Zinc finger Protein207 orchestrates glioma migration through regulation of epithelial-mesenchymal transition.

BACKGROUND: Glioma represents the predominant primary malignant brain tumor. For several years, molecular profiling has been instrumental in the management and therapeutic stratification of glioma, providing a deeper understanding of its biological complexity. Accumulating evidence unveils the putative involvement of zinc finger proteins (ZNFs) in cancer. This study aimed to elucidate the role and significance of ZNF207 in glioma. METHODS: Utilizing online data such as The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), the Genotype-Tissue Expression (GTEx) project, the Clinical Proteomic Tumor Analysis Consortium (CPTAC), and the Human Protein Atlas (HPA) databases, in conjunction with bioinformatics methodologies including GO, KEGG, GSEA, CIBERSORT immune cell infiltration estimation, and protein-protein interaction (PPI) analysis, enabled a comprehensive exploration of ZNF207's involvement in gliomagenesis. Immunohistochemistry and RT-PCR techniques were employed to validate the expression level of ZNF207 in glioma samples. Subsequently, the biological effects of ZNF207 on glioma cells were explored through in vitro assays. RESULTS: Our results demonstrate elevated expression of ZNF207 in gliomas, correlating with unfavorable patient outcomes. Stratification analyses were used to delineate the prognostic efficacy of ZNF207 in glioma with different clinicopathological characteristics. Immunocorrelation analysis revealed a significant association between ZNF207 expression and the infiltration levels of T helper cells, macrophages, and natural killer (NK) cells. Utilizing ZNF207 expression and clinical features, we constructed an OS prediction model and displayed well discrimination with a C-index of 0.861. Moreover, the strategic silencing of ZNF207 attenuated glioma cell advancement, evidenced by diminished cellular proliferation, weakened cell tumorigenesis, augmented apoptotic activity, and curtailed migratory capacity alongside the inhibition of the epithelial-mesenchymal transition (EMT) pathway. CONCLUSIONS: ZNF207 may identify as a prospective biomarker and therapeutic candidate for glioma prevention, providing valuable insights into understanding glioma pathogenesis and treatment strategies.

Oncolytic virus Ad-TD-nsIL-12 inhibits glioma growth and reprograms the tumor immune microenvironment.

AIMS: Gliomas are the most common central nervous system malignancies, with limited therapeutic options and poor prognosis, which are primarily attributed to the "immune desert" microenvironment. Previously, we constructed a three-gene-deleted oncolytic adenovirus (Ad-TD) loaded with non-secreting interleukin-12 (nsIL-12), which could be amplified in tumor cells and induce immunity to suppress tumors. However, the effects of this oncolytic virus on gliomas and their immune microenvironment remain unclear. There is an urgent need for further research. MATERIALS AND METHODS: We constructed a Syrian hamster brain tumor model and demonstrated the efficacy and mechanism of the novel oncolytic virus in treating brain tumors through a series of in vitro and in vivo experiments. We investigated the efficacy and safety (the number of hamsters in each group is either 5 or 10) of the oncolytic virus treatment in Syrian hamsters using a virus-treated group, a control virus-treated group, and a blank control group. KEY FINDINGS: In vitro assays showed that Ad-TD-nsIL-12 could specifically proliferate in brain tumor cells which induce tumor cell apoptosis and intracellular expression of interleukin (IL)-12. Moreover, in vivo experiments demonstrated that Ad-TD-nsIL-12 could effectively inhibit the progression of brain tumors and prolong survival. Ad-TD-nsIL-12 significantly enhanced T-cell infiltration in the brain tumor microenvironment. SIGNIFICANCE: Ad-TD-nsIL-12 can inhibit glioma progression and increase T-cell infiltration in the tumor tissue, particularly infiltration by cytotoxic T cells (CD8+). Ad-TD-nsIL-12 can amplify and produce IL-12, inducing anti-glioma immune responses to inhibit tumor progression.

Development and Validation of a Clinical Prediction Model for Venous Thromboembolism Following Neurosurgery: A 6-Year, Multicenter, Retrospective and Prospective Diagnostic Cohort Study.

BACKGROUND: Based on the literature and data on its clinical trials, the incidence of venous thromboembolism (VTE) in patients undergoing neurosurgery has been 3.0%~26%. We used advanced machine learning techniques and statistical methods to provide a clinical prediction model for VTE after neurosurgery. METHODS: All patients (n = 5867) who underwent neurosurgery from the development and retrospective internal validation cohorts were obtained from May 2017 to April 2022 at the Department of Neurosurgery at the Sanbo Brain Hospital. The clinical and biomarker variables were divided into pre-, intra-, and postoperative. A univariate logistic regression (LR) was applied to explore the 67 candidate predictors with VTE. We used a multivariable logistic regression (MLR) to select all significant MLR variables of MLR to build the clinical risk prediction model. We used a random forest to calculate the importance of significant variables of MLR. In addition, we conducted prospective internal (n = 490) and external validation (n = 2301) for the model. RESULTS: Eight variables were selected for inclusion in the final clinical prediction model: D-dimer before surgery, activated partial thromboplastin time before neurosurgery, age, craniopharyngioma, duration of operation, disturbance of consciousness on the second day after surgery and high dose of mannitol, and highest D-dimer within 72 h after surgery. The area under the curve (AUC) values for the development, retrospective internal validation, and prospective internal validation cohorts were 0.78, 0.77, and 0.79, respectively. The external validation set had the highest AUC value of 0.85. CONCLUSIONS: This validated clinical prediction model, including eight clinical factors and biomarkers, predicted the risk of VTE following neurosurgery. Looking forward to further research exploring the standardization of clinical decision-making for primary VTE prevention based on this model.

Cuproptosis-related gene SLC31A1 expression correlates with the prognosis and tumor immune microenvironment in glioma.

Cuproptosis is a newly discovered form of cell death. It is regulated by a string of genes. The genes are identified to influence the tumor progression, but in glioma, the cuproptosis-related genes are little studied. The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) were used to screen for SLC31A1 gene expression in glioma and healthy tissue samples. The results were validated using the Gene Expression Omnibus (GEO) and quantitative real-time polymerase chain reaction (qPCR). The Human Protein Atlas (HPA) and the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) were used to validate our results at the protein level. Multivariable analysis and Kaplan-Meier survival curves were used to examine the relationship among SLC31A1 gene expression, clinical parameters, and survival rates. The online Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) was used to find the genes and proteins that correlate to SLC31A1. The immune infiltration analysis was performed using the Tumor Immune Estimation Resource (TIMER) databases. Small interfering RNA was used to knock down the SLC31A1 expression, and the cell proliferation, apoptosis, and migration were analyzed using cell counting kit-8, flow cytometry, and transwell. The glioma patients have higher SLC31A1 expression levels, which increase as the World Health Organization (WHO) grade escalates. The survival analysis illustrates that the SLC31A1 gene expression negatively correlates with overall survival (OS), progression-free survival (PFS), and disease-specific survival (DSS). The immune infiltration analysis shows the SLC31A1 gene positively correlates with T helper 2 (Th2) cells, macrophages, and M2-type macrophages and negatively correlates with plasmacytoid dendritic cells (pDCs), natural killer (NK) CD56bright cells, and CD8 T cells. The in vitro KD experiment shows the SLC31A1 knockdown depressed the glioma cell proliferation and migration and promoted the apoptosis rate. The SLC31A1 gene expression can shorten the survival time of glioma patients. In vitro study shows that SLC31A1 can promote cell proliferation, and migration, and depress the cell apoptosis of glioma cells. It also can promote the formation of a tumor-suppressive microenvironment.

Mutation-derived, genomic instability-associated lncRNAs are prognostic markers in gliomas.

Background: Gliomas are the most commonly-detected malignant tumors of the brain. They contain abundant long non-coding RNAs (lncRNAs), which are valuable cancer biomarkers. LncRNAs may be involved in genomic instability; however, their specific role and mechanism in gliomas remains unclear. LncRNAs that are related to genomic instability have not been reported in gliomas. Methods: The transcriptome data from The Cancer Genome Atlas (TCGA) database were analyzed. The co-expression network of genomic instability-related lncRNAs and mRNA was established, and the model of genomic instability-related lncRNA was identified by univariate Cox regression and LASSO analyses. Based on the median risk score obtained in the training set, we divided the samples into high-risk and low-risk groups and proved the survival prediction ability of genomic instability-related lncRNA signatures. The results were verified in the external data set. Finally, a real-time quantitative polymerase chain reaction assay was performed to validate the signature. Results: The signatures of 17 lncRNAs (LINC01579, AL022344.1, AC025171.5, LINC01116, MIR155HG, AC131097.3, LINC00906, CYTOR, AC015540.1, SLC25A21.AS1, H19, AL133415.1, SNHG18, FOXD3.AS1, LINC02593, AL354919.2 and CRNDE) related to genomic instability were identified. In the internal data set and Gene Expression Omnibus (GEO) external data set, the low-risk group showed better survival than the high-risk group (P < 0.001). In addition, this feature was identified as an independent risk factor, showing its independent prognostic value with different clinical stratifications. The majority of patients in the low-risk group had isocitrate dehydrogenase 1 (IDH1) mutations. The expression levels of these lncRNAs were significantly higher in glioblastoma cell lines than in normal cells. Conclusions: Our study shows that the signature of 17 lncRNAs related to genomic instability has prognostic value for gliomas and could provide a potential therapeutic method for glioblastoma.

Comprehensive analysis and molecular map of Hippo signaling pathway in lower grade glioma: the perspective toward immune microenvironment and prognosis.

Background: The activation of YAP/TAZ transcriptional co-activators, downstream effectors of the Hippo/YAP pathway, is commonly observed in human cancers, promoting tumor growth and invasion. The aim of this study was to use machine learning models and molecular map based on the Hippo/YAP pathway to explore the prognosis, immune microenvironment and therapeutic regimen of patients with lower grade glioma (LGG). Methods: SW1783 and SW1088 cell lines were used as in vitro models for LGG, and the cell viability of the XMU-MP-1 (a small molecule inhibitor of the Hippo signaling pathway) treated group was evaluated using a Cell Counting Kit-8 (CCK-8). Univariate Cox analysis on 19 Hippo/YAP pathway related genes (HPRGs) was performed to identify 16 HPRGs that exhibited significant prognostic value in meta cohort. Consensus clustering algorithm was used to classify the meta cohort into three molecular subtypes associated with Hippo/YAP Pathway activation profiles. The Hippo/YAP pathway's potential for guiding therapeutic interventions was also investigated by evaluating the efficacy of small molecule inhibitors. Finally, a composite machine learning models was used to predict individual patients' survival risk profiles and the Hippo/YAP pathway status. Results: The findings showed that XMU-MP-1 significantly enhanced the proliferation of LGG cells. Different Hippo/YAP Pathway activation profiles were associated with different prognostic and clinical features. The immune scores of subtype B were dominated by MDSC and Treg cells, which are known to have immunosuppressive effects. Gene Set Variation Analysis (GSVA) indicated that subtypes B with a poor prognosis exhibited decreased propanoate metabolic activity and suppressed Hippo pathway signaling. Subtype B had the lowest IC50 value, indicating sensitivity to drugs that target the Hippo/YAP pathway. Finally, the random forest tree model predicted the Hippo/YAP pathway status in patients with different survival risk profiles. Conclusions: This study demonstrates the significance of the Hippo/YAP pathway in predicting the prognosis of patients with LGG. The different Hippo/YAP Pathway activation profiles associated with different prognostic and clinical features suggest the potential for personalized treatments.

Epithelial-mesenchymal transition is the main way in which glioma-associated microglia/macrophages promote glioma progression.

Microglia/macrophages make up the largest population of tumor-infiltrating cells. Numerous studies have demonstrated that glioma-associated microglia/macrophages (GAMs) could promote the malignant progression of gliomas in various pathways. However, the primary function of GAMs in glioma remains inconclusive. First, by the CIBERSORT algorithm, we evaluated the content of microglia/macrophages in glioma tissues by bioinformatic analysis of omic data from thousands of glioma samples. Subsequently, we analyzed and confirmed the significant relationship between GAMs and the malignant phenotype of glioma, including survival time, IDH mutation status, and time of symptom onset. Afterward, Epithelial-Mesenchymal Transition (EMT) was identified by Gene Set Enrichment Analysis (GSEA) from numerous biological processes as the most relevant mechanism of malignant progression to GAMs. Moreover, a series of clinical samples were detected, including normal brain and various-grade glioma tissues. The results not only showed that GAMs were significantly associated with gliomas and their malignancy but also that GAMs were highly correlated with the degree of EMT in gliomas. In addition, we isolated GAMs from glioma samples and constructed co-culture models (in vitro) to demonstrate the promotion of the EMT process in glioma cells by GAMs. In conclusion, our study clarified that GAMs exert oncogenic effects with EMT in gliomas, suggesting the possibility of GAMs as immunotherapeutic targets.

Remdesivir inhibits the progression of glioblastoma by enhancing endoplasmic reticulum stress.

Glioblastoma (GBM) is one of the most aggressive primary malignant brain tumors. The major challenge is the lack of effective therapeutic drugs due to the blood-brain barrier (BBB) and tumor heterogeneity. Remdesivir (RDV), a new member of the nucleotide analog family, has previously been shown to have excellent antiviral effects and BBB penetration, and was predicted here to have anti-GBM effects. In vitro experiments, RDV significantly inhibited the growth of GBM cells, with IC50 values markedly lower than those of normal cell lines or the same cell lines treated with temozolomide. Moreover, in multiple mouse models, RDV not only distinctly inhibited the progression and improved the prognosis of GBM but also exhibited a promising biosafety profile, as manifested by the lack of significant body weight loss, liver or kidney dysfunction or organ structural damage after administration. Furthermore, we investigated the anti-GBM mechanism by RNA-seq and identified that RDV might induce apoptosis of GBM cells by enhancing endoplasmic reticulum (ER) stress and activating the PERK-mediated unfolded protein response. In conclusion, our results indicated that RDV might serve as a novel agent for GBM treatment by increasing ER stress and inducing apoptosis in GBM cells.

Whole-genome sequencing of extrachromosomal circular DNA of cerebrospinal fluid of medulloblastoma.

Background: Medulloblastoma (MB) is a malignant tumor associated with a poor prognosis in part due to a lack of effective detection methods. Extrachromosomal circular DNA (eccDNA) has been associated with multiple tumors. Nonetheless, little is currently known on eccDNA in MB. Methods: Genomic features of eccDNAs were identified in MB tissues and matched cerebrospinal fluid (CSF) and compared with corresponding normal samples using Circle map. The nucleotides on both sides of the eccDNAs' breakpoint were analyzed to understand the mechanisms of eccDNA formation. Bioinformatics analysis combined with the Gene Expression Omnibus (GEO) database identified features of eccDNA-related genes in MB. Lasso Cox regression model, univariate and multivariate Cox regression analysis, time-dependent ROC, and Kaplan-Meier curve were used to assess the potential diagnostic and prognostic value of the hub genes. Results: EccDNA was profiled in matched tumor and CSF samples from MB patients, and control, eccDNA-related genes enriched in MB were identified. The distribution of eccDNAs in the genome was closely related to gene density and the mechanism of eccDNA formation was evaluated. EccDNAs in CSF exhibited similar distribution with matched MB tissues but were differentially expressed between tumor and normal. Ten hub genes prominent in both the eccDNA dataset and the GEO database were selected to classify MB patients to either high- or low-risk groups, and a prognostic nomogram was thus established. Conclusions: This study provides preliminary evidence of the characteristics and formation mechanism of eccDNAs in MB and CSF. Importantly, eccDNA-associated hub genes in CSF could be used as diagnostic and prognostic biomarkers for MB.

An integrated imaging sensor for aberration-corrected 3D photography.

Planar digital image sensors facilitate broad applications in a wide range of areas1-5, and the number of pixels has scaled up rapidly in recent years2,6. However, the practical performance of imaging systems is fundamentally limited by spatially nonuniform optical aberrations originating from imperfect lenses or environmental disturbances7,8. Here we propose an integrated scanning light-field imaging sensor, termed a meta-imaging sensor, to achieve high-speed aberration-corrected three-dimensional photography for universal applications without additional hardware modifications. Instead of directly detecting a two-dimensional intensity projection, the meta-imaging sensor captures extra-fine four-dimensional light-field distributions through a vibrating coded microlens array, enabling flexible and precise synthesis of complex-field-modulated images in post-processing. Using the sensor, we achieve high-performance photography up to a gigapixel with a single spherical lens without a data prior, leading to orders-of-magnitude reductions in system capacity and costs for optical imaging. Even in the presence of dynamic atmosphere turbulence, the meta-imaging sensor enables multisite aberration correction across 1,000 arcseconds on an 80-centimetre ground-based telescope without reducing the acquisition speed, paving the way for high-resolution synoptic sky surveys. Moreover, high-density accurate depth maps can be retrieved simultaneously, facilitating diverse applications from autonomous driving to industrial inspections.

Noise-robust phase-space deconvolution for light-field microscopy.

SIGNIFICANCE: Light-field microscopy has achieved success in various applications of life sciences that require high-speed volumetric imaging. However, existing light-field reconstruction algorithms degrade severely in low-light conditions, and the deconvolution process is time-consuming. AIM: This study aims to develop a noise robustness phase-space deconvolution method with low computational costs. APPROACH: We reformulate the light-field phase-space deconvolution model into the Fourier domain with random-subset ordering and total-variation (TV) regularization. Additionally, we build a time-division-based multicolor light-field microscopy and conduct the three-dimensional (3D) imaging of the heart beating in zebrafish larva at over 95 Hz with a low light dose. RESULTS: We demonstrate that this approach reduces computational resources, brings a tenfold speedup, and achieves a tenfold improvement for the noise robustness in terms of SSIM over the state-of-the-art approach. CONCLUSIONS: We proposed a phase-space deconvolution algorithm for 3D reconstructions in fluorescence imaging. Compared with the state-of-the-art method, we show significant improvement in both computational effectiveness and noise robustness; we further demonstrated practical application on zebrafish larva with low exposure and low light dose.

Identification of N6-Methyladenosine-Related lncRNAs as a Prognostic Signature in Glioma.

N6-methyladenosine (m6A) modification is the most abundant modification in long noncoding RNAs (lncRNAs). Current studies have shown that the abnormal expression of m6A-related genes is closely associated with the tumorigenesis and progression of glioma. However, the role of m6A-related lncRNAs in glioma development is still unclear. Herein, we screened 566 m6A-related lncRNAs in glioma from The Cancer Genome Atlas (TCGA) database. The expression pattern of these lncRNAs could cluster samples into two groups, in which various classical tumor-related functions and the tumor immune microenvironment were significantly different. Subsequently, a nine-factor m6A-related lncRNA prognostic signature (MLPS) was constructed by using a LASSO regression analysis in the training set and was validated in the test set and independent datasets. The AUC values of the MLPS were 0.881, 0.918 and 0.887 for 1-, 3- and 5-year survival in the training set, respectively, and 0.856, 0.916 and 0.909 for 1-, 3-, and 5-year survival in the test set, respectively. Stratification analyses of the MLPS illustrated its prognostic performance in gliomas with different characteristics. Correlation analyses showed that the infiltrations of monocytes and tumor-associated macrophages (TAMs) were significantly relevant to the risk score in the MLPS. Moreover, we detected the expression of four MLPS factors with defined sequences in glioma and normal cells by using RT-PCR. Afterwards, we investigated the functions of LNCTAM34A (one of the MLPS factors) in glioma cells, which have rarely been reported. Via in vitro experiments, LNCTAM34A was demonstrated to promote the proliferation, migration and epithelial-mesenchymal transition (EMT) of glioma cells. Overall, our study revealed the critical role of m6A-related lncRNAs in glioma and elucidated that LNCTAM34A could promote glioma proliferation, migration and EMT.

Iterative tomography with digital adaptive optics permits hour-long intravital observation of 3D subcellular dynamics at millisecond scale.

Long-term subcellular intravital imaging in mammals is vital to study diverse intercellular behaviors and organelle functions during native physiological processes. However, optical heterogeneity, tissue opacity, and phototoxicity pose great challenges. Here, we propose a computational imaging framework, termed digital adaptive optics scanning light-field mutual iterative tomography (DAOSLIMIT), featuring high-speed, high-resolution 3D imaging, tiled wavefront correction, and low phototoxicity with a compact system. By tomographic imaging of the entire volume simultaneously, we obtained volumetric imaging across 225 × 225 × 16 µm3, with a resolution of up to 220 nm laterally and 400 nm axially, at the millisecond scale, over hundreds of thousands of time points. To establish the capabilities, we investigated large-scale cell migration and neural activities in different species and observed various subcellular dynamics in mammals during neutrophil migration and tumor cell circulation.

Development of a prognostic model based on an immunogenomic landscape analysis of medulloblastoma.

Medulloblastoma (MB) is one of the most common central nervous system tumors in children. At present, the vital role of immune abnormalities has been proved in tumorigenesis and progression. However, the immune mechanism in MB is still poorly understood. In the present study, 51 differentially expressed immune-related genes (DE-IRGs) and 226 survival associated immune-related genes (Sur-IRGs) were screened by an integrated analysis of multi-array. Moreover, the potential pathways were enriched by functional analysis, such as 'cytokine-cytokine receptor interaction', 'Ras signaling pathway', 'PI3K-Akt signaling pathway' and 'pathways in cancer'. Furthermore, 10 core IRGs were identified from DE-IRGs and Sur-IRGs. And the potential regulatory mechanisms of core IRGs were also explored. Additionally, a new prognostic model, including 7 genes (HDGF, CSK, PNOC, S100A13, RORB, FPR1, and ICAM2) based on IRGs, was established by multivariable COX analysis. In summary, our study revealed the underlying immune mechanism of MB. Moreover, we developed a prognostic model associated with clinical characteristics and could reflect the infiltration of immune cells.

Comprehensive Analyses of Glucose Metabolism in Glioma Reveal the Glioma-Promoting Effect of GALM.

Glioma is the most common tumor with the worst prognosis in the central nervous system. Current studies showed that glucose metabolism could affect the malignant progression of tumors. However, the study on the dysregulation of glucose metabolism in glioma is still limited. Herein, we firstly screened 48 differentially expressed glucose metabolism-related genes (DE-GMGs) by comparing glioblastomas to low-grade gliomas. Then a glucose metabolism-related gene (GMG)-based model (PC, lactate dehydrogenase A (LDHA), glucuronidase beta (GUSB), galactosidase beta 1 (GLB1), galactose mutarotase (GALM), or fructose-bisphosphatase 1 (FBP1)) was constructed by a protein-protein interaction (PPI) network and Lasso regression. Thereinto, the high-risk group encountered a worse prognosis than the low-risk group, and the M2 macrophage was positively relevant to the risk score. Various classical tumor-related functions were enriched by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Since protein GALM was rarely studied in glioma, we detected high expression of GALM by western blot and immunohistochemistry in glioma tissues. And experiments in vitro showed that GALM could promote the epithelial-to-mesenchymal transition (EMT) process of glioma cells and could be regulated by TNFAIP3 in glioma cells. Overall, our study revealed the critical role of glucose metabolism in the prognosis of patients with glioma. Furthermore, we demonstrated that GALM was significantly related to the malignancy of glioma and could promote glioma cells' EMT process.

Identification of two core genes in glioblastomas with different isocitrate dehydrogenase mutation status.

Glioblastoma (GBM) is one of the most common malignancies of the central nervous system, and the Isocitrate Dehydrogenase (IDH) mutation status of GBM has been recognized as a critical prognostic indicator. However, the molecular mechanism underlying the GBM with different IDH mutation status is still not unclear. In this study, a total of 353 DEGs including 207 up-regulated and 146 down-regulated were screened from multiple GBM data sets. Moreover, the biological processes and pathways enriched by DEGs were mainly associated with tumor progression, especially invasion and migration. Then, eight hub genes, including SDC4, SERPINE1, TNC, THBS1, COL1A1, CXCL8, TIMP1 and VEGFA, were selected from a PPI network. Finally, core genes, SERPINE1 and TIMP1, were identified from hub genes by survival analysis and sample validation. Overall, in this study, we revealed underlying molecular mechanisms in GBMs with different IDH mutation status and identified core genes that could be potential markers and targets for diagnosis and treatment of GBMs.

UBE2T promotes glioblastoma invasion and migration via stabilizing GRP78 and regulating EMT.

Glioblastoma (GBM) generally has a dismal prognosis, and it is associated with a poor quality of life as the disease progresses. However, the development of effective therapies for GBM has been deficient. Ubiquitin-conjugating enzyme E2T (UBE2T) is a member of the E2 family in the ubiquitin-proteasome pathway and a vital regulator of tumour progression, but its role in GBM is unclear. In this study, we aimed to clarify the role of UBE2T in GBM. Bioinformatics analysis identified UBE2T as an independent risk factor for gliomas. Immunohistochemistry was used to measure UBE2T expression in GBM and normal tissue samples obtained from patients with GBM. The effects of UBE2T on GBM cell invasion and migration were analysed using the Transwell assay. BALB/c nude mice were used for the in vivo assays. Immunoblotting and immunoprecipitation were performed to determine the molecular mechanisms. UBE2T was highly expressed in GBM tissues, and its expression was linked to a poor prognosis. In vitro, depletion of UBE2T significantly suppressed cell invasion and migration. Moreover, UBE2T depletion suppressed the growth of GBM subcutaneous tumours in vivo. Further experiments revealed that UBE2T suppressed invasion and migration by regulating epithelial- mesenchymal transition (EMT) via stabilising GRP78 in GBM cells. We uncovered a novel UBE2T/GRP78/EMT regulatory axis that modulates the malignant progression and recurrence of GBM, indicating that the axis might be a valuable therapeutic target.

Identification of Core Genes and Pathways in Medulloblastoma by Integrated Bioinformatics Analysis.

Medulloblastoma (MB) is one of the most common intracranial malignancies in children. The present study applied integrated bioinformatics to identify potential core genes associated with the pathogenesis of MB and reveal potential molecular mechanisms. Through the integrated analysis of multiple data sets from the Gene Expression Omnibus (GEO), 414 differentially expressed genes (DEGs) were identified. Combining the protein-protein interaction (PPI) network analysis with gene set enrichment analysis (GSEA), eight core genes, including CCNA2, CCNB1, CCNB2, AURKA, CDK1, MAD2L1, BUB1B, and RRM2, as well as four core pathways, including "cell cycle", "oocyte meiosis", "p53 pathway" and "DNA replication" were selected. In independent data sets, the core genes showed superior diagnostic values and significant prognostic correlations. Moreover, in the pan-caner data of the cancer genome atlas (TCGA), the core genes were also widely abnormally expressed. In conclusion, this study identified core genes and pathways of MB through integrated analysis to deepen the understanding of the molecular mechanisms underlying the MB and provide potential targets and pathways for diagnosis and treatment of MB.

Reciprocal control of ADAM17/EGFR/Akt signaling and miR-145 drives GBM invasiveness.

INTRODUCTION: Glioblastoma multiforme (GBM) is one of the most devastating brain malignancies worldwide and is considered to be incurable. However, the mechanisms underlying its aggressiveness remain unclear. METHODS: The expression of ADAM17 in tissue samples was detected by immunohistochemistry. Knockdown and rescue experiments were used to demonstrate the regulatory effect of ADAM17 on the invasion ability of GBM cells. Western Blot and qPCR were used to detect the expression of related proteins and RNAs. Moreover, a luciferase reporter assay was performed to verify whether miR-145 directly binds to the 3'-UTR of ADAM17. RESULTS: We revealed that ADAM17 was overexpressed in GBM tissues and correlated positively with poor prognosis. The knockdown of ADAM17 obviously suppressed the invasiveness of GBM cell lines. Furthermore, we found that knockdown of ADAM17 decreased activation of EGFR/Akt/C/EBP-ß signaling, and consequently upregulated miR-145 expression in GBM cell lines. Notably, miR-145 directly targeted the ADAM17 3'-UTR and suppressed expression levels of ADAM17. CONCLUSIONS: Our findings define an ADAM17/EGFR/miR-145 feedback loop that drives the GBM invasion. Reciprocal regulation between ADAM17 and miR-145 results in aberrant activation of EGFR signaling, suggesting that inhibition of ADAM17 expression can be an ideal therapeutic strategy for the treatment of GBM.

Identification of Hub Genes in Pediatric Medulloblastoma by Multiple-Microarray Analysis.

Pediatric medulloblastoma is the leading cause of cancer-related death in children. However, few studies have reported gene expression profiles of pediatric medulloblastoma and the molecular mechanism underlying this disease is unclear. To identify essential genes in pediatric medulloblastoma, we analyzed three microarray data sets from the Gene Expression Omnibus (GEO). We identified 1798 differentially expressed genes (DEGs) using the limma package. Gene set enrichment analysis demonstrated that "entrainment of circadian clock by photoperiod," "regulation of triglyceride biosynthetic process," and "snare complex" pathway were significantly enriched gene sets that correlated with pediatric medulloblastoma. Enriched Gene Ontology annotations of DEGs mostly included "ion-gated channel activity," "gated channel activity," and "channel activity." Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that DEGs were enriched in "glutamatergic synapse," "synaptic vesicle cycle," and "GABAergic synapse." Protein-protein interaction (PPI) network analysis showed that RAB5C, VAMP2, AP2M1, FNBP1, AP2A1, SYT1, SYNJ2, SYT2, HIP1R, UBB, WNT5A, SH3GL2, SYNJ1, EPN1, and DNM1 were hub genes. In conclusion, the identification of the above hub genes and pathways will help to reveal the pathogenesis of pediatric medulloblastoma and will also provide prognostic markers and therapeutic targets for pediatric medulloblastoma.