To examine whether MRI with routine gadolinium-based contrast agent (GBCA) administration in the long-term surveillance of adult-type diffuse glioma identifies tumour progression earlier than T2-weighted (T2w) and/or T2w fluid-attenuated inversion recovery (FLAIR) MRI only.

In this longitudinal retrospective multicentre cohort study patients with histopathologically confirmed adult-type diffuse glioma and at least two years survival after diagnosis in 2009-2010 were included. Progression was determined by the treating physician or during the multidisciplinary team meeting and defined as the moment a change in treatment or follow-up was required. The primary outcome was the proportion of patients that showed an increase of abnormalities on both contrast-enhanced T1-weighted (CET1w) and T2w/T2w-FLAIR at the time of progression. Chi-square testing was performed to analyse the relationship between the detection of progression on both scan sequences, with calculating the Phi coefficient to determine the degree of association.

One hundred eight consecutive patients were included (58 male; 53 grade 2, 21 grade 3, 34 grade 4). Progression was present in 82 patients and was determined on both CET1w and T2w/T2w-FLAIR images in 59 patients (72.0%). In 20 patients (24.4%), progression was determined based solely on T2w/T2w-FLAIR abnormalities. Only three patients showed progression exclusively on CET1w (3.7%). There was a strong positive significant relationship between the detection of progression on both scan types (p < 0.001; Phi = 0.467).

An increase in CET1w abnormalities was generally accompanied by an increase in T2w/T2w-FLAIR abnormalities, raising the question of whether routine administration of GBCA is always necessary for long-term survivors of glioma.

Question Long-term survivors with glioma undergo many contrast-enhanced MRI scans, which involve a patient, financial, and environmental burden. Findings In almost all patients, an increase in T2w/T2w-FLAIR abnormalities was present at the time of tumour progression, mostly but not always accompanying contrast-enhancing findings. Clinical relevance T2w/T2-FLAIR MRI seems to detect glioma progression in long-term surviving patients similar to contrast-enhanced T1w MRI, raising the question of whether the routine administration of GBCA is necessary and justified in patients under long-term surveillance of glioma.

Brain tumor segmentation is critical in medical imaging due to its significance in accurate diagnosis and treatment planning. Deep learning (DL) methods, particularly the U-Net architecture, have demonstrated considerable promise. However, optimizing U-Net variants to enhance performance and computational efficiency remains challenging.

To develop an optimized Residual U-Net (Res-UNET) architecture enhanced by deep supervision techniques to improve segmentation accuracy of brain tumors on MRI datasets, specifically addressing challenges of conventional segmentation methods.

The study implemented a detailed evaluation of multiple U-Net variations, including basic U-Net, Res-UNet with Autoencoder regularization, and attention-enhanced U-Net architectures. Training was conducted using the BraTS 2018 public MRI dataset. Deep supervision was integrated to improve gradient propagation and segmentation accuracy. The model employed a Dice loss combined with focal loss to handle data imbalance effectively. The proposed network was evaluated using extensive ablation studies, examining the effects of encoder complexity, convolutional filter count, and strategic post-processing.

The proposed Res-UNET with deep supervision outperformed other variants, achieving an average Dice score of 0.9498 through five-fold cross-validation. Post-processing strategies improved the robustness of segmentation, particularly enhancing the accuracy of small tumor regions. Comparatively, conventional U-Net architectures yielded lower Dice scores and required significantly longer training times. The study indicates the benefit of integrating deep supervision and residual connections for enhanced model performance.

Optimized Res-UNET with deep supervision significantly enhances segmentation accuracy for brain tumors in MRI images, surpassing traditional U-Net models. This model addresses critical issues such as dataset imbalance, lack of annotated data, and computational inefficiencies. Future studies should consider the broader application of optimized U-Net variants across other medical imaging segmentation tasks.

Dysregulated fatty acid metabolism is a key contributor to poor prognosis in glioma, and targeting cholesterol metabolism represents a promising therapeutic strategy. Apolipoprotein L4 (APOL4), a member of the Apolipoprotein L family, has been implicated in lipid metabolism, but its role in glioma remains unclear.

RNA-sequencing were performed to analysis gene expression under exogenous cholesterol treatment. Comprehensive bioinformatics analyses were performed using CGGA datasets to evaluate APOL4 expression, clinical correlations, and prognostic significance in GBM. In vitro experiments, including CRISPR-Cas9 mediated APOL4 knockdown, MTT assays, wound healing assays and immunofluorescence were performed to validate the oncogenic role of APOL4. Xenograft mouse models were employed to validate tumor growth in vivo.

RNA-sequencing showed that exogenous cholesterol upregulated the expression of APOL4 in U-87 cells. Clinical database analysis revealed that APOL4 was significantly upregulated in human glioblastoma. Genetic depletion of APOL4 markedly suppressed glioblastoma cell proliferation in vitro and impaired xenograft tumor growth in vivo. Furthermore, APOL4 localized to late endosomes and lysosomes, where it likely facilitated the cytoplasmic transport of exogenous cholesterol, supporting tumor cell growth.

Our study identifies APOL4 as a novel regulator of cholesterol trafficking in glioma cells, promoting glioblastoma progression. These findings highlight APOL4 as a potential therapeutic target for glioma treatment.

Global comparisons of the burden and impact of cancers of the brain and central nervous system (CNS) are critical for developing effective control strategies and generating etiological hypotheses to drive future research.

National incidence estimates were obtained from GLOBOCAN 2022, and recorded incidence data from the Cancer in Five Continents series, both developed and compiled by the International Agency for Research on Cancer. We examined the estimated age-standardized incidence rates in 185 countries, as well as time trends in recorded incidence in 35 countries, quantifying the direction and change in the magnitude of the rates using the estimated average percentage change (EAPC).

In 2022, 322,000 new cases of brain and CNS tumors were estimated globally. By world region, the highest incidence rate was seen in Northern America (5.46 per 100,000), Eastern Asia (3.95), and Western Europe (5.56). Africa had relatively lower incidence rates. By country and age group, Austria and the U.S. exhibited the highest rates in boys (3.5 in both), while in adolescents and young adults (AYA), Norway had the highest incidence rates in both males (4.7) and females (3.8). Among adults (+ 40yo), the highest rates in males were observed in the Northern European countries of Norway (18.6), Lithuania (18.4), and Latvia (16.7). In terms of time trends, incidence rates tended to be rather stable in most world regions over the last decade, though increases were observed in selected countries. Trends-based predictions indicate that if incidence rates remain stable, population ageing and growth would mean there would be 474,000 new cases by the year 2045, a 47% increase from 2022.

While the increased incidence rates in certain populations require further study, the future predictions based on stable rates to 2045 are of particular concern, with a close to 50% increase in the number of brain and CNS cancer patients expected over the coming decades. A global 2% decline in rates would be needed to ensure the future brain and CNS cancer burden does not exceed present levels.

IDH-mutant astrocytomas exhibit a more indolent natural history and better prognosis compared to their IDH-wild type counterparts. WHO 2021 classification integrated CDKN2A/B homozygous deletion as a crucial criterion for grading these tumors, emphasizing its prognostic implications. FISH assay is commonly used to assess CDKN2A status, but guidelines for interpreting FISH results for glioma prognostication are not well-defined in the literature. We conducted an ambispective study involving 22 cases of recurrent IDH-mutant astrocytomas, including primary tumor samples. Histopathological assessments, including WHO grading and molecular profiling, were performed. Immunohistochemistry confirmed IDH mutation status, and FISH analysis evaluated CDKN2A homozygous deletion. Homozygous CDKN2A deletion was detected in only 1/22 (4.8%) of primary tumors, which was grade 3 astrocytoma, and significantly more frequent in recurrent cases, particularly in histological grade 2/3 tumors (35.3%). Patients harboring CDKN2A deletions exhibited significantly poorer overall survival, highlighting its prognostic significance. Our findings highlight the clinical relevance of CDKN2A assessment in recurrent IDH-mutant astrocytomas and its utility as a prognostic marker. We propose a selective approach to FISH testing, focusing on primary grade 3 and all recurrent cases, regardless of histology grade, to optimize diagnostic accuracy and stratification for personalized treatment strategies.

SEPN1, a selenoprotein involved in redox regulation and endoplasmic reticulum stress response, has an unclear role in cancer. This study aims to investigate the expression, prognostic significance, and tumor microenvironment (TME) relevance of SEPN1 across pan-cancer, with a particular focus on glioma.

We analyzed SEPN1 expression and prognosis using the TCGA pan-cancer cohort. SEPN1 in glioma was further examined using data from TCGA, CGGA, GEO, and ZN-GC cohorts, along with survival analysis, single-cell RNA sequencing analysis, and enrichment analysis. We developed an SEPN1-related risk score (SRS) based on SEPN1-related long non-coding RNAs and validated its prognostic value. Drug sensitivity data and connectivity map analysis identified potential anti-glioma drugs based on the SRS.

We found that SEPN1 was significantly upregulated in glioma, associated with poor prognosis, functioned as an independent risk factor, and predominantly expressed in malignant glioma cells. Enrichment analysis indicated the involvement of SEPN1 in immune-related processes and signaling pathways. Suppressing SEPN1 in glioblastoma cells inhibited proliferation and induced G2/M arrest and apoptosis. The SRS demonstrated strong prognostic value and correlated with enhanced immune infiltration in the glioma TME. Potential anti-glioma drugs were identified based on the SRS.

SEPN1 emerges as a novel biomarker and therapeutic target in glioma, providing a basis for future development of targeted therapies.

Many patients with a malignant (i.e., grade II-IV) glioma are of working age, yet they are rarely included in "cancer and work" studies. Here, we explored (1) the work-related experiences and unmet needs of patients with a malignant glioma and (2) the experiences and needs of relevant healthcare and occupational (health) professionals ("professionals") in providing work-related support to this patient group.

Individual semi-structured interviews were held with patients with a malignant glioma who were of working age and had an employment contract at diagnosis, and relevant professionals. Interviews were transcribed verbatim and analysed thematically.

Patients (n = 22) were on average 46 ± 13 years of age (64% male) and diagnosed with a grade II (n = 12), III (n = 4), or IV glioma (n = 6). Professionals (n = 16) had on average 15 ± 9 years of relevant work experience with the patient group. Four themes emerged from the data: (1) having a malignant glioma: experienced consequences on work ability, (2) communicating about the consequences of a malignant glioma at work, (3) distilling the right approach: generic or tailored work-related support, and (4) accessibility of work-related support.

Glioma-specific consequences on patients' work ability necessitate better communication between, and tailored guidance for, patients, relevant professionals, and the workplace. Suggestions for improvement, e.g., the periodic use of comprehensive neuropsychological assessments, are provided in the article.

Patients with a malignant glioma would benefit from tailored and proactive outreach about work-related issues bv relevant professionals.

Genetic variants associated with molecular traits that are also associated with liability to glioma can provide causal evidence for the identification and prioritisation of drug targets.

We performed comprehensive two-sample Mendelian randomisation (Wald ratio and/or IVW) and colocalisation analyses of molecular traits on glioma. Instrumentable traits (QTLs P < 5 × 10-8) were identified amongst 11 985 gene expression measures, 13 285 splicing isoforms and 10 198 protein abundance measures, derived from 15 brain regions. Glioma summary-level data was extracted from a genome-wide association meta-analysis of 12 496 cases and 18 190 controls.

We found evidence for causal effect of 22 molecular traits (across 18 genes/proteins) on glioma risk. Thirteen molecular traits have been previously linked with glioma risk and five were novel; HBEGF (5q31.3) expression and all glioma [OR 1.36 (95%CI 1.19-1.55); P = 4.41 × 10-6]; a CEP192 (18p11.21) splice isoform and glioblastoma [OR 4.40 (95%CI 2.28-8.48); P = 9.78 × 10-4]; a FAIM (3q22.3) splice isoform and all glioma [OR 2.72-3.43; P = 1.03 × 10-5 to 1.09 × 10-5]; a SLC8A1 (2p22.1) splice isoform and all glioma [OR 0.37 (95%CI 0.24-0.56; P = 5.72 × 10-6]; D2HGDH (2q37.3) protein and all glioma [OR 0.86 (95%CI 0.80-0.92); P = 5.94 × 10-6)].

We provide robust causal evidence for prioritising genes and their protein products in glioma research. Our results highlight the importance of alternative splicing as a mechanism in gliomagenesis and as an avenue for exploration of drug targets.

Background/Objectives: The methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) promoter in gliomas has emerged as a critical biomarker for prognosis and treatment response. Conventional methods for assessing MGMT promoter methylation, such as methylation-specific PCR, are invasive and require tissue sampling. Methods: A comprehensive literature search was performed in compliance with the updated PRISMA 2020 guidelines within electronic databases MEDLINE/PubMed, Scopus, and IEEE Xplore. Search terms, including "MGMT", "methylation", "glioma", "glioblastoma", "machine learning", "deep learning", and "radiomics", were adopted in various MeSH combinations. Original studies in the English, Italian, German, and French languages were considered for inclusion. Results: This review analyzed 34 studies conducted in the last six years, focusing on assessing MGMT methylation status using radiomics (RD), deep learning (DL), or combined approaches. These studies utilized radiological data from the public (e.g., BraTS, TCGA) and private institutional datasets. Sixteen studies focused exclusively on glioblastoma (GBM), while others included low- and high-grade gliomas. Twenty-seven studies reported diagnostic accuracy, with fourteen achieving values above 80%. The combined use of DL and RD generally resulted in higher accuracy, sensitivity, and specificity, although some studies reported lower minimum accuracy compared to studies using a single model. Conclusions: The integration of RD and DL offers a powerful, non-invasive tool for precisely recognizing MGMT promoter methylation status in gliomas, paving the way for enhanced personalized medicine in neuro-oncology. The heterogeneity of study populations, data sources, and methodologies reflected the complexity of the pipeline and machine learning algorithms, which may require general standardization to be implemented in clinical practice.

Gliomas are the most common primary tumors of the nervous system, which is generally treated using adjuvant chemotherapy following surgical resection. However, patient survival time is still short, and there is currently no successful treatment for highly malignant gliomas. Bullatine A (BLA) is a diterpenoid alkaloid of the genus Aconitum which antirheumatic and anti-inflammatory pharmacological properties. The effects of BLA on gliomas have not yet been elucidated. In this study, we investigated the effects of BLA on human brain malignant glioblastoma cells. Our results showed that BLA inhibited the proliferation of U87MG and U251 cells in a dose-dependent manner and decreased their survival rate. BLA dose-dependently induced apoptosis in U87MG cells, upregulated the expression of cleaved caspase-9, cleaved caspase-3 pro-apoptotic protein, and Bax protein, and downregulated the expression of Bcl-2 anti-apoptotic protein. Moreover, BLA dose-dependently induced U87MG and U251 cell cycle arrest in the G2/M phase, and downregulated the expression of p-ERK and Myc proteins. Further, BLA significantly inhibited the acetylation of histones H3K9 and H3K56, and upregulated the expression of the protein deacetylase SIRT6. Mechanistic studies revealed that the effect of BLA on inducing apoptosis and inhibiting the proliferation of glioma cells was blocked by SIRT6 knockout. In summary, our study indicated that BLA is a potential therapeutic agent for glioma that targets SIRT6 to inhibit glioma cell proliferation and induce apoptosis.

The presence of specific genetic mutations in patients with glioblastoma multiforme (GBM) is associated with improved survival outcomes. Disruption of the DNA damage response (DDR) pathway in tumor cells enhances the effectiveness of radiotherapy drugs, while increased mutational burden following tumor cell damage also facilitates the efficacy of immunotherapy. The ATRX gene, located on chromosome X, plays a crucial role in DDR. The aim of this research is to elucidate the correlation between ATRX mutations and GBM. Dataset obtained from TCGA-GBM were conducted an analysis on the genomic features, biological characteristics, immunopathological markers, and clinical prognosis of patients carrying ATRX mutations. Our findings revealed a significantly elevated level of microsatellite instability in individuals with ATRX mutants, along with significant alterations in the receptor-tyrosine kinase (RTK)-ras pathway among patients exhibiting combined ATRX mutations. TCGA-GBM patients with concurrent ATRX mutations exhibited sensitivity to 26 chemotherapeutic and anticancer drugs, which exerted their effects by modulating the DDR of tumor cells through highly correlated mechanisms involving the RTK-ras pathway. Additionally, we observed an enrichment of ATRX mutations in specific pathways associated with DDR among TCGA-GBM patients. Our model also demonstrated prolonged overall survival in patients carrying ATRX mutations, particularly showing strong predictive value for 3- and 5-year survival rates. Furthermore, additional protective factors such as younger age, female gender, combined IDH mutations, and TP53 mutations were identified. The results underscore the protective role and prognostic significance of ATRX mutations in GBM as a potential therapeutic target and biomarker for patient survival.

Glioma is a malignant primary brain tumor with a poor prognosis and short survival. NAD+ is critical for cancer growth; however, clinical trials targeting NAD+ biosynthesis had limited success, indicating the need for mechanistic characterization. Nuclear atypia, aberrations in the size and shape of the nucleus, is widely observed in cancer and is often considered a distinctive feature in diagnosis; however, the molecular underpinnings are unclear.

We carried out high-resolution immunohistochemical analyses on glioma tissue samples from 19 patients to analyze the expression of NAD+ synthase nicotinamide mononucleotide adenylyltransferase 1 (NMNAT1), and its correlation with nuclear atypia in gliomas. Utilizing a Drosophila model of glial neoplasia, we investigated the genetic role of nuclear NMNAT in glioma growth in vivo, elucidating the cellular mechanisms of NMNAT1 in promoting nuclear atypia and glioma growth.

In low-grade glioma and glioblastoma, a higher transcription level of NMNAT1 is correlated with poorer disease-free survival. Samples of high-grade gliomas contained a higher percentage of glial cells enriched with NMNAT1 protein. We identified a specific correlation between nuclear NMNAT1 protein level with nuclear atypia. Mechanistic studies in human glioma cell lines and in vivo Drosophila model suggest that NMNAT1 disrupts the integrity of the nuclear lamina by altering the distribution of lamin A/C and promotes glioma growth.

Our study uncovers a novel functional connection between the NAD+ metabolic pathway and glioma growth, reveals the contribution of the NAD+ biosynthetic enzyme NMNAT1 to nuclear atypia, and underscores the role of nuclear NMNAT1 in exacerbating glioma pathology.

Two undescribed isoquinolines (1-2), including one undescribed carbon skeleton isoquinoline together with six known ones (4-9) as well as an undescribed amide (3) and three known ones (10-12) were isolated from C. tomentella. Their planar structures and absolute configurations were elucidated by extensive analyses of UV, NMR, HRESIMS, DP4+ statistical analysis and ECD calculations, respectively. Tomentediline A (1) is an isoquinoline alkaloid dimer that forms an undescribed carbon carbon bond at the C-13 position of (2H)-protoberberine in a natural product discovered for the first time. Meantime, 1 exerted moderate cytotoxicity against the U251 cell lines, indicating that the undescribed dimer skeleton of isoquinoline compound has the potential for anti-glioma.

Glioblastoma (GB) is the most aggressive and frequent tumor in the central nervous system and, in humans, represents the worst prognosis for cancer. GB develops a very complex microenvironment, recruiting and interacting with a variety of cells and soluble factors, including immune cells, cytokines, and sex hormones, that contribute to GB survival and progression. Recent evidence has shown a crosstalk between cytokine and sex hormone signaling in GB. This communication could provide GB resistance to treatments and malignancy. Then, how GB orchestrates this communication is a matter of interest. For instance, a critical interaction between tumor necrosis factor-beta (TGF-β) and estrogen receptor signaling has been reported in regulating epithelial-mesenchymal transition, an essential step in GB progression. Furthermore, an inhibition of TGF-β signaling by androgen receptor has been reported to promote GB tumorigenesis in men. Conversely, it has been described that cytokines regulate steroid hormone production in different organs, and this mechanism could be involved in GB development and progression. All these data suggest an intercommunication between the immune and endocrine systems in the tumor microenvironment. Thus, in this review, we focus on explaining the knowledge about this critical intercommunication system and its implication in GB progression.

Glioblastoma (GBM) is a highly aggressive primary brain tumor with limited treatment success and poor prognosis. Despite surgical resection and adjuvant therapies, GBM often recurs, and resistance to radiotherapy and temozolomide presents significant challenges. This study aimed to elucidate molecular signatures associated with treatment responses, identify potential biomarkers, and enhance personalized treatment strategies for GBM.

We conducted a comprehensive analysis using the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The GEO dataset (GSE206225) was used to identify differentially expressed genes (DEGs) between radiation-sensitive/resistant and temozolomide-sensitive/resistant GBM samples. TCGA data were utilized for subsequent analyses, including Lasso-Cox regression, risk score model construction, Kaplan-Meier survival analysis, and gene set enrichment analysis (GSEA). Hub genes were identified through survival analysis, and a gene prognostic nomogram was developed. Additionally, validation of the three-gene risk signature through multiple external cohorts and validation of protein expression levels were performed.

DEG analysis identified 111 genes associated with chemoradiotherapy resistance, providing insights into the complex landscape of GBM treatment response. The risk score model effectively stratified patients, showing significant differences in overall survival and progression-free survival. GSEA offered a deeper understanding of pathway activities, emphasizing the intricate molecular mechanisms involved. NNAT, IGFBP6, and CYGB were identified as hub genes, and a gene prognostic nomogram demonstrated predictive accuracy.

This study sheds light on the molecular intricacies governing GBM treatment response. The identified hub genes and the gene prognostic nomogram offer valuable tools for predicting patient outcomes and guiding personalized treatment strategies. These findings contribute to advancing our understanding of GBM biology and may pave the way for improved clinical management.

Glioma is the most common type of brain cancer, associated with a high mortality rate. Diet is one of the most modifiable factors that can influence the risk of various cancers, including glioma. While the relationship between diet and glioma has been explored in recent years, the number of studies in this area remains limited, and the findings are often controversial. Moreover, all existing studies are observational, which means they may be influenced by a range of confounding variables. In this mini-review, we aim to provide a comprehensive and informative overview of the dietary recommendations related to glioma that have been published to date.

Research suggests that adherence to healthy dietary patterns-such as the Mediterranean diet, Dietary Approaches to Stop Hypertension (DASH) diet, Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet, Paleolithic diet, high-protein dietary patterns, and vegetarian dietary patterns-may be associated with a reduced risk of glioma. These diets are rich in phytochemicals and antioxidants. Additionally, certain food groups, including fruits, vegetables, legumes, nuts, eggs, fresh fish, tea, and coffee, are emphasized for their protective effects against glioma. Conversely, adherence to unhealthy dietary patterns, such as the Western diet, or diets with high inflammatory potential, glycemic and insulinemic loads, and high consumption of grains (especially refined grains), processed meats, and processed fish, has been linked to an increased risk of glioma. Current studies suggest that following a healthy diet may reduce the odds of developing glioma. However, due to the limited number of studies and the observational nature of the existing research, further investigations with more robust designs, such as randomized controlled trials, are needed to clarify these associations.

Patients with glioma often fail to achieve satisfactory outcomes despite receiving surgery, radiotherapy, and chemotherapy. Photodynamic therapy (PDT) shows promise in addressing the limitations of traditional treatments. However, the immunological effects of PDT in glioma patients remain underexplored. This study aims to fill this gap by analyzing lymphocyte subpopulations and inflammatory markers in glioma patients undergoing PDT-assisted surgery.

To enhance our comprehension of the immunobiology of glioma within a clinical framework, we conducted a retrospective analysis of glioma patients from September 2019 to December 2023. Peripheral blood lymphocyte subpopulations (CD3+, CD19+, CD4+, CD8+, CD4+/CD8+) and hematological inflammatory factors were compared among 18 patients who underwent surgery with PDT, 10 patients treated with surgery alone, and healthy controls. Additionally, lymphocyte subpopulations from 48 healthy individuals and hematology inflammatory factors from 38 healthy controls were regarded as controls.

PDT-assisted surgery resulted in significant alterations in lymphocyte subpopulations and inflammatory markers before and after treatment, particularly in CD4+ and CD8+ T cells. PDT-treated patients demonstrated a superior therapeutic response compared to surgery alone (P=0.035). Notably, primary glioma patients had more prolonged overall survival than recurrent glioma patients (P=0.039).

PDT-assisted surgery significantly affects lymphocyte subpopulations and inflammatory markers, enhancing immune response in glioma patients. These findings support the use of PDT as an effective adjuvant therapy. Monitoring lymphocyte subpopulations and inflammatory markers may be valuable for glioma prognosis and treatment optimization.

Brain surgery is a widely practised and effective treatment for brain tumours, but accurately identifying and classifying tumour boundaries is crucial to maximise resection and avoid neurological complications. This precision in classification is essential for guiding surgical decisions and subsequent treatment planning. Hyperspectral (HS) imaging (HSI) is an emerging multidimensional optical imaging method that captures detailed spectral information across multiple wavelengths, allowing for the identification of nuanced differences in tissue composition, with the potential to enhance intraoperative tissue classification. However, current frameworks often require retraining models for each HSI to extract meaningful features, resulting in long processing times and high computational costs. Additionally, most methods utilise the deep semantic features at the end of the network for classification, ignoring the spatial details contained in the shallow features. To overcome these challenges, we propose a novel approach called MedDiffHSI, which combines diffusion and transformer techniques. Our method involves training an unsupervised learning framework based on the diffusion model to extract high-level and low-level spectral-spatial features from HSI. This approach eliminates the need for retraining of spectral-spatial feature learning model, thereby reducing time complexity. We then extract intermediate multistage features from different timestamps for classification using a pretrained denoising U-Net. To fully explore and exploit the rich contextual semantics and textual information hidden in the extracted diffusion feature, we utilise a spectral-spatial attention module. This module not only learns multistage information about features at different depths, but also extracts and enhances effective information from them. Finally, we employ a supervised transformer-based classifier with weighted majority voting (WMV) to perform the HSI classification. To validate our approach, we conduct comprehensive experiments on in vivo brain database data sets and also extend the analysis to include additional HSI data sets for breast cancer to evaluate the framework performance across different types of tissue. The results demonstrate that our framework outperforms existing approaches by using minimal training samples (5%) while achieving state-of-the-art performance.

Background/Objectives: Targeted delivery of chemotherapeutic agents is a well-established approach to cancer therapy. Antibody-drug conjugates (ADCs) typically carry toxic payloads attached to a tumor-associated antigen-targeting IgG antibody via an enzyme-cleavable linker that releases the drug inside the cell. Aptamers are a promising alternative to antibodies in terms of antigen targeting; however, their polynucleotide nature and smaller size result in a completely different PK/PD profile compared to an IgG. This may prove advantageous: owing to their lower molecular weight, aptamer-drug conjugates may achieve better penetration of solid tumors compared to ADCs. Methods: On the way to therapeutic aptamer-drug conjugates, we aimed to develop a versatile and modular approach for the assembly of aptamer-enzymatically cleavable payload conjugates of various drug-aptamer ratios. We chose the epidermal growth factor receptor (EGFR), a transmembrane protein often overexpressed in brain tumors, as the target antigen. We used the 46 mer EGFR-targeting DNA sequence GR-20, monomethylauristatin E (MMAE) on the cathepsin-cleavable ValCit-p-aminobenzylcarbamate linker as the payload, and pentaerythritol-based tetraazide as the branching point for the straightforward synthesis of aptamer-drug conjugates by means of a stepwise Cu-catalyzed azide-alkyne cycloaddition (CuAAC) click reaction. Results: Branched aptamer conjugates of 1:3, 2:2, and 3:1 stoichiometry were synthesized and showed higher cytotoxic activity compared to a 1:1 conjugate, particularly on several glioma cell lines. Conclusions: This approach is convenient and potentially applicable to any aptamer sequence, as well as other payloads and cleavable linkers, thus paving the way for future development of aptamer-drug therapeutics by easily providing a range of branched conjugates for in vitro and in vivo testing.

Malignant gliomas exhibit rapid tumor progression and resistance to treatment, leading to high lethality. One of the causes is the reduced progression of apoptosis in glioma cells. Layilin is a type 1 transmembrane protein with a C-type lectin motif in its extracellular domain. We previously reported that layilin is mainly localized to mitochondria or their close proximity and that layilin is essential for maintaining of the fragmented type of mitochondria. This study investigates the effects of layilin on mitochondria-mediated apoptosis, focusing on B cell lymphoma (BCL)-2 family proteins in a glioma cell line of A172 cells.

We compared the levels of pro-apoptotic BCL-2 family proteins of BAD, BAK, BAX, and BIM and anti-apoptotic BCL-2 family proteins of BCL-2 and BCL-XL between layilin- knockdown (KD) cells and control cells using western blot. The protein levels of BAD were significantly smaller in layilin-KD cells than in control cells, while those of BCL-2 were significantly larger. We then compared the mitochondrial membrane potential (ΔΨm) under p-trifluoromethoxyphenyl hydrazone (FCCP)-treated conditions using MT-1 staining. In layilin-KD cells, ΔΨm was significantly larger and FCCP-induced ΔΨm reduction was significantly lower than in control cells. Furthermore, we examined the levels of cell membrane-bound Annexin V and DNA-bound propidium idodide (PI) in layilin-KD cells with/without staurosporine (STS) treatment. Layilin-KD significantly decreased levels of cell membrane-bound Annexin V with/without STS treatment. On the other hand, PI levels were not changed by layilin-KD. We also investigated the amounts of the active caspase (CASP)-3, CASP-6, CASP-7, and poly (ADP-ribose) polymerase-1 (PARP1, cleaved form), as well as DNA fragmentation in layilin-KD cells under apoptotic conditions induced by STS, using western blot and the DNA ladder method, respectively. Under STS-treated conditions, the amounts of active CASP-3, CASP-7, and poly (ADP-ribose) PARP1 were significantly smaller in layilin-KD cells than in control cells. Accordingly, DNA fragmentation was significantly suppressed in layilin-KD cells compared to control cells under STS-treated conditions.

This study demonstrates that layilin contributes to ΔΨm reduction to promote apoptosis by up-regulating BAD and down-regulating BCL-2 in glioma cells. Our data elucidates a new function of layilin: regulation of mitochondria-mediated apoptosis.

Formyl peptide receptor 3 (FPR3) is known to have implications in the progression of various cancer types. Despite this, its biological significance within pan-cancer datasets has yet to be investigated. In this investigation, we scrutinized FPR3's expression profiles, genetic alterations, prognostic significance, immune-related characteristics, methylation status, tumor mutation burden (TMB), and microsatellite instability (MSI) across different types of cancer. We utilized TISCH's single-cell data to identify immune cells closely associated with FPR3. The predictive significance of FPR3 was evaluated independently in gliomas using data from TCGA and CGGA datasets, leading to the development of a prognostic nomogram. Immunohistochemistry and Western blot analysis confirmed FPR3 expression in gliomas. Lastly, the CCK-8 and wound-healing assays were employed to assess the impact of FPR3 on the proliferation and metastasis of GBM cell lines. In numerous cancer types, heightened FPR3 expression correlated with adverse outcomes, immune cell infiltration, immune checkpoints, TMB, and MSI. In glioma, FPR3 emerged as a notable risk factor, with the prognostic model effectively forecasting patient results. The potential biological relevance of FPR3 was confirmed in glioma, and it was shown to have significant involvement in the processes of glioma growth, immune infiltration, and metastasis. Our results imply a potential association of FPR3 with tumor immunity, indicating its viability as a prognostic indicator in glioma.

Gliomas, the predominant form of brain cancer, comprise diverse malignant subtypes with limited curative therapies available. The insufficient understanding of their molecular diversity and evolutionary processes hinders the advancement of new treatments. Technical complexities associated with formalin-fixed paraffin-embedded (FFPE) clinical samples hinder molecular-level analyses of gliomas. Current single-cell RNA sequencing (scRNA-seq) platforms are inadequate for large-scale clinical applications. In this study, automated snRandom-seq is developed, a high-throughput single-nucleus total RNA sequencing platform optimized for archival FFPE samples. This platform integrates automated single-nucleus isolation and droplet barcoding systems with the random primer-based scRNA-seq chemistry, accommodating a broad spectrum of sample types. The automated snRandom-seq is applied to analyze 116 492 single nuclei from 17 FFPE samples of various glioma subtypes, including rare clinical samples and matched primary-recurrent glioblastomas (GBMs). The study provides comprehensive insights into the molecular characteristics of gliomas at the single-cell level. Abundant non-coding RNAs (ncRNAs) with distinct expression profiles across different glioma clusters and uncovered promising recurrence-related targets and pathways in primary-recurrent GBMs are identified. These findings establish automated snRandom-seq as a robust tool for scRNA-seq of FFPE samples, enabling exploration of molecular diversities and tumor evolution. This platform holds significant implications for large-scale integrative and retrospective clinical research.

Malignant gliomas are an exceptionally lethal form of cancer with limited treatment options. Dihydroartemisinin (DHA), a sesquiterpene lactone antimalarial compound, has demonstrated therapeutic effects in various solid tumors. In our study, we aimed to investigate the mechanisms underlying the anticancer effects of DHA in gliomas. To explore the therapeutic and molecular mechanisms of DHA, we employed various assays, including cell viability, flow cytometry, mitochondrial membrane potential, glucose uptake and glioma xenograft models. Our data demonstrated that DHA significantly inhibited glioma cell proliferation in both temozolomide-resistant cells and glioma stem-like cells. We found that DHA-induced apoptosis occurred via the mitochondria-mediated pathway by initiating mitochondrial dysfunction before promoting apoptosis. Moreover, we discovered that DHA treatment substantially reduced the expression of the mitochondrial biogenesis-related gene, ERRα, in glioma cells. And the ERRα pathway is a critical target in treating glioma with DHA. Our results also demonstrated that the combination of DHA and temozolomide synergistically inhibited the proliferation of glioma cells. In vivo, DHA treatment remarkably extended survival time in mice bearing orthotopic glioblastoma xenografts. Thus, our findings suggest that DHA has a novel role in modulating cancer cell metabolism and suppressing glioma progression by activating the ERRα-regulated mitochondrial apoptosis pathway.

Gliomas are the most common primary central nervous system neoplasm. Despite recent advances in the diagnosis and treatment of gliomas, patient prognosis remains dismal. Therefore, it is imperative to identify novel diagnostic biomarkers and therapeutic targets of glioma to effectively improve treatment outcomes.

To investigate the association between oligodendrocyte transcription factor 2 (Olig2) expression and the outcomes of glioma patients.

The PubMed, Embase, Cochrane Library, and China National Knowledge Infrastructure databases were searched for studies (published up to October 2023) that investigated the relationship between Olig2 expression and prognosis of glioma patients. The quality of the studies was assessed using the Newcastle Ottawa Scale. Data analyses were performed using Stata Version 12.0 software.

A total of 1205 glioma patients from six studies were included in the meta-analysis. High Olig2 expression was associated with better outcomes in glioma patients [hazard ratio (HR): 0.81; 95% (confidence interval) CI: 0.51-1.27; P = 0.000]. Furthermore, the results of subgroup meta-analysis showed that high expression of Olig2 was associated with poor overall survival in European patients (HR: 1.34; 95%CI: 0.79-2.27) and better prognosis in Asian patients (HR: 0.43; 95%CI: 0.22-0.84). The sensitivity analysis showed that no single study had a significant effect on pooled HR, and there was also no indication of publication bias according to the Egger's and Begger's P value test or funnel plot test.

High Olig2 expression may have a positive impact on the prognosis of glioma patients, and should be investigated further as a prognostic biomarker and therapeutic target for glioma.

In 2017, the FDA authorized 5-aminolevulinic acid (5-ALA) for intraoperative optical imaging of suspected high-grade gliomas. This was the first authorized optical imaging agent for brain tumor surgery to enhance the visualization of malignant tissue. Herein we report the synthesis of a racemic and enantiopure fluorinated analog of 5-ALA, i.e., 3-fluoro-5-aminolevulinic acid (3F-5-ALA). We anticipate that these studies will provide the foundation for the future construction of a fluorine-18-labeled 5-ALA PET tracer to be used for functional and metabolic imaging of gliomas.

Glioblastoma (GBM), a highly aggressive malignant tumor of the central nervous system, is mainly treated with radiotherapy. However, since irradiation may lead to the acquisition of migration ability by cancer cells, thereby promoting tumor metastasis and invasion, it is important to understand the mechanism of cell migration enhancement in order to prevent recurrence of GBM. The receptor for advanced glycation end products (RAGE) is a pattern recognition receptor activated by high mobility group box 1 (HMGB1). In this study, we found that RAGE plays a role in the enhancement of cell migration by γ-irradiation in human GBM A172 cells. γ-Irradiation induced actin remodeling, a marker of motility acquisition, and enhancement of cell migration in A172 cells. Both phenotypes were suppressed by specific inhibitors of RAGE (FPS-ZM1 and TTP488) or by knockdown of RAGE. The HMGB1 inhibitor ethyl pyruvate similarly suppressed γ-irradiation-induced enhancement of cell migration. In addition, γ-irradiation-induced phosphorylation of STAT3 was suppressed by RAGE inhibitors, and a STAT3 inhibitor suppressed γ-irradiation-induced enhancement of cell migration, indicating that STAT3 is involved in the migration enhancement downstream of RAGE. Our results suggest that HMGB1-RAGE-STAT3 signaling is involved in radiation-induced enhancement of GBM cell migration, and may contribute to GBM recurrence by promoting metastasis and invasion.

Gliomas, comprising nearly 80% of brain malignancies, present a formidable challenge with glioblastomas being the most aggressive subtype. Despite multidisciplinary care, including surgery and chemoradiotherapy, the prognosis remains grim, emphasizing the need for innovative treatment strategies. The blood-brain barrier complicates drug access, and the diverse histopathology hinders targeted therapies. Oncolytic herpes viruses (oHSVs), particularly HSV1716, G207, and rQNestin34.5v, show promise in glioma treatment by selectively replicating in tumor cells. Preclinical and clinical studies demonstrate the safety and efficacy of oHSVs, with T-Vec being FDA-approved. However, challenges like viral delivery limitations and antiviral responses persist. The combination of oHSVs and combining cyclophosphamide (CPA) addresses these challenges, demonstrating increased transgene expression and viral activity. The immunosuppressive properties of CPA, particularly in metronomic schedules, enhance oHSV efficacy, supporting the development of this combination for recurrent malignant gliomas. CPA with oHSVs enhances viral oncolysis and extends survival. CPA's immunomodulatory effects, suppressing regulatory T cells, improve oHSV efficiency. While obstacles remain, this synergistic approach offers hope for improved outcomes, necessitating further research and clinical validation.

Brain tumors are a leading cause of death globally, with numerous types varying in malignancy, and only 12% of adults diagnosed with brain cancer survive beyond five years. This research introduces a hyperparametric convolutional neural network (CNN) model to identify brain tumors, with significant practical implications. By fine-tuning the hyperparameters of the CNN model, we optimize feature extraction and systematically reduce model complexity, thereby enhancing the accuracy of brain tumor diagnosis. The critical hyperparameters include batch size, layer counts, learning rate, activation functions, pooling strategies, padding, and filter size. The hyperparameter-tuned CNN model was trained on three different brain MRI datasets available at Kaggle, producing outstanding performance scores, with an average value of 97% for accuracy, precision, recall, and F1-score. Our optimized model is effective, as demonstrated by our methodical comparisons with state-of-the-art approaches. Our hyperparameter modifications enhanced the model performance and strengthened its capacity for generalization, giving medical practitioners a more accurate and effective tool for making crucial judgments regarding brain tumor diagnosis. Our model is a significant step in the right direction toward trustworthy and accurate medical diagnosis, with practical implications for improving patient outcomes.

Glioma is an aggressive malignant brain tumor with a very poor prognosis for survival. The poor tumor targeting efficiency and tumor microenvironment penetration barrier also as troubles inhibited the effective glioma chemotherapy. Here, we design a core-shell structure cascade amplified hybrid catalytic nanopotentiators CFpAD with DM1 encapsulated to overcome the glioma therapeutic obstacles. NIR laser-based BBB penetrating enhances the tumor accumulation of CFpAD. When CFpAD, as the cascade amplified drug, is treated on the cancer cells, the bomb-like CFpAD releases gold nanoparticles as glucose oxidase (GOx) and ferric oxide nanoparticles (FNPs) as peroxides (POx) after blasting, producing ROS via a cascade amplification for tumor cell apoptosis. Gold nanoparticles can rest CAFs and reduce ECM secretion, achieving deep penetration of CFpAD. Moreover, CFpAD also cuts off the nutritional supply of the tumor, reduces the pH value, and releases free radicals to destroy the cancer. The glioma cell viability was significantly decreased through DNA damage and ROS aggregation due to the DM1-based chemotherapy synergistically combined with interventional photothermal therapy (IPTT) and radiotherapy (RT). This domino cascade amplified loop, combined with starvation therapy with IPTT and RT, has good tumor penetration and outstanding antitumor efficacy, and is a promising glioma treatment system.

The expression dysregulation of microRNAs (miRNA) has been widely reported during cancer development, however, the underling mechanism remains largely unanswered. In the present work, we performed a systematic integrative study for genome-wide DNA methylation, copy number variation and miRNA expression data to identify mechanisms underlying miRNA dysregulation in lower grade glioma. We identify 719 miRNAs whose expression was associated with alterations of copy number variation or promoter methylation. Integrative multi-omics analysis revealed four subtypes with differing prognoses. These glioma subtypes exhibited distinct immune-related characteristics as well as clinical and genetic features. By construction of a miRNA regulatory network, we identified candidate miRNAs associated with immune evasion and response to immunotherapy. Finally, eight prognosis related miRNAs were validated to promote cell migration, invasion and proliferation through in vitro experiments. Our study reveals the crosstalk among DNA methylation, copy number variation and miRNA expression for immune regulation in glioma, and could have important implications for patient stratification and development of biomarkers for immunotherapy approaches.

Gliomas are recognized as the most frequent type of malignancies in the central nervous system, and efficacious prognostic indicators are essential to treat patients with gliomas and improve their clinical outcomes. The chemokine (C-C motif) ligand 2 (CCL2) is a promising predictor for glioma malignancy and progression. However, at present, the methods to evaluate CCL2 expression level are invasive and operator-dependent.

It was expected to noninvasively predict CCL2 expression levels in malignant glioma tissues by magnetic resonance imaging (MRI)-based radiomics and assess the association between the developed radiomics model and prognostic indicators and related genes.

MRI-based radiomics was used to predict CCL2 expression level using data obtained from The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA) databases. A support vector machine (SVM)-based radiomics model and a logistic regression (LR)-based radiomics model were used to predict the radiomics score, and its correlation with CCL2 expression level was analyzed.

The results revealed that there was an association between CCL2 expression level and the overall survival of cases with gliomas, and bioinformatics correlation analysis showed that CCL2 expression level was highly correlated with disease-related pathways, such as mTOR signaling pathway, cGMP-PKG signaling pathway, and MAPK signaling pathway. Both SVM- and LR-based radiomics data robustly predicted CCL2 expression level, and radiomics scores could also be used to predict the overall survival of patients. Moreover, the high/low radiomics scores were highly correlated with the known glioma-related genes, including CD70, CD27, and PDCD1.

An MRI-based radiomics model was successfully developed, and its clinical benefits were confirmed, including the prediction of CCL2 expression level and patients' prognosis.

The fifth edition of the WHO classification of tumors of the central nervous system (WHO CNS5) was published in 2021 which is the sixth version of the international standard for the diagnostics of CNS tumors. Regular updates of the consortium to inform molecular and practical approaches to CNS tumor taxonomy (cIMPACT-NOW) shaped the WHO CNS5 which continues the trend of incorporating the molecular characteristics of tumors into the histological and immunohistochemical findings. The various updates can be classified into general changes across all tumors and specific changes within the tumor groups. This mini-review highlights the general changes and the major changes in adult diffuse gliomas.

The most prevalent primary brain tumors in adults are gliomas. In addition to insufficient therapeutic alternatives, gliomas are fatal mostly due to the rapid proliferation and continuous infiltration of tumor cells into the surrounding healthy brain tissue. According to a growing body of research, aerobic glycolysis, or the Warburg effect, promotes glioma development because gliomas are heterogeneous cancers that undergo metabolic reprogramming. Therefore, addressing the Warburg effect might be a useful therapeutic strategy for treating cancer. Lactate plays a critical role in reprogramming energy metabolism, allowing cells to rapidly access large amounts of energy. Lactate, a byproduct of glycolysis, is therefore present in rapidly proliferating cells and tumors. In addition to the protumorigenesis pathways of lactate synthesis, circulation, and consumption, lactate-induced lactylation has been identified in recent investigations. Lactate plays crucial roles in modulating immune processes, maintaining homeostasis, and promoting metabolic reprogramming in tumors, which are processes regulated by the lactate-induced lactylation of the lysine residues of histones. In this paper, we discuss the discovery and effects of lactylation, review the published studies on how protein lactylation influences cancer growth and further explore novel treatment approaches to achieve improved antitumor effects by targeting lactylation. These findings could lead to a new approach and guidance for improving the prognosis of patients with gliomas.

Glioblastoma (GBM) is the most common and aggressive brain tumor in adults. To identify genes differentially required for the viability of GBM stem-like cells (GSCs), we performed functional genomic lethality screens comparing GSCs and control human neural stem cells. Among top-scoring hits in a subset of GBM cells was the F-box-containing gene FBXO42, which was also predicted to be essential in ∼15% of cell lines derived from a broad range of cancers. Mechanistic studies revealed that, in sensitive cells, FBXO42 activity prevents chromosome alignment defects, mitotic cell cycle arrest and cell death. The cell cycle arrest, but not the cell death, triggered by FBXO42 inactivation could be suppressed by brief exposure to a chemical inhibitor of Mps1, a key spindle assembly checkpoint (SAC) kinase. FBXO42's cancer-essential function requires its F-box and Kelch domains, which are necessary for FBXO42's substrate recognition and targeting by SCF (SKP1-CUL1-F-box protein) ubiquitin ligase complex. However, none of FBXO42's previously proposed targets, including ING4, p53 and RBPJ, were responsible for the observed phenotypes. Instead, our results suggest that FBOX42 alters the activity of one or more proteins that perturb chromosome-microtubule dynamics in cancer cells, which in turn leads to induction of the SAC and cell death.

The tumor microenvironment plays a vital role in glioblastoma growth and invasion. PD-1 and PD-L1 modulate the immunity in the brain tumor microenvironment. However, the underlying mechanisms remain unclear. In the present study, in vivo and in vitro experiments were conducted to reveal the effects of PD-1/PD-L1 on the crosstalk between microglia and glioma. Results showed that glioma cells secreted PD-L1 to the peritumoral areas, particularly microglia containing highly expressed PD-1. In the early stages of glioma, microglia mainly polarized into the pro-inflammatory subtype (M1). Subsequently, the secreted PD-L1 accumulated and bound to PD-1 on microglia, facilitating their polarization toward the microglial anti-inflammatory (M2) subtype primarily via the STAT3 signaling pathway. The role of PD-1/PD-L1 in M2 polarization of microglia was partially due to PD-1/PD-L1 depletion or application of BMS-1166, a novel inhibitor of PD-1/PD-L1. Consistently, co-culturing with microglia promoted glioma cell growth and invasion, and blocking PD-1/PD-L1 significantly suppressed these processes. Our findings reveal that the PD-1/PD-L1 axis engages in the microglial M2 polarization in the glioma microenvironment and promotes tumor growth and invasion.

Glioblastoma (GBM) is a highly aggressive primary malignant brain tumor with a dismal prognosis despite current treatment strategies. Inflammation plays an essential role in GBM pathophysiology, contributing to tumor growth, invasion, immunosuppression, and angiogenesis. As a result, pharmacological intervention with anti-inflammatory drugs has been used as a potential approach for the management of GBM. To provide an overview of the current understanding of GBM pathophysiology, potential therapeutic applications of anti-inflammatory drugs in GBM, conventional treatments of glioblastoma and emerging therapeutic approaches currently under investigation. A narrative review was carried out, scanning publications from 2000 to 2023 on PubMed and Google Scholar. The search was not guided by a set research question or a specific search method but rather focused on the area of interest. Conventional treatments such as surgery, radiotherapy, and chemotherapy have shown some benefits, but their effectiveness is limited by various factors such as tumor heterogeneity and resistance.

According to the WHO 2016 classification, glioblastoma is the most prevalent primary tumor in the adult central nervous system (CNS) and is categorized as grade IV. With an average lifespan of about 15 months from diagnosis, glioblastoma has a poor prognosis and presents a significant treatment challenge. Aberrant angiogenesis, which promotes tumor neovascularization and is a prospective target for molecular target treatment, is one of its unique and aggressive characteristics. Recently, the existence of glioma stem cells (GSCs) within the tumor, which are tolerant to chemotherapy and radiation, has been linked to the highly aggressive form of glioblastoma. Anti-angiogenic medications have not significantly improved overall survival (OS), despite various preclinical investigations and clinical trials demonstrating encouraging results. This suggests the need to discover new treatment options. Glioblastoma is one of the numerous cancers for which metformin, an anti-hyperglycemic medication belonging to the Biguanides family, is used as first-line therapy for type 2 diabetes mellitus (T2DM), and it has shown both in vitro and in vivo anti-tumoral activity. Based on these findings, the medication has been repurposed, which has shown the inhibition of many oncopromoter mechanisms and, as a result, identified the molecular pathways involved. Metformin inhibits cancer cell growth by blocking the LKB1/AMPK/mTOR/S6K1 pathway, leading to selective cell death in GSCs and inhibiting the proliferation of CD133+ cells. It has minimal impact on differentiated glioblastoma cells and normal human stem cells. The systematic retrieval of information was performed on PubMed. A total of 106 articles were found in a search on metformin for glioblastoma. Out of these six articles were Meta-analyses, Randomized Controlled Trials, clinical trials, and Systematic Reviews. The rest were Literature review articles. These articles were from the years 2011 to 2024. Appropriate studies were isolated, and important information from each of them was understood and entered into a database from which the information was used in this article. The clinical trials on metformin use in the treatment of glioblastoma were searched on clinicaltrials.gov. In this article, we examine and evaluate metformin's possible anti-tumoral effects on glioblastoma, determining whether or not it may appropriately function as an anti-angiogenic substance and be safely added to the treatment and management of glioblastoma patients.

Early diagnosis of diseases, especially cancer, is critical for effective treatment. The unique properties of terahertz technology have attracted attention in this field. However, current terahertz bio-detection methods face challenges due to differences between the test environment and the actual in vivo conditions. In this study, a novel method is proposed for detecting in vivo-like cells using a biosensor chip composed of metamaterials and a cavity. The cavity has a thickness of ~50 μm. The structure can protect cells from damage and provides a liquid environment like an in vivo state. Through simulation analysis, the metamaterials sensor exhibits a theoretical sensitivity of 0.287 THz/RIU (Refractive Index Unit) with a 50 μm thick analyte. The detection method is experimentally validated using the apoptosis of glioma cells and various cell types. The biosensor investigates the apoptosis of glioma cells under the impact of temozolomide, and the trend of the results was consistent with the Cell Counting Kit-8 method. Furthermore, at a concentration of ~5200 cells/cm2, the experimental results demonstrate that the sensor can distinguish between neurons and glioma cells with a resonance frequency difference of approximately 30 GHz. This research has significant potential for detecting glioma cells and offers an alternative approach to in vivo-like cell detection.