute amounts of tumor-derived material in circulation, we synthesized an ultrasensitive 3D nanosensor, adopted SERS as a diagnostic methodology, and undertook a DEEP neural network-based brain cancer surveillance. Detection of primary and secondary tumor achieved 100% accuracy. Prediction of intracranial tumor location achieved 96% accuracy. This modality of using patient sera for deep surveillance is a promising noninvasive liquid biopsy tool with the potential to complement current brain cancer diagnostic methodologies.

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.

Metabolomic and Lipidomic Profiling of Gliomas-A New Direction in Personalized Therapies

Simple Summary

Gliomas comprise an extremely diverse category of brain tumors that are difficult to diagnose and treat. As a result, scientists continue to search for new treatment solutions, with personalized medicine having emerged as a particularly promising therapeutic approach. Metabolomics and its sub-discipline, lipidomics, are two scientific fields well-suited to support this search. Metabolomics focuses on the physicochemical changes in the metabolome, which include all of the small endogenous and exogenous compounds in a biological system. As such, metabolic analysis can help identify important biochemical pathways which could be the targets for new therapeutic approaches. This review examines the new directions of personalized therapies for gliomas and how metabolomic and lipidomic analysis assists in developing these strategies and monitoring their effectiveness. The discussion of new strategies is preceded by a brief overview of the current “gold standard” treatment for gliomas and the obstacles that new treatment approaches must overcome.

Abstract

In addition to being the most common primary brain tumor, gliomas are also among the most difficult to diagnose and treat. At present, the “gold standard” in glioma treatment entails the surgical resection of the largest possible portion of the tumor, followed by temozolomide therapy and radiation. However, this approach does not always yield the desired results. Additionally, the ability to cross the blood-brain barrier remains a major challenge for new potential drugs. Thus, researchers continue to search for targeted therapies that can be individualized based on the specific characteristics of each case. Metabolic and lipidomic research may represent two of the best ways to achieve this goal, as they enable detailed insights into the changes in the profile of small molecules in a biological system/specimen. This article reviews the new approaches to glioma therapy based on the analysis of alterations to biochemical pathways, and it provides an overview of the clinical results that may support personalized therapies in the future.

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.

KCNK3 inhibits proliferation and glucose metabolism of lung adenocarcinoma via activation of AMPK-TXNIP pathway

Non-small cell lung cancer (NSCLC) is a primary histological subtype of lung cancer with increased morbidity and mortality. K⁺ channels have been revealed to be involved in carcinogenesis in various malignant tumors. However, TWIK-related acid-sensitive potassium channel 1 (TASK-1, also called KCNK3), a genetic member of K2P channels, remains an enigma in lung adenocarcinoma (LUAD). Herein, we investigated the pathological process of KCNK3 in proliferation and glucose metabolism of LUAD. The expressions of KCNK3 in LUAD tissues and corresponding adjacent tissues were identified by RNA sequencing, quantitative real-time polymerase chain reaction, western blot, and immunohistochemistry. Gain and loss-of-function assays were performed to estimate the role of KCNK3 in proliferation and glucose metabolism of LUAD. Additionally, energy metabolites of LUAD cells were identified by targeted metabolomics analysis. The expressions of metabolic molecules and active biomarkers associated with AMPK-TXNIP signaling pathway were detected via western blot and immunofluorescence. KCNK3 was significantly downregulated in LUAD tissues and correlated with patients' poor prognosis. Overexpression of KCNK3 largely regulated the process of oncogenesis and glycometabolism in LUAD in vitro and in vivo. Mechanistic studies found that KCNK3-mediated differential metabolites were mainly enriched in AMPK signaling pathway. Furthermore, rescue experiments demonstrated that KCNK3 suppressed proliferation and glucose metabolism via activation of the AMPK-TXNIP pathway in LUAD cells. In summary, our research highlighted an emerging role of KCNK3 in the proliferative activity and glycometabolism of LUAD, suggesting that KCNK3 may be an optimal predictor for prognosis and a potential therapeutic target of LUAD.