Glioma Group Research Articles

Changes and significance of serum ubiquitin carboxyl-terminal hydrolase L1 and glial fibrillary acidic protein in patients with glioma

Brain gliomas are malignant tumors with high postoperative recurrence rates. Early prediction of prognosis using specific indicators is of great significance. To assess changes in ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) and glial fibrillary acidic protein (GFAP) levels in patients with glioma pre-and postoperatively. Between June 2018 and June 2021, 91 patients with gliomas who underwent surgery at our hospital were enrolled in the glioma group. Sixty healthy volunteers were included in the control group. Serum UCH-L1 and GFAP levels were measured in peripheral blood collected from patients with glioma before and 3 d after surgery. UCH-L1 and GFAP levels in patients with glioma with different clinicopathological characteristics were compared before and after surgery. The patients were followed-up until February 2022. Postoperative glioma recurrence was recorded to determine the serum UCH-L1 and GFAP levels, which could assist in predicting postoperative glioma recurrence. UCH-L1 and GFAP levels in patients with glioma decreased significantly 3 d after surgery compared to those before therapy (P < 0.05). However, UCH-L1 and GFAP levels in the glioma group were significantly higher than those in the control group before and after surgery (P < 0.05). There were no statistically significant differences in preoperative serum UCH-L1 and GFAP levels among patients with glioma according to sex, age, pathological type, tumor location, or number of lesions (P > 0.05). Serum UCH-L1 and GFAP levels were significantly lower in the patients with WHO grade I-II tumors than in those with grade III-IV tumors (P < 0.05). Serum UCH-L1 and GFAP levels were lower in the patients with tumor diameter ≤ 5 cm than in those with diameter > 5 cm, in which the differences were statistically significant (P < 0.05). Glioma recurred in 22 patients. The preoperative and 3-d postoperative serum UCH-L1 and GFAP levels were significantly higher in the recurrence group than these in the non-recurrence group (P < 0.05). Receiver operating characteristic curves were plotted. The areas under the curves of preoperative serum UCH-L1 and GFAP levels for predicting postoperative glioma recurrence were 0.785 and 0.775, respectively. However, the efficacy of serum UCH-L1 and GFAP levels 3 d after surgery in predicting postoperative glioma recurrence was slightly lower compared with their preoperative levels. UCH-L1 and GFAP efficiently reflected the development and recurrence of gliomas and could be used as potential indicators for the recurrence and prognosis of glioma.

Impact of redox-related genes on tumor microenvironment immune characteristics and prognosis of high-grade gliomas.

High-grade glioma (HGG) defines a group of brain gliomas characterized by contrast enhancement, high tumor heterogeneity, and poor clinical outcome. Disturbed reduction-oxidation (redox) balance has been frequently associated with the development of tumor cells and their microenvironment (TME). To study the influence of redox balance on HGGs and their microenvironment, we collected mRNA-sequencing and clinical data of HGG patients from TCGA and CGGA databases and our own cohort. Redox-related genes (ROGs) were defined as genes in the MSigDB pathways with keyword "redox" that were differentially expressed between HGGs and normal brain samples. Unsupervised clustering analysis was used to discover ROG expression clusters. Over-representation analysis (ORA), gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were also employed to understand the biological implication of differentially expressed genes between HGG clusters. CIBERSORTx and ESTIMATE were used to profile the immune TME landscapes of tumors, and TIDE was used to evaluated the potential response to immune checkpoint inhibitors. Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression was used to construct HGG-ROG expression risk signature (GRORS). Seventy-five ROGs were found and consensus clustering using the expression profile of ROGs divided the both IDH-mutant (IDHmut) and IDH-wildtype (IDHwt) HGGs into subclusters with different prognosis. Functional enrichment analysis revealed that the differential aggressiveness between redox subclusters in IDHmut HGGs were significantly associated with cell cycle regulation pathways, while IDHwt HGG redox subclusters showed differentially activated immune-related pathways. In silico TME analysis on immune landscapes in the TME showed that the more aggressive redox subclusters in both IDHmut and IDHwt HGGs may harbor a more diverse composition of tumor-infiltrating immune cells, expressed a higher level of immune checkpoints and were more likely to respond to immune checkpoint blockade. Next, we established a GRORS which showed AUCs of 0.787, 0.884, and 0.917 in predicting 1-3-year survival of HGG patients in the held-out validation datasets, and the C-index of a nomogram combining the GRORS and other prognostic information reached 0.835. Briefly, our results suggest that the expression pattern of ROGs was closely associated with the prognosis as well as the TME immune profile of HGGs, and may serve as a potential indicator for their response to immunotherapies.

Elevated LILRB1 expression predicts poor prognosis and is associated with tumor immune infiltration in patients with glioma

BackgroundLeukocyte immunoglobulin-like receptor subfamily B1 (LILRB1) is regarded as an inhibitory molecule. However, the importance of LILRB1 expression in glioma has not yet been determined. This investigation examined the immunological signature, clinicopathological importance and prognostic value of LILRB1 expression in glioma.MethodsWe used data from the UCSC XENA database, the Cancer Genome Atlas (TCGA) database, the Chinese Glioma Genome Atlas (CGGA) database, the STRING database, the MEXPRESS database and our clinical glioma samples to perform bioinformatic analysis and used vitro experiments to examine the predictive value and potential biological roles of LILRB1 in glioma.ResultsHigher LILRB1 expression was considerably present in the higher WHO grade glioma group and was linked to a poorer prognosis in patients with glioma. Gene set enrichment analysis (GSEA) revealed that LILRB1 was positively correlated with the JAK/STAT signaling pathway. LILRB1 combined with tumor mutational burden (TMB) and microsatellite instability (MSI) may be a promising indicator for the effectiveness of immunotherapy in patients with glioma. Increased LILRB1 expression was positively linked with the hypomethylation, M2 macrophage infiltration, immune checkpoints (ICPs) and M2 macrophage makers. Univariate and multivariate Cox regression analyses determined that increased LILRB1 expression was a standalone causal factor for glioma. Vitro experiments determined that LILRB1 positively enhanced the proliferation, migration and invasion in glioma cells. MRI images demonstrated that higher LILRB1 expression was related with larger tumor volume in patients with glioma.ConclusionDysregulation of LILRB1 in glioma is correlated with immune infiltration and is a standalone causal factor for glioma.

Electroencephalography characteristics of patients with supratentorial glioma in different consciousness states induced by propofol

Gliomas are the most common primary intracranial malignant tumors. Some of these patients exhibit previously clinically undetected neurological deficits after sedation. The absence of neurophysiological evidence for this phenomenon limits the use of time-sensitive monitoring methods. The study aims to compare differences between glioma patients under sedation and those without intracranial lesions by comparing their EEG features. Twenty-one patients without intracranial tumors and 21 with frontal lobe supratentorial gliomas were enrolled. The EEG power spectrum of the glioma group was comparable to that of the control group for both sides of the brain (P > 0.05 for all frequencies). Compared with those without intracranial lesions, the weighted phase lag index (wPLI) in the alpha and beta bands on the non-occupied side decreased. Glioma patients had weaker functional connectivity during sedation than patients without intracranial lesions, manifesting as reduced functional connectivity on the non-occupied side.

Brain Tumor Vascularity Estimation by Arterial Spin Label Perfusion MRI—A Preoperative Tool for Patient Prognostication

Abstract Introduction Brain tumors remain a significant cause of morbidity and mortality around the globe. Preoperative estimation of tumor vascularity is of great significance for a neurosurgeon. Aim of our study was to correlate tumor blood flow (TBF) using arterial spin labeling perfusion imaging (ASL-PI) with microvessel density (MVD), tumor grade, and preoperative prognostication of brain tumors. Materials and Methods This was a prospective observational cross-sectional study conducted in 63 patients of primary brain tumors already referred for magnetic resonance imaging. Absolute and relative mean and maximum TBF were calculated using ASL-PI and correlated with tumor grade and MVD at 10x and 40x magnificantion; thereby stydying the role of ASL-PI in brain tumor prognostication. Results The mean of maxTBF values (mL/min/100 g) in the gliomas group, meningiomas group, schwannoma group, craniopharyngioma group, and hemangioblastoma group was 147.15, 251.55, 96.43, 43.3, and 578.3, respectively. The median of maxTBF value in the gliomas group, meningiomas group, schwannoma group, craniopharyngioma group, and hemangioblastoma group was 131.5, 158.63, 94.5, 43.4, and 578.3, respectively. Discussion Significant correlation between meanTBF and MVD at 10X magnification (p-value &lt; 0.001, rho =0.88) and a positive correlation between meanTBF and MVD at 40X magnification (p-value &lt; 0.001) were seen. Significant correlation was also seen between maxTBF and MVD at 10X magnification (p-value &lt; 0.001, rho = 0.91) and between maxTBF and MVD at 40X magnification. TBF in case of the hemangioblastoma was higher than other types of brain tumors (gliomas, meningiomas, and schwannomas). HighTBF value was seen in high-grade gliomas compared with low-grade gliomas with worse prognosis. TBF was high in typical meningiomas whereas low in atypical meningioma. Conclusion TBF by ASL-PI can be considered a noninvasive in vivo marker in predicting the grade of brain tumors and further assist in envisaging prognosis of the patients with brain tumors.

Efficacy of three-dimensional arterial spin labeling and how it compares against that of contrast enhanced magnetic resonance imaging in preoperative grading of brain gliomas.

To evaluate the efficacy of three-dimensional arterial spin labeling (3D-ASL) imaging in preoperative grading of brain gliomas, and compare the discrepancy between images obtained from 3D-ASL and contrast enhanced magnetic resonance imaging (CE-MRI) in grading of gliomas. Fifty-one patients with brain gliomas received plain MRI, CE-MRI and 3D-ASL scanning before surgery. In 3D-ASL images, the maximum tumor blood flow (TBF) of tumor parenchyma was measured, relative TBF-M and rTBF-WM were calculated. The cases were categorized into "ASL dominant" and "CE dominant" to compare the discrepancy between 3D-ASL and CE-MRI results. Independent samples t test, Mann-Whitney and U test and one-way analysis of variance (ANOVA) were performed to test the differences of TBF, rTBF-M and rTBF-WM values among brain gliomas with different grades. Spearman rank correlation analysis was performed to assess the correlation between TBF, rTBF-M, rTBF-WM and glioma grades respectively. To compare the discrepancy between 3D-ASL and CE-MRI results. In high-grade gliomas (HGG) group, TBF, rTBF-M and rTBF-WM values were higher than those in low-grade gliomas (LGG) group (p < .05). Multiple comparison showed TBF and rTBF-WM values were different between grade I and IV gliomas, grade II and IV gliomas (both p < .05), the rTBF-M value was different between grade I and IV gliomas (p < .05). The values of all 3D-ASL derived parameters were positively correlated with gliomas grading (all p < .001). TBF showed highest specificity (89.3%) and rTBF-WM showed highest sensitivity (96.4%) when discriminating LGG and HGG using ROC curve. There were 29 CE dominant cases (23 cases were HGG), 9 ASL dominant cases (4 cases were HGG). CONCLUSION: 3D-ASL is of significance to preoperative grading of brain gliomas and might be more sensitive than CE-MRI in detection of tumor perfusion.

Ion Channels in Gliomas-From Molecular Basis to Treatment.

Ion channels provide the basis for the nervous system's intrinsic electrical activity. Neuronal excitability is a characteristic property of neurons and is critical for all functions of the nervous system. Glia cells fulfill essential supportive roles, but unlike neurons, they also retain the ability to divide. This can lead to uncontrolled growth and the formation of gliomas. Ion channels are involved in the unique biology of gliomas pertaining to peritumoral pathology and seizures, diffuse invasion, and treatment resistance. The emerging picture shows ion channels in the brain at the crossroads of neurophysiology and fundamental pathophysiological processes of specific cancer behaviors as reflected by uncontrolled proliferation, infiltration, resistance to apoptosis, metabolism, and angiogenesis. Ion channels are highly druggable, making them an enticing therapeutic target. Targeting ion channels in difficult-to-treat brain tumors such as gliomas requires an understanding of their extremely heterogenous tumor microenvironment and highly diverse molecular profiles, both representing major causes of recurrence and treatment resistance. In this review, we survey the current knowledge on ion channels with oncogenic behavior within the heterogeneous group of gliomas, review ion channel gene expression as genomic biomarkers for glioma prognosis and provide an update on therapeutic perspectives for repurposed and novel ion channel inhibitors and electrotherapy.

The diagnostic value of ADC histogram and direct ADC measurements for coexisting isocitrate dehydrogenase mutation and O6-methylguanine-DNA methyltransferase promoter methylation in glioma.

To non-invasively predict the coexistence of isocitrate dehydrogenase (IDH) mutation and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation in adult-type diffuse gliomas using apparent diffusion coefficient (ADC) histogram and direct ADC measurements and compare the diagnostic performances of the two methods. A total of 118 patients with adult-type diffuse glioma who underwent preoperative brain magnetic resonance imaging (MRI) and diffusion weighted imaging (DWI) were included in this retrospective study. The patient group included 40 patients with coexisting IDH mutation and MGMT promoter methylation (IDHmut/MGMTmet) and 78 patients with other molecular status, including 32 patients with IDH wildtype and MGMT promoter methylation (IDHwt/MGMTmet), one patient with IDH mutation and unmethylated MGMT promoter (IDHmut/MGMTunmet), and 45 patients with IDH wildtype and unmethylated MGMT promoter (IDHwt/MGMTunmet). ADC histogram parameters of gliomas were extracted by delineating the region of interest (ROI) in solid components of tumors. The minimum and mean ADC of direct ADC measurements were calculated by placing three rounded or elliptic ROIs in solid components of gliomas. Receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC) were used to evaluate the diagnostic performances of the two methods. The 10th percentile, median, mean, root mean squared, 90th percentile, skewness, kurtosis, and minimum of ADC histogram analysis and minimum and mean ADC of direct measurements were significantly different between IDHmut/MGMTmet and the other glioma group (P < 0.001 to P = 0.003). In terms of single factors, 10th percentile of ADC histogram analysis had the best diagnostic efficiency (AUC = 0.860), followed by mean ADC obtained by direct measurements (AUC = 0.844). The logistic regression model combining ADC histogram parameters and direct measurements had the best diagnostic efficiency (AUC = 0.938), followed by the logistic regression model combining the ADC histogram parameters with statistically significant difference (AUC = 0.916) and the logistic regression model combining minimum ADC and mean ADC (AUC = 0.851). Both ADC histogram analysis and direct measurements have potential value in predicting the coexistence of IDHmut and MGMTmet in adult-type diffuse glioma. The diagnostic performance of ADC histogram analysis was better than that of direct ADC measurements. The combination of the two methods showed the best diagnostic performance.

Evaluation of Two Post-Processing Analysis Methods of Proton Magnetic Resonance Spectroscopy in Glioma Tumors.

Magnetic resonance spectroscopy (MRS) is a non-invasive diagnostic and the neuroimaging method of choice for the noninvasive monitoring of brain metabolism in patients with glioma tumors. 1H-MRS is a reliable and non-invasive tool used to study glioma. However, the metabolite spectra obtained by 1H-MRS requires a specific quantification procedure for post-processing. According to our knowledge, no comparisons have yet been made between spectrum analysis software for quantification of gliomas metabolites. Current study aims to evaluate the difference between this two common software in quantifying cerebral metabolites. In this analytical study, we evaluate two post-processing software packages, java-based graphical for MR user interface packages (jMRUI) and totally automatic robust quantitation in NMR (TARQUIN) software. 1H-MRS spectrum from the brain of patients with gliomas tumors was collected for post-processing. AMARES algorithms were conducted to metabolite qualification on jMRUI software, and TARQUIN software were implemented with automated quantification algorithms. The study included a total of 30 subjects. For quantification, subjects were divided into a normal group (n=15) and group of gliomas (n=15). When calculated by TARQUIN, the mean metabolites ratio was typically lower than by jMRUI. While, the mean ratio of metabolites varied when quantified by jMRUI vs. TARQUIN, both methods apparent clinical associations. TARQUIN and jMRUI are feasible choices for the post-processing of cerebral MRS data obtained from glioma tumors.

Association of Kinase-Insert-Domain-Containing Receptor Polymorphisms with Glioma Susceptibility in a Chinese Population: A Hospital-Based Case-Control Study.

Gliomas are the most common malignant tumors of the central nervous system. However, the inherited genetic variation in gliomas is presently unclear. Therefore, this study investigated the association of the rs2071559 and rs2239702 gene polymorphisms with glioma susceptibility in Chinese patients. In this study, a case-control approach was used to compare and analyze whether two genes, rs2071559 and rs2239702, were associated with the risk of glioma formation. The cases and controls were matched for sex, smoking status, and family history of cancer using single nucleotide polymorphisms. Specific rs2071559 and rs2239702 alleles were found much more frequently in the glioma group than in the control group (P < 0.001 and P = 0.014, respectively). These findings suggest that specific rs2071559 and rs2239702 polymorphisms are associated with a higher risk of glioma development; the risk allele is C in rs2071559 or A in rs2239702. Moreover, the kinase-insert-domain-containing receptor may act as a suppressor of tumor progression.

Expression analysis of human glioma susceptibility gene and P53 in human glioma and its clinical significance based on bioinformatics.

The exact mechanism of glioblastoma multiforme (GBM) remains unclear. This study was to clarify the expression of P53 in glioma and its molecular mechanism, and to explore the possibility of P53 as a potential therapeutic target of glioma and its clinical application value, so as to provide a new theoretical basis for the treatment of glioma. Firstly, a dataset was established to analyze the expression of P53 in different stages of glioma and its relationship with prognosis by using The Cancer Genome Atlas (TCGA) database, RNA-seq data, and survival data of glioma and normal control samples in gene expression profiling and interactive analysis (GEPIA). The genes co-expressed with P53 were screened out, their differential expression between glioma and normal control group was analyzed, and their functions were analyzed by enrichment analysis. The TGGA database was used for data verification and analysis. The correlation between P53 expression and clinicopathological parameters was analyzed. Kaplan-Meier survival analysis was used to analyze the relationship between P53 expression and overall survival (OS) and progression-free survival (PFS) of glioma patients, and Cox regression analysis was used to analyze the independent factors affecting OS and PFS of glioma patients. The results of TCGA data analysis were as follows: The expression level of P53 was different from that of different stages of glioma, namely, the expression level of P53 between grade II and grade III, grade III and grade IV, and grade II and grade IV were significantly different (P<0.05). The results of P53 gene-related survival analysis showed that KNL1 high expression and low expression were significantly different in OS, and the high expression group was associated with poor prognosis (P<0.05). The P53 expression can be an effective biological indicator of poor prognosis of glioma.

The Role of Epigenetics in Brain and Spinal Cord Tumors.

Identification of distinct genetic and epigenetic profiles in various neuroepithelial tumors has improved the classification and uncovered novel diagnostic, prognostic, and predictive molecular biomarkers for improved prediction of treatment response and outcome. Especially, in pediatric high-grade brain tumors, such as diffuse midline glioma, H3K27M-altered and posterior fossa group A-ependymoma, epigenetic changes predominate, along with changes in expression of known oncogenes and tumor suppressor genes induced by histone modifications and DNA methylation. The precise role of epigenetic abnormalities is important for understanding tumorigenesis and the establishment of brain tumor treatment strategies. Using powerful epigenetic-based therapies for cancer cells, the aberrantly regulated epigenome can be restored to a more normal state through epigenetic reprogramming. Combinations of agents targeting DNA methylation and/or other epigenetic modifications may be a promising cancer treatment. Therefore, the integration of multi-omics data including epigenomics is now important for classifying primary brain tumors and predicting their biological behavior. Recent advances in molecular genetics and epigenetic integrated diagnostics of brain tumors influence new strategies for targeted therapy.

Lipid Alterations in Glioma: A Systematic Review.

Gliomas are highly lethal tumours characterised by heterogeneous molecular features, producing various metabolic phenotypes leading to therapeutic resistance. Lipid metabolism reprogramming is predominant and has contributed to the metabolic plasticity in glioma. This systematic review aims to discover lipids alteration and their biological roles in glioma and the identification of potential lipids biomarker. This systematic review was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Extensive research articles search for the last 10 years, from 2011 to 2021, were conducted using four electronic databases, including PubMed, Web of Science, CINAHL and ScienceDirect. A total of 158 research articles were included in this study. All studies reported significant lipid alteration between glioma and control groups, impacting glioma cell growth, proliferation, drug resistance, patients' survival and metastasis. Different lipids demonstrated different biological roles, either beneficial or detrimental effects on glioma. Notably, prostaglandin (PGE2), triacylglycerol (TG), phosphatidylcholine (PC), and sphingosine-1-phosphate play significant roles in glioma development. Conversely, the most prominent anti-carcinogenic lipids include docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and vitamin D3 have been reported to have detrimental effects on glioma cells. Furthermore, high lipid signals were detected at 0.9 and 1.3 ppm in high-grade glioma relative to low-grade glioma. This evidence shows that lipid metabolisms were significantly dysregulated in glioma. Concurrent with this knowledge, the discovery of specific lipid classes altered in glioma will accelerate the development of potential lipid biomarkers and enhance future glioma therapeutics.

MPC-15 CLINICAL FEATURE OF NON-MIDLINE GLIOMA WITH H3F3A GENE MUTATION

Abstract Introduction Diffuse midline glioma (DMG), H3K27-altered, is a CNS WHO grade 4 glioma that usually occurs mainly in the brainstem region in children and also in the thalamus and spinal cord in older children and adults. On the other hand, glioma with histone H3 p. G34R/V mutations in the cerebral hemispheres are defined in a new classification of Diffuse hemispheric glioma, H3G34-mutant (DHG), in the WHO 2021 classification. However, there are some reports of H3K27-altered non-midline gliomas (NDMG) that are not located in the midline, but the differences between these hemispheric tumors with mutations in different regions of histone H3 are unknown. In this study, we report a comparative study of the clinical characteristics between two groups of glioma, H3K27-altered NDMGs and H3G34-mutant DHGs. Methods Among 4128 brain tumor specimens collected in the Kansai Network for Molecular Diagnosis of Central Nervous System Tumors, 25 NDMG cases, excluding 93 cases defined as DMG, were included out of 118 cases with mutations in the H3F3A gene. Both 16 H3K27-altered NDMG cases and 9 H3G34-mutant DHG cases were examined for comparison of clinical characteristics. Results There were no differences in gender, tumor location, or pathology between NDMG and DHG. The median age was 47.3 years in NDMG and 26.2 years in DHG, and NDMG was significantly older than DHG (p=0.003). The rate of MGMT promoter methylation is no significant difference between 4 cases (25%) in NDMG and 6 cases (66.7%) in DHG (p=0.087). The Kaplan-Meier survival curve showed no significant difference, with a median survival of 495 days for NDMG and 587 days for DHG (p=0.765). Discussion and Conclusion We reported on gliomas with H3F3A mutations that occur in the cerebral hemispheres. We compared the clinical characteristics of NDMG with H3K27-altered and DHG with H3G34-mutant, which have similar tumor locations of occurrence.

Clinical Features and Differential Gene Screening of Invasive Behaviors between Glioma and Brain Metastasis

Objective: To analyze invasive behaviors between glioma and Brain Metastasis (BM), and to screen invasive differentially expressed genes. Methods: Patients diagnosed pathologically with glioma or BM divided into low-grade glioma groups (n = 19), high-grade glioma group (n = 18), and BM group (n = 15). The survival period was determined. The clinical characteristics were retrospectively analyzed to draw Kaplan-Meier survival curve. Glioma and BM samples were obtained for RNA sequencing. By GO, KEGG, PubMed, and GeneCard, invasive genes were theoretical selected. Correlation between invasive genes and pathological grade was performed. The expression level of invasive genes was verified. Results: The survival curve found that the clinical invasive behavior related to short lifetime includes: size, edema range, blood supply, vascular invasion, grade, and Ki 67 expression. Theoretical analysis finally found that the expression levels of CALM3, CAMK2A, CAMK2B, and PRKCG were negatively correlated with pathological grade (P&lt; 0.01), of which CALM3 was highly correlated with BM (P&lt; 0.01). CALM3 mRNA was significantly down-regulated in BM (P&lt; 0.05), and PRKCG mRNA was significantly down-regulated in both glioma and BM (P&lt; 0.05). Conclusion: The clinical invasive behavior between glioma and BM have significantly shortened the median survival time of patients. Down-regulation of CALM3 suggested a higher correlation with BM, meanwhile Down-regulation of PRKCG played a role in glioma and BM The detection of CALM3 and PRKCG may be helpful for invasive behavior and provide a reference for the targeted therapy in glioma and BM.

MODL-19. CREATION OF AN IN VITRO MODEL SYSTEM FOR THE STUDY OF H3.1K27M DMG

Abstract Diffuse Midline Gliomas (DMG) are a devastating group of pediatric high-grade gliomas that occur in the brainstem with a median survival of less than 1 year. A greater understanding of the early tumorigenic events is essential for the development of effective therapeutics. DMG is characterized by founder mutations in histone H3, either H3.1K27M or H3.3K27M. These mutations cause global hypomethylation, resulting in aberrant gene expression. It is unknown how this mechanism contributes to tumorigenesis. Interestingly, H3.1K27M DMG show an increased incidence in females, whereas H3.3K27M DMG shows no sex difference. This illustrates that the tumorigenic potential of H3.1K27M may be different between the sexes. Few models of DMG incorporate the study of H3.1K27M, even though it represents a unique opportunity to obtain valuable information on the tumorigenesis of DMG through the study of the sex difference. Additionally, an important regulatory element, a stem loop structure, present in mammals is missing from all previous models studying H3.1K27M. Thus, we have created an in vitro model system for H3.1K27M DMG that incorporates the stem loop structure utilizing the RCAS mouse model system. This system utilizes RCAS vectors and a RCAS-ntva transgenic mouse line to deliver specific mutations to nestin expressing cells in the brainstem, including neural and glial progenitor cells, the potential cells of origin. Confirmed through immunofluorescence staining, we can isolate a pure population of NPCs and transduce them with RCAS vectors in vitro to produce stable expression of H3.1K27M. Verified via immunocytochemistry and flow cytometry, delivering H3.1K27M with the stem loop included limits its expression to S phase of the cell cycle, mimicking the human disease biology. These results demonstrate that we have created an in vitro H3.1K27M DMG model system for the study of sex differences and tumorigenesis in DMG.

Value of DWI Combined with Magnetic Resonance Spectroscopy in the Differential Diagnosis between Recurrent Glioma and Radiation Injury: A Meta-Analysis.

To analyse the value of the apparent diffusion coefficient (ADC) in diffusion-weighted imaging (DWI) and the choline (Cho)/creatine (Cr) ratio and Cho/N-acetyl-aspartate (NAA) ratio in magnetic resonance spectroscopy (MRS) in the differential diagnosis between recurrent glioma and radiation injury. Chinese and English studies related to the diagnosis of recurrent glioma and radiation injury using DWI and MRS and published before 15 October 2022 were retrieved from PubMed, Embase, the Cochrane Library, China National Knowledge Infrastructure, China Biomedical Literature Database, VIP Journal Database, and Wanfang Database for a meta-analysis. A total of 11 articles were included in this study. ADC was lower in the recurrent glioma group than in the radiation injury group (standardized mean difference = -1.29, 95% confidence interval (CI) (-1.87, -0.71), P < 0.001). The Cho/Cr ratio was higher in the recurrent glioma group than in the radiation injury group (weighted mean difference = 0.65, 95% CI (0.40, 0.90), and P < 0.001). The Cho/NAA ratio was higher in the recurrent glioma group than in the radiation injury group, as evidenced by the sensitivity analysis. The sensitivity and specificity of the Cho/Cr ratio were 0.85 (0.73-0.92) and 0.82 (0.67-0.91), respectively, and the area under the curve was 0.86. The sensitivity and specificity of the Cho/NAA ratio were 0.82 (0.66-0.91) and 0.94 (0.69-0.99), respectively, and the area under the curve was 0.93. This meta-analysis showed that ADC, Cho/Cr, and Cho/NAA ratios all had high sensitivity and specificity. Therefore, DWI combined with MRS can effectively improve the diagnosis of recurrent glioma and radiation injury.

Radiomic study on preoperative multi-modal magnetic resonance images identifies IDH-mutant TERT promoter-mutant gliomas.

Gliomas with comutations of isocitrate dehydrogenase (IDH) genes and telomerase reverse transcriptase (TERT) gene promoter (IDHmut pTERTmut) show distinct biological features and respond to first-line treatment differently in comparison with other gliomas. This study aimed to characterize the IDHmut pTERTmut gliomas in multimodal MRI using the radiomic method and establish a precise diagnostic model identifying this group of gliomas. A total of 140 patients with untreated primary gliomas were admitted between 2016 and 2020 to West China Hospital as a discovery cohort, including 22 IDHmut pTERTmut patients. Thirty-four additional cases from a different hospital were included in the study as an independent validation cohort. A total of 3654 radiomic features were extracted from the preoperative multimodal MRI images (T1c, FLAIR, and ADC maps) and filtered in a data-driven approach. The discovery cohort was split into training and test sets by a 4:1 ratio. A diagnostic model (multilayer perceptron classifier) for detecting the IDHmut pTERTmut gliomas was trained using an automatic machine-learning algorithm named tree-based pipeline optimization tool (TPOT). The most critical radiomic features in the model were identified and visualized. The model achieved an area under the receiver-operating curve (AUROC) of 0.971 (95% CI, 0.902-1.000), the sensitivity of 0.833 (95% CI, 0.333-1.000), and the specificity of 0.966 (95% CI, 0.931-1.000) in the test set. The area under the precision-recall curve (AUCPR) was 0.754 (95% CI, 0.572-0.833) and the F1 score was 0.833 (95% CI, 0.500-1.000). In the independent validation set, the model reached 0.952 AUROC, 0.714 sensitivity, 0.963 specificity, 0.841 AUCPR, and 0.769 F1 score. MR radiomic features of the IDHmut pTERTmut gliomas represented homogenous low-complexity texture in three modalities. An accurate diagnostic model was constructed for detecting IDHmut pTERTmut gliomas using multimodal radiomic features. The most important features were associated with the homogenous simple texture of IDHmut pTERTmut gliomas in MRI images transformed using Laplacian of Gaussian and wavelet filters.

Noninvasive Delineation of Glioma Infiltration with Combined 7T Chemical Exchange Saturation Transfer Imaging and MR Spectroscopy: A Diagnostic Accuracy Study.

For precise delineation of glioma extent, amino acid PET is superior to conventional MR imaging. Since metabolic MR sequences such as chemical exchange saturation transfer (CEST) imaging and MR spectroscopy (MRS) were developed, we aimed to evaluate the diagnostic accuracy of combined CEST and MRS to predict glioma infiltration. Eighteen glioma patients of different tumor grades were enrolled in this study; 18F-fluoroethyltyrosine (FET)-PET, amide proton transfer CEST at 7 Tesla(T), MRS and conventional MR at 3T were conducted preoperatively. Multi modalities and their association were evaluated using Pearson correlation analysis patient-wise and voxel-wise. Both CEST (R = 0.736, p < 0.001) and MRS (R = 0.495, p = 0.037) correlated with FET-PET, while the correlation between CEST and MRS was weaker. In subgroup analysis, APT values were significantly higher in high grade glioma (3.923 ± 1.239) and IDH wildtype group (3.932 ± 1.264) than low grade glioma (3.317 ± 0.868, p < 0.001) or IDH mutant group (3.358 ± 0.847, p < 0.001). Using high FET uptake as the standard, the CEST/MRS combination (AUC, 95% CI: 0.910, 0.907–0.913) predicted tumor infiltration better than CEST (0.812, 0.808–0.815) or MRS (0.888, 0.885–0.891) alone, consistent with contrast-enhancing and T2-hyperintense areas. Probability maps of tumor presence constructed from the CEST/MRS combination were preliminarily verified by multi-region biopsies. The combination of 7T CEST/MRS might serve as a promising non-radioactive alternative to delineate glioma infiltration, thus reshaping the guidance for tumor resection and irradiation.

Comprehensive analysis of m6A/m5C/m1A-related gene expression, immune infiltration, and sensitivity of antineoplastic drugs in glioma.

This research aims to develop a prognostic glioma marker based on m6A/m5C/m1A genes and investigate the potential role in the tumor immune microenvironment. Data for patients with glioma were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). The expression of genes related to m6A/m5C/m1A was compared for normal and glioma groups. Gene Ontology and Kyoto Encyclopedia of Genes and Gene enrichment analysis of differentially expressed genes were conducted. Consistent clustering analysis was performed to obtain glioma subtypes and complete the survival analysis and immune analysis. Based on TCGA, Lasso regression analysis was used to obtain a prognostic model, and the CGGA database was used to validate the model. The model-based risk scores and the hub genes with the immune microenvironment, clinical features, and antitumor drug susceptibility were investigated. The clinical glioma tissues were collected to verify the expression of hub genes via immunohistochemistry. Twenty genes were differentially expressed, Consensus cluster analysis identified two molecular clusters. Overall survival was significantly higher in cluster 2 than in cluster 1. Immunological analysis revealed statistically significant differences in 26 immune cells and 17 immune functions between the two clusters. Enrichment analysis detected multiple meaningful pathways. We constructed a prognostic model that consists of WTAP, TRMT6, DNMT1, and DNMT3B. The high-risk and low-risk groups affected the survival prognosis and immune infiltration, which were related to grade, gender, age, and survival status. The prognostic value of the model was validated using another independent cohort CGGA. Clinical correlation and immune analysis revealed that four hub genes were associated with tumor grade, immune cells, and antitumor drug sensitivity, and WTAP was significantly associated with microsatellite instability(MSI). Immunohistochemistry confirmed the high expression of WTAP, DNMT1, and DNMT3B in tumor tissue, but the low expression of TRMT6. This study established a strong prognostic marker based on m6A/m5C/m1A methylation regulators, which can accurately predict the prognosis of patients with gliomas. m6A/m5C/m1A modification mode plays an important role in the tumor microenvironment, can provide valuable information for anti-tumor immunotherapy, and have a profound impact on the clinical characteristics.