Prognosis Of Glioma Research Articles

10184-BT-14 CLINICAL FEATURE OF HEMISPHERIC GLIOMA WITH H3F3A, PEDIATRIC-TYPE HIGH GRADE GLIOMA, H3 K27-ALTERED, NEC AND DIFFUSE HEMISPHERIC GLIOMA, H3 G34-MUTANT, CNS WHO GRADE 4

Abstract INTRODUCTION Diffuse midline glioma (DMG), H3K27-altered, is a CNS WHO grade 4 glioma that usually located mainly in the brainstem, thalamus and spinal cord. However, DMG located in non-midline lesions are now described as pediatric-type high grade glioma, H3K27-altered, NEC (NDMG). On the other hand, diffuse hemispheric glioma, H3G34-mutant (DHG) located in the cerebral hemispheres, and is classified under the WHO 2021 classification. It is unknown that the differences in clinical characteristics of these hemispheric tumors with H3F3A mutations. In the present study, we report a comparative study of the clinical characteristics of two groups of NDMG and DHG. METHODS Among 4128 brain tumor samples collected in the Kansai Network for Molecular Diagnosis of Central Nervous System Tumors, 16 NDMG and 9 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). There was no significant difference in MGMT promoter methylation between NDMG and 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). There was no significant different survival rate between WHO grade 3 (n=15) and grade 4 (n=9) for pathological diagnosis. DISCUSSION AND CONCLUSION We compared the clinical characteristics of NDMG and DHG. There are some reports that NDMG and DHG gliomas located in non-midline lesion. Removing much tumor volume may improve the prognosis of non-midline glioma. We discuss the gliomas with H3F3A mutations located in a hemispheric lesions by literature review.

Leveraging a disulfidptosis‑related lncRNAs signature for predicting the prognosis and immunotherapy of glioma

BackgroundGliomas, a prevalent form of primary brain tumors, are linked with a high mortality rate and unfavorable prognoses. Disulfidptosis, an innovative form of programmed cell death, has received scant attention concerning disulfidptosis-related lncRNAs (DRLs). The objective of this investigation was to ascertain a prognostic signature utilizing DRLs to forecast the prognosis and treatment targets of glioma patients.MethodsRNA-seq data were procured from The Cancer Genome Atlas database. Disulfidptosis-related genes were compiled from prior research. An analysis of multivariate Cox regression and the least absolute selection operator was used to construct a risk model using six DRLs. The risk signature’s performance was evaluated via Kaplan-Meier survival curves and receiver operating characteristic curves. Additionally, functional analysis was carried out using GO, KEGG, and single-sample GSEA to investigate the biological functions and immune infiltration. The research also evaluated tumor mutational burden, therapeutic drug sensitivity, and consensus cluster analysis. Reverse transcription quantitative PCR was conducted to validate the expression level of DRLs.ResultsA prognostic signature comprising six DRLs was developed to predict the prognosis of glioma patients. High-risk patients had significantly shorter overall survival than low-risk patients. The robustness of the risk model was validated by receiver operating characteristic curves and subgroup survival analysis. Risk model was used independently as a prognostic indicator for the glioma patients. Notably, the low-risk patients displayed a substantial decrease in the immune checkpoints, the proportion of immune cells, ESTIMATE and immune score. IC50 values from the different risk groups allowed us to discern three drugs for the treatment of glioma patients. Lastly, the potential clinical significance of six DRLs was determined.ConclusionsA novel six DRLs signature was developed to predict prognosis and may provide valuable insights for patients with glioma seeking novel immunotherapy and targeted therapy.

Construction and validation of a risk model based on the key SNARE proteins to predict the prognosis and immune microenvironment of gliomas.

Synaptic transmission between neurons and glioma cells can promote glioma progression. The soluble N-ethylmaleimide-sensitive fusion factor attachment protein receptors (SNARE) play a key role in synaptic functions. We aimed to construct and validate a novel model based on the SNARE proteins to predict the prognosis and immune microenvironment of glioma. Differential expression analysis and COX regression analysis were used to identify key SRGs in glioma datasets, and we constructed a prognostic risk model based on the key SRGs. The prognostic value and predictive performance of the model were assessed in The Cancer Genome Atlas (TCGA) and Chinese glioma Genome Atlas (CGGA) datasets. Functional enrichment analysis and immune-related evaluation were employed to reveal the association of risk scores with tumor progression and microenvironment. A prognostic nomogram containing the risk score was established and assessed by calibration curves and time-dependent receiver operating characteristic curves. We verified the changes of the key SRGs in glioma specimens and cells by real-time quantitative PCR and Western blot analyses. Vesicle-associated membrane protein 2 (VAMP2) and vesicle-associated membrane protein 5 (VAMP5) were identified as two SRGs affecting the prognoses of glioma patients. High-risk patients characterized by higher VAMP5 and lower VAMP2 expression had a worse prognosis. Higher risk scores were associated with older age, higher tumor grades, IDH wild-type, and 1p19q non-codeletion. The SRGs risk model showed an excellent predictive performance in predicting the prognosis in TCGA and CGGA datasets. Differentially expressed genes between low- and high-risk groups were mainly enriched in the pathways related to immune infiltration, tumor metastasis, and neuronal activity. Immune score, stromal score, estimate score, tumor mutational burden, and expression of checkpoint genes were positively correlated with risk scores. The nomogram containing the risk score showed good performance in predicting the prognosis of glioma. Low VAMP2 and high VAMP5 were found in different grades of glioma specimens and cell lines. We constructed and validated a novel risk model based on the expression of VAMP2 and VAMP5 by bioinformatics analysis and experimental confirmation. This model might be helpful for clinically predicting the prognosis and response to immunotherapy of glioma patients.

The involvement of brain regions associated with lower KPS and shorter survival time predicts a poor prognosis in glioma.

Isocitrate dehydrogenase-wildtype glioblastoma (IDH-wildtype GBM) and IDH-mutant astrocytoma have distinct biological behaviors and clinical outcomes. The location of brain tumors is closely associated not only with clinical symptoms and prognosis but also with key molecular alterations such as IDH. Therefore, we hypothesize that the key brain regions influencing the prognosis of glioblastoma and astrocytoma are likely to differ. This study aims to (1) identify specific regions that are associated with the Karnofsky Performance Scale (KPS) or overall survival (OS) in IDH-wildtype GBM and IDH-mutant astrocytoma and (2) test whether the involvement of these regions could act as a prognostic indicator. A total of 111 patients with IDH-wildtype GBM and 78 patients with IDH-mutant astrocytoma from the Cancer Imaging Archive database were included in the study. Voxel-based lesion-symptom mapping (VLSM) was used to identify key brain areas for lower KPS and shorter OS. Next, we analyzed the structural and cognitive dysfunction associated with these regions. The survival analysis was carried out using Kaplan-Meier survival curves. Another 72 GBM patients and 48 astrocytoma patients from Harbin Medical University Cancer Hospital were used as a validation cohort. Tumors located in the insular cortex, parahippocampal gyrus, and middle and superior temporal gyrus of the left hemisphere tended to lead to lower KPS and shorter OS in IDH-wildtype GBM. The regions that were significantly correlated with lower KPS in IDH-mutant astrocytoma included the subcallosal cortex and cingulate gyrus. These regions were associated with diverse structural and cognitive impairments. The involvement of these regions was an independent predictor for shorter survival in both GBM and astrocytoma. This study identified the specific regions that were significantly associated with OS or KPS in glioma. The results may help neurosurgeons evaluate patient survival before surgery and understand the pathogenic mechanisms of glioma in depth.

Identification of FXYD6 as the novel biomarker for glioma based on differential expression and DNA methylation.

As a single-transmembrane protein of the FXYD family, FXYD6 plays different roles under physiological and pathological status, especially in the nervous system. This study aims to identify FXYD6 as a biomarker for glioma, by analyzing its expression and methylation patterns. Using TCGA and GTEx datasets, we analyzed FXYD6 expression in various tissues, confirming its levels in normal brain and different glioma grades via immunoblotting and immunostaining. FXYD6 biological functions were explored through enrichment analysis, and tumor immune infiltration was assessed using ESTIMATE and TIMER algorithms. Pearson correlation analysis probed FXYD6 associations with biological function-related genes. A glioma detection model was developed using FXYD6 methylation data from TCGA and GEO. Consistently, a FXYD6 methylation-based prognostic model was constructed for glioma via LASSO Cox regression. FXYD6 was observed to be downregulated in GBM and implicated in a range of cellular functions, including synapse formation, cell junctions, immune checkpoint, ferroptosis, EMT, and pyroptosis. Hypermethylation of specific FXYD6 CpG sites in gliomas was identified, which could be used to build a diagnostic model. Additionally, FXYD6 methylation-based prognostic model could serve as an independent factor as well. FXYD6 is a promising biomarker for the diagnosis and prognosis of glioma, with its methylation-based prognostic model serving as an independent factor. This highlights its potential in clinical application for glioma management.

Risk prediction and treatment assessment in glioma patients using SEER database: a prospective observational study

ObjectivesTo use a nomogram to predict the risk of mortality and estimate the impact of current treatment on the prognosis of glioma patients.MethodsA total of 3798 cases were obtained from...

Abstract B024: TrkB.T1 receptor promotes an immunosuppressive microenvironment driven by neutrophil recruitment in gliomas

Abstract Gliomas are the most common type of brain tumor in both children and adults. Communication between cancer cells and the brain tumor microenvironment (TME) is a fundamental component of brain cancer pathophysiology. Glioma cells release factors that function as chemoattractants and influence the TME. Reciprocally, the activity of neurons from the surrounding TME drives the proliferation and growth of glial malignancies through paracrine signaling, brain-derived neurotrophic factor (BDNF) being a key secreted factor. BDNF binds with high affinity to the tropomyosin receptor kinase B (TrkB). Recent work from our group has shown that the TrkB.T1 splice variant is upregulated in human gliomas. In addition, TrkB.T1 overexpression enhances the tumor aggressiveness in vivo and is associated with the downregulation of genes involved in facilitating tumor cell recognition and elimination in vitro. However, the role of TrkB.T1 splice variant in this bidirectional communication between glioma cells and the surrounding cells remains unknown. Our aim was to assess if increased levels of TrkB.T1 observed in gliomas harbor a role in modulating immune responses. Thus, we explored the immune cell heterogeneity associated with increased levels of TrkB.T1 in vivo using a glioma mouse model engineered with RCAS/tv-a technology. Tumors overexpressing TrkB.T1 show decreased overall immune infiltration but increased neutrophil recruitment. Neutrophils have been associated with unfavorable prognosis in gliomas, a decrease in the tumor-infiltrating effector lymphocytes, and worst patterns of response to immunotherapy. In fact, we also observe a decrease in the CD8+ population when TrkB.T1 is overexpressed, suggesting that TrkB.T1 might support an immunosuppressive microenvironment. Thus, we next explored in vitro the communication mechanisms associated with an increase in TrkB.T1 using 3T3 cells that were transduced with pLJM1-lentivirus to overexpress TrkB.T1. These cells were serum-starved and treated with BDNF and the conditioned media was subjected to a cytokine multiplex analysis. The results show that TrkB.T1 significantly increases key chemokine levels previously described to be involved in the recruitment of neutrophils. Taken together, this work shows that the highly expressed TrkB.T1 receptor in gliomas might support an immunosuppressive microenvironment through the recruitment of neutrophils and represents a potential target for modulating glioma-immune cell interactions needed to curb disease progression, and warrants further investigation. Citation Format: Leyre Merino-Galan, Sergio Ortiz-Espinosa, Matthew Hathaway, Ashmitha Rajendran, Hawa Larissa Jagana, Gabriel Rubio, Maryam Shabar, Noemi Reche-Ley, Siobhan S Pattwell. TrkB.T1 receptor promotes an immunosuppressive microenvironment driven by neutrophil recruitment in gliomas [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr B024.

An Intra- and Inter-Modality Fusion Model with Invariant- and Specific-Constraints Using MR Images for Prediction of Glioma Isocitrate Dehydrogenase Mutation Status

In the 2021 World Health Organization classification of gliomas, it is proposed that Isocitrate Dehydrogenase (IDH) plays a key role. The prognosis of glioma is largely affected by IDH mutation status. Therefore, IDH mutation status needs to be predicted in advance before surgery. In the past decade, with the development of machine learning, more and more machine learning methods, especially deep learning methods, have been applied to the development of computer-aided diagnosis systems. At present, in this field, many deep learning and radiomics based methods have been proposed for IDH prediction using multimodal Magnetic Resonance Imaging (MRI). In this study, we proposed an intra- and inter-modality fusion model with invariant- and specific- constraints to improve the performance of IDH status prediction. First, MRI-based radiomics features were fused with deep learning features in each modality (intra-modality fusion) and then the features extracted from each modality of brain MRI were fused by using an inter-modality fusion model with invariant and specific constraints. We experimented our proposed method on the dataset provided by the Affiliated Hospital of Zhengzhou University in Zhengzhou, China and demonstrated the effectiveness of the proposed method. In our study, we propose two inter-modality fusion models, and our experimental results show that our best proposed method outperformed state-of-the-art methods with an accuracy of 0.79, precision of 0.80, recall of 0.75, and F1 score of 0.78. Thus, we predicted the IDH mutation status for glioma treatment with a 2% increase in accuracy and 4% increase in precision to predict the IDH mutation status for glioma treatment.

Identification of RP11-770J1.4 as immune-related lncRNA regulating the CTXN1-cGAS-STING axis in histologically lower-grade glioma.

Human gliomas are lethal brain cancers. Emerging evidence revealed the regulatory role of long noncoding RNAs (lncRNAs) in tumors. Here, we performed a comprehensive analysis of the expression profiles of RNAs in histologically lower-grade glioma (LGG). Enrichment analysis revealed that glioma is influenced by immune-related signatures. Survival analysis further established the close correlation between network features and glioma prognosis. Subsequent experiments showed lncRNA RP11-770J1.4 regulates CTXN1 expression through hsa-miR-124-3p. Correlation analysis identified lncRNA RP11-770J1.4 was immune related, specifically involved in the cytosolic DNA sensing pathway. Downregulated lncRNA RP11-770J1.4 resulted in increased spontaneous gene expression of the cGAS-STING pathway. Single-cell RNA sequencing analysis, along with investigations in a glioblastoma stem cell model and patient sample analysis, demonstrated the predominant localization of CTXN1 within tumor cores rather than peripheral regions. Immunohistochemistry staining established a negative correlation between CTXN1 expression and infiltration of CD8+ T cells. In vivo, Ctxn1 knockdown in GL261 cells led to decreased tumor burden and improved survival while increasing infiltration of CD8+ T cells. These findings unveil novel insights into the lncRNA RP11-770J1.4-CTXN1 as a potential immune regulatory axis, highlighting its therapeutic implications for histologically LGGs.

TREM1 as a novel prognostic biomarker and tumor immune microenvironment evaluator in glioma.

Glioma is the most malignant tumor in the central nervous system with a poor prognosis. The tumor immune microenvironment plays a crucial role in glioma formation and progress. TREM1, as a vital immune regulator, has not been investigated in glioma. This study aims to explore the role of TREM1 in prognosis and tumor immune microenvironment of glioma. The mRNA expression level of TREM1 was collected from TCGA and GEO databases. The correlations between the clinic-pathological features and TREM1 expression were analyzed using Cox regression analysis. Kaplan-Meier was used to evaluate the effect of TREM1 on OS. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes were performed to analyze the functional annotations and signaling pathways of the TREM1 coexpression genes. ESTIMATE and TIMER explored the correlations between TREM1 and immune cell infiltration. Spearman correlation analysis was conducted to examine the association between the TREM1 and immune checkpoint expression. The expression level of TREM1 was significantly increased in glioma. TREM1 overexpression was positively related to poor prognosis, higher World Health Organization grade, isocitrate dehydrogenase wildtype, and 1p/19q non-codeletion. TREM1 coexpression genes were mainly related to immunoregulation and inflammatory response. TREM1 participated in the initiation and progression of glioma by regulating immune cell infiltration and expression of immune checkpoints. TREM1 is an effective prognostic and diagnostic biomarker in glioma. It can be adopted as a novel predictor for clinical prognosis, pathological characteristics, and immune microenvironment in glioma patients.

A Prediction Model for Deciphering Intratumoral Heterogeneity Derived from the Microglia/Macrophages of Glioma Using Non-Invasive Radiogenomics.

Microglia and macrophages play a major role in glioma immune responses within the glioma microenvironment. We aimed to construct a prognostic prediction model for glioma based on microglia/macrophage-correlated genes. Additionally, we sought to develop a non-invasive radiogenomics approach for risk stratification evaluation. Microglia/macrophage-correlated genes were identified from four single-cell datasets. Hub genes were selected via lasso-Cox regression, and risk scores were calculated. The immunological characteristics of different risk stratifications were assessed, and radiomics models were constructed using corresponding MRI imaging to predict risk stratification. We identified eight hub genes and developed a relevant risk score formula. The risk score emerged as a significant prognostic predictor correlated with immune checkpoints, and a relevant nomogram was drawn. High-risk groups displayed an active microenvironment associated with microglia/macrophages. Furthermore, differences in somatic mutation rates, such as IDH1 missense variant and TP53 missense variant, were observed between high- and low-risk groups. Lastly, a radiogenomics model utilizing five features from magnetic resonance imaging (MRI) T2 fluid-attenuated inversion recovery (Flair) effectively predicted the risk groups under a random forest model. Our findings demonstrate that risk stratification based on microglia/macrophages can effectively predict prognosis and immune functions in glioma. Moreover, we have shown that risk stratification can be non-invasively predicted using an MRI-T2 Flair-based radiogenomics model.

Identification of telomere-associated gene signatures to predict prognosis and drug sensitivity in glioma

ObjectiveGliomas are a heterogeneous group of brain tumors with distinct biological and clinical properties, leading to significant mortality and morbidity. Emerging evidence shows telomere maintenance has implicated in glioma susceptibility and prognosis. In this study, we comprehensively analyzed gene signatures related to telomere maintenance in glioma and their predictive values for predicting the prognosis and drug sensitivity in glioma. MethodsWe initially identified telomere-related genes differentially expressed between low-grade glioma (LGG) and glioblastoma (GBM) and accordingly developed a risk model by univariate and multivariate Cox analysis to assess the expressions of telomere-related genes across the risk groups. Finally, to assess these genes in immune function the anti-tumor medications often used in the clinical treatment of glioma, we computed immune cell infiltration analysis and drug sensitivity analysis. ResultsThe consensus clustering analysis identified 20 telomere-related genes which split LGG patients into two distinct subtypes. The patient survival, the expressions of key telomere-related DEGs, and immune cell infiltration significantly differed between Cluster 1 and Cluster 2. The LASSO risk model [riskScore=(0.086)*HOXA7+(0.242)*WEE1+(0.247)*IGF2BP3+(0.052)*DUSP10] showed significant differences regarding the 1-, 3-, 5-year overall survival, immune cell infiltration, and drug sensitivity between high- and low-risk groups. The predictive nomogram constructed to quantify the survival probability of each sample at 1, 3, and 5 years was consistent with the actual patient survival. ConclusionOur comprehensive characterization of telomere-associated gene signatures in glioma reveals their possible roles in the development, tumor microenvironment, and prognosis. The study provides some suggestive relationships between four telomere-related genes (HOXA7, WEE1, IGF2BP3, and DUSP10) and glioma prognosis.

MrGPS: an m6A-related gene pair signature to predict the prognosis and immunological impact of glioma patients.

N6-methyladenosine (m6A) RNA methylation is the predominant epigenetic modification for mRNAs that regulates various cancer-related pathways. However, the prognostic significance of m6A modification regulators remains unclear in glioma. By integrating the TCGA lower-grade glioma (LGG) and glioblastoma multiforme (GBM) gene expression data, we demonstrated that both the m6A regulators and m6A-target genes were associated with glioma prognosis and activated various cancer-related pathways. Then, we paired m6A regulators and their target genes as m6A-related gene pairs (MGPs) using the iPAGE algorithm, among which 122 MGPs were significantly reversed in expression between LGG and GBM. Subsequently, we employed LASSO Cox regression analysis to construct an MGP signature (MrGPS) to evaluate glioma prognosis. MrGPS was independently validated in CGGA and GEO glioma cohorts with high accuracy in predicting overall survival. The average area under the receiver operating characteristic curve (AUC) at 1-, 3- and 5-year intervals were 0.752, 0.853 and 0.831, respectively. Combining clinical factors of age and radiotherapy, the AUC of MrGPS was much improved to around 0.90. Furthermore, CIBERSORT and TIDE algorithms revealed that MrGPS is indicative for the immune infiltration level and the response to immune checkpoint inhibitor therapy in glioma patients. In conclusion, our study demonstrated that m6A methylation is a prognostic factor for glioma and the developed prognostic model MrGPS holds potential as a valuable tool for enhancing patient management and facilitating accurate prognosis assessment in cases of glioma.

DNALI1 is a prognosis-related biomarker and correlates with immune infiltrates in low grade glioma.

Dynein axonemal light intermediate chain 1 (DNALI1) is a component of axonemal dyneins and its role in cancer progression is not known. The influence of DNALI1 expression on the prognosis of low-grade gliomas (LGG) and the possible mechanisms of DNALI1 in promoting the progression of LGG was investigated by applying multiple bioinformatics analyses using datasets from TCGA, GTEx, CPTAC, and CGGA. The expression of DNALI1 in different tumor tissues including LGG was investigated. GO functional annotation, KEGG pathway analysis, and GSEA enrichment analysis were performed. The correlation between DNALI1 and prognosis, tumor microenvironment (TME) and immune checkpoints in LGG were assessed. DNALI1 is mainly expressed in malignant cells in the TME of LGG and positively correlated with the development of LGG. DNALI1 expression is negatively correlated with isocitrate dehydrogenase (IDH) mutations and 1p/19q co-deletion. High DNALI1 expression is associated with poor prognosis in LGG. DNALI1 may promote LGG progression through multiple immune-related pathways. The expression of DNALI1 is positively correlated with the infiltration of certain types of immune cells and the expression of some immune checkpoints. DNALI1 is a potential prognostic marker for LGG, and high expression of DNALI1 may play an important role in maintaining the immunosuppressive microenvironment of LGG.

Integrating bulk and single-cell RNA sequencing data reveals epithelial-mesenchymal transition molecular subtype and signature to predict prognosis, immunotherapy efficacy, and drug candidates in low-grade gliomas.

Objective: Epithelial-mesenchymal transition (EMT) is a tightly regulated and dynamic process occurring in both embryonic development and tumor progression. Our study aimed to comprehensively explore the molecular subtypes, immune landscape, and prognostic signature based on EMT-related genes in low-grade gliomas (LGG) in order to facilitate treatment decision-making and drug discovery. Methods: We curated EMT-related genes and performed molecular subtyping with consensus clustering algorithm to determine EMT expression patterns in LGG. The infiltration level of diverse immune cell subsets was evaluated by implementing the single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE algorithms. The distinctions in clinical characteristics, mutation landscape, and immune tumor microenvironment (TME) among the subtypes were subjected to further investigation. Gene Set Variation Analysis (GSVA) was performed to explore the biological pathways that were involved in subtypes. The chemo drug sensitivity and immunotherapy of subtypes were estimated through GDSC database and NTP algorithm. To detect EMT subtype-related prognostic gene modules, the analysis of weighted gene co-expression network (WGCNA) was performed. The LASSO algorithm was utilized to construct a prognostic risk model, and its efficacy was verified through an independent CGGA dataset. Finally, the expression of the hub genes from the prognostic model was evaluated through the single-cell dataset and in-vitro experiment. Results: The TCGA-LGG dataset revealed the creation of two molecular subtypes that presented different prognoses, clinical implications, TME, mutation landscapes, chemotherapy, and immunotherapy. A three-gene signature (SLC39A1, CTSA and CLIC1) based on EMT expression pattern were established through WGCNA analysis. Low-risk patients showed a positive outlook, increased immune cell presence, and higher expression of immune checkpoint proteins. In addition, several promising drugs, including birinapant, fluvastatin, clofarabine, dasatinib, tanespimycin, TAK-733, GDC-0152, AZD8330, trametinib and ingenol-mebutate had great potential to the treatment of high risk patients. Finally, CTSA and CLIC1 were highly expressed in monocyte cell through single-cell RNA sequencing analysis. Conclusion: Our research revealed non-negligible role of EMT in the TME diversity and complexity of LGG. A prognostic signature may contribute to the personalized treatment and prognostic determination.

Cancer-associated fibroblast-associated gene IGFBP2 promotes glioma progression through induction of M2 macrophage polarization.

We elucidated the molecular mechanism of cancer-associated fibroblast (CAF)-associated gene insulin-like growth factor binding protein-2 (IGFBP2)-induced M2 macrophage polarization in the tumor microenvironment involved in glioma progression. The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) provided bulk RNA-sequencing datasets, ESTIMATE scores for glioma stromal cells, and overall survival-clinicopathological correlation analyses. TIMER provided CAF abundance in the TCGA glioma-related dataset, differential gene analysis was performed for high- and low-CAF groups, and weighted gene coexpression network analysis identified CAF-related genes. Univariate and multifactorial cyclooxygenase (COX) regression analyses created the CAF risk models single sample gene set enrichment analysis, CIBERSORT, and GSE84465. Mice were implanted with gliomas, and Western blot and RT-quantitative PCR showed IGFBP2 in tumor tissues. Adeno-associated virus (AAV) decreased IGFBP2, flow cytometry measured M1 and M2 macrophage ratios, and immunohistochemistry detected markers. TCGA and CGGA transcriptome data showed malignant gliomas had higher stromal cell scores and worse prognoses. Low- and high-CAF TCGA gliomas were detected, and differential expression, WGCNA, and multifactorial COX identified 132 CAF-related genes and seven high-risk genes (CPQ, EFEMP2, IGFBP2, RAB42, TNFRSF12A, and VASN). Neither CAF risk score, grade, nor 1p/19q affected glioma prognosis. CAF only enriched EFEMP2 and IGFBP2. Gene Expression Profiling Interactive Analysis compared EFEMP2 and IGFBP2 expression in normal brain tissue and gliomas. Low-grade glioma and malignant glioblastoma highly expressed IGFBP2 and EFEMP2. GSEA raised IGFBP2. CIBERSORT linked M2 macrophage infiltration to TCGA glioma immune cell subpopulation IGFBP2 expression. IGFBP2 knockdown stopped mouse glioma and M2 macrophage polarization. CAF plays a procarcinogenic role in glioma, and the CAF-related gene IGFBP2 could promote glioma progression by inducing M2 macrophage polarization.NEW & NOTEWORTHY The cancer-associated fibroblast (CAF)-related gene insulin-like growth factor binding protein-2 (IGFBP2) is highly expressed in gliomas and is associated with poor prognosis. CAF-related gene IGFBP2 promotes glioma progression by inducing polarization of M2 macrophages. This study provides a new basis for an in-depth investigation of the functional mechanisms of the glioma tumor microenvironment and the search for key genes involved in immune regulation in CAF.

Ferroptosis sensitization in glioma: exploring the regulatory mechanism of SOAT1 and its therapeutic implications

Glioma, the most common primary malignant tumor of the central nervous system, lacks effective targeted therapies. This study investigates the role of SOAT1, a key gene involved in cholesterol esterification, in glioma prognosis and its association with ferroptosis. Although the impact of SOAT1 on glioma prognosis has been recognized, its precise mechanism remains unclear. In this study, we demonstrate that inhibiting SOAT1 increases the sensitivity of glioma cells to ferroptosis, both in vitro and in vivo. Mechanistically, SOAT1 positively modulates the expression of SLC40A1, an iron transporter, resulting in enhanced intracellular iron outflow, reduced intracellular iron levels, and subsequent disruption of ferroptosis. Importantly, we find that SOAT1 regulates ferroptosis independently of SREBPs, which are known to be involved in ferroptosis regulation. Furthermore, we identify the involvement of the PI3K-AKT-mTOR signaling pathway in mediating the regulatory effects of SOAT1 on SLC40A1 expression and ferroptosis sensitivity. These findings highlight the contribution of intracellular signaling cascades in the modulation of ferroptosis by SOAT1. We show that inhibiting SOAT1 enhances the efficacy of radiotherapy in gliomas, both in vitro and in vivo, by promoting sensitivity to ferroptosis. This suggests that targeting SOAT1 could potentially improve therapeutic outcomes for glioma patients. In summary, this study uncovers the pivotal role of SOAT1 as a link between cholesterol esterification and ferroptosis in glioma. Our findings underscore the potential of SOAT1 as a promising clinical therapeutic target, providing new avenues for the development of effective treatments for glioma. Further research is warranted to unravel the complete regulatory mechanisms of SOAT1 and explore its clinical applications.

Autophagy Intervened by MicroRNAs Causes Gliomas

miRNAs are found in organisms like animals, plants and a few viruses. They play a role in the modulation of post-transcriptional genome function and in the suppression of RNA. Glial cells, which support the functioning of the neuron (the alternative major type of brain cell), are the cause of brain tumors known as gliomas. Gliomagenesis is the process of the formation and growth of gliomas. A solitary miRNA has the ability to regulate several receptors at distinct stages of autophagy. Numerous miRNAs associated to autophagy were implicated in various phases of the development and advancement of carcinoma. These regulate a number of crucial metabolic processes, such as the cancer autophagic reflex. It has been observed that the activity of genes involved in gliomagenesis, tumor growth, proliferation, apoptosis and posttranscriptional control of anti-oncogenes is impacted by microRNA (miRNA) expression profile. Gliomas may thus deteriorate as a result of compromised miRNAs. The prognosis, therapeutic response and glioma origin may all be determined by miRNA profiling. miRNAs have the ability to be released into circulation and Cerebrospinal Fluid (CSF). They can also be transferred freely or via exosomes between normal and tumor cells, changing them into possible biomarkers for prognosis and/or diagnosis for gliomas.

Significance of NotchScore and JAG1 in predicting prognosis and immune response of low-grade glioma.

Low-grade glioma (LGG) is a prevalent malignant tumor in the intracranial region. Despite the advancements in treatment methods for this malignancy over the past decade, significant challenges still persist in the form of drug resistance and tumor recurrence. The Notch signaling pathway plays essential roles in many physiological processes as well as in cancer development. However, the significance of the pathway and family genes in LGG are poorly understood. We conducted gene expression profiling analysis using the TCGA dataset to investigate the gene set associated with the Notch signaling pathway. we have proposed a metric called "NotchScore" that quantifies the strength of the Notch signaling pathway and enables us to assess its significance in predicting prognosis and immune response in LGG. We downregulated JAG1 in low-grade gliomas to assess its influence on the proliferation and migration of these tumors. Ultimately, we determined the impact of the transcription factor VDR on the transcription of PDL1 through chip-seq data analysis. Our findings indicate that tumors with a higher NotchScore, exhibit poorer prognosis, potentially due to their ability to evade the anti-tumor effects of immune cells by expressing immune checkpoints. Among the genes involved in the Notch signaling pathway, JAG1 has emerged as the most representative in terms of capturing the characteristics of both NotchScore and Notch pathways. The experimental results demonstrate that silencing JAG1 yielded a significant decrease in tumor cell proliferation in LGG cell lines. Our study revealed mechanisms by which tumors evade the immune system through the modulation of PDL1 transcription levels via the PI3K-Akt signaling pathway. Additionally, JAG1 potentially influences PDL1 in LGG by regulating the PI3K-Akt signaling pathway and the expression of the transcription factor VDR. These findings contribute to our understanding of immune evasion by tumors in LGG. The insights gained from this research may have implications for the development of therapeutic interventions for LGG.

IMMU-57. EFFECT OF THE ONCOMETABOLITE D2HG ON MYELOID-DERIVED SUPPRESSOR CELL POPULATIONS

Abstract Mutations in the isocitrate dehydrogenase 1/2 (IDH1/2) enzyme correlate with better prognosis of gliomas, partly due to enhanced infiltration of nonimmunosuppressive granulocytic cells compared to IDH wild-type (IDHwt) tumors. Altered cytokine/chemokine secretion from tumor cells and reprogramming of myeloid cell metabolism are among the factors that drive differences in immune profiles of IDHwt vs. IDHmut tumors. IDH mutant protein produces the oncometabolite D-2-hydroxyglutarate (D2HG) instead of the canonical alpha-ketoglutarate (αKG), a co-factor for histone and DNA demethylases. Since D2HG is known to be secreted into the tumor microenvironment (TME), we interrogated the effect of this metabolite on the epigenetic landscape and behavior of granulocytic and monocytic myeloid-derived suppressor cells (g/mMDSCs). Co-culturing bone marrow cells with either IDHmut or IDHwt glioma cells demonstrated that mMDSCs, which we previously showed to be the abundant tumor infiltrating MDSC subtype in IDHwt tumors, but not gMDSCs specifically experience higher levels of apoptosis when exposed to IDHmut cells. Treatment of bone marrow cells with physiologically relevant concentrations of either D2HG or αKG demonstrated that D2HG re-capitulates the pro-apoptotic effect on mMDSCs. Furthermore, co-cultures of IDHmut glioma cells and bone-marrow cells induced a pronounced increase in global methylation on mMDSCs specifically, and we observed that mMDSCs and gMDSCs differentially express histone demethylases via western blotting. Collectively, these results suggest that D2HG can differentially impact mMDSC vs gMDSC biology by epigenetic reprogramming. Future studies will elucidate the specific targets of D2HG in mMDSCs that renders these cells more susceptible to apoptosis with the goal of identifying the mechanisms that can be modulated to down-regulate mMDSC infiltration and/or survival within the TME.