Exploring the Causal Role of Immune Cells in Cerebral Aneurysm Through Single-Cell Transcriptomics and Mendelian Randomization Analysis.

Cerebral aneurysm (CA) represent a significant clinical challenge, characterized by pathological dilation of cerebral arteries. Recent evidence underscores the crucial involvement of immune cells in CA pathogenesis. This study aims to explore the complex interplay between immune cells and CA formation. We analyzed single-cell RNA sequencing data from the GSE193533 dataset, focusing on unruptured CA and their controls. Comprehensive cell-type identification and pseudotime trajectory analyses were conducted to delineate the dynamic shifts in immune cell populations. Additionally, a two-sample Mendelian Randomization (MR) approach was employed to investigate the causal influence of various immunophenotypes on CA susceptibility and the reciprocal effect of CA formation on immune phenotypes. Single-cell transcriptomic analysis revealed a progressive loss of vascular smooth muscle cells (VSMCs) and an increase in monocytes/macrophages (Mo/MΦ) and other immune cells, signifying a shift from a structural to an inflammatory milieu in CA evolution. MR analysis identified some vital immunophenotypes, such as CD64 on CD14+ CD16+ monocytes (OR: 1.236, 95% CI: 1.064 to 1.435, p=0.006), as potential risk factors for CA development, while others, like CD28- CD8br %CD8br (OR: 0.883, 95% CI: 0.789 to 0.988, p=0.030), appeared protective. Reverse MR analysis demonstrated that CA formation could modulate specific immunophenotypic expressions, highlighting a complex bidirectional interaction between CA pathology and immune response. This study underscores the pivotal role of immune cells in this process through the integration of single-cell transcriptomics with MR analysis, offering a comprehensive perspective on CA pathogenesis, potentially guiding future therapeutic strategies targeting specific immune pathways.

Identification of MDK as a Hypoxia- and Epithelial-Mesenchymal Transition-Related Gene Biomarker of Glioblastoma Based on a Novel Risk Model and In Vitro Experiments.

BACKGROUND: Tumor cells are commonly exposed to a hypoxic environment, which can easily induce the epithelial-mesenchymal transition (EMT) of tumor cells, further affecting tumor proliferation, invasion, metastasis, and drug resistance. However, the predictive role of hypoxia and EMT-related genes in glioblastoma (GBM) has not been investigated. METHODS: Intersection genes were identified by weighted correlation network analysis (WGCNA) and differential expression analyses, and a risk model was further constructed by LASSO and Cox analyses. Clinical, immune infiltration, tumor mutation, drug treatment, and enrichment profiles were analyzed based on the risk model. The expression level of the MDK gene was tested using RT-PCR, immunohistochemistry, and immunofluorescence. CCK8 and EdU were employed to determine the GBM cells' capacity for proliferation while the migration and invasion ability were detected by a wound healing assay and transwell assay, respectively. RESULTS: Based on the GBM data of the TCGA and GTEx databases, 58 intersection genes were identified, and a risk model was constructed. The model was verified in the CGGA cohort, and its accuracy was confirmed by the ROC curve (AUC = 0.807). After combining clinical subgroups, univariate and multivariate Cox regression analyses showed that risk score and age were independent risk factors for GBM patients. Furthermore, our subsequent analysis of immune infiltration, tumor mutation, and drug treatment showed that risk score and high- and low-risk groups were associated with multiple immune cells, mutated genes, and drugs. Enrichment analysis indicated that the differences between high- and low-risk groups were manifested in tumor-related pathways, including the PI3K-AKT and JAK-STAT pathways. Finally, in vivo experiments proved that the hypoxia environment promoted the expression of MDK, and MDK knockdown reduced the proliferation, migration, and EMT of GBM cells induced by hypoxia. CONCLUSIONS: Our novel prognostic correlation model provided more potential treatment strategies for GBM patients.

TMEM2 induces epithelial-mesenchymal transition and promotes resistance to temozolomide in GBM cells.

Glioblastoma multiforme (GBM) is the most common intracranial malignant tumor and is notorious for its poor prognosis. An important element in the short overall survival of GBM patients is the lack of understanding the pathogenesis and progression of tumor and deficiency biomarkers that can be used for early diagnosis and therapeutic sensitivity monitoring. Studies have shown that transmembrane protein 2 (TMEM2) is participated in tumorigenesis of various human tumors, including rectal and breast cancers. Although Qiuyi Jiang et al. have reported that TMEM2 combined with IDH1/2 and 1p19q can predict the survival time of glioma patients based on bioinformatics, its expression and biological role of glioma remain unclear. In our study, we investigated the effect of TMEM2 expression level on glioma malignancy in public datasets and an independent internal dataset. We revealed TEMM2 expression was higher in GBM tissues than in non-tumor brain tissues (NBT). Moreover, the increase in TMEM2 expression level was closely related to tumor malignancy. The survival analysis showed that TMEM2 high expression reduces survival time in all glioma patients, including GBM and LGG patients. Subsequent experiments demonstrated that knockdown TMEM2 inhibited proliferation of GBM cells. In addition, we analyzed TMEM2 mRNA levels in different GBM subtypes, and demonstrated that TMEM2 expression was upregulated in mesenchymal subtype. Meanwhile, bioinformatics analysis and transwell assay indicated that knockdown TMEM2 suppressed epithelial-mesenchymal transition (EMT) in GBM. Importantly, Kaplan-Meier analysis demonstrated that TMEM2 high expression reduced the treatment response to TMZ in GBM patients. Knockdown of TMEM2 alone did not reduce apoptosis GBM cells, but significant apoptotic cells were observed in the group treated with additional TMZ. These studies may contribute to improving the accuracy of early diagnosis and evaluating the effectiveness of TMZ treatment in GBM patients.

Grade scoring system reveals distinct molecular subtypes and identifies KIF20A as a novel biomarker for predicting temozolomide treatment efficiency in gliomas.

BACKGROUND: The importance of molecular diagnostics is increasingly emphasized in the 2021 WHO guidelines for gliomas. There is considerable variability in molecular features and prognosis among glioma patients with the same pathological WHO grade. METHODS: mRNA data and clinical information of human glioma patients were obtained from TCGA and CGGA databases, while expression profiles and TMZ resistance phenotypes of human glioma stem cells were acquired from the GEO database. Differentially expressed genes were identified across distinct WHO grades. Unsupervised clustering was performed on glioma patients based on DEG expression profiles. The Boruta algorithm was employed to identify feature genes for distinct molecular subtypes, and PCA was used to reduce the dimensionality of the feature gene expression data. Grade scores for each sample were calculated and correlated with patients' clinical molecular pathological features and immune microenvironment. Gene set enrichment analysis identified grade score-related functional pathways. Weighted gene co-expression network analysis identified grade score-associated biomarkers. The impact of the hub gene on malignant glioma behavior was validated through in vitro experiments, including CCK-8, EdU, colony formation, Transwell, wound healing, and immunofluorescence assays. RESULTS: A total of 672 and 687 samples were screened from TCGA and CGGA databases, respectively, along with 6 control, 24 low-grade, and 40 glioblastoma samples from our hospital. Two robust gene clusters were identified based on the expression profiles of 4,476 DEGs among grades 2, 3, and 4 tissues, revealing distinct prognoses. The grade scores exhibited significant heterogeneity across different WHO grade samples, representing diverse immune microenvironments. Grade scores served as independent risk factors for predicting patient prognosis, with higher sensitivity than traditional biomarkers. KIF20A, identified as a grade score-related biomarker, was independently associated with glioma prognosis. Exclusively expressed in tumor cells, KIF20A knockdown significantly inhibited tumor growth, invasion, and EMT biological behavior in glioma cells. Furthermore, KIF20A could serve as a biological marker for predicting patient response to TMZ treatment. CONCLUSION: The grade scoring system enhances our understanding of the glioma tumor microenvironment. KIF20A, a novel biomarker for predicting TMZ treatment efficiency, influences malignant tumor behavior by affecting the EMT biological behavior of glioma cells.

Phosducin-like 3 is a novel prognostic and onco-immunological biomarker in glioma: A multi-omics analysis with experimental verification.

Malignant glioma is the most frequent primary tumor of the central nervous system. PDCL3 is a member of the phosducin-like protein family, and its imbalance has been shown to be associated with several human diseases. However, the underlying role of PDCL3 in human malignant cancers, especially in malignant gliomas, is unclear. In this study, we combined public database analysis and experimental verification to explore the differential expression, prognostic value and potential functions and mechanisms of PDCL3. The results revealed that PDCL3 is upregulated in multiple cancers and acts as a potential prognostic biomarker of glioma. Mechanistically, PDCL3 expression is associated with epigenetic modifications and genetic mutations. PDCL3 may directly interact with the chaperonin-containing TCP1 complex, regulating cell malignancy, cell communication and the extracellular matrix. More importantly, the association of PDCL3 with the infiltration of immune cells, immunomodulatory genes, immune checkpoints, cancer stemness and angiogenesis suggested that PDCL3 may regulate the glioma immune landscape. Furthermore, PDCL3 interference also decreased the proliferation, invasion and migration of glioma cells. In conclusion, PDCL3 is a novel oncogene and can be adopted as a biomarker with value in assisting clinical diagnosis, predicting patient outcomes and assessing the immune landscape of the tumor microenvironment in glioma.

Fatostatin induces ferroptosis through inhibition of the AKT/mTORC1/GPX4 signaling pathway in glioblastoma.

Glioblastoma multiforme (GBM) is the most common and fatal primary malignant central nervous system tumor in adults. Although there are multiple treatments, the median survival of GBM patients is unsatisfactory, which has prompted us to continuously investigate new therapeutic strategies, including new drugs and drug delivery approaches. Ferroptosis, a kind of regulated cell death (RCD), has been shown to be dysregulated in various tumors, including GBM. Fatostatin, a specific inhibitor of sterol regulatory element binding proteins (SREBPs), is involved in lipid and cholesterol synthesis and has antitumor effects in a variety of tumors. However, the effect of fatostatin has not been explored in the field of ferroptosis or GBM. In our study, through transcriptome sequencing, in vivo experiments, and in vitro experiments, we found that fatostatin induces ferroptosis by inhibiting the AKT/mTORC1/GPX4 signaling pathway in glioblastoma. In addition, fatostatin inhibits cell proliferation and the EMT process through the AKT/mTORC1 signaling pathway. We also designed a p28-functionalized PLGA nanoparticle loaded with fatostatin, which could better cross the blood-brain barrier (BBB) and be targeted to GBM. Our research identified the unprecedented effects of fatostatin in GBM and presented a novel drug-targeted delivery vehicle capable of penetrating the BBB in GBM.

Identification and validation of a novel prognostic signature based on mitochondria and oxidative stress related genes for glioblastoma.

BACKGROUND: Mitochondria represent a major source of reactive oxygen species (ROS) in cells, and the direct increase in ROS content is the primary cause of oxidative stress, which plays an important role in tumor proliferation, invasion, angiogenesis, and treatment. However, the relationship between mitochondrial oxidative stress-related genes and glioblastoma (GBM) remains unclear. This study aimed to investigate the value of mitochondria and oxidative stress-related genes in the prognosis and therapeutic targets of GBM. METHODS: We retrieved mitochondria and oxidative stress-related genes from several public databases. The LASSO regression and Cox analyses were utilized to build a risk model and the ROC curve was used to assess its performance. Then, we analyzed the correlation between the model and immunity and mutation. Furthermore, CCK8 and EdU assays were utilized to verify the proliferative capacity of GBM cells and flow cytometry was used to analyze apoptosis rates. Finally, the JC-1 assay and ATP levels were utilized to detect mitochondrial function, and the intracellular ROS levels were determined using MitoSOX and BODIPY 581/591 C11. RESULTS: 5 mitochondrial oxidative stress-related genes (CTSL, TXNRD2, NUDT1, STOX1, CYP2E1) were screened by differential expression analysis and Cox analysis and incorporated in a risk model which yielded a strong prediction accuracy (AUC value = 0.967). Furthermore, this model was strongly related to immune cell infiltration and mutation status and could identify potential targeted therapeutic drugs for GBM. Finally, we selected NUDT1 for further validation in vitro. The results showed that NUDT1 was elevated in GBM, and knockdown of NUDT1 inhibited the proliferation and induced apoptosis of GBM cells, while knockdown of NUDT1 damaged mitochondrial homeostasis and induced oxidative stress in GBM cells. CONCLUSION: Our study was the first to propose a prognostic model of mitochondria and oxidative stress-related genes, which provided potential therapeutic strategies for GBM patients.

TFR2 regulates ferroptosis and enhances temozolomide chemo-sensitization in gliomas.

Glioma is a common type of brain tumor with high incidence and mortality rates. Iron plays an important role in various physiological and pathological processes. Iron entry into the cell is promoted by binding the transferrin receptor 2 (TFR2) to the iron-transferrin complex. This study was designed to assess the association between TFR2 and ferroptosis in glioma. Lipid peroxidation levels in glioma cells were assessed by determination of lipid reactive oxygen species (ROS), glutathione content, and mitochondrial membrane potential. The effect of TFR2 on TMZ sensitivity was examined by cell viability assays, flow cytometry, and colony formation assays. We found that Low TFR2 expression predicted a better prognosis for glioma patients. And overexpression of TFR2 promoted the production of reactive oxygen species and lipid peroxidation in glioma cells, thereby further promoting ferroptosis. This could be reversed by the ferroptosis inhibitors Fer-1 and DFO (both inhibitors of ferroptosis). Moreover, TFR2 potentiated the cytotoxic effect of TMZ (temozolomide) via activating ferroptosis. In conclusion, we found that TFR2 induced ferroptosis and enhanced TMZ sensitivity in gliomas. Our findings might provide a new treatment strategy for glioma patients and improve their prognosis.

The RNA-binding protein CSTF2 regulates BAD to inhibit apoptosis in glioblastoma.

RNA-binding proteins (RBP) regulate several aspects of co- and post-transcriptional gene expression in cancer cells. CSTF2 is involved in the expression of many cellular mRNAs and involved in the 3'-end cleavage and polyadenylation of pre-mRNAs to terminate transcription. However, the role of CSTF2 in human glioblastoma (GBM) and the underlying mechanisms remain unclear. In the present study, CSTF2 was found to be upregulated in GBM, and its high expression predicted poor prognosis. Knockdown CSTF2 induced GBM cell apoptosis both in vitro and in vivo. Specific mechanism studies showed that CSTF2 unstabilized the mRNA of the BAD protein by shortening its 3' UTR. Additionally, an increase in the expression level of CSTF2 decreased the expression level of BAD. In conclusion, CSTF2 binds to the mRNA of the BAD protein to shorten its 3'UTR, which negatively affects the BAD mediated apoptosis and promotes GBM cell survival.

Immunogenic cell death-related risk signature predicts prognosis and characterizes the tumour microenvironment in lower-grade glioma.

Lower-grade glioma (LGG) is a common malignant primary tumour in the central nervous system, and most patients eventually develop highly aggressive gliomas despite comprehensive traditional treatment. Tumour molecular subtypes and prognostic biomarkers play a crucial role in LGG diagnosis and treatment. Therefore, the identification of novel biomarkers in LGG patients is crucial for predicting the prognosis of glioma. Immunogenic cell death (ICD) is defined as regulated cell death that is sufficient to activate the adaptive immune response of immunocompetent hosts. The combination of ICD and immunotherapy might exert a greater and more persistent antitumour effect in gliomas. In our study, we explored the expression, function, and genetic alterations of 34 ICD-related genes. Using 12 ICD-related genes, including IL17RA, IL1R1, EIF2AK3, CD4, PRF1, CXCR3, CD8A, BAX, PDIA3, CASP8, MYD88, and CASP1, we constructed and validated an ICD-related risk signature via least absolute shrinkage and selection operator (LASSO) Cox regression analysis. All the information was obtained from public databases, including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and the Chinese Glioma Genome Atlas (CGGA) databases. Our results revealed that ICD-high risk groups have a poor prognosis and might be more sensitive to immune checkpoint blockade (ICB) immunotherapy. In addition, ICD-high risk groups were associated with 1p19q noncodeletion, higher WHO grade, wild type IDH, and an immunosuppressive tumour microenvironment. We verified the prognostic value of 12 ICD-related genes in TCGA and CGGA databases. Immunohistochemistry was performed to verify the expression of several ICD-related genes at the protein level. Our study provides a novel and comprehensive perspective to elucidate the underlying mechanisms of LGG prognosis and direction for future individualized cancer immunotherapy.

Identification and validation of a 17-gene signature to improve the survival prediction of gliomas.

Gliomas are one of the most frequent types of nervous system tumours and have significant morbidity and mortality rates. As a result, it is critical to fully comprehend the molecular mechanism of glioma to predict prognosis and target gene therapy. The goal of this research was to discover the hub genes of glioma and investigate their prognostic and diagnostic usefulness. In this study, we collected mRNA expression profiles and clinical information from glioma patients in the TCGA, GTEx, GSE68848, and GSE4920 databases. WGCNA and differential expression analysis identified 170 DEGs in the collected datasets. GO and KEGG pathway analyses revealed that DEGs were mainly enriched in gliogenesis and extracellular matrix. LASSO was performed to construct prognostic signatures in the TCGA cohort, and 17 genes were used to build risk models and were validated in the CGGA database. The ROC curve confirmed the accuracy of the prognostic signature. Univariate and multivariate Cox regression analyses showed that all independent risk factors for glioma except gender. Next, we performed ssGSEA to demonstrate a high correlation between risk score and immunity. Subsequently, 7 hub genes were identified by the PPI network and found to have great drug targeting potential. Finally, RPL39, as one of the hub genes, was found to be closely related to the prognosis of glioma patients. Knockdown of RPL39 in vitro significantly inhibited the proliferation and migration of glioma cells, whereas overexpression of RPL39 had the opposite effect. And we found that knockdown of RPL39 inhibited the polarization and infiltration of M2 phenotype macrophages. In conclusion, our new prognosis-related model provides more potential therapeutic strategies for glioma patients.

FAIM2 is a potential pan-cancer biomarker for prognosis and immune infiltration.

Fas apoptosis inhibitory molecule 2 (FAIM2) is an important member of the transmembrane BAX inhibitor motif containing (TMBIM) family. However, the role of FAIM2 in tumor prognosis and immune infiltration has rarely been studied. Here, we conducted a pan-cancer analysis to explore the role of FAIM2 in various tumors and further verified the results in glioma through molecular biology experiment. FAIM2 expression and clinical stages in tumor samples and para-cancerous samples were analyzed by TIMER2 database, GEPIA database, and the TISIDB database. The role of FAIM2 on prognosis was analyzed via GEPIA2. We utilized the ESTIMATE algorithm to evaluate the ImmuneScore and StromalScore of various tumors. In addition, we explored the correlation between FAIM2 expression and tumor immune cell infiltration by the TIMER2 database. The immune checkpoint genes, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), and DNA methylation related to FAIM2 were analyzed based on the TCGA database. The correlation between FAIM2 expression with Copy number variations (CNV) and methylation is explored by GSCA database. Protein-Protein Interaction (PPI) analysis was obtained from the STRING database and the CellMiner database was used to explore the association between FAIM2 expression and drug response. FAIM2 co-expression genes were studied by the LinkedOmics database. Immunohistochemistry, Western Blotting Analysis, Cell Viability Assay, Colony Formation Assay, and Edu staining assay were used in the molecular biology experiments section. The FAIM2 expression was down-regulated in most tumors and highly expressed FAIM2 was associated with a better prognosis in several cancers. FAIM2 plays an essential role in the tumor microenvironment and is closely associated with immune Infiltration in various tumors. The expression of FAIM2 was closely correlated to TMB, MSI, MMR, CNV, and DNA methylation. Furthermore, FAIM2 related genes in the PPI network and its co-expression genes in glioma are involved in a large number of immune-related pathways. Molecular biology experiments verified a cancer suppressor role for FAIM2 in glioma. FAIM2 may serve as a potential pan-cancer biomarker for prognosis and immune infiltration, especially in glioma. Moreover, this study might provide a potential target for tumor immunotherapy.

Development and validation of cuproptosis-associated prognostic signatures in WHO 2/3 glioma.

WHO 2/3 glioma is a common intracranial tumor that seriously affects the quality of life and survival time of patients. Previous studies have shown that the tricarboxylic acid (TCA) cycle is closely related to the occurrence and development of glioma, while recent studies have shown that cuproptosis, a novel programmed death pathway, is closely related to the inhibition of the TCA cycle. In our study, eight of ten cuproptosis-related genes (CRGs) were found to be differentially expressed between normal and WHO 2/3 glioma tissues. Through the LASSO algorithm, the cuproptosis-associated risk signatures (CARSs) were constructed, which can effectively predict the prognosis of WHO 2/3 glioma patients and are closely related to clinicopathological features. We analyzed the relationship between risk score and immune cell infiltration through Xcell, ssGSEA, TIMER database, and immune checkpoint molecules. In addition, the relationship between risk score and chemotherapeutic drug sensitivity was also investigated. The prognosis-related independent risk factors FDX1 and CDKN2A identified from CARSs are considered potential prognostic biomarkers for WHO 2/3 glioma. The clinical prognosis model based on cuproptosis is expected to provide an effective reference for the diagnosis and treatment of clinical WHO 2/3 glioma patients.

Exploring the inverse association of glioblastoma multiforme and Alzheimer's disease via bioinformatics analysis.

Glioblastoma multiforme (GBM) and Alzheimer's disease (AD) are two major diseases in the nervous system with a similar peak age of onset, which has the typical characteristics of high cost, difficult treatment, and poor prognosis. Epidemiological studies and a few molecular biological studies have hinted at an opposite relationship between AD and GBM. However, there are few studies on their reverse relationship, and the regulatory mechanism is still unclear, indicating that further systematic research is urgently needed. Our study firstly employs advanced bioinformatics methods to explore the inverse relationship between them and find various target drugs. We obtained the gene expression dataset from public databases (GEO, TCGA, and GTEx). Then, we identified 122 differentially expressed genes (DEGs) of AD and GBM. Four significant gene modules were identified through protein-protein interaction (PPI) and module construction, and 13 hub genes were found using cytoHubba. We constructed co-expression networks and found various target drugs through these hub genes. Functional enrichment analysis revealed that the AMPK pathway, cell cycle, and cellular senescence play important roles in AD and GBM. Our study may provide a potential direction for studying the opposite molecular mechanism of AD and GBM in the future.

IRF2-ferroptosis related gene is associated with prognosis and EMT in gliomas.

Ferroptosis is a new type of programmed cell death that has excellent anti-tumor potential in different tumors. However, the research on ferroptosis in glioma is still incomplete. In this study, we aimed to revealed the relationship between ferroptosis-related genes (FRGs) and glioma. We collected gene expression profiles of glioma patients from the TCGA and CGGA databases. All glioma samples were classified into five subtypes using the R software ConsensusClusterPlus. Subsequently, we performed single sample gene set enrichment analysis (ssGSEA) to explore the correlation between different subtypes and immune status and ferroptosis. Then co-expression modules were constructed via weighted gene co-expression network analysis (WGCNA). A Gene Ontology (GO) analysis was conducted to analyze the potential biological functions of the genes in the modules. Finally, we identified 10 hub genes using the PPI network. The in vitro experiments were used to validate our predictions. We found that the expression level of IRF2 is positively correlated with the grade of glioma. The overexpression of IRF2 could protect glioma cells from ferroptosis and enhance the invasive and migratory abilities. Silence of IRF2 had the opposite effect. In conclusion, we demonstrated a novel ferroptosis-related signature for predicting prognosis, and IRF2 could be a potential biomarker for diagnosis and treatment in glioma.

MS4A6A is a new prognostic biomarker produced by macrophages in glioma patients.

MS4A6A has been recognized as being associated with aging and the onset of neurodegenerative disease. However, the mechanisms of MS4A6A in glioma biology and prognosis are ill-defined. Here, we show that MS4A6A is upregulated in glioma tissues, resulting in unfavorable clinical outcomes and poor responses to adjuvant chemotherapy. Multivariate Cox regression analysis suggested that MS4A6A expression can act as a strong and independent predictor for glioma outcomes (CGGA1: HR: 1.765, p < 0.001; CGGA2: HR: 2.626, p < 0.001; TCGA: HR: 1.415, p < 0.001; Rembrandt: HR: 1.809, p < 0.001; Gravendeel: HR: 1.613, p < 0.001). A protein-protein interaction (PPI) network revealed that MS4A6A might be coexpressed with CD68, CD163, and macrophage-specific signatures. Enrichment analysis showed the innate immune response and inflammatory response to be markedly enriched in the high MS4A6A expression group. Additionally, single-cell RNA sequencing (scRNA-seq) analysis revealed distinctive expression features for MS4A6A in macrophages in the glioma immune microenvironment (GIME). Immunofluorescence staining confirmed colocalization of CD68/MS4A6A and CD163/MS4A6A in macrophages. Correlation analysis revealed that MS4A6A expression is positively related to the tumor mutation burden (TMB) of glioma, displaying the high potential of applying MS4A6A to evaluate responsiveness to immunotherapy. Altogether, our research indicates that MS4A6A upregulation may be used as a promising and effective indicator for adjuvant therapy and prognosis assessment.

Esterase-responsive and size-optimized prodrug nanoparticles for effective intracranial drug delivery and glioblastoma treatment.

Glioblastoma multiforme (GBM) is the intracranial malignancy with the highest rates of morbidity and mortality. Chemotherapy is often ineffective against GBM due to the presence of the blood-brain barrier (BBB); however, the application of nanotechnology is expected to overcome this limitation. Poly(lactic-co-glycolic acid) (PLGA) is a degradable and nontoxic functional polymer with good biocompatibility that is widely used in the pharmaceutical industry. Previous studies have shown that the ability of PLGA nanoparticles (NPs) to penetrate the BBB is largely determined by their size; however, determination of the optimal PLGA NP size requires further research. Here, we report a tandutinib-based prodrug (proTan), which responds to the GBM microenvironment, that was combined with NPs to overcome the BBB. AMD3100-PLGA NPs loaded with proTan inhibited tumor growth and effectively prolonged the survival of tumor-bearing mice.

BCAS3 accelerates glioblastoma tumorigenesis by restraining the P53/GADD45α signaling pathway.

As in many other cancers, highly malignant proliferation and disordered cell division play irreplaceable roles in the exceedingly easy recurrence and complex progression of glioblastoma multiforme (GBM); however, mechanistic studies of the numerous regulators involved in this process are still insufficiently thorough. The role of BCAS3 has been studied in other cancers, but its role in GBM is unclear. Here, our goal was to investigate the expression pattern of BCAS3 in GBM and its potential mechanism of action. Using TCGA database and human GBM samples, we found that BCAS3 expression was up-regulated in GBM, and its high expression predicted poor prognosis. To further investigate the relationship between BCAS3 and GBM characteristics, we up-regulated and down-regulated BCAS3 expression in GBM to detect its effect on cell proliferation and cell cycle. At the same time, we established U87 cells stably overexpressing BCAS3 and generated an intracranial xenograft model to investigate the Potential role of BCAS3 in vivo. Finally, based on in vitro cell experiments and in vivo GBM xenograft models, we observed that BCAS3 significantly regulates GBM cell proliferation and cell cycle and that this regulation is associated with p53/GADD45α Signaling pathway. Taken together, our findings suggest that BCAS3 is inextricably linked to the progression of GBM and that targeting BCAS3 may have therapeutic effects in GBM patients.

TMCO1 expression promotes cell proliferation and induces epithelial-mesenchymal transformation in human gliomas.

Transmembrane and coiled-coil domains 1 (TMCO1) is a recently discovered transmembrane protein of endoplasmic reticulum (ER), which plays a critical role in maintaining calcium homeostasis. TMCO1 dysfunction has been proved to be closely related to a variety of human diseases, including glaucoma, deformities, mental retardation and tumorigenesis. However, the role of TMCO1 in gliomas remains unclear. The purpose of this study was to detect the role of TMCO1 in the pathogenesis and progression of gliomas. This study demonstrated that TMCO1 was upregulated in gliomas and its overexpression predicted poor prognosis. We also revealed that the expression of TMCO1 was associated with the World Health Organization (WHO) grade of gliomas. Knockdown of TMCO1 inhibited the proliferation and induced apoptosis of U87 and U251 cells. In addition, TMCO1 induced GBM cell migration and invasion by promoting epithelial-mesenchymal transition (EMT). These date collectively proved the crucial role of TMCO1 as a novel prognostic factor and underlying therapeutic target for glioma patients.

TMBIM1 promotes proliferation and attenuates apoptosis in glioblastoma cells by targeting the p38 MAPK signalling pathway.

Glioblastoma multiforme (GBM) is the most common and most fatal primary malignant brain tumour in adults. The average survival time of patients after diagnosis is only 12-15 months. And its characteristics of excessive proliferation and apoptosis evasion play a crucial role in the poor prognosis of patients. Therefore, it is worth investigating the molecular mechanism of GBM to find an effective therapeutic target to overcome the dilemma. In the current study, Transmembrane BAX inhibitor motif containing 1 (TMBIM1) was highly expressed in GBM tissues and high TMBIM1 expression in GBM cell lines (U87 and U251) could promote cell proliferation and inhibit cell cycle arrest. In addition, TMBIM1 could significantly attenuate GBM cell apoptosis and decrease the sensitivity of GBM cells to temozolomide (TMZ). In terms of the molecular mechanism, we revealed that TMBIM1 interferes with the p38/MAPK pathway by inhibiting p38 phosphorylation to promote cell proliferation and attenuate cell apoptosis. In vivo experiments showed that the survival time of mice in TMBIM1 knockdown group was significantly prolonged. Our discovery provided an important basis for future intensive molecular mechanism research in GBM and presented a potential target for the treatment of GBM.