Current and future strategies for treatment of glioma

Brain-computer interfaces inspired spiking neural network model for depression stage identification

BACKGROUND

Depression is a global mental disorder, and traditional diagnostic methods mainly rely on scales and subjective evaluations by doctors, which cannot effectively identify symptoms and even carry the risk of misdiagnosis. Brain-Computer Interfaces inspired deep learning-assisted diagnosis based on physiological signals holds promise for improving traditional methods lacking physiological basis and leads next generation neuro-technologies. However, traditional deep learning methods rely on immense computational power and mostly involve end-to-end network learning. These learning methods also lack physiological interpretability, limiting their clinical application in assisted diagnosis.

METHODOLOGY

A brain-like learning model for diagnosing depression using electroencephalogram (EEG) is proposed. The study collects EEG data using 128-channel electrodes, producing a 128×128 brain adjacency matrix. Given the assumption of undirected connectivity, the upper half of the 128×128 matrix is chosen in order to minimise the input parameter size, producing 8,128-dimensional data. After eliminating 28 components derived from irrelevant or reference electrodes, a 90×90 matrix is produced, which can be used as an input for a single-channel brain-computer interface image.

RESULT

At the functional level, a spiking neural network is constructed to classify individuals with depression and healthy individuals, achieving an accuracy exceeding 97.5 %.

COMPARISON WITH EXISTING METHODS

Compared to deep convolutional methods, the spiking method reduces energy consumption.

CONCLUSION

At the structural level, complex networks are utilized to establish spatial topology of brain connections and analyse their graph features, identifying potential abnormal brain functional connections in individuals with depression.

Multi-omics Analysis Revealed that the CCN Family Regulates Cell Crosstalk, Extracellular Matrix, and Immune Escape, Leading to a Poor Prognosis of Glioma

The CCN family is a group of matricellular proteins associated with the extracellular matrix. This study aims to explore the role of the CCN family in glioma development and its implications in the tumor microenvironment. Through analysis of bulk RNA-seq cohorts, correlations between CCN family expression and glioma subtypes, patient survival, and bioactive pathway enrichment were investigated. Additionally, single-cell datasets were employed to identify novel cell subgroups, followed by analyses of cell communication and transcription factors. Spatial transcriptomic analysis was utilized to validate the CCN family's involvement in glioma. Results indicate overexpression of CYR61,CTGF, and WISP1 in glioma, associated with unfavorable subtypes and reduced survival. Enrichment analyses revealed associations with oncogenic pathways, while CTGF and WISP1 expression correlated with increased infiltration of regulatory T cells and M2 macrophages. Single-cell analysis identified MES-like cells as the highest CCN expression. Moreover, intercellular signal transduction analysis demonstrated active pathways, including SPP1-CD44, in cell subgroups with elevated CYR61 and CTGF expression. Spatial transcriptomic analysis confirmed co-localization of CYR61,CTGF and SPP1-CD44 with high oncogenic pathway activity. These findings suggest that CCN family members may serve as potential prognostic biomarkers and therapeutic targets for glioma.

Relationship between chemokine/chemokine receptor and glioma prognosis and outcomes: Systematic review and meta-analysis

BACKGROUND

Glioma is a primary tumor originating from the central nervous system, and despite ongoing efforts to improve treatment, its overall survival rate remains low. There are a limited number of reports regarding the clinical grading, prognostic impact, and utility of chemokines. Therefore, conducting a meta-analysis is necessary to obtain convincing and conclusive results.

METHODS

A comprehensive literature search was conducted using various databases, including PubMed, Web of Science, The Cochrane Library, Embase, Ovid Medline, CNKI, Wanfang Database, VIP, and CBM. The search encompassed articles published from the inception of the databases until March 2024. The estimated odds ratio (ORs), standard mean difference (SMDs), and hazard ratio (HR) with their corresponding 95% confidence intervals (95% CI) were calculated to assess the predictive value of chemokine and receptor levels in glioma risk. Additionally, heterogeneity tests and bias tests were performed to evaluate the reliability of the findings.

RESULTS

This meta-analysis included a total of 36 studies, involving 2,480 patients diagnosed with glioma. The results revealed a significant association between the expression levels of CXCR4 (n = 8; OR = 22.28; 95 % CI = 11.47-43.30; p = 0.000), CXCL12 (n = 4; OR = 10.69; 95 % CI = 7.03-16.24; p = 0.000), CCL2 (n = 6; SMD = -0.83; 95 % CI = -0.98--0.67; p = 0.000), CXCL8 (n = 3; SMD = 0.75; 95 % CI = 0.47-1.04; p = 0.000), CXCR7 (n = 3; OR = 20.66; 95 % CI = 10.20-41.82; p = 0.000), CXCL10 (n = 2; SMD = 3.27; 95 % CI = 2.91-3.62; p = 0.000) and the risk of glioma. Additionally, a significant correlation was observed between CXCR4 (n = 8; OR = 4.39; 95 % CI = 3.04-6.32; p = 0.000), (n = 6; SMD = 1.37; 95 % CI = 1.09-1.65; p = 0.000), CXCL12 (n = 6; OR = 6.30; 95 % CI = 3.87-10.25; p = 0.000), (n = 5; ES = 2.25; 95 % CI = 1.15-3.34; p = 0.041), CCL2 (n = 3; OR = 9.65; 95 % CI = 4.55-20.45; p = 0.000), (n = 4; SMD = -1.47; 95 % CI = -1.68--1.26; p = 0.000), and CCL18 (n = 3; SMD = 1.62; 95 % CI = 1.30-1.93; p = 0.000) expression levels and high-grade glioma (grades 3-4). Furthermore, CXCR4 (HR = 2.38, 95 % CI = 1.66-3.40; p = 0.000) exhibited a strong correlation with poor overall survival (OS) rates in glioma patients.

CONCLUSION

The findings of this study showed a robust association between elevated levels of CXCR4, CXCL12, CCL2, CXCL8, CXCL10 and CXCR7 with a higher risk of glioma. Furthermore, the WHO grading system was validated by the strong correlation shown between higher expression of CXCR4, CXCL12, CCL2, and CCL18 and WHO high-grade gliomas (grades 3-4). Furthermore, the results of the meta-analysis suggested that CXCR4 might be a helpful biomarker for predicting the worse prognosis of glioma patients.

A novel disulfide death-related genes prognostic signature identifies the role of IPO4 in glioma progression

BACKGROUND

"Disulfide death," a form of cellular demise, is triggered by the abnormal accumulation of intracellular disulfides under conditions of glucose deprivation. However, its role in the prognosis of glioma remains undetermined. Therefore, the main objective of this study is to establish prognostic signature based on disulfide death-related genes (DDRGs) and to provide new solutions in choosing the effective treatment of glioma.

METHODS

The RNA transcriptome, clinical information, and mutation data of glioma samples were sourced from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA), while normal samples were obtained from the Genotype-Tissue Expression (GTEx). DDRGs were compiled from previous studies and selected through differential analysis and univariate Cox regression analysis. The molecular subtypes were determined through consensus clustering analysis. Further, LASSO analysis was employed to select characteristic genes, and subsequently, a risk model comprising seven DDRGs was constructed based on multivariable Cox analysis. Kaplan-Meier survival curves were employed to assess survival differences between high and low-risk groups. Additionally, functional analyses (GO, KEGG, GSEA) were conducted to explore the potential biological functions and signaling pathways of genes associated with the model. The study also explored immune checkpoint (ICP) genes, immune cell infiltration levels, and immune stromal scores. Finally, the effect of Importin-4(IPO4) on glioma has been further confirmed through RT-qPCR, Western blot, and cell functional experiments.

RESULTS

7 genes associated with disulfide death were obtained and two subgroups of patients with different prognosis and clinical characteristics were identified. Risk signature was subsequently developed and proved to serve as an prognostic predictor. Notably, the high-risk group exhibited an immunosuppressive microenvironment characterized by a high concentration of M2 macrophages and regulatory T cells (Tregs). In contrast, the low-risk group showed lower half-maximal inhibitory concentration (IC50) values. Therefore, patients in the high-risk group may benefit more from immunotherapy, while patients in the low-risk group may benefit more from chemotherapy. In addition, in vitro experiments have shown that inhibition of the expression of IPO4 leads to a significant reduction in the proliferation, migration, and invasion of glioma cells.

CONCLUSION

This study identified two glioma subtypes and constructed a prognostic signature based on DDRGs. The signature has the potential to optimize the selection of patients for immune- and chemotherapy and provided a potential therapeutic target for glioma.

THOC6 is a novel biomarker of glioma and a target of anti-glioma drugs: An analysis based on bioinformatics and molecular docking

Glioma is a typical malignant tumor of the nervous system. It is of great significance to identify new biomarkers for accurate diagnosis of glioma. In this context, THOC6 has been studied as a highly diagnostic prognostic biomarker, which contributes to improve the dilemma in diagnosing gliomas. We used online databases and a variety of statistical methods, such as Wilcoxon rank sum test, Dunn test and t test. We analyzed the mutation, location and expression profile of THOC6, revealing the network of THOC6 interaction with disease. Wilcoxon rank sum test showed that THOC6 is highly expressed in gliomas (P < 0.001). Dunn test, Wilcoxon rank sum test and t test showed that THOC6 expression was correlated with multiple clinical features. Logistic regression analysis further confirmed that THOC6 gene expression was a categorical dependent variable related to clinical features of poor prognosis. Kaplan-Meier survival analysis showed that the overall survival (OS) of glioma patients with high expression of THOC6 was poor (P < 0.001). Both univariate (P < 0.001) and multivariate (P = 0.04) Cox analysis confirmed that THOC6 gene expression was an independent risk factor for OS in patients with glioma. ROC curve analysis showed that THOC6 had a high diagnostic value in glioma (AUC = 0.915). Based on this, we constructed a nomogram to predict patient survival. Enrichment analysis showed that THOC6 expression was associated with multiple signal pathways. Immuno-infiltration analysis showed that the expression of THOC6 in glioma was closely related to the infiltration level of multiple immune cells. Molecular docking results showed that THOC6 might be the target of anti-glioma drugs. THOC6 is a novel diagnostic factor and prognostic biomarker of glioma.

Transcriptomic analysis identifies the neuropeptide cortistatin (CORT) as an inhibitor of temozolomide (TMZ) resistance by suppressing the NF-κB-MGMT signaling axis in human glioma

Glioma is a common tumor originating in the brain that has a high mortality rate. Temozolomide (TMZ) is the first-line treatment for high-grade gliomas. However, a large proportion of gliomas are resistant to TMZ, posing a great challenge to their treatment. In the study, the specific functions and mechanism(s) by which cortistatin (CORT) regulates TMZ resistance and glioma progression were evaluated. The decreased expression of CORT was detected in glioma tissues, and highly expressed CORT was associated with a better survival rate in patients with glioma. CORT overexpression notably decreased the capacity of glioma cells to proliferate and migrate in vitro and to form tumors in vivo. CORT overexpression also markedly suppressed the viability and enhanced the apoptosis of TMZ-resistant U251 cells by regulating MGMT, p21, and Puma expression. Importantly, CORT overexpression reduced the resistance of gliomas to TMZ in vivo. CORT expression was negatively correlated with MGMT expression in both glioma tissues and cells, and it was found that CORT inhibited NF-κB pathway activation in glioma cells, thereby inhibiting MGMT expression. In conclusion, CORT regulates glioma cell growth, migration, apoptosis, and TMZ resistance by weakening the activity of NF-κB/p65 and thereby regulating MGMT expression. The CORT/NF-κB/MGMT axis might be regarded as a molecular mechanism contributing to the resistance of glioma to TMZ. Our data also suggest that CORT regulates the viability and metastatic potential of glioma cells, independent of its effects on TMZ resistance, providing evidence of novel therapeutic targets for glioma that should be evaluated in further studies.

Focus on current and emerging treatment options for glioma: A comprehensive review

This comprehensive review delves into the current updates and challenges associated with the management of low-grade gliomas (LGG), the predominant primary tumors in the central nervous system. With a general incidence rate of 5.81 per 100000, gliomas pose a significant global concern, necessitating advancements in treatment techniques to reduce mortality and morbidity. This review places a particular focus on immunotherapies, discussing promising agents such as Zotiraciclib and Lerapolturev. Zotiraciclib, a CDK9 inhibitor, has demonstrated efficacy in glioblastoma treatment in preclinical and clinical studies, showing its potential as a therapeutic breakthrough. Lerapolturev, a viral immunotherapy, induces inflammation in glioblastoma and displays positive outcomes in both adult and pediatric patients. Exploration of immunotherapy extends to Pembrolizumab, Nivolumab, and Entrectinib, revealing the challenges and variabilities in patient responses. Despite promising preclinical data, the monoclonal antibody Depatuxizumab has proven ineffective in glioblastoma treatment, emphasizing the critical need to understand resistance mechanisms. The review also covers the success of radiation therapy in pediatric LGG, with evolving techniques, such as proton therapy, showing potential improvements in patient quality of life. Surgical treatment is discussed in the context of achieving a balance between preserving the patient's quality of life and attaining gross total resection, with the extent of surgical resection significantly influencing the survival outcomes. In addition to advancements in cancer vaccine development, this review highlights the evolving landscape of LGG treatment, emphasizing a shift toward personalized and targeted therapies. Ongoing research is essential for refining strategies and enhancing outcomes in the management of LGG.

Signature Construction and Disulfidptosis-Related Molecular Cluster Identification for Better Prediction of Prognosis in Glioma

Disulfidptosis is a newly discovered form of regulatory cell death. However, the identification of disulfidptosis-related molecular subtypes and potential biomarkers in gliomas and their prognostic predictive potential need to be further elucidated. RNA sequencing profiles and the relevant clinical data were obtained from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Disulfidptosis-related clusters were identified by unsupervised clustering analysis. Immune cell infiltration analysis and drug sensitivity analysis were used to explore the differences between clusters. Gene set enrichment analysis (GSEA) of differential genes between clusters was performed to explore the potential biological functions and signaling. A disulfidptosis-related scoring system (DRSS) was constructed based on a combined COX and LASSO analysis. Mendelian randomization (MR) analyses were used to further explore the causal relationship between levels of genes in DRSS and an increased risk of glioma. A prognosis nomogram was constructed based on the DRSS and 3 clinical features (age, WHO stage, and IDH status). The accuracy and stability of the prognosis nomogram were also validated in different cohorts. We identified two clusters that exhibited different prognoses, drug sensitivity profiles, and tumor microenvironment infiltration profiles. The overall survival (OS) of Cluster2 was significantly better than Cluster1. Cluster1 had an overall greater infiltration of immune cells compared to Cluster2. However, the Monocytes, activated B cells had higher infiltration abundance in Cluster2. GSEA results showed significant enrichment of immune-related biological processes in Cluster1, while Cluster2 was more enriched for functions related to neurotransmission and regulation. PER3, RAB34, NKX3-2, GPX7, FRA10AC1, and TGIF1 were finally included to construct DRSS. DRSS was independently related to prognosis. There was a significant difference in overall survival between the low-risk score group and the high-risk score group. Among six genes in DRSS, GPX7 levels were demonstrated to have a causal relationship with an increased risk of glioma. GPX7 may become a more promising biomarker for gliomas. The prognosis nomogram constructed based on the DRSS and three clinical features has considerable potential for predicting the prognosis of patients with glioma. Free online software for implementing this nomogram was established:  https://yekun-zhuang.shinyapps.io/DynNomapp/ . Our study established a novel glioma classification based on the disulfidptosis-related molecular subtypes. We constructed the DRSS and the prognosis nomogram to accurately stratify the prognosis of glioma patients. GPX7 was identified as a more promising biomarker for glioma. We provide important insights into the treatment and prognosis of gliomas.

Rotor-based image-guided therapy of glioblastoma

Glioblastoma (GBM), deep in the brain, is more challenging to diagnose and treat than other tumors. Such challenges have blocked the development of high-impact therapeutic approaches that combine reliable diagnosis with targeted therapy. Herein, effective cyanine dyes (IRLy) with the near-infrared two region (NIR-II) adsorption and aggregation-induced emission (AIE) have been developed via an "extended conjugation & molecular rotor" strategy for multimodal imaging and phototherapy of deep orthotopic GBM. IRLy was synthesized successfully through a rational molecular rotor modification with stronger penetration, higher signal-to-noise ratio, and a high photothermal conversion efficiency (PCE) up to ∼60%, which can achieve efficient NIR-II photo-response. The multifunctional nanoparticles (Tf-IRLy NPs) were further fabricated to cross the blood-brain barrier (BBB) introducing transferrin (Tf) as a targeting ligand. Tf-IRLy NPs showed high biosafety and good tumor enrichment for GBM in vitro and in vivo, and thus enabled accurate, efficient, and less invasive NIR-II multimodal imaging and photothermal therapy. This versatile Tf-IRLy nanosystem can provide a reference for the efficient, precise and low-invasive multi-synergistic brain targeted photo-theranostics. In addition, the "extended conjugation & molecular rotor" strategy can be used to guide the design of other photothermal agents.

Post-treatment imaging of gliomas: challenging the existing dogmas

Gliomas are the commonest malignant central nervous system tumours in adults and imaging is the cornerstone of diagnosis, treatment, and post-treatment follow-up of these patients. With the ever-evolving treatment strategies post-treatment imaging and interpretation in glioma remains challenging, more so with the advent of anti-angiogenic drugs and immunotherapy, which can significantly alter the appearance in this setting, thus making interpretation of routine imaging findings such as contrast enhancement, oedema, and mass effect difficult to interpret. This review details the various methods of management of glioma including the upcoming novel therapies and their impact on imaging findings, with a comprehensive description of the imaging findings in conventional and advanced imaging techniques. A systematic appraisal for the existing and emerging techniques of imaging in these settings and their clinical application including various response assessment guidelines and artificial intelligence based response assessment will also be discussed.

Microneedle Patch Delivery of PLCG1-siRNA Efficient Enhanced Temozolomide Therapy for Glioblastoma

The blood-brain barrier (BBB) and drug resistance present challenges for chemotherapy of glioblastoma (GBM). A microneedle (MN) patch with excellent biocompatibility and biodegradability was designed to bypass the BBB and release temozolomide (TMZ) and PLCG1-siRNA directly into the tumor site for synergistic treatment of GBM. The codelivery of TMZ and PLCG1-siRNA enhanced DNA damage and apoptosis. The potential mechanism behind this enhancement is to knockdown of PLCG1 expression, which positively regulates the expression of signal transducer and activator of transcription 3 genes, thereby preventing DNA repair and enhancing the sensitivity of GBM to TMZ. The MN patch enables long-term sustainable drug release through in situ implantation and increases local drug concentrations in diseased areas, significantly extending mouse survival time compared to other drug treatment groups. MN drug delivery provides a platform for the combination treatment of GBM and other central nervous system diseases.

Brain tumor classification from MRI scans: a framework of hybrid deep learning model with Bayesian optimization and quantum theory-based marine predator algorithm

Brain tumor classification is one of the most difficult tasks for clinical diagnosis and treatment in medical image analysis. Any errors that occur throughout the brain tumor diagnosis process may result in a shorter human life span. Nevertheless, most currently used techniques ignore certain features that have particular significance and relevance to the classification problem in favor of extracting and choosing deep significance features. One important area of research is the deep learning-based categorization of brain tumors using brain magnetic resonance imaging (MRI). This paper proposes an automated deep learning model and an optimal information fusion framework for classifying brain tumor from MRI images. The dataset used in this work was imbalanced, a key challenge for training selected networks. This imbalance in the training dataset impacts the performance of deep learning models because it causes the classifier performance to become biased in favor of the majority class. We designed a sparse autoencoder network to generate new images that resolve the problem of imbalance. After that, two pretrained neural networks were modified and the hyperparameters were initialized using Bayesian optimization, which was later utilized for the training process. After that, deep features were extracted from the global average pooling layer. The extracted features contain few irrelevant information; therefore, we proposed an improved Quantum Theory-based Marine Predator Optimization algorithm (QTbMPA). The proposed QTbMPA selects both networks' best features and finally fuses using a serial-based approach. The fused feature set is passed to neural network classifiers for the final classification. The proposed framework tested on an augmented Figshare dataset and an improved accuracy of 99.80%, a sensitivity rate of 99.83%, a false negative rate of 17%, and a precision rate of 99.83% is obtained. Comparison and ablation study show the improvement in the accuracy of this work.

Current Photodynamic Therapy for Glioma Treatment: An Update

Research on the development of photodynamic therapy for the treatment of brain tumors has shown promise in the treatment of this highly aggressive form of brain cancer. Analysis of both in vivo studies and clinical studies shows that photodynamic therapy can provide significant benefits, such as an improved median rate of survival. The use of photodynamic therapy is characterized by relatively few side effects, which is a significant advantage compared to conventional treatment methods such as often-used brain tumor surgery, advanced radiotherapy, and classic chemotherapy. Continued research in this area could bring significant advances, influencing future standards of treatment for this difficult and deadly disease.

Total intravenous anaesthesia with propofol and remifentanil is associated with reduction in operative time in surgery for glioblastoma when compared with inhalational anaesthesia with sevoflurane

BACKGROUND

Total intravenous anaesthesia (TIVA) is emerging as a preferred neuroanaesthetic agent compared with inhalational anaesthetic (IA) agents. We asked if TIVA with propofol and remifentanil was associated with shorter operative times compared to IA using sevoflurane in brain tumour surgery under GA.

METHODS

We performed a retrospective analysis of all patients undergoing surgery for glioblastoma (GBM). We assessed choice of GA agent (TIVA or IA) with total time patient was under GA (anaesthetic time), operative time and time taken to recover fully from GA (recovery time).

RESULTS

Over a two year period 263 patients underwent surgery under GA for their GBM including 188 craniotomy operations, 63 burr hole biopsy procedures and 12 open biopsy procedures. Of these, 79 operations took place under TIVA and 184 operations under IA. TIVA was associated with significantly reduced mean operative time including time taken to wake up in theatre (104 min with TIVA, 129 min with IA; p = 0.02). TIVA was also associated with trends toward shorter mean recovery time (118 min, versus 135 min with IA; p = 0.08) and shorter mean anaesthetic time (163 min, versus 181 min with IA; p = 0.07). There was no difference between TIVA and IA groups as regards duration of inpatient stay, readmission rates, complications or survival.

CONCLUSIONS

TIVA with propofol and remifentanil may reduce anaesthetic, operative and recovery times in patients undergoing surgery for their GBM. These findings may be attributable to favourable effects on intracranial pressure and cerebral perfusion, as well as rapid recovery from GA. In addition to clinical advantages, there may be financial and logistical benefits.

LncRNA FTH1P3: A New Biomarker for Cancer-Related Therapeutic Development

Cancer is a persistent and urgent health problem that affects the entire world. Not long ago, regulatory biomolecules referred to as long noncoding RNAs (lncRNAs) might have value for their innate abundance and stability. These single-stranded RNAs potentially interfere with several physiological and biochemical cellular processes involved in many human pathological situations, particularly cancer diseases. Ferritin heavy chain1 pseudogene 3 (FTH1P3), a lncRNA that is ubiquitously transcribed and belongs to the ferritin heavy chain (FHC) family, represents a novel class of lncRNAs primarily found in oral squamous cell carcinoma. Further research has shown that FTH1P3 is involved in other malignancies such as uveal melanoma, glioma, esophageal squamous cell carcinoma, non-small cell lung cancer, breast cancer, laryngeal squamous cell carcinoma, and cervical cancer. Accordingly, FTH1P3 significantly enhances cancer symptoms, including cell proliferation, invasion, metastasis, chemoresistance, and inhibition of apoptosis through many specific mechanisms. Notably, the clinical data significantly demonstrated the association of FTH1P3 overexpression with poor prognosis and poor overall survival within the examined samples. Here, we summarize all the research published to date (13 articles) on FTH1P3, focusing on the biological function underlying the regulatory mechanism and its possible clinical relevance.

SENP1-mediated SUMOylation of SIRT1 affects glioma development through the NF-κB pathway

Gliomas are the most common primary brain tumors in adults. Although they exist in different malignant stages, most gliomas are clinically challenging because of their infiltrative growth patterns and inherent relapse tendency with increased malignancy. Epigenetic alterations have been suggested to be an important factor for glioma genesis. Using mRNA probe hybridization, we identified SUMO-specific protease 1 (SENP1) as the most significantly upregulated SUMOylation regulator in glioma. Moreover, SENP1 was overexpressed in gliomas and predicted poor prognoses. Depletion of SENP1 reduced glioma cell activity, cycle arrest, and increased apoptotic activity. Mechanistically, SENP1 inhibited the protein expression of sirtuin 1 (SIRT1) through de-SUMOylation, and SIRT1 inhibited the activity of nuclear factor kappaB (NF-κB) by deacetylation. Rescue experiments revealed that downregulation of SIRT1 reversed the inhibitory effect of sh-SENP1 on glioma cell malignant phenotype, while downregulation of NF-κB reversed the activating effect of sh-SIRT1 on glioma cell malignant phenotype. Thus, SENP1-mediated de-SUMOylation of SIRT1 might be therapeutically important in gliomas.

Neuro-oncology Treatment Strategies for Primary Glial Tumors

Primary brain tumors underwent reclassification in the 2021 World Health Organization update, relying on molecular findings (especially isocitrate dehydrogenase mutations and chromosomal changes in 1p, 19q, gain of chromosome 7 and loss of chromosome 10). Newer entities have also been described including histone 3 mutant midline gliomas. These updated pathologic classifications improve prognostication and reliable diagnosis, but may confuse interpretation of prior clinical trials and require reclassification of patients diagnosed in the past. For patients over seventy, multiple studies have now confirmed the utility of shorter courses of radiation, and the risk of post-operative delirium. Ongoing studies are comparing proton to photon radiation. Long term follow up of prior clinical trials have confirmed the roles and length of chemotherapy (mainly temozolomide) in different tumors, as well as the wearable novottf device. New oral isocitrate dehydrogenase inhibitors have also shown efficacy in clinical trials.

Structure-based virtual screening and molecular docking approaches to identify potential inhibitors against KIF2C to combat glioma

Glioma, a kind of malignant brain tumor, is extremely lethal. Kinesin family member 2C (KIF2C) was found to have an aberrant expression in several cancer types, including lung cancer and glioma. KIF2C may therefore be a useful therapeutic target for the treatment of glioma. In the current study, new drug candidates that may function as KIF2C enzyme inhibitors were discovered. MTi OpenScreen was used to carry out the structure-based virtual screening of an inbuilt drug library containing 150,000 compounds. These compounds belong to different classes, such as natural product-based compounds (NP-lib), purchasable approved drugs (Drugs-lib), and food constituents compound collection (FOOD-lib). Based on their binding affinities, a total of 84 compounds were further pushed to calculate ADMET properties. The compounds (16) meeting the ADMET cutoff ranges were then further docked to the receptor to find their plausible binding modes using the Glide tool's standard precision (SP) technique. The docking results were examined using the Glide gscore, and the best binding compounds (Rimacalib and Sarizotan) were chosen to test their stability with KIF2C protein through molecular dynamics (MD) simulation. Similarly, Principal Component Analysis and cross-correlation matrix were also examined. The MM/GBSA binding free energies showed a considerable energy contribution in the binding of hits with the KIF2C. Collectively, these findings strongly suggest the potential of the lead compounds to inhibit the biological function of KIF2C, emphasizing the need for further investigation in this area.Communicated by Ramaswamy H. Sarma.

Effects of PKCε knockdown on mitochondrial membrane potential of human glioma cells in vitro and growth of U251 cell-derived tumors in vivo

Glioma is the most common type of primary brain tumor; it exhibits great invasive capacity, morbidity and mortality. Protein kinase Cε (PKCε), a serine/threonine kinase, contributes to the development and progression of many cancers. We investigated whether knockdown of PKCε could affect the mitochondrial membrane potential of human glioma cell lines, U251 and U87, and the growth of U251 cell-derived tumors in nude mice. We found that the expression of PKCε was greater in human glioma tissues than in human normal brain tissues. Knockdown of PKCε reduced mitochondrial membrane potential in U251 and U87 cells. Knockdown of PKCε also suppressed the growth of tumors derived from U251 cells and induced apoptosis of U251 cells in vivo. Our findings indicate that PKCε is important for development and progression of glioma and may be a potential therapeutic target for glioma treatment.

AI Deployment on GBM Diagnosis: A Novel Approach to Analyze Histopathological Images Using Image Feature-Based Analysis

BACKGROUND

Glioblastoma (GBM) is one of the most common malignant primary brain tumors, which accounts for 60-70% of all gliomas. Conventional diagnosis and the decision of post-operation treatment plan for glioblastoma is mainly based on the feature-based qualitative analysis of hematoxylin and eosin-stained (H&E) histopathological slides by both an experienced medical technologist and a pathologist. The recent development of digital whole slide scanners makes AI-based histopathological image analysis feasible and helps to diagnose cancer by accurately counting cell types and/or quantitative analysis. However, the technology available for digital slide image analysis is still very limited. This study aimed to build an image feature-based computer model using histopathology whole slide images to differentiate patients with glioblastoma (GBM) from healthy control (HC).

METHOD

Two independent cohorts of patients were used. The first cohort was composed of 262 GBM patients of the Cancer Genome Atlas Glioblastoma Multiform Collection (TCGA-GBM) dataset from the cancer imaging archive (TCIA) database. The second cohort was composed of 60 GBM patients collected from a local hospital. Also, a group of 60 participants with no known brain disease were collected. All the H&E slides were collected. Thirty-three image features (22 GLCM and 11 GLRLM) were retrieved from the tumor volume delineated by medical technologist on H&E slides. Five machine-learning algorithms including decision-tree (DT), extreme-boost (EB), support vector machine (SVM), random forest (RF), and linear model (LM) were used to build five models using the image features extracted from the first cohort of patients. Models built were deployed using the selected key image features for GBM diagnosis from the second cohort (local patients) as model testing, to identify and verify key image features for GBM diagnosis.

RESULTS

All five machine learning algorithms demonstrated excellent performance in GBM diagnosis and achieved an overall accuracy of 100% in the training and validation stage. A total of 12 GLCM and 3 GLRLM image features were identified and they showed a significant difference between the normal and the GBM image. However, only the SVM model maintained its excellent performance in the deployment of the models using the independent local cohort, with an accuracy of 93.5%, sensitivity of 86.95%, and specificity of 99.73%.

CONCLUSION

In this study, we have identified 12 GLCM and 3 GLRLM image features which can aid the GBM diagnosis. Among the five models built, the SVM model proposed in this study demonstrated excellent accuracy with very good sensitivity and specificity. It could potentially be used for GBM diagnosis and future clinical application.

PD-L1-related IncRNAs are associated with malignant characteristics and immune microenvironment in glioma

BACKGROUND

The expression of long non-coding RNA (lncRNA) can function as diagnostic and therapeutic biomarker for tumors. This research explores the role of PD-L1-related lncRNAs in affecting malignant characteristics and the immune microenvironment of glioma.

METHODS

Downloading gene expression profiles and clinicopathological information of glioma from TCGA and CGGA databases, 6 PD-L1-related lncRNAs were identified through correlation analysis, Cox and LASSO regression analysis, establishing the risk score model based on them. Bioinformatics analysis and cell experiments in vitro were adopted to verify the effects of LINC01271 on glioma.

RESULTS

Risk scores based on 6 PD-L1-related lncRNAs (AL355974.3, LINC01271, AC011899.3, MIR4500HG, LINC02594, AL357055.3) can reflect malignant characteristics and immunotherapy response of glioma. Patients with high LINC01271 expression had a worse prognosis, a higher abundance of M1 subtype macrophages in the immune microenvironment, and a higher degree of tumor malignancy. Experiments in vitro confirmed its positive regulatory effect on the proliferation and migration of glioma cells.

CONCLUSIONS

The risk score model based on 6 PD-L1-related lncRNAs can reflect the malignant characteristics and prognosis of glioma. LINC01271 can independently be used as a new target for prognosis evaluation and therapy.

The evaluation of six genes combined value in glioma diagnosis and prognosis

PURPOSE

Glioma is the most common and fatal type of brain tumour. Owing to its aggressiveness and lethality, early diagnosis and prediction of patient survival are very important. This study aimed to identify key genes and biomarkers for glioma that can guide clinicians in making rapid diagnosis and prognostication.

METHODS

Data mining of The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Repository of Molecular Brain Neoplasia Data, and Genotype-Tissue Expression Project brain expression data revealed significantly differentially expressed genes (DEGs), and the risk scores of individual patients were calculated. WGCNA was utilized to screen for genes most related to clinical diagnosis. Prognostic genes associated with glioma were selected via combining the LASSO regression with univariate and multivariate Cox regression and protein-protein interaction network analyses. Then, a nomogram was constructed. And CGGA dataset was utilized to validated. The protein expression levels of the signature were detected using the human protein atlas. Drug response prediction was carried out using the package "pRRophetic".

RESULTS

A six-gene signature (KLF6, CHI3L1, SERPINE1, ANGPT2, TGFBR1, and PTX3) was identified and used to stratify patients into low- and high-risk groups. Survival, ROC curve, and Cox analyses clarified that the six hub genes were a favourable independent prognostic factor for patients with glioma. A nomogram was set up by integrating clinical parameters with risk signatures, showing high precision for predicting 2-, 3-, 4-, 5-years survival. In addition, the expression of most genes was consistent with protein expression. Furthermore, the sensitivity to the top ten drugs in the GDSC database of the high-risk group was significantly higher than the low-risk group.

CONCLUSION

Based on genetic profiles and clinicopathological features, including age, grade, isocitrate dehydrogenase mutation status, we constructed a comprehensive prognostic model for patients with glioma. These signatures can be regarded as biomarkers to predict the prognosis of gliomas, possibly providing more therapeutic strategies for future clinical research.

Photodynamic therapy and associated targeting methods for treatment of brain cancer

Brain tumors, including glioblastoma multiforme, are currently a cause of suffering and death of tens of thousands of people worldwide. Despite advances in clinical treatment, the average patient survival time from the moment of diagnosis of glioblastoma multiforme and application of standard treatment methods such as surgical resection, radio- and chemotherapy, is less than 4 years. The continuing development of new therapeutic methods for targeting and treating brain tumors may extend life and provide greater comfort to patients. One such developing therapeutic method is photodynamic therapy. Photodynamic therapy is a progressive method of therapy used in dermatology, dentistry, ophthalmology, and has found use as an antimicrobial agent. It has also found wide application in photodiagnosis. Photodynamic therapy requires the presence of three necessary components: a clinically approved photosensitizer, oxygen and light. This paper is a review of selected literature from Pubmed and Scopus scientific databases in the field of photodynamic therapy in brain tumors with an emphasis on glioblastoma treatment.

Development and validation of a personalized classifier to predict the prognosis and response to immunotherapy in glioma based on glycolysis and the tumor microenvironment

Background

Glycolysis is closely associated with cancer progression and treatment outcomes. However, the role of glycolysis in the immune microenvironment, prognosis, and immunotherapy of glioma remains unclear.

Methods

This study investigated the role of glycolysis on prognosis and its relationship with the tumor microenvironment (TME). Subsequently, we developed and validated the glycolysis-related gene signature (GRS)-TME classifier using multiple independent cohorts. Furthermore, we also examined the prognostic value, somatic alterations, molecular characteristics, and potential benefits of immunotherapy based on GRS-TME classifier. Lastly, the effect of kinesin family member 20A (KIF20A) on the proliferation and migration of glioma cells was evaluated in vitro.

Results

Glycolysis was identified as a significant prognostic risk factor in glioma, and closely associated with an immunosuppressive microenvironment characterized by altered distribution of immune cells. Furthermore, a personalized GRS-TME classifier was developed and validated by combining the glycolysis (18 genes) and TME (seven immune cells) scores. Patients in the GRSlow/TMEhigh subgroup exhibited a more favorable prognosis compared to other subgroups. Distinct genomic alterations and signaling pathways were observed among different subgroups, which are closely associated with cell cycle, epithelial-mesenchymal transition, p53 signaling pathway, and interferon-alpha response. Additionally, we found that patients in the GRSlow/TMEhigh subgroup exhibit a higher response rate to immunotherapy, and the GRS-TME classifier can serve as a novel biomarker for predicting immunotherapy outcomes. Finally, high expression of KIF20A is associated with an unfavorable prognosis in glioma, and its knockdown can inhibit the proliferation and migration of glioma cells.

Conclusions

Our study developed a GRS-TME classifier for predicting the prognosis and potential benefits of immunotherapy in glioma patients. Additionally, we identified KIF20A as a prognostic and therapeutic biomarker for glioma.

Lipid-based nanoparticles via nose-to-brain delivery: a mini review

Central nervous system disorders significantly affect the lives and health of millions of people worldwide. Despite many therapeutic drugs are available that could potentially target central nervous system disorders, their clinical utility is severely constrained by their inability to cross the blood-brain barrier (BBB). Fortunately, nanotechnology has been advanced to offers a solution to allow drugs reaching the targeted brain regions safely, efficiently, and precisely through nasal drug delivery system (NDDS), bypassing the BBB completely. This strategy can promote the drug accumulated in the targeted brain region, improve drug bioavailability, and minimal side effects and mucociliary clearance effectively. In this review, we elaborate recent advances in the use of lipid-based nanoparticles, involving liposomes, nanoemulsions, nanostructured lipid carriers, and solid lipid nanoparticles. Besides, we particularly introduced the nasal cavity physiological structure, and further summarized the nose-to-brain drug delivery pathways, including olfactory, trigeminal, and blood circulation pathway. Moreover, the mechanism and route of NDDS by various types of nanoparticles are also highlighted.

Outcome of glioblastoma patients after intensive care unit admission with invasive mechanical ventilation: a multicenter analysis

PURPOSE

Patients with glioblastoma are exposed to severe symptoms and organs failures (e.g., coma or acute respiratory failure), that may require intensive care unit (ICU) admission and invasive mechanical ventilation (IMV). However, only limited data are available concerning the prognosis of patients with glioblastoma receiving IMV. We sought to describe the reasons for ICU admission, and outcomes of patients with glioblastoma requiring IMV for unplanned critical complications.

METHODS

In this retrospective analysis, four certified interdisciplinary brain tumor centers performed a retrospective review of their electronic data systems. All patients with glioblastoma admitted to an in-house ICU and receiving IMV between January 2015 and December 2019 were included. Clinical and prognostic factors as well as relevant outcome parameters were evaluated by group comparisons and Kaplan Meier survival curves.

RESULTS

We identified 33 glioblastoma patients with a duration of IMV of 9.2 ± 9.4 days. Main reasons for ICU admission were infection (n = 12; 34.3%) including 3 cases of Pneumocystis jirovecii pneumonia, status epilepticus (31.4%) and elevated intracranial pressure (22.9%). In-hospital mortality reached 60.6%. Younger age, low number of IMV days, better Karnofsky Performance Status Scale before admission and elevated intracranial pressure as cause of ICU admission were associated with positive prognostic outcome.

CONCLUSION

We conclude that less than 50% of patients with glioblastoma have a favorable short-term outcome when unplanned ICU treatment with IMV is required. Our data mandate a careful therapy guidance and frequent reassessment of goals during ICU stay.

Association of prognostic nutritional index with prognostic outcomes in patients with glioma: a meta-analysis and systematic review

Background

The potential link between Prognostic Nutritional Index (PNI) and prognosis in patients with glioma remains uncertain. This meta-analysis was conducted to assess the clinical value of PNI in glioma patients by integrating all available evidence to enhance statistical power.

Method

A systematic search of databases including Medline, EMBASE, Google Scholar, and Cochrane Library was conducted from inception to January 8, 2023 to retrieve all pertinent peer-reviewed articles. The primary outcome of the study was to examine the association between a high PNI value and overall survival, while secondary outcome included the relationship between a high PNI and progression-free survival.

Results

In this meta-analysis, we included 13 retrospective studies published from 2016 to 2022, which analyzed a total of 2,712 patients. Across all studies, surgery was the primary treatment modality, with or without chemotherapy and radiotherapy as adjunct therapies. A high PNI was linked to improved overall survival (Hazard Ratio (HR) = 0.61, 95% CI: 0.52 to 0.72, p < 0.00001, I2 = 25%), and this finding remained consistent even after conducting sensitivity analysis. Subgroup analyses based on ethnicity (Asian vs. non-Asian), sample size (<200 vs. >200), and source of hazard ratio (univariate vs. multivariate) yielded consistent outcomes. Furthermore, patients with a high PNI had better progression-free survival than those with a low PNI (HR=0.71, 95% CI: 0.58 to 0.88, p=0.001, I2 = 0%).

Conclusion

Our meta-analysis suggested that a high PNI was associated with better overall survival and progression-free survival in patients with glioma. These findings may have important implications in the treatment of patients with glioma. Additional studies on a larger scale are necessary to investigate if integrating the index into the treatment protocol leads to improved clinical outcomes in individuals with glioma.

Systematic review registration

[https://www.crd.york.ac.uk/prospero/], identifier [CRD42023389951].

Metformin-loaded nanoerythrosomes: An erythrocyte-based drug delivery system as a therapeutic tool for glioma

Glioma is an intra-cranial malignancy with the origin of neural stem cells or precursor cells, the most prevalent brain tumor worldwide. Glioblastoma, the fourth-grade glioma, is a common brain tumor whose incidence rate is 5-7 people per 100,000 populations annually. Despite their high mortality rate, all efforts for treatment have yet to achieve any desirable clinical outcome. The Wnt signaling pathway is a conserved pathway among species that seems to be a candidate for cancer therapy by its inhibition. Metformin is a known inhibitor of the Wnt signaling pathway. Its effects on glioma treatment have been observed in cellular, animal, and clinical experiments. Nanoerythrosomes are drug carriers obtained from the cellular membrane of red blood cells in nano size which can offer several characteristics to deliver metformin to brain tumors. They are good at loading and carrying hydrophilic drugs, they can protect metformin from its metabolizing enzymes, which are present in the blood-brain barrier, and they can extend the period of metformin presence in circulation. In this study, nanoerythrosomes were prepared by using the hypotonic buffer. They had particle sizes in the range of 97.1 ± 34.2 nm, and their loading efficiency and loading capacity were 72.6% and 1.66%, respectively. Nanoerythrosomes could reserve metformin in their structure for a long time, and only 50% of metformin was released after 30 h. Moreover, they released metformin at a low and approximately constant rate. Besides, nanoerythrosomes could tolerate various kinds of stress and maintain most of the drug in their structure. Altogether, nanoerythrosome can be a suitable drug delivery system to deliver therapeutic amounts of metformin to various tissues.

Combination of B7H6-siRNA and temozolomide synergistically reduces stemness and migration properties of glioblastoma cancer cells

Glioblastoma multiforme (GBM) is among the malignant brain tumors of the central nervous system (CNS). The survival of this disease is about 14 months after diagnosis. To date, temozolomide is known as first-line therapy for glioma. Drug resistance and severe side effects against this drug are important obstacles to the effective treatment of this cancer. Small interfering RNA (siRNA) can adjust the expression of several genes and is used as a new method of gene therapy. Recent studies have shown that siRNAs can increase the sensitivity of cancer cells to chemotherapy drugs. This study aimed to understand the potential role and molecular mechanism of the combination therapy of B7H6-siRNA and temozolomide in glioblastoma cancer. U87 cells were treated with B7H6-siRNA and temozolomide, separately and in combination. Cell viability, stemness, cell migration, and apoptosis were measured. The results of this work presented the synergistic effect of B7H6-siRNA and temozolomide in inhibiting the cancerous features of the U87 cell line. Down-regulating B7H6-siRNA expression inhibited the cell viability of U87 glioblastoma cancer cells and increased their sensitivity to temozolomide. In addition, a noteworthy decrease in cell migration ability and stemness, an increase in apoptosis were observed in the combined groups compared to B7H6-siRNA and temozolomide individually. According to the results, a combination of B7H6-siRNA and temozolomide can be a promising strategy in glioblastoma cancer therapy.

Prognostic characterization of the pyroptosis-related subtypes and tumor microenvironment infiltration in glioma

BACKGROUND

Pyroptosis could regulate tumor cell trafficking, invasion, and metastasis, as well as the tumor microenvironment (TME). However, prognostic characteristics of pyroptosis-related genes (PRGs) and their effect on the progression of glioma remain insufficient.

METHODS

The genetic, transcriptional, and survival data of patients with glioma used for bioinformatic analysis were obtained from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases.

RESULTS

Screening of two different molecular subtypes revealed that PRG variations were associated with characteristics of TME cell infiltration, clinicopathological characteristics, and prognosis of patients with glioma. After Cox regression of differentially expressed genes, a risk score for predicting overall survival (OS) and progression-free survival (PFS) were calculated. Its predictive accuracy in patients with glioma was validated. The high-risk group of PRG signature had a poorer OS than the low-risk group (training cohort, P< 0.001; validation cohort, P< 0.001). A high risk score implies more immune cell infiltration and better immunotherapy response to immune checkpoint blockers. In addition, the differential expression of three pyroptosis-pairs in tumor and normal tissues was identified. Furthermore, the risk score was significantly associated with chemotherapeutic drug sensitivity and cancer stem cell (CSC) index. Subsequently, a highly accurate nomogram was established to facilitate applicability in the preliminary clinical application of risk score.

CONCLUSION

Our findings may provide the basis for future research targeting pyroptosis in glioma and evaluation of prognosis and development of more effective immunotherapy strategies.

Robustness of the wide-field imaging Mueller polarimetry for brain tissue differentiation and white matter fiber tract identification in a surgery-like environment: an ex vivo study

During neurooncological surgery, the visual differentiation of healthy and diseased tissue is often challenging. Wide-field imaging Muller polarimetry (IMP) is a promising technique for tissue discrimination and in-plane brain fiber tracking in an interventional setup. However, the intraoperative implementation of IMP requires realizing imaging in the presence of remanent blood, and complex surface topography resulting from the use of an ultrasonic cavitation device. We report on the impact of both factors on the quality of polarimetric images of the surgical resection cavities reproduced in fresh animal cadaveric brains. The robustness of IMP is observed under adverse experimental conditions, suggesting a feasible translation of IMP for in vivo neurosurgical applications.

Tumor Suppressor Candidate 2 (TUSC2): Discovery, Functions, and Cancer Therapy

Tumor Suppressor Candidate 2 (TUSC2) was first discovered as a potential tumor suppressor gene residing in the frequently deleted 3p21.3 chromosomal region. Since its discovery, TUSC2 has been found to play vital roles in normal immune function, and TUSC2 loss is associated with the development of autoimmune diseases as well as impaired responses within the innate immune system. TUSC2 also plays a vital role in regulating normal cellular mitochondrial calcium movement and homeostasis. Moreover, TUSC2 serves as an important factor in premature aging. In addition to TUSC2's normal cellular functions, TUSC2 has been studied as a tumor suppressor gene that is frequently deleted or lost in a multitude of cancers, including glioma, sarcoma, and cancers of the lung, breast, ovaries, and thyroid. TUSC2 is frequently lost in cancer due to somatic deletion within the 3p21.3 region, transcriptional inactivation via TUSC2 promoter methylation, post-transcriptional regulation via microRNAs, and post-translational regulation via polyubiquitination and proteasomal degradation. Additionally, restoration of TUSC2 expression promotes tumor suppression, eventuating in decreased cell proliferation, stemness, and tumor growth, as well as increased apoptosis. Consequently, TUSC2 gene therapy has been tested in patients with non-small cell lung cancer. This review will focus on the current understanding of TUSC2 functions in both normal and cancerous tissues, mechanisms of TUSC2 loss, TUSC2 cancer therapeutics, open questions, and future directions.

Immunotherapy in glioblastoma treatment: Current state and future prospects

Glioblastoma remains as the most common and aggressive malignant brain tumor, standing with a poor prognosis and treatment prospective. Despite the aggressive standard care, such as surgical resection and chemoradiation, median survival rates are low. In this regard, immunotherapeutic strategies aim to become more attractive for glioblastoma, considering its recent advances and approaches. In this review, we provide an overview of the current status and progress in immunotherapy for glioblastoma, going through the fundamental knowledge on immune targeting to promising strategies, such as Chimeric antigen receptor T-Cell therapy, immune checkpoint inhibitors, cytokine-based treatment, oncolytic virus and vaccine-based techniques. At last, it is discussed innovative methods to overcome diverse challenges, and future perspectives in this area.

Application of colony-stimulating factor 3 in determining the prognosis of high-grade gliomas based on magnetic resonance imaging radiomics

Rationale and objectives

Radiomics is a promising, non-invasive method for determining the prognosis of high-grade glioma (HGG). The connection between radiomics and the HGG prognostic biomarker is still insufficient.

Materials and methods

In this study, we collected the pathological, clinical, RNA-sequencing, and enhanced MRI data of HGG from TCIA and TCGA databases. We characterized the prognostic value of CSF3. Kaplan-Meier (KM) analysis, univariate and multivariate Cox regression, subgroup analysis, Spearman analysis, and gene set variation analysis enrichment were used to elucidate the prognostic value of the CSF3 gene and the correlation between CSF3 and tumor features. We used CIBERSORT to analyze the correlation between CSF3 and cancer immune infiltrates. Logistic regression (LR) and support vector machine methods (SVM) were used to build the radiomics models for the prognosis prediction of HGG based on the expression of CSF3.

Results

Based on the radiomics score calculated from LR model, 182 patients with HGG from TCGA database were divided into radiomics score (RS) high and low groups. CSF3 expression varied between tumor and normal group tissues. CSF3 expression was found to be a significant risk factor for survival outcomes. A positive association was found between CSF3 expression and immune infiltration. The radiomics model based on both LR and SVM methods showed high clinical practicability.

Conclusion

The results showed that CSF3 has a prognostic value in HGG. The developed radiomics models can predict the expression of CSF3, and further validate the predictions of the radiomics models for HGG.

Prognostic role of the pretreatment systemic immune-inflammation index in patients with glioma: A meta-analysis

Background

The systemic immune-inflammation index (SII) has been recognized as the indicator that reflects the status of immune responses. The SII is related to the prognostic outcome of many malignancies, whereas its role in gliomas is controversial. For patients with glioma, we, therefore, conducted a meta-analysis to determine if the SII has a prognostic value.

Methods

Studies relevant to this topic were searched from 16 October 2022 in several databases. In patients with glioma, the relation of the SII level with the patient prognosis was analyzed based on hazard ratios (HRs) as well as corresponding 95% confidence intervals (CIs). Moreover, subgroup analysis was conducted to examine a possible heterogeneity source.

Results

There were eight articles involving 1,426 cases enrolled in the present meta-analysis. The increased SII level predicted the dismal overall survival (OS) (HR = 1.81, 95% CI = 1.55–2.12, p &lt; 0.001) of glioma cases. Furthermore, an increased SII level also predicted the prognosis of progression-free survival (PFS) (HR = 1.87, 95% CI = 1.44–2.43, p &lt; 0.001) in gliomas. An increased SII was significantly associated with a Ki-67 index of ≥30% (OR = 1.72, 95% CI = 1.10–2.69, p = 0.017). However, a high SII was not correlated with gender (OR = 1.05, 95% CI = 0.78–1.41, p = 0.734), KPS score (OR = 0.64, 95% CI = 0.17–2.37, p = 0.505), or symptom duration (OR 1.22, 95% CI 0.37–4.06, p = 0.745).

Conclusion

There was a significant relation between an increased SII level with poor OS and the PFS of glioma cases. Moreover, patients with glioma with a high SII value have a positive relationship with a Ki-67 of ≥30%.

ATRX, a guardian of chromatin

ATRX (alpha-thalassemia mental retardation X-linked) is one of the most frequently mutated tumor suppressor genes in human cancers, especially in glioma, and recent findings indicate roles for ATRX in key molecular pathways, such as the regulation of chromatin state, gene expression, and DNA damage repair, placing ATRX as a central player in the maintenance of genome stability and function. This has led to new perspectives about the functional role of ATRX and its relationship with cancer. Here, we provide an overview of ATRX interactions and molecular functions and discuss the consequences of its impairment, including alternative lengthening of telomeres and therapeutic vulnerabilities that may be exploited in cancer cells.

Reconstruction of the Corticospinal Tract in Patients with Motor-Eloquent High-Grade Gliomas Using Multilevel Fiber Tractography Combined with Functional Motor Cortex Mapping

BACKGROUND AND PURPOSE

Tractography of the corticospinal tract is paramount to presurgical planning and guidance of intraoperative resection in patients with motor-eloquent gliomas. It is well-known that DTI-based tractography as the most frequently used technique has relevant shortcomings, particularly for resolving complex fiber architecture. The purpose of this study was to evaluate multilevel fiber tractography combined with functional motor cortex mapping in comparison with conventional deterministic tractography algorithms.

MATERIALS AND METHODS

Thirty-one patients (mean age, 61.5 [SD, 12.2] years) with motor-eloquent high-grade gliomas underwent MR imaging with DWI (TR/TE = 5000/78 ms, voxel size = 2 × 2 × 2 mm3, 1 volume at b = 0 s/mm2, 32 volumes at b = 1000 s/mm2). DTI, constrained spherical deconvolution, and multilevel fiber tractography-based reconstruction of the corticospinal tract within the tumor-affected hemispheres were performed. The functional motor cortex was enclosed by navigated transcranial magnetic stimulation motor mapping before tumor resection and used for seeding. A range of angular deviation and fractional anisotropy thresholds (for DTI) was tested.

RESULTS

For all investigated thresholds, multilevel fiber tractography achieved the highest mean coverage of the motor maps (eg, angular threshold = 60°; multilevel/constrained spherical deconvolution/DTI, 25% anisotropy threshold = 71.8%, 22.6%, and 11.7%) and the most extensive corticospinal tract reconstructions (eg, angular threshold = 60°; multilevel/constrained spherical deconvolution/DTI, 25% anisotropy threshold = 26,485 mm3, 6308 mm3, and 4270 mm3).

CONCLUSIONS

Multilevel fiber tractography may improve the coverage of the motor cortex by corticospinal tract fibers compared with conventional deterministic algorithms. Thus, it could provide a more detailed and complete visualization of corticospinal tract architecture, particularly by visualizing fiber trajectories with acute angles that might be of high relevance in patients with gliomas and distorted anatomy.

Antisecretory factor is safe to use as add-on treatment in newly diagnosed glioblastoma

PURPOSE

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults. Despite the best available treatment, prognosis remains poor. Current standard therapy consists of surgical removal of the tumor followed by radiotherapy and chemotherapy with the alkylating agent temozolomide (TMZ). Experimental studies suggest that antisecretory factor (AF), an endogenous protein with proposed antisecretory and anti-inflammatory properties, may potentiate the effect of TMZ and alleviate cerebral edema. Salovum is an egg yolk powder enriched for AF and is classified as a medical food in the European Union. In this pilot study, we evaluate the safety and feasibility of add-on Salovum in GBM patients.

METHODS

Eight patients with newly diagnosed, histologically confirmed GBM were prescribed Salovum during concomitant radiochemotherapy. Safety was determined by the number of treatment-related adverse events. Feasibility was determined by the number of patients who completed the full prescribed Salovum treatment.

RESULTS

No serious treatment-related adverse events were observed. Out of 8 included patients, 2 did not complete the full treatment. Only one of the dropouts was due to issues directly related to Salovum, which were nausea and loss of appetite. Median survival was 23 months.

CONCLUSIONS

We conclude that Salovum is safe to use as an add-on treatment for GBM. In terms of feasibility, adherence to the treatment regimen requires a determined and independent patient as the large doses prescribed may cause nausea and loss of appetite.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04116138. Registered on 04/10/2019.

Macrophage cell membrane infused biomimetic liposomes for glioblastoma targeted therapy

Glioblastoma (GBM) is a highly aggressive malignant brain tumor currently without an effective treatment. Inspired by the recent advances in cell membrane biomimetic nanocarriers and by the key role of macrophages in GBM pathology, we developed macrophage membrane liposomes (MML) for GBM targeting. For the first time, it was assessed the role of macrophage polarization states in the effectiveness of these drug delivery systems. Interestingly, we observed that MML derived from M2 macrophages (M2 MML) presents higher uptake and increased delivery of the anticarcinogenic drug doxorubicin compared to M1 macrophage-derived nanocarriers (M1 MML) and control liposomes (CL). Moreover, the lowest uptake by macrophages of MML reveals promising immune escaping properties. Notably, M2 macrophages unveiled a higher expression of integrin CD49d, a crucial protein involved in the bilateral communication of macrophages with tumor cells. Therefore, our findings suggest the potential of using M2 macrophage membranes to develop novel nanocarriers targeting GBM.

LncRNA WEE2-AS1 is a diagnostic biomarker that predicts poor prognoses in patients with glioma

BACKGROUND

Glioma is characterized by high morbidity, high mortality, and poor prognosis. Despite tremendous advances in the treatment of glioma, the prognosis of patients with glioma is still unsatisfactory. There is an urgent need to discover novel molecular markers that effectively predict prognosis in patients with glioma. The investigation of the role of WEE2-AS1 in various tumors is an emerging research field, but the biological function and prognostic value of WEE2-AS1 in glioma have rarely been reported. This study aimed to assess the value of WEE2-AS1 as a potential prognostic marker of glioma.

METHODS

Gene expression (RNA-Seq) data of patients with glioma were extracted from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. The Wilcoxon rank sum test was used to analyze the expression of WEE2-AS1 in the cells and tissues of glioma. The Kruskal-Wallis rank sum test, Wilcoxon rank sum test, and logistic regression were used to evaluate the relationship between clinical variables and expression of WEE2-AS1. Cox regression analysis and the Kaplan-Meier method were used to evaluate the prognostic factors in glioma. A nomogram based on Cox multivariate analysis was used to predict the impact of WEE2-AS1 on glioma prognosis. Gene Set Enrichment Analysis (GSEA) was used to identify key WEE2-AS1-associated signaling pathways. Spearman's rank correlation was used to elucidate the association between WEE2-AS1 expression and immune cell infiltration levels.

RESULTS

We found that WEE2-AS1 was overexpressed in a variety of cancers, including glioma. High expression of WEE2-AS1 was associated with glioma progression. We determined that the expression of WEE2-AS1 might be an independent risk factor for the survival and prognosis of patients with glioma. We further observed that the mechanism of WEE2-AS1-mediated tumorigenesis involved neuroactive ligand-receptor interaction, cell cycle, and the infiltration of immune cells into the glioma microenvironment.

CONCLUSION

These findings demonstrate that WEE2-AS1 is a promising biomarker for the diagnosis and prognosis of patients with glioma. An increased understanding of its effects on the regulation of cell growth may lead to the development of clinical applications that improve the prognostic status of patients with glioma.

MTHFD2 suppresses glioblastoma progression via the inhibition of ERK1/2 phosphorylation

Glioblastoma (GBM) is a WHO grade 4 tumor and is the most malignant form of glioma. Methylenetetrahydrofolate dehydrogenase 2 (MTHFD2), a mitochondrial enzyme involved in folate metabolism, has been reported to be highly expressed in several human tumors. However, little is known about the role of MTHFD2 in GBM. In this study, we aimed to explore the biological functions of MTHFD2 in GBM and identify the associated mechanisms. We performed experiments such as immunohistochemistry, Western blot, and transwell assays and found that MTHFD2 expression was lower in high-grade glioma than in low-grade glioma. Furthermore, a high expression of MTHFD2 was associated with a favorable prognosis, and MTHFD2 levels showed good prognostic accuracy for glioma patients. The overexpression of MTHFD2 could inhibit the migration, invasion, and proliferation of GBM cells, whereas its knockdown induced the opposite effect. Mechanistically, our findings revealed that MTHFD2 suppressed GBM progression independent of its enzymatic activity, likely by inducing cytoskeletal remodeling through the regulation of extracellular signal-regulated kinase 1/2 (ERK1/2) phosphorylation, thereby influencing GBM malignance. Collectively, these findings uncover a potential tumor-suppressor role of MTHFD2 in GBM cells. MTHFD2 may act as a promising diagnostic and therapeutic target for GBM treatment.

Capsaicin induces redox imbalance and ferroptosis through ACSL4/GPx4 signaling pathways in U87-MG and U251 glioblastoma cells

Glioblastoma is one of the deadliest malignant gliomas. Capsaicin is a homovanillic acid derivative that can show anti-cancer effects by regulating various signaling pathways. The aim of this study is to investigate the effects of capsaicin on cell proliferation via ferroptosis in human U87-MG and U251 glioblastoma cells. Firstly, effects of capsaicin treatment on cell viability were determined by MTT analysis. Next, cellular-proliferation and cytotoxicity assays were determined by analyzing bromodeoxyuridine (BrdU) and lactate dehydrogenase (LDH) activity, respectively. Following, acyl-CoA synthetase long chain family member 4 (ACSL4), glutathione peroxidase 4 (GPx4), 5-hydroxyeicosatetraenoic acid (5-HETE), total oxidant status (TOS), malondialdehyde (MDA), total antioxidant status (TAS) and reduced glutathione (GSH) levels were determined by ELISA. Additionally, ACSL4 and GPx4 mRNA and protein levels were analyzed. Capsaicin showed a concentration-dependent anti-proliferative effects in U87-MG and U251 cells. Cell viability was decreased in the both cell lines treated with capsaicin concentrations above 50 μM, while LDH activity increased. Treatment of 121.6, 188.5, and 237.2 μM capsaicin concentrations for 24 h indicated an increase in ACSL4, 5-HETE, TOS and MDA levels in U87-MG and U251 cells (p < 0.05). On the other hand, we found that capsaicin administration caused a decrease in BrdU, GPx4, TAS and GSH levels in U87-MG and U251 cells (p < 0.05). Besides, ACSL4 mRNA and protein levels were increased in the glioblastoma cells treated with capsaicin, whereas GPx4 mRNA and protein levels were decreased. Finally, capsaicin might be used as a potential anticancer agent with ferroptosis-induced anti-proliferative effects in the treatment of human glioblastoma.

A pyroptosis-related signature predicts prognosis and indicates immune microenvironment infiltration in glioma

BACKGROUND

Glioma, the most common malignant brain tumor, leads to high recurrence rates and disabilities in patients. Pyroptosis is an inflammasomes-induced programmed cell death in response to infection or chemotherapy. However, the role of pyroptosis in glioma has not yet been elucidated.

METHODS

RNA-seq data and clinical information of 660 gliomas and 847 samples were downloaded from the TCGA and CGGA, respectively. Then, data of 104 normal brain tissues was retrieved from the GTEx for differential expression analysis. Twelve pairs of peritumoral tissue and glioma samples were used for validation. Gene alteration status of differentially expressed pyroptosis-related regulators in gliomas was detected in cBioPortal algorithm. Consensus clustering was employed to classify gliomas based on differentially expressed pyroptosis-related regulators. Subsequently, a PS-signature was constructed using LASSO-congressional analysis for clinical application. The immune infiltration of glioma microenvironment (TME) was explored using ESTIMATE, CIBERSORT, and the other immune signatures.

RESULTS

cBioPortal algorithm revealed alteration of these regulators was correlated to better prognosis of gliomas. Then, our study showed that pyroptosis-related regulators can be used to sort out patients into two clusters with distinct prognostic outcome and immune status. Moreover, a PS-signature for predicting the prognosis of glioma patients was developed based on the identified subtypes. The high PS-score group showed more abundant inflammatory cell infiltration and stronger immune response, but with poorer prognosis of gliomas.

CONCLUSION

The findings of this study provide a therapeutic basis for future research on pyroptosis and unravel the relationship between pyroptosis and glioma prognosis. The risk signature can be utilized as a prognostic biomarker for glioma.

Development of prognostic indicator based on NAD+ metabolism related genes in glioma

Background

Studies have shown that Nicotinamide adenine dinucleotide (NAD+) metabolism can promote the occurrence and development of glioma. However, the specific effects and mechanisms of NAD+ metabolism in glioma are unclear and there were no systematic researches about NAD+ metabolism related genes to predict the survival of patients with glioma.

Methods

The research was performed based on expression data of glioma cases in the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Firstly, TCGA-glioma cases were classified into different subtypes based on 49 NAD+ metabolism-related genes (NMRGs) by consensus clustering. NAD+ metabolism-related differentially expressed genes (NMR-DEGs) were gotten by intersecting the 49 NMRGs and differentially expressed genes (DEGs) between normal and glioma samples. Then a risk model was built by Cox analysis and the least shrinkage and selection operator (LASSO) regression analysis. The validity of the model was verified by survival curves and receiver operating characteristic (ROC) curves. In addition, independent prognostic analysis of the risk model was performed by Cox analysis. Then, we also identified different immune cells, HLA family genes and immune checkpoints between high and low risk groups. Finally, the functions of model genes at single-cell level were also explored.

Results

Consensus clustering classified glioma patients into two subtypes, and the overall survival (OS) of the two subtypes differed. A total of 11 NAD+ metabolism-related differentially expressed genes (NMR-DEGs) were screened by overlapping 5,995 differentially expressed genes (DEGs) and 49 NAD+ metabolism-related genes (NMRGs). Next, four model genes, PARP9, BST1, NMNAT2, and CD38, were obtained by Cox regression and least absolute shrinkage and selection operator (Lasso) regression analyses and to construct a risk model. The OS of high-risk group was lower. And the area under curves (AUCs) of Receiver operating characteristic (ROC) curves were >0.7 at 1, 3, and 5 years. Cox analysis showed that age, grade G3, grade G4, IDH status, ATRX status, BCR status, and risk Scores were reliable independent prognostic factors. In addition, three different immune cells, Mast cells activated, NK cells activated and B cells naive, 24 different HLA family genes, such as HLA-DPA1 and HLA-H, and 8 different immune checkpoints, such as ICOS, LAG3, and CD274, were found between the high and low risk groups. The model genes were significantly relevant with proliferation, cell differentiation, and apoptosis.

Conclusion

The four genes, PARP9, BST1, NMNAT2, and CD38, might be important molecular biomarkers and therapeutic targets for glioma patients.

Frequency and burden of potentially treatable symptoms in glioma patients with stable disease

Background & aims

Glioma patients experience a multitude of symptoms that negatively affect their health-related quality of life. Symptoms vary greatly across disease phases, and the patients' stable phase might be particularly suitable for assessing and treating symptoms. Identifying symptoms and patients' needs is a first step toward improving patient care. In glioma patients with stable disease, we assessed the frequency and burden of patient-reported symptoms, examined how these symptoms co-occur, and also determined whether patients would consider treatment to ameliorate specific symptoms.

Methods

In this retrospective study, patients rated the frequency and burden of seventeen symptoms on a seven-point Likert scale and stated whether they would consider treatment for these symptoms. Correlations between frequency, burden, and considering treatment were evaluated with Kendall's Tau correlation coefficients. Based on partial correlations between symptom frequencies we visualized the symptoms as a network.

Results

Fifty-two glioma patients with stable disease were included (31 WHO grade II/III, 21 WHO grade IV). The top five symptoms were fatigue, memory problems, reduced physical fitness, concentration problems, and drowsiness. Fatigue had the highest median frequency (4.5, interquartile range 2.5). Over half of the patients experienced three or more symptoms simultaneously and associations between all symptoms were depicted as a network. Overall, 35% of patients would consider treatment for at least one symptom. The wish to undergo symptom treatment correlated only moderately with symptom frequency and burden (range of correlations 0.24-0.57 and 0.28-0.61, respectively).

Conclusion

Glioma patients with stable disease experience multiple symptoms with a consequently high symptom burden. Despite the high prevalence of symptoms, the inclination for symptom management interventions was relatively low. The most frequent and burdensome symptoms and the way they are interrelated could serve as a roadmap for future research on symptom management in these patients.

Risk factors, prognostic potency, and longitudinal variation of anxiety and depression in postoperative glioma patients

Objective

Anxiety and depression are common mental disorders in glioma patients. This study aimed to evaluate the risk factors, prognostic role, and longitudinal changes in anxiety and depression in postoperative glioma patients.

Methods

Anxiety and depression were assessed by Hospital Anxiety and Depression Scale at baseline, month (M) 6, M12, M24 and M36 in 270 glioma patients after surgical resection. Furthermore, comprehensive clinic characteristics and treatment-related information were collected.

Results

Gender (female vs. male) (P = 0.014, odds ratio (OR) = 1.974), marital status (single/divorced/widowed vs. married) (P = 0.019, OR = 2.172), Karnofsky performance status (KPS) score (≤70 vs. > 70) (P = 0.002, OR = 2.556), World Health Organization (WHO) classification (high-grade glioma (HGG) vs. low-grade glioma (LGG)) (P = 0.005, OR = 2.155), and postoperative complications (yes vs. not) (P = 0.001, OR = 2.525) were independently related to anxiety occurrence. Marital status (single/divorced/widowed vs. married) (P = 0.034, OR = 2.026), KPS score (≤70 vs. > 70) (P < 0.001, OR = 3.880), WHO classification (HGG vs. LGG) (P = 0.032, OR = 1.810), and postoperative complications (yes vs. not) (P = 0.001, OR = 2.602) were independently related to depression occurrence. Besides, anxiety (P = 0.038) and depression (P = 0.013) were linked with shorter overall survival (OS), and depression was an independent risk factor for worse OS (P = 0.040, hazard ratio = 1.596). More importantly, anxiety and depression remained at a high prevalence during a 3-year follow-up.

Conclusion

Gender, marital status, KPS score, WHO classification, and postoperative complications are risk factors for anxiety and depression; moreover, anxiety and depression are at high prevalence continuously and correlated with worse survival in postoperative glioma patients.

Biomimetic Nanosonosensitizers Combined with Noninvasive Ultrasound Actuation to Reverse Drug Resistance and Sonodynamic-Enhanced Chemotherapy against Orthotopic Glioblastoma

Glioblastoma (GBM) is the most devastating brain tumor and highly resistant to conventional chemotherapy. Herein, we introduce biomimetic nanosonosensitizer systems (MDNPs) combined with noninvasive ultrasound (US) actuation for orthotopic GBM-targeted delivery and sonodynamic-enhanced chemotherapy. MDNPs were fabricated with biodegradable and pH-sensitive polyglutamic acid (PGA) and the chemotherapeutic agent and sonosensitizer doxorubicin (DOX), camouflaged with human GBM U87 cell membranes. MDNPs presented homologous targeting accumulation and in vivo long-term circulation ability. They effectively passed through the blood-brain barrier (BBB) under US assistance and reached the orthotopic GBM site. MDNPs exhibited controllable US-elicited sonodynamic effect by generation of reactive oxygen species (ROS). ROS not only induced cancer cell apoptosis but also downregulated drug-resistance-related factors to disrupt chemoresistance and increase sensitivity to chemotherapy. The in vivo study of orthotopic GBM treatments further proved that MDNPs exhibited US-augmented synergistic antitumor efficacy and strongly prolonged the survival rate of mice. The use of low-dose DOX and the safety of US enabled repeated treatment (4 times) without obvious cardiotoxicity. This effective and safe US-enhanced chemotherapy strategy with the advantages of noninvasive brain delivery and high drug sensitivity holds great promise for deep-seated and drug-resistant tumors.

URB2 as an important marker for glioma prognosis and immunotherapy

Introduction: Glioma is the most common primary brain tumor and primary malignant tumor of the brain in clinical practice. Conventional treatment has not significantly altered the prognosis of patients with glioma. As research into immunotherapy continues, glioma immunotherapy has shown great potential. Methods: The clinical data were acquired from the Chinese Glioma Genome Atlas (CGGA) database and validated by the Gene Expression Omnibus (GEO) database, The Cancer Genome Atlas (TCGA) dataset, Clinical Proteomic Tumor Analysis Consortium (CPTAP) database, and Western blot (WB) analysis. By Cox regression analyses, we examined the association between different variables and overall survival (OS) and its potential as an independent prognostic factor. By constructing a nomogram that incorporates both clinicopathological variables and the expression of URB2, we provide a model for the prediction of prognosis. Moreover, we explored the relationship between immunity and URB2 and elucidated its underlying mechanism of action. Results: Our study shows that URB2 likely plays an oncogenic role in glioma and confirms that URB2 is a prognostic independent risk factor for glioma. Furthermore, we revealed a close relationship between immunity and URB2, which suggests a new approach for the immunotherapy of glioma. Conclusion: URB2 can be used for prognosis prediction and immunotherapy of glioma.