Integrating network pharmacology and transcriptomic omics reveals that akebia saponin D attenuates neutrophil extracellular traps-induced neuroinflammation via NTSR1/PKAc/PAD4 pathway after intracerebral hemorrhage.

Neutrophils and their production of neutrophil extracellular traps (NETs) significantly contribute to neuroinflammation and brain damage after intracerebral hemorrhage (ICH). Although Akebia saponin D (ASD) demonstrates strong anti-inflammatory activities and blood-brain barrier permeability, its role in regulating NETs formation and neuroinflammation following ICH is uncharted. Our research focused on unraveling the influence of ASD on neuroinflammation mediated by NETs and the mechanisms involved. We found that increased levels of peripheral blood neutrophils post-ICH are correlated with worse prognostic outcomes. Through network pharmacology, we identified ASD as a promising therapeutic target for ICH. ASD administration significantly improved neurobehavioral performance and decreased NETs production in neutrophils. Furthermore, ASD was shown to upregulate the membrane protein NTSR1 and activate the cAMP signaling pathway, confirmed through transcriptome sequencing, western blot, and immunofluorescence. Interestingly, the NTSR1 inhibitor SR48692 significantly nullified ASD's anti-NETs effects and dampened cAMP pathway activation. Mechanistically, suppression of PKAc via H89 negated ASD's anti-NETs effects but did not affect NTSR1. Our study suggests that ASD may reduce NETs formation and neuroinflammation, potentially involving the NTSR1/PKAc/PAD4 pathway post-ICH, underlining the potential of ASD in mitigating neuroinflammation through its anti-NETs properties.

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

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

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

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

Identification of tumor antigens and immune subtypes in lower grade gliomas for mRNA vaccine development.

BACKGROUND: As an important part of tumor immunotherapy for adjunct, therapeutic tumor vaccines have been effective against multiple solid cancers, while their efficacy against lower grade glioma (LGG) remains undefined. Immunophenotyping of tumors is an essential tool to evaluate the immune function of patients with immunodeficiency or autoimmunity. Therefore, this study aims to find the potential tumor antigen of LGG and identify the suitable population for cancer vaccination based on the immune landscape. METHOD: The genomic and clinical data of 529 patients with LGG were obtained from TCGA, the mRNA_seq data of normal brain tissue were downloaded from GTEx. Differential expression gene and mutation analysis were performed to screen out potential antigens, K-M curves were carried out to investigate the correlation between the level of potential antigens and OS and DFS of patients. TIMER dataset was used to explore the correlation between genes and immune infiltrating cells. Immunophenotyping of 529 tumor samples was based on the single-sample gene sets enrichment analysis. Cibersort and Estimate algorithm were used to explore the tumor immune microenvironment characteristics in each immune subtype. Weighted gene co-expression network analysis (WGCNA) clustered immune-related genes and screened the hub genes, and pathway enrichment analyses were performed on the hub modules related to immune subtype in the WGCNA. RESULTS: Selecting for the mutated, up-regulated, prognosis- and immune-related genes, four potential tumor antigens were identified in LGG. They were also significantly positively associated with the antigen-presenting immune cells (APCs). Three robust immune subtypes, IS1, IS2 and IS3, represented immune status "desert", "immune inhibition", and "inflamed" respectively, which might serve as a predictive parameter. Subsequently, clinicopathological features, including the codeletion status of 1p19q, IDH mutation status, tumor mutation burden, tumor stemness, etc., were significantly different among subtypes. CONCLUSION: FCGBP, FLNC, TLR7, and CSF2RA were potential antigens for developing cancer vaccination, and the patients in IS3 were considered the most suitable for vaccination in LGG.

Identification of TMZ resistance-associated histone post-translational modifications in glioblastoma using multi-omics data.

BACKGROUD: Glioblastoma multiforme (GBM) is among the most aggressive cancers, with current treatments limited in efficacy. A significant hurdle in the treatment of GBM is the resistance to the chemotherapeutic agent temozolomide (TMZ). The methylation status of the MGMT promoter has been implicated as a critical biomarker of response to TMZ. METHODS: To explore the mechanisms underlying resistance, we developed two TMZ-resistant GBM cell lines through a gradual increase in TMZ exposure. Transcriptome sequencing of TMZ-resistant cell lines revealed that alterations in histone post-translational modifications might be instrumental in conferring TMZ resistance. Subsequently, multi-omics analysis suggests a strong association between histone H3 lysine 9 acetylation (H3K9ac) levels and TMZ resistance. RESULTS: We observed a significant correlation between the expression of H3K9ac and MGMT, particularly in the unmethylated MGMT promoter samples. More importantly, our findings suggest that H3K9ac may enhance MGMT transcription by facilitating the recruitment of the SP1 transcription factor to the MGMT transcription factor binding site. Additionally, by analyzing single-cell transcriptomics data from matched primary and recurrent GBM tumors treated with TMZ, we modeled the molecular shifts occurring upon tumor recurrence. We also noted a reduction in tumor stem cell characteristics, accompanied by an increase in H3K9ac, SP1, and MGMT levels, underscoring the potential role of H3K9ac in tumor relapse following TMZ therapy. CONCLUSIONS: The increase in H3K9ac appears to enhance the recruitment of the transcription factor SP1 to its binding sites within the MGMT locus, consequently upregulating MGMT expression and driving TMZ resistance in GBM.

Use of circulating tumor cells and microemboli to predict diagnosis and prognosis in diffuse glioma.

OBJECTIVE: Circulating tumor cell (CTC) detection is a promising noninvasive technique that can be used to diagnose cancer, monitor progression, and predict prognosis. In this study, the authors aimed to investigate the clinical utility of CTCs in the management of diffuse glioma. METHODS: Sixty-three patients with newly diagnosed diffuse glioma were included in this multicenter clinical cohort. The authors used a platform based on isolation by size of epithelial tumor cells (ISET) to detect and analyze CTCs and circulating tumor microemboli (CTMs) in the peripheral blood of patients both before and after surgery. Least absolute shrinkage and selector operation (LASSO) and Cox regression analyses were used to verify whether CTCs and CTMs are independent prognostic factors for diffuse glioma. RESULTS: CTC levels were closely related to the degree of malignancy, WHO grade, and pathological subtypes. Receiver operating characteristic curve analysis revealed that a high CTC level was a predictor for glioblastoma. The results also showed that CTMs originate from the parental tumor rather than from the circulation and are an independent prognostic factor for diffuse glioma. The postoperative CTC level is related to the peripheral immune system and patient survival. Cox regression analysis showed that postoperative CTC levels and CTM status are independent prognostic factors for diffuse glioma, and CTC- and CTM-based survival models had high accuracy in internal validation. CONCLUSIONS: The authors revealed a correlation between CTCs and clinical characteristics and demonstrated that CTCs and CTMs are independent predictors for the diagnosis and prognosis of diffuse glioma. Their CTC- and CTM-based survival models can enable clinicians to evaluate patients' response to surgery as well as their outcomes.

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

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

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

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

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

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

Characteristic analysis and identification of novel molecular biomarkers in elderly glioblastoma patients using the 2021 WHO Classification of Central Nervous System Tumors.

Introduction: Elderly glioblastoma (GBM) patients is characterized by high incidence and poor prognosis. Currently, however, there is still a lack of adequate molecular characterization of elderly GBM patients. The fifth edition of the WHO Classification of Central Nervous System Tumors (WHO5) gives a new classification approach for GBM, and the molecular characteristics of elderly GBM patients need to be investigated under this new framework. Methods: The clinical and radiological features of patients with different classifications and different ages were compared. Potential prognostic molecular markers in elderly GBM patients under the WHO5 classification were found using Univariate Cox regression and Kaplan-Meier survival analysis. Results: A total of 226 patients were included in the study. The prognostic differences between younger and elderly GBM patients were more pronounced under the WHO5 classification. Neurological impairment was more common in elderly patients (p = 0.001), while intracranial hypertension (p = 0.034) and epilepsy (p = 0.038) were more common in younger patients. Elderly patients were more likely to have higher Ki-67(p = 0.013), and in elderly WHO5 GBM patients, KMT5B (p = 0.082), KRAS (p = 0.1) and PPM1D (p = 0.055) were each associated with overall survival (OS). Among them, KRAS and PPM1D were found to be prognostic features unique to WHO5 elderly GBM patients. Conclusion: Our study demonstrates that WHO5 classification can better distinguish the prognosis of elderly and younger GBM. Furthermore, KRAS and PPM1D may be potential prognostic predictors in WHO5 elderly GBM patients. The specific mechanism of these two genes in elderly GBM remains to be further studied.

Combination of multi-modal MRI radiomics and liquid biopsy technique for preoperatively non-invasive diagnosis of glioma based on deep learning: protocol for a double-center, ambispective, diagnostical observational study.

Background: 2021 World Health Organization (WHO) Central Nervous System (CNS) tumor classification increasingly emphasizes the important role of molecular markers in glioma diagnoses. Preoperatively non-invasive "integrated diagnosis" will bring great benefits to the treatment and prognosis of these patients with special tumor locations that cannot receive craniotomy or needle biopsy. Magnetic resonance imaging (MRI) radiomics and liquid biopsy (LB) have great potential for non-invasive diagnosis of molecular markers and grading since they are both easy to perform. This study aims to build a novel multi-task deep learning (DL) radiomic model to achieve preoperative non-invasive "integrated diagnosis" of glioma based on the 2021 WHO-CNS classification and explore whether the DL model with LB parameters can improve the performance of glioma diagnosis. Methods: This is a double-center, ambispective, diagnostical observational study. One public database named the 2019 Brain Tumor Segmentation challenge dataset (BraTS) and two original datasets, including the Second Affiliated Hospital of Nanchang University, and Renmin Hospital of Wuhan University, will be used to develop the multi-task DL radiomic model. As one of the LB techniques, circulating tumor cell (CTC) parameters will be additionally applied in the DL radiomic model for assisting the "integrated diagnosis" of glioma. The segmentation model will be evaluated with the Dice index, and the performance of the DL model for WHO grading and all molecular subtype will be evaluated with the indicators of accuracy, precision, and recall. Discussion: Simply relying on radiomics features to find the correlation with the molecular subtypes of gliomas can no longer meet the need for "precisely integrated prediction." CTC features are a promising biomarker that may provide new directions in the exploration of "precision integrated prediction" based on the radiomics, and this is the first original study that combination of radiomics and LB technology for glioma diagnosis. We firmly believe that this innovative work will surely lay a good foundation for the "precisely integrated prediction" of glioma and point out further directions for future research. Clinical trail registration: This study was registered on ClinicalTrails.gov on 09/10/2022 with Identifier NCT05536024.

An online survival predictor in glioma patients using machine learning based on WHO CNS5 data.

Background: The World Health Organization (WHO) CNS5 classification system highlights the significance of molecular biomarkers in providing meaningful prognostic and therapeutic information for gliomas. However, predicting individual patient survival remains challenging due to the lack of integrated quantitative assessment tools. In this study, we aimed to design a WHO CNS5-related risk signature to predict the overall survival (OS) rate of glioma patients using machine learning algorithms. Methods: We extracted data from patients who underwent an operation for histopathologically confirmed glioma from our hospital database (2011-2022) and split them into a training and hold-out test set in a 7/3 ratio. We used biological markers related to WHO CNS5, clinical data (age, sex, and WHO grade), and prognosis follow-up information to identify prognostic factors and construct a predictive dynamic nomograph to predict the survival rate of glioma patients using 4 kinds machine learning algorithms (RF, SVM, XGB, and GLM). Results: A total of 198 patients with complete WHO5 molecular data and follow-up information were included in the study. The median OS time of all patients was 29.77 [95% confidence interval (CI): 21.19-38.34] months. Age, FGFR2, IDH1, CDK4, CDK6, KIT, and CDKN2A were considered vital indicators related to the prognosis and OS time of glioma. To better predict the prognosis of glioma patients, we constructed a WHO5-related risk signature and nomogram. The AUC values of the ROC curves of the nomogram for predicting the 1, 3, and 5-year OS were 0.849, 0.835, and 0.821 in training set, and, 0.844, 0.943, and 0.959 in validation set. The calibration plot confirmed the reliability of the nomogram, and the c-index was 0.742 in training set and 0.775 in validation set. Additionally, our nomogram showed a superior net benefit across a broader scale of threshold probabilities in decision curve analysis. Therefore, we selected it as the backend for the online survival prediction tool (Glioma Survival Calculator, https://who5pumch.shinyapps.io/DynNomapp/), which can calculate the survival probability for a specific time of the patients. Conclusion: An online prognosis predictor based on WHO5-related biomarkers was constructed. This therapeutically promising tool may increase the precision of forecast therapy outcomes and assess prognosis.

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

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

Advances in research on fat infiltration and lumbar intervertebral disc degeneration.

Low back pain (LBP) is a disabling condition with no available cure, severely affecting patients' quality of life. Intervertebral disc degeneration (IVDD) is the leading cause of chronic low back pain (CLBP). IVDD is a common and recurrent condition in spine surgery. Disc degeneration is closely associated with intervertebral disc inflammation. The intervertebral disc is an avascular tissue in the human body. Transitioning from hematopoietic bone marrow to bone marrow fat may initiate an inflammatory response as we age, resulting in bone marrow lesions in vertebrae. In addition, the development of LBP is closely associated with spinal stability imbalance. An excellent functional state of paraspinal muscles (PSMs) plays a vital role in maintaining spinal stability. Studies have shown that the diminished function of PSMs is mainly associated with increased fat content, but whether the fat content of PSMs is related to the degree of disc degeneration is still under study. Given the vital role of PSMs lesions in CLBP, it is crucial to elucidate the interaction between PSMs changes and CLBP. Therefore, this article reviews the advances in the relationship and the underlying mechanisms between IVDD and PSMs fatty infiltration in patients with CLBP.

Pallidus Stimulation for Chorea-Acanthocytosis: A Systematic Review and Meta-Analysis of Individual Data.

A significant proportion of patients with chorea-acanthocytosis (ChAc) fail to respond to standard therapies. Recent evidence suggests that globus pallidus internus (GPi) deep brain stimulation (DBS) is a promising treatment option; however, reports are few and limited by sample sizes. We conducted a systematic literature review to evaluate the clinical outcome of GPi-DBS for ChAc. PubMed, Embase, and Cochrane Library databases were searched for relevant articles published before August 2021. The improvement of multiple motor and nonmotor symptoms was qualitatively presented. Improvements in the Unified Huntington's Disease Rating Scale motor score (UHDRS-MS) were also analyzed during different follow-up periods. A multivariate linear regression analysis was conducted to identify potential predictors of clinical outcomes. Twenty articles, including 27 patients, were eligible. Ninety-six percent of patients with oromandibular dystonia reported significant improvement. GPi-DBS significantly improved the UHDRS-motor score at < 6 months (p < 0.001) and ≥ 6 months (p < 0.001). The UHDRS-motor score improvement rate was over 25% in 75% (15/20 cases) of patients at long-term follow-up (≥ 6 months). The multiple linear regression analysis showed that sex, age at onset, course of disease, and preoperative movement score had no linear relationship with motor improvement at long-term follow-up (p > 0.05). GPi-DBS is an effective and safe treatment in most patients with ChAc, but no reliable predictor of efficacy has been found. Oromandibular dystonia-dominant patients might be the best candidates for GPi-DBS.

The dual role of p62 in ferroptosis of glioblastoma according to p53 status.

BACKGROUND: Ferroptosis plays a key role in human cancer, but its function and mechanism in glioma is not clear. P62/SQSTM1 was reported to inhibit ferroptosis via the activation of NRF2 signaling pathway. In this study we reveal a dual role of p62 in ferroptosis of glioblastoma (GBM) according to p53 status. METHOD: Lipid peroxidation analysis, transmission electron microscopy (TEM), GSH assay were performed to determine the level of ferroptosis. Western blot and qPCR were obtained to detect the expression of ferroptosis markers. Construction of mutant plasmids, immunoprecipitation, luciferase assay and rescue-experiments were performed to explore the regulatory mechanism. RESULTS: P62 overexpression facilitates ferroptosis and inhibits SLC7A11 expression in p53 mutant GBM, while attenuates ferroptosis and promotes SLC7A11 expression in p53 wild-type GBM. P62 associates with p53 and inhibits its ubiquitination. The p53-NRF2 association and p53-mediated suppression of NRF2 antioxidant activity are diversely regulated by p62 according to p53 status. P53 mutation status is required for the dual regulation of p62 on ferroptosis. In wild-type p53 GBM, the classical p62-mediated NRF2 activation pathway plays a major regulatory role of ferroptosis, leading to increased SLC7A11 expression, resulting in a anti-ferroptosis role. In mutant p53 GBM, stronger interaction of mutant-p53/NRF2 by p62 enhance the inhibitory effect of mutant p53 on NRF2 signaling, which reversing the classical p62-mediated NRF2 activation pathway, together with increased p53's transcriptional suppression on SLC7A11 by p62, leading to a decrease of SLC7A11, resulting in a pro-ferroptosis role. CONCLUSION: Together, this study shows novel molecular mechanisms of ferroptosis regulated by p62; the mutation status of p53 is an important factor that determines the therapeutic response to p62-mediated ferroptosis-targeted therapies in GBM.

Hsa_circ_0072309 enhances autophagy and TMZ sensitivity in glioblastoma.

AIMS: Circular RNAs have been reported to play key roles in the progression of various cancers, including gliomas. The present study was designed to investigate the role of hsa_circ_0072309 in autophagy and temozolomide (TMZ) sensitivity in glioblastoma (GBM). METHODS: The effect of hsa_circ_0072309 on autophagy and TMZ sensitivity were examined by GFP-RFP-LC3, transmission electron microscopy(TEM), flow cytometry, Western blot, and immunofluorescence. The mechanism of hsa_circ_0072309 regulating p53 signaling pathway was analyzed using Western blot, IP, and rescue experiments. RESULTS: Low hsa_circ_0072309 expression predicts poor prognosis for glioma patients. The regulation of hsa_circ_0072309 on autophagy and TMZ sensitivity depends on the status of p53. Hsa_circ_0072309 promoted autophagy by p53 signaling pathway and enhanced sensitivity of glioblastoma to temozolomide (TMZ) in p53 wild-type GBM, but not in p53 mutant GBM. Hsa_circ_0072309 inhibits p53 ubiquitination and increases the stability of p53 protein in the context of p53 wild-type. MiR-100 mediates hsa_circ_0072309 regulating p53. P53 inhibitor or autophagy inhibitor could reverse the effect of hsa_circ_0072309 on TMZ sensitivity in p53 wild-type GBM. CONCLUSIONS: This study revealed a function of hsa_circ_0072309 promoting autophagy by p53 signaling pathway and enhancing TMZ sensitivity. These findings demonstrated that hsa_circ_0072309 may be a potential and promising target in designing the treatment strategy for GBM.

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

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

HSP27 protects against ferroptosis of glioblastoma cells.

Ferroptosis, as an new form of non-apoptotic regulated cell death, plays an important role in human cancers. Although it is reported that HSP27 is an novel regulator of ferroptosis in cancer, it remains unknown how HSP27 affects ferroptosis in glioma. In this study, we examined the effect of HSP27 on the ferroptosis of glioblasotma. HSP27 overexpression protects glioblastoma cells from erastin-induced ferroptosis while HSP27 depletion promotes erastin-induced ferroptosis of glioblastoma. Notably, HSP27 phosphorylation is required for the protective function of HSP27 in erastin-induced ferroptosis. Overall, our study reveal novel molecular mechanisms of ferroptosis in glioma and also identify HSP27 as a negative regulator of ferroptosis and a potential target for the treatment of glioma.

Predictive effects of admission white blood cell counts and hounsfield unit values on delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage.

OBJECTIVE: Neuroinflammatory response is deemed the primary pathogenesis of delayed cerebral ischemia (DCI) caused by aneurysmal subarachnoid hemorrhage (aSAH). Both white blood cell (WBC) count and Hounsfield Unit (HU) are gradually considered can reflect inflammation in DCI. This study aims to identify the relationship between WBC count and HU value and investigate the effects of both indicators in predicting DCI after aSAH. METHODS: We enrolled 109 patients with aSAH admitted within 24 h of onset in our study. A multivariate logistic regression analysis was used to evaluate the admission WBC count, HU value, and combined WBC-HU associated with DCI. The receiver operating characteristic curve and area under the curve (AUC) were used to determine thresholds and detect the predictive ability of these predictors. These indicators were also compared with the established inflammation markers. RESULTS: Thirty-six (33%) patients developed DCI. Both WBC count and HU value were strongly associated with the admission glucose level (ρ = .303, p = .001; ρ = .273, p = .004), World Federation of Neurosurgical Societies grade (ρ = .452, p < .001; ρ = .578; p < .001), Hunt-Hess grade (ρ = .450, p < .001; ρ = .510, p < .001), and modified Fisher scale score (ρ = .357, p < .001; ρ = .330, p < .001). After controlling these public variables, WBC count (ρ = .300, p = .002) positively correlated with HU value. An early elevated WBC (odds ratio [OR] 1.449, 95% confidence interval [CI]: 1.183-1.774, p < .001) count and HU value (OR 1.304, 95%CI: 1.149-1.479, p < .001) could independently predict the occurrence of DCI. However, only these patients with both WBC count and HU value exceeding the cut-off points (OR 36.89, 95%CI: 5.606-242.78, p < .001) were strongly correlated with DCI. Compared with a single WBC count (AUC 0.811, 95%CI: 0.729-0.892, p < .001) or HU value (AUC 0.869, 95%CI: 0.803-0.936, p < .001), the combined WBC-HU (AUC 0.898, 95%CI: 0.839-0.957, p < .001) demonstrated a better ability to predict the occurrence of DCI. Inspiringly, the prediction performance of these indicators outperformed the established inflammatory markers. CONCLUSION: An early elevated WBC count and HU value could independently predict DCI occurrence between 4 and 30 days after aSAH. Furthermore, WBC count was positively correlated with HU value, and the combined WBC-HU demonstrated a superior prediction ability for DCI development compared with the individual indicator.