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Glioblastoma multiforme (GBM) is a significantly malignant and lethal brain tumor with an average survival time of less than 12 months. Several researches had shown that Claudin-3 (CLDN3) is overexpressed in various cancers and might be important in their growth and spread. In this study, we used qRT-PCR, western blotting, immunohistochemistry, and immunofluorescence staining assays to investigate the expression levels of various proteins. To explore the proliferation abilities of GBM cells, we conducted the CCK-8 and EdU-DNA formation assays. Wound healing and transwell assays were used to investigate the capacities of invasion and migration of GBM cells. Additionally, we constructed an intracranial xenograft model of GBM to study the in vivo role of CLDN3. Our study devoted to investigate the function of CLDN3 in the pathogenesis and progression of GBM. Our study revealed that CLDN3 was upregulated in GBM and could stimulate tumor cell growth and epithelial-mesenchymal transition (EMT) in both laboratory and animal models. We also discovered that CLDN3 expression could be triggered by transforming growth factor-β (TGF-β) and reduced by specific inhibitors of the TGF-β signaling pathway, such as ITD-1. Further analysis revealed that increased CLDN3 levels enhanced TGF-β-induced growth and EMT in GBM cells, while reducing CLDN3 levels weakened these effects. Our study demonstrated the function of CLDN3 in facilitating GBM growth and metastasis and indicated its involvement in the tumorigenic effects of TGF-β. Developing specific inhibitors of CLDN3 might, therefore, represent a promising new approach for treating this devastating disease. [ABSTRACT FROM AUTHOR]

Simple Summary: Glioma is a malignant primary brain tumor accounting for 75% of the total cases. Notably, several immunotherapeutic and chemotherapeutic agents in glioma have been demonstrated to induce immunogenic cell death (ICD). However, the studies on glioma have targeted individual ICD-related genes, and comprehensive analyses of all the ICD-related genes are still lacking. The aim of this study was to identify a novel molecular signature based on ICD-related genes in glioma, which might be beneficial for the diagnosis and treatment of glioma. We eventually identified a 14 ICD-related gene signature, which could effectively predict prognosis and immunotherapy response in glioma. These findings might be significantly helpful in selecting the best therapeutic strategy for glioma. Immunogenic cell death (ICD) is a type of regulated cell death (RCD) and is correlated with the progression, prognosis, and therapy of tumors, including glioma. Numerous studies have shown that the immunotherapeutic and chemotherapeutic agents of glioma might induce ICD. However, studies on the comprehensive analysis of the role of ICD-related genes and their correlations with overall survival (OS) in glioma are lacking. The genetic, transcriptional, and clinical data of 1896 glioma samples were acquired from five distinct databases and analyzed in terms of genes and transcription levels. The method of consensus unsupervised clustering divided the patients into two disparate molecular clusters: A and B. All of the patients were randomly divided into training and testing groups. Employing the training group data, 14 ICD-related genes were filtered out to develop a risk-score model. The correlations between our risk groups and prognosis, cells in the tumor microenvironment (TME) and immune cells infiltration, chemosensitivity and cancer stem cell (CSC) index were assessed. A highly precise nomogram model was constructed to enhance and optimize the clinical application of the risk score. The results demonstrated that the risk score could independently predict the OS rate and the immunotherapeutic response of glioma patients. This study analyzed the ICD-related genes in glioma and evaluated their role in the OS, clinicopathological characteristics, TME and immune cell infiltration of glioma. Our results may help in assessing the OS of glioma and developing better immunotherapeutic strategies. [ABSTRACT FROM AUTHOR]

Backgrounds: As a most widely used machine learning method, tree-based algorithms have not been applied to predict delayed cerebral ischemia (DCI) in elderly patients with aneurysmal subarachnoid hemorrhage (aSAH). Hence, this study aims to develop the conventional regression and tree-based models and determine which model has better prediction performance for DCI development in hospitalized elderly patients after aSAH. Methods: This was a multicenter, retrospective, observational cohort study analyzing elderly patients with aSAH aged 60 years and older. We randomly divided the multicentral data into model training and validation cohort in a ratio of 70–30%. One conventional regression and tree-based model, such as least absolute shrinkage and selection operator (LASSO), decision tree (DT), random forest (RF), and eXtreme Gradient Boosting (XGBoost), was developed. Accuracy, sensitivity, specificity, area under the precision-recall curve (AUC-PR), and area under the receiver operating characteristic curve (AUC-ROC) with 95% CI were employed to evaluate the model prediction performance. A DeLong test was conducted to calculate the statistical differences among models. Finally, we figured the importance weight of each feature to visualize the contribution on DCI. Results: There were 111 and 42 patients in the model training and validation cohorts, and 53 cases developed DCI. According to AUC-ROC value in the model internal validation, DT of 0.836 (95% CI : 0.747–0.926, p = 0.15), RF of 1 (95% CI : 1–1, p < 0.05), and XGBoost of 0.931 (95% CI : 0.885–0.978, p = 0.01) outperformed LASSO of 0.793 (95% CI : 0.692–0.893). However, the LASSO scored a highest AUC-ROC value of 0.894 (95% CI : 0.8–0.989) than DT of 0.764 (95% CI : 0.6–0.928, p = 0.05), RF of 0.821 (95% CI : 0.683–0.959, p = 0.27), and XGBoost of 0.865 (95% CI : 0.751–0.979, p = 0.69) in independent external validation. Moreover, the LASSO had a highest AUC-PR value of 0.681 than DT of 0.615, RF of 0.667, and XGBoost of 0.622 in external validation. In addition, we found that CT values of subarachnoid clots, aneurysm therapy, and white blood cell counts were the most important features for DCI in elderly patients with aSAH. Conclusions: The LASSO had a superior prediction power than tree-based models in external validation. As a result, we recommend the conventional LASSO regression model to predict DCI in elderly patients with aSAH. [ABSTRACT FROM AUTHOR]

The Fc Fragment of IgG Binding Protein (FCGBP) has been proven to participate in intestinal tumor immunity. However, the biological role of FCGBP has remained unclear in glioma. The differential expression of FCGBP was explored by Oncomine and GEPIA databases. The effect of FCGBP on prognosis was analyzed via Kaplan–Meier plotter and GEPIA. The Tumor Immune Estimation Resource (TIMER) tool was used to determine the correlations of FCGBP expression with tumor immune infiltration. Firstly, FCGBP was highly expressed in glioma and correlated with a worse prognosis. Gene Ontology (GO) and KEGG pathway enrichment analyses revealed that the differentially expressed genes (DEGs) and co-expression genes of FCGBP were mainly involved in the immune response. Furthermore, FCGBP expression was positively associated with multiple immune cells infiltrates as well as the expression levels of multiple immune markers in glioma. FCGBP co-expression networks mostly participated in the regulation of immune response. Finally, immunohistochemistry (IHC) assays were conducted to explore the expression of FCGBP, PD-L1, CCL2 and CD8 in glioma and correlations between them. We found that PDL1 and FCGBP were synchronously upregulated in glioma tissues. These findings revealed a new mechanism by which FCGBP participates in the immune tolerance of glioma, and implied the potential of FCGBP as a therapeutic target or predictive marker for patients. [ABSTRACT FROM AUTHOR]

Recent studies showed that molecule interacting with CasL2 (MICAL2) could be a novel tumor growth factor, and it is closely associated with tumor growth and invasion. However, the role it plays in glioblastoma (GBM) and its potential mechanisms are currently unknown. Our study is designed to identify the effect of MICAL2 on GBM cells and the potential mechanisms behind it. Here, we found that MICAL2 interacts with TGF receptor-type I (TGFRI) and promotes the proliferation and migration of glioblastoma through the TGF-β/p-Smad2/EMT-like signaling pathway. MICAL2-knockdown inhibited the proliferation of glioblastoma cells, which was related to cell cycle arrest and downregulation of DNA replication. The invasion abilities of U87 and U251 cells were reduced after the knockdown of MICAL2. MICAL2 promoted the growth of GBM in nude mice. High MICAL2 predicts poor outcome of GBM patients. MICAL2 could be identified as a novel promising therapeutic target for human GBM. [ABSTRACT FROM AUTHOR]

Subarachnoid hemorrhage (SAH) is a subtype of stroke with high mortality and morbidity due to the lack of effective therapy. Atorvastatin has been reported to alleviate early brain injury (EBI) following subarachnoid hemorrhage (SAH) via reducing reactive oxygen species, antiapoptosis, regulated autophagy, and neuroinflammation. Which was the related to the pyroptosis? Pyroptosis can be defined as a highly specific inflammatory programmed cell death, distinct from classical apoptosis and necrosis. However, the precise role of pyroptosis in atorvastatin‐mediated neuroprotection following SAH has not been confirmed. The present study aimed to investigate the neuroprotection and potential molecular mechanisms of atorvastatin in the SAH‐induced EBI via regulating neural pyroptosis using the filament perforation model of SAH in male C57BL/6 mice, and the hemin‐induced neuron damage model in HT‐22. Atorvastatin or vehicle was administrated 2 h after SAH and hemin‐induced neuron damage. The mortality, neurological score, brain water content, and neuronal death were evaluated. The results show that the atorvastatin treatment markedly increased survival rate, neurological score, greater survival of neurons, downregulated the protein expression of NLRP1, cleaved caspase‐1, interleukin‐1β (IL‐1β), and IL‐18, which indicated that atorvastatin‐inhibited pyroptosis and neuroinflammation, ameliorated neuron death in vivo/vitro subjected to SAH. Taken together, this study demonstrates that atorvastatin improved the neurological outcome in rats and reduced the neuron death by against neural pyroptosis and neuroinflammation. [ABSTRACT FROM AUTHOR]