SNAP25 Inhibits Glioma Progression by Regulating Synapse Plasticity via GLS-Mediated Glutaminolysis

A CYCLIC PEPTIDE TARGETS GLIOBLASTOMA BY BINDING TO ABERRANTLY EXPOSED SNAP25

Disease-specific changes in tumors and other diseased tissues are an important target of research because they provide clues on the pathophysiology of the disease as well as uncovering potentially useful markers for diagnosis and treatment. Here, we report a new cyclic peptide, CESPLLSEC (CES), that specifically accumulated (homed) in intracranial U87MG and the WT-GBM model of glioblastoma from intravenous (IV) injection, associating with the vasculature. Affinity chromatography of U87MG tumor extracts on insolubilized CES peptide identified Synaptosomal Associated Protein 25 (SNAP25) as a candidate target molecule (receptor) for CES. Several results supported the identification of SNAP25 as the CES receptor. IV-injected FAM-CES colocalized with SNAP25 in the tumors, and direct binding studies showed specific CES peptide binding to recombinant human SNAP25. A CES peptide-drug conjugate designed for photodynamic therapy showed selective cytotoxicity to SNAP25+ glioblastoma cell lines. Specific accumulation of systemically injected anti-SNAP25 antibody in U87MG glioblastoma, and labeling of intact U87MG cells with anti-SNAP in flow cytometry showed that SNAP25 is available from the circulation but not in normal tissues and that it is present at the cell surface. Using an array of ECM proteins and surface plasmon resonance revealed that SNAP25 binds moderately to collagen V and strongly to collagen VI. Modeling studies suggested that CES and collagen VI compete for the same binding site on SNAP25. Our results introduce CES as a valuable targeting peptide for drug delivery, and its receptor SNAP25 as a possible molecular marker of interest for glioblastoma.

The complex molecular epileptogenesis landscape of glioblastoma

The cortical microenvironment surrounding malignant glioblastoma is a source of depolarizing crosstalk favoring hyperexcitability, tumor expansion, and immune evasion. Neosynaptogenesis, excess glutamate, and altered intrinsic membrane currents contribute to excitability dyshomeostasis, yet only half of the cases develop seizures, suggesting that tumor and host genomics, along with location, rather than mass effect, play a critical role. We analyzed the spatial contours and expression of 358 clinically validated human epilepsy genes in the human glioblastoma transcriptome compared to non-tumor adult and developing cortex datasets. Nearly half, including dosage-sensitive genes whose expression levels are securely linked to monogenic epilepsy, are strikingly enriched and aberrantly regulated at the leading edge, supporting a complex epistatic basis for peritumoral epileptogenesis. Surround hyperexcitability induced by complex patterns of proepileptic gene expression may explain the limited efficacy of narrowly targeted antiseizure medicines and the persistence of epilepsy following tumor resection and clarify why not all brain tumors provoke seizures.

Moniezia benedeni drives the SNAP-25 expression of the enteric nerves in sheep's small intestine

BACKGROUND

The neuroimmune network plays a crucial role in regulating mucosal immune homeostasis within the digestive tract. Synaptosome-associated protein 25 (SNAP-25) is a presynaptic membrane-binding protein that activates ILC2s, initiating the host's anti-parasitic immune response.

METHODS

To investigate the effect of Moniezia benedeni (M. benedeni) infection on the distribution of SNAP-25 in the sheep's small intestine, the recombinant plasmid pET-28a-SNAP-25 was constructed and expressed in BL21, yielding the recombinant protein. Then, the rabbit anti-sheep SNAP-25 polyclonal antibody was prepared and immunofluorescence staining was performed with it. The expression levels of SNAP-25 in the intestines of normal and M. benedeni-infected sheep were detected by ELISA.

RESULTS

The results showed that the SNAP-25 recombinant protein was 29.3 KDa, the titer of the prepared immune serum reached 1:128,000. It was demonstrated that the rabbit anti-sheep SNAP-25 polyclonal antibody could bind to the natural protein of sheep SNAP-25 specifically. The expression levels of SNAP-25 in the sheep's small intestine revealed its primary presence in the muscular layer and lamina propria, particularly around nerve fibers surrounding the intestinal glands. Average expression levels in the duodenum, jejunum, and ileum were 130.32 pg/mg, 185.71 pg/mg, and 172.68 pg/mg, respectively. Under conditions of M. benedeni infection, the spatial distribution of SNAP-25-expressing nerve fibers remained consistent, but its expression level in each intestine segment was increased significantly (P < 0.05), up to 262.02 pg/mg, 276.84 pg/mg, and 326.65 pg/mg in the duodenum, jejunum, and ileum, and it was increased by 101.06%, 49.07%, and 89.16% respectively.

CONCLUSIONS

These findings suggest that M. benedeni could induce the SNAP-25 expression levels in sheep's intestinal nerves significantly. The results lay a foundation for further exploration of the molecular mechanism by which the gastrointestinal nerve-mucosal immune network perceives parasites in sheep.

Cuproptosis in cancer: biological implications and therapeutic opportunities

Cuproptosis, a newly identified copper (Cu)-dependent form of cell death, stands out due to its distinct mechanism that sets it apart from other known cell death pathways. The molecular underpinnings of cuproptosis involve the binding of Cu to lipoylated enzymes in the tricarboxylic acid cycle. This interaction triggers enzyme aggregation and proteotoxic stress, culminating in cell death. The specific mechanism of cuproptosis has yet to be fully elucidated. This newly recognized form of cell death has sparked numerous investigations into its role in tumorigenesis and cancer therapy. In this review, we summarized the current knowledge on Cu metabolism and its link to cancer. Furthermore, we delineated the molecular mechanisms of cuproptosis and summarized the roles of cuproptosis-related genes in cancer. Finally, we offered a comprehensive discussion of the most recent advancements in Cu ionophores and nanoparticle delivery systems that utilize cuproptosis as a cutting-edge strategy for cancer treatment.

APOE Christchurch enhances a disease-associated microglial response to plaque but suppresses response to tau pathology

Background

Apolipoprotein E ε4 (APOE4) is the strongest genetic risk factor for late-onset Alzheimer's disease (LOAD). A recent case report identified a rare variant in APOE, APOE3-R136S (Christchurch), proposed to confer resistance to autosomal dominant Alzheimer's Disease (AD). However, it remains unclear whether and how this variant exerts its protective effects.

Methods

We introduced the R136S variant into mouse Apoe (ApoeCh) and investigated its effect on the development of AD-related pathology using the 5xFAD model of amyloidosis and the PS19 model of tauopathy. We used immunohistochemical and biochemical analysis along with single-cell spatial transcriptomics and proteomics to explore the impact of the ApoeCh variant on AD pathological development and the brain's response to plaques and tau.

Results

In 5xFAD mice, ApoeCh enhances a Disease-Associated Microglia (DAM) phenotype in microglia surrounding plaques, and reduces plaque load, dystrophic neurites, and plasma neurofilament light chain. By contrast, in PS19 mice, ApoeCh suppresses the microglial and astrocytic responses to tau-laden neurons and does not reduce tau accumulation or phosphorylation, but partially rescues tau-induced synaptic and myelin loss. We compared how microglia responses differ between the two mouse models to elucidate the distinct DAM signatures induced by ApoeCh. We identified upregulation of antigen presentation-related genes in the DAM response in a PS19 compared to a 5xFAD background, suggesting a differential response to amyloid versus tau pathology that is modulated by the presence of ApoeCh.

Conclusions

These findings highlight the ability of the ApoeCh variant to modulate microglial responses based on the type of pathology, enhancing DAM reactivity in amyloid models and dampening neuroinflammation to promote protection in tau models. This suggests that the Christchurch variant's protective effects likely involve multiple mechanisms, including changes in receptor binding and microglial programming.

Molecular subtype identification and prognosis stratification based on golgi apparatus-related genes in head and neck squamous cell carcinoma

BACKGROUND

Abnormal dynamics of the Golgi apparatus reshape the tumor microenvironment and immune landscape, playing a crucial role in the prognosis and treatment response of cancer. This study aims to investigate the potential role of Golgi apparatus-related genes (GARGs) in the heterogeneity and prognosis of head and neck squamous cell carcinoma (HNSCC).

METHODS

Transcriptional data and corresponding clinical information of HNSCC were obtained from public databases for differential expression analysis, consensus clustering, survival analysis, immune infiltration analysis, immune therapy response assessment, gene set enrichment analysis, and drug sensitivity analysis. Multiple machine learning algorithms were employed to construct a prognostic model based on GARGs. A nomogram was used to integrate and visualize the multi-gene model with clinical pathological features.

RESULTS

A total of 321 GARGs that were differentially expressed were identified, out of which 69 were associated with the prognosis of HNSCC. Based on these prognostic genes, two molecular subtypes of HNSCC were identified, which showed significant differences in prognosis. Additionally, a risk signature consisting of 28 GARGs was constructed and demonstrated good performance for assessing the prognosis of HNSCC. This signature divided HNSCC into the high-risk and low-risk groups with significant differences in multiple clinicopathological characteristics, including survival outcome, grade, T stage, chemotherapy. Immune response-related pathways were significantly activated in the high-risk group with better prognosis. There were significant differences in chemotherapy drug sensitivity and immune therapy response between the high-risk and low-risk groups, with the low-risk group being more suitable for receiving immunotherapy. Riskscore, age, grade, and radiotherapy were independent prognostic factors for HNSCC and were used to construct a nomogram, which had good clinical applicability.

CONCLUSIONS

We successfully identified molecular subtypes and prognostic signature of HNSCC that are derived from GARGs, which can be used for the assessment of HNSCC prognosis and treatment responses.

Construction and validation of a risk model based on the key SNARE proteins to predict the prognosis and immune microenvironment of gliomas

Background

Synaptic transmission between neurons and glioma cells can promote glioma progression. The soluble N-ethylmaleimide-sensitive fusion factor attachment protein receptors (SNARE) play a key role in synaptic functions. We aimed to construct and validate a novel model based on the SNARE proteins to predict the prognosis and immune microenvironment of glioma.

Methods

Differential expression analysis and COX regression analysis were used to identify key SRGs in glioma datasets, and we constructed a prognostic risk model based on the key SRGs. The prognostic value and predictive performance of the model were assessed in The Cancer Genome Atlas (TCGA) and Chinese glioma Genome Atlas (CGGA) datasets. Functional enrichment analysis and immune-related evaluation were employed to reveal the association of risk scores with tumor progression and microenvironment. A prognostic nomogram containing the risk score was established and assessed by calibration curves and time-dependent receiver operating characteristic curves. We verified the changes of the key SRGs in glioma specimens and cells by real-time quantitative PCR and Western blot analyses.

Results

Vesicle-associated membrane protein 2 (VAMP2) and vesicle-associated membrane protein 5 (VAMP5) were identified as two SRGs affecting the prognoses of glioma patients. High-risk patients characterized by higher VAMP5 and lower VAMP2 expression had a worse prognosis. Higher risk scores were associated with older age, higher tumor grades, IDH wild-type, and 1p19q non-codeletion. The SRGs risk model showed an excellent predictive performance in predicting the prognosis in TCGA and CGGA datasets. Differentially expressed genes between low- and high-risk groups were mainly enriched in the pathways related to immune infiltration, tumor metastasis, and neuronal activity. Immune score, stromal score, estimate score, tumor mutational burden, and expression of checkpoint genes were positively correlated with risk scores. The nomogram containing the risk score showed good performance in predicting the prognosis of glioma. Low VAMP2 and high VAMP5 were found in different grades of glioma specimens and cell lines.

Conclusion

We constructed and validated a novel risk model based on the expression of VAMP2 and VAMP5 by bioinformatics analysis and experimental confirmation. This model might be helpful for clinically predicting the prognosis and response to immunotherapy of glioma patients.

Revealing Tissue Heterogeneity and Spatial Dark Genes from Spatially Resolved Transcriptomics by Multiview Graph Networks

Spatially resolved transcriptomics (SRT) is capable of comprehensively characterizing gene expression patterns and providing an unbiased image of spatial composition. To fully understand the organizational complexity and tumor immune escape mechanism, we propose stMGATF, a multiview graph attention fusion model that integrates gene expression, histological images, spatial location, and gene association. To better extract information, stMGATF exploits SimCLRv2 for visual feature exaction and employs edge feature enhanced graph attention networks for the learning potential embedding of each view. A global attention mechanism is used to adaptively integrate 3 views to obtain low-dimensional representation. Applied to diverse SRT datasets, stMGATF is robust and outperforms other methods in detecting spatial domains and denoising data even with different resolutions and platforms. In particular, stMGATF contributes to the elucidation of tissue heterogeneity and extraction of 3-dimensional expression domains. Importantly, considering the associations between genes in tumors, stMGATF can identify the spatial dark genes ignored by traditional methods, which can be used to predict tumor-driving transcription factors and reveal tumor immune escape mechanisms, providing theoretical evidence for the development of new immunotherapeutic strategies.

Identification and validation of cuproptosis related genes and signature markers in bronchopulmonary dysplasia disease using bioinformatics analysis and machine learning

BACKGROUND

Bronchopulmonary Dysplasia (BPD) has a high incidence and affects the health of preterm infants. Cuproptosis is a novel form of cell death, but its mechanism of action in the disease is not yet clear. Machine learning, the latest tool for the analysis of biological samples, is still relatively rarely used for in-depth analysis and prediction of diseases.

METHODS AND RESULTS

First, the differential expression of cuproptosis-related genes (CRGs) in the GSE108754 dataset was extracted and the heat map showed that the expression of NFE2L2 gene was significantly higher in the control group whereas the expression of GLS gene was significantly higher in the treatment group. Chromosome location analysis showed that both the genes were positively correlated and associated with chromosome 2. The results of immune infiltration and immune cell differential analysis showed differences in the four immune cells, significantly in Monocytes cells. Five new pathways were analyzed through two subgroups based on consistent clustering of CRG expression. Weighted correlation network analysis (WGCNA) set the screening condition to the top 25% to obtain the disease signature genes. Four machine learning algorithms: Generalized Linear Models (GLM), Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGB) were used to screen the disease signature genes, and the final five marker genes for disease prediction. The models constructed by GLM method were proved to be more accurate in the validation of two datasets, GSE190215 and GSE188944.

CONCLUSION

We eventually identified two copper death-associated genes, NFE2L2 and GLS. A machine learning model-GLM was constructed to predict the prevalence of BPD disease, and five disease signature genes NFATC3, ERMN, PLA2G4A, MTMR9LP and LOC440700 were identified. These genes that were bioinformatics analyzed could be potential targets for identifying BPD disease and treatment.

Metabolic Adjustments following Glutaminase Inhibition by CB-839 in Glioblastoma Cell Lines

Most tumor cells can use glutamine (Gln) for energy generation and biosynthetic purposes. Glutaminases (GAs) convert Gln into glutamate and ammonium. In humans, GAs are encoded by two genes: GLS and GLS2. In glioblastoma, GLS is commonly overexpressed and considered pro-oncogenic. We studied the metabolic effects of inhibiting GLS activity in T98G, LN229, and U87MG human glioblastoma cell lines by using the inhibitor CB-839. We performed metabolomics and isotope tracing experiments using U-13C-labeled Gln, as well as 15N-labeled Gln in the amide group, to determine the metabolic fates of Gln carbon and nitrogen atoms. In the presence of the inhibitor, the results showed an accumulation of Gln and lower levels of tricarboxylic acid cycle intermediates, and aspartate, along with a decreased oxidative labeling and diminished reductive carboxylation-related labeling of these metabolites. Additionally, CB-839 treatment caused decreased levels of metabolites from pyrimidine biosynthesis and an accumulation of intermediate metabolites in the de novo purine nucleotide biosynthesis pathway. The levels of some acetylated and methylated metabolites were significantly increased, including acetyl-carnitine, trimethyl-lysine, and 5-methylcytosine. In conclusion, we analyzed the metabolic landscape caused by the GLS inhibition of CB-839 in human glioma cells, which might lead to the future development of new combination therapies with CB-839.

Proteomic analysis of spinal cord tissue in a rat model of cancer-induced bone pain

Background

Cancer-induced bone pain (CIBP) is a moderate to severe pain and seriously affects patients' quality of life. Spinal cord plays critical roles in pain generation and maintenance. Identifying differentially expressed proteins (DEPs) in spinal cord is essential to elucidate the mechanisms of cancer pain.

Methods

CIBP rat model was established by the intratibial inoculation of MRMT-1 cells. Positron emission tomography (PET) scan and transmission electron microscopy (TEM) were used to measure the stats of spinal cord in rats. Label free Liquid Chromatography with tandem mass spectrometry (LC-MS-MS) were used to analyze the whole proteins from the lumbar spinal cord. Differentially expressed proteins (DEPs) were performed using Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, and verified using Western blot and immunofluorescence assay.

Results

In the current study, CIBP rats exhibited bone damage, spontaneous pain, mechanical hyperalgesia, and impaired motor ability. In spinal cord, an hypermetabolism and functional abnormality were revealed on CIBP rats. An increase of synaptic vesicles density in active zone and a disruption of mitochondrial structure in spinal cord of CIBP rats were observed. Meanwhile, 422 DEPs, consisting of 167 up-regulated and 255 down-regulated proteins, were identified among total 1539 proteins. GO enrichment analysis indicated that the DEPs were mainly involved in catabolic process, synaptic function, and enzymic activity. KEGG pathway enrichment analysis indicated a series of pathways, including nervous system disease, hormonal signaling pathways and amino acid metabolism, were involved. Expression change of synaptic and mitochondrial related protein, such as complexin 1 (CPLX1), synaptosomal-associated protein 25 (SNAP25), synaptotagmin 1 (SYT1), aldehyde dehydrogenase isoform 1B1 (ALDH1B1), Glycine amidinotransferase (GATM) and NADH:ubiquinone oxidoreductase subunit A11 (NDUFA11), were further validated using immunofluorescence and Western blot analysis.

Conclusion

This study provides valuable information for understanding the mechanisms of CIBP, and supplies potential therapeutic targets for cancer pain.

Prognostic value of γ‐aminobutyric acidergic synapse-associated signature for lower-grade gliomas

Background

Synapse-associated proteins (SAPs) play important roles in central nervous system (CNS) tumors. Recent studies have reported that γ-aminobutyric acidergic (GABAergic) synapses also play critical roles in the development of gliomas. However, biomarkers of GABAergic synapses in low-grade gliomas (LGGs) have not yet been reported.

Methods

mRNA data from normal brain tissue and gliomas were obtained from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases, respectively. A validation dataset was also obtained from the Chinese Glioma Genome Atlas (CGGA) database. The expression patterns of GABAergic synapse-related genes (GSRGs) were evaluated with difference analysis in LGGs. Then, a GABAergic synapse-related risk signature (GSRS) was constructed with least absolute shrinkage and selection operator (LASSO) Cox regression analysis. According to the expression value and coefficients of identified GSRGs, the risk scores of all LGG samples were calculated. Univariate and multivariate Cox regression analyses were conducted to evaluate related risk scores for prognostic ability. Correlations between characteristics of the tumor microenvironment (TME) and risk scores were explored with single-sample gene set enrichment analysis (ssGSEA) and immunity profiles in LGGs. The GSRS-related pathways were investigated by gene set variation analysis (GSVA). Real-time PCR and the Human Protein Atlas (HPA) database were applied to explore related expression of hub genes selected in the GSRS.

Results

Compared with normal brain samples, 25 genes of 31 GSRGs were differentially expressed in LGG samples. A constructed five-gene GSRS was related to clinicopathological features and prognosis of LGGs by the LASSO algorithm. It was shown that the risk score level was positively related to the infiltrating level of native CD4 T cells and activated dendritic cells. GSVA identified several cancer-related pathways associated with the GSRS, such as P53 pathways and the JAK-STAT signaling pathway. Additionally, CA2, PTEN, OXTR, and SLC6A1 (hub genes identified in the GSRS) were regarded as the potential predictors in LGGs.

Conclusion

A new five-gene GSRS was identified and verified by bioinformatics methods. The GSRS provides a new perspective in LGG that may contribute to more accurate prediction of prognosis of LGGs.

The upregulation of glutamate decarboxylase 67 against hippocampal excitability damage in male fetal rats by prenatal caffeine exposure

As a kind of xanthine alkaloid, caffeine is widely present in beverages, food, and analgesic drugs. Our previous studies have shown that prenatal caffeine exposure (PCE) can induce programmed hypersensitivity of the hypothalamic-pituitary-adrenal (HPA) axis in offspring rats, which is involved in developing many chronic adult diseases. The present study further examined the potential molecular mechanism and toxicity targets of hippocampal dysfunction, which might mediate the programmed hypersensitivity of the HPA axis in offspring. Pregnant rats were intragastrically administered with 0, 30, and 120 mg/kg/day caffeine from gestational days (GD) 9-20, and the fetal rats were extracted at GD20. Rat fetal hippocampal H19-7/IGF1R cell line was treated with caffeine, adenosine A2A receptor (A2AR) agonist (CGS-21680) or adenylate cyclase agonist (forskolin) plus caffeine. Compared with the control group, hippocampal neurons of male fetal rats by PCE displayed increased apoptosis and reduced synaptic plasticity, whereas glutamate decarboxylase 67 (GAD67) expression was increased. Moreover, the expression of A2AR was down-regulated, PCE inhibited the cAMP/PKA/CREB/BDNF/TrkB pathway. Furthermore, the results in vitro were consistent with the in vivo study. Both CGS21680 and forskolin could reverse the above alteration caused by caffeine. These results indicated that PCE inhibits the BDNF pathway and mediates the hippocampus's glutamate (Glu) excitotoxicity. The compensatory up-regulation of GAD67 unbalanced the Glu/gamma-aminobutyric acid (GABA)ergic output, leading to the impaired negative feedback to the hypothalamus and hypersensitivity of the HPA axis.

The cuproptosis-related signature associated with the tumor environment and prognosis of patients with glioma

Background

Copper ions are essential for cellular physiology. Cuproptosis is a novel method of copper-dependent cell death, and the cuproptosis-based signature for glioma remains less studied.

Methods

Several glioma datasets with clinicopathological information were collected from TCGA, GEO and CGGA. Robust Multichip Average (RMA) algorithm was used for background correction and normalization, cuproptosis-related genes (CRGs) were then collected. The TCGA-glioma cohort was clustered using ConsensusClusterPlus. Univariate Cox regression analysis and the Random Survival Forest model were performed on the differentially expressed genes to identify prognostic genes. The cuproptosis-signature was constructed by calculating CuproptosisScore using Multivariate Cox regression analysis. Differences in terms of genomic mutation, tumor microenvironment, and enrichment pathways were evaluated between high- or low-CuproptosisScore. Furthermore, drug response prediction was carried out utilizing pRRophetic.

Results

Two subclusters based on CRGs were identified. Patients in cluster2 had better clinical outcomes. The cuproptosis-signature was constructed based on CuproptosisScore. Patients with higher CuproptosisScore had higher WHO grades and worse prognosis, while patients with lower grades were more likely to develop IDH mutations or MGMT methylation. Univariate and Multivariate Cox regression analysis demonstrated CuproptosisScore was an independent prognostic factor. The accuracy of the signature in prognostic prediction was further confirmed in 11 external validation datasets. In groups with high-CuproptosisScore, PIK3CA, MUC16, NF1, TTN, TP53, PTEN, and EGFR showed high mutation frequency. IDH1, TP53, ATRX, CIC, and FUBP1 demonstrated high mutation frequency in low-CuproptosisScore group. The level of immune infiltration increased as CuproptosisScore increased. SubMap analysis revealed patients with high-CuproptosisScore may respond to anti-PD-1 therapy. The IC50 values of Bexarotene, Bicalutamide, Bortezomib, and Cytarabine were lower in the high-CuproptosisScore group than those in the low-CuproptosisScore group. Finally, the importance of IGFBP2 in TCGA-glioma cohort was confirmed.

Conclusion

The current study revealed the novel cuproptosis-based signature might help predict the prognosis, biological features, and appropriate treatment for patients with glioma.

The Circ_0001367/miR-545-3p/LUZP1 Axis Regulates Cell Proliferation, Migration and Invasion in Glioma Cells

Glioma is the most common primary intracranial malignant tumour in adults. It has a high incidence and poses a serious threat to human health. Circular RNA is a hotspot of cancer research. In this study, we aimed to explore the role of circ_0001367 in gliomagenesis and the underlying mechanism. First, qRT-PCR was conducted, which showed that circ_0001367 level was downregulated in glioma tissues and cells. Next, gain-of-function and loss-of-function assays were performed, which indicated that circ_0001367 inhibited the proliferation, migration and invasion of glioma cells. Subsequent bioinformatics analysis, dual-luciferase reporter assays, RNA immunoprecipitation assays and cell function assays demonstrated that circ_0001367 inhibited the proliferation, migration and invasion of glioma cells by absorbing miR-545-3p and thereby regulating the expression of leucine zipper protein (LUZP1). Finally, an in vivo experiment was conducted, which demonstrated that circ_0001367 inhibited glioma growth in vivo by modulating miR-545-3p and LUZP1. Taken together, the results of this study demonstrate that the circ_0001367/miR-545-3p/LUZP1 axis may be a novel target for glioma therapy.