Prognosis Of Low-grade Gliomas Research Articles

Cancer-Associated Fibroblast Subtypes Reveal Distinct Gene Signatures in the Tumor Immune Microenvironment of Vestibular Schwannoma.

Cancer-associated fibroblast (CAF) composition within the same organ varies across different cancer subtypes. Distinct CAF subtypes exhibit unique features due to interactions with immune cells and the tumor microenvironment. However, data on CAF subtypes in individuals with vestibular schwannoma (VS) are lacking. Therefore, we aimed to distinguish CAF subtypes at the single-cell level, investigate how stem-like CAF characteristics influence the tumor immune microenvironment, and identify CAF subtype-specific metabolic reprogramming pathways that contribute to tumor development. Data were analyzed from three patients with VS, encompassing 33,081 single cells, one bulk transcriptome cohort, and The Cancer Genome Atlas Pan-Cancer database (RNA sequencing and clinical data). Our findings revealed that antigen-presenting CAFs are linked to substantially heightened immune activity, supported by metabolic reprogramming, which differs from tumorigenesis. High expression of the stem-like CAF gene signature correlated with poor prognosis in low-grade gliomas within the pan-cancer database. This is the first study to classify CAF subtypes in VS patients and identify a therapeutic vulnerability biomarker by developing a stem-like CAF gene signature. Personalized treatments tailored to individual patients show promise in advancing precision medicine.

Selenoprotein S (SELENOS) is a potential prognostic biomarker for brain lower grade glioma

BackgroundSelenium, an essential micronutrient, primarily exists as selenocysteine in various selenoproteins. Selenoprotein S (SELENOS) is crucial in the development of human cancer. This study aimed to explore the correlation between SELENOS gene expression and the prognosis of brain lower-grade glioma (LGG). MethodsSELENOS protein and mRNA expression in human normal and tumor tissues were explored through the HPA database. SELENOS expression differences between normal and tumor tissues, along with its prognostic significance in gliomas, were analyzed using the TCGA, GTEx datasets, while the CGGA dataset was used to further assess its prognostic potential in a Chinese cohort. The association between SELENOS expression and tumor immune infiltration was also assessed. Multivariate and univariate Cox models were used to screen for clinicopathological parameters associated with SELENOS expression. The GDSC datasets was utilized to explore the connection between SELENOS and chemotherapeutic responses in LGG. A protein-protein interaction network for SELENOS was created. SELENOS expression in LGG cell lines were determined by Western blotting and qRT-PCR, and its functions were ascertained by routine in vitro experiments. ResultsSELENOS was upregulated in 11 cancers and downregulated in 10 cancers relative to the corresponding normal tissues, and correlated significantly with the prognosis, especially for GBM, LGG and GBMLGG. Furthermore, It displayed a positive correlation with immune cell infiltration levels in LGG. Multivariate and Univariate Cox analyses confirmed that the impact of SELENOS on the prognosis of LGG is the combined result of factors such as age and tumor grade. The expression of SELENOS was significantly negatively correlated with temozolomide IC50 in LGG. We found that SELENOS interacts with 10 proteins, which are upregulated in LGG compared to human normal tissues. The expression of these interactors is positively correlated with SELENOS expression and LGG survival/prognosis. In vitro experiments confirmed the aberrant expression of SELENOS in LGG cell lines, and siRNA-mediated knockdown of SELENOS reduced the proliferation, viability, invasion and migration of LGG cells, and induced apoptosis. ConclusionsSELENOS is a potential prognostic marker and therapeutic target for LGG, and its low expression is associated with favorable prognosis in LGG.

The prognostic significance of androgen receptor expression in gliomas

Androgen receptor (AR) overexpression has been identified in gliomas and its stem cells, suggesting that AR plays an important role in tumor carcinogenesis. The prognostic significance of AR overexpression in gliomas remains unknown. AR mRNA expression in gliomas and relevant clinical data were obtained from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. AR expression levels were compared across gliomas of different histopathologic grades and molecular subtypes. Kaplan–Meier analyses in patients with different AR expression levels were investigated for the potential prognostic values of AR. Compared with normal brain tissue, gliomas show significantly higher AR mRNA expression (p < 0.01). AR mRNA expression was more prominent in higher grade disease and in worse prognostic molecular subtypes (p < 0.01). AR protein is more abundant in glioblastoma than in lower grade gliomas (LGG) (grade 2/3) (p < 0.0001). This is corroborated by a linear association between AR mRNA and protein expression (r = 0.65). In LGG, both higher AR mRNA and protein expression was associated with significantly worse overall survival (OS). Five-year OS for LGG patients with high versus low AR expression were 59.1% and 73.3%, respectively (p < 0.0001). AR expression is not prognostic for OS within glioblastoma patients. Gender was not associated with AR expression or prognosis. Higher AR expression levels are associated with higher grade disease and histopathologic features predicting poorer prognosis in lower grade gliomas. Higher gene expression in LGG patients is correlated with poor prognosis but not in the glioblastoma cohort suggesting saturated expression/functions of AR in glioblastoma.

Prognostic relevance and validation of ARPC1A in the progression of low-grade glioma.

Low-grade glioma (LGG) is a grade II-III glioma accompanied by distinct clinical and molecular characteristics and the studies related to its prognosis are still unclear. The objective of this study is to explore the involvement of mitochondrial-related genes SLBP, COMMD7, LSM4, TOMM34, RPP40, FKBP1A, ARPC1A, and TBCA for the prognosis of LGG. We detected differences in the expression of some of the genes by analyzing the bioinformatics dataset and combining it with RT-PCR experiments. Subsequently, a nomogram was constructed and validated for the clinical relevance of risk factors such as age, WHO grade, IDH mutation status, Ch.1p19q co-deletion status, and high and low expression of ARPC1A to predict the 1-, 3-, 5-year overall survival and prognostic relevance of ARPC1A. Gene set enrichment analysis was performed for the relevant datasets pertinent to the expression of ARPC1A to elucidate the cancer-promoting pathways involved in the LGG through KEGG and GO analysis. Transfection assays, CCK-8 assays, and flow cytometry were used to determine the proliferation rate, and apoptosis rate of the HS683 and SW1783 cell lines respectively. Western blotting was used to examine the involvement of the cancer-promoting activity of ARPC1A through MAPK signaling. In this study, the prognostic value of ARPC1A in LGG was found by bioinformatics analysis combined with experimental approach analysis and may be a significant independent risk factor. ARPC1A fosters a higher LGG proliferation rate that may control the MAP kinase signaling and could be a prominent biomarker for LGG. Future studies are warranted to explore its clinical implications.

Mitochondrial RNA modification-based signature to predict prognosis of lower grade glioma: a multi-omics exploration and verification study

Mitochondrial RNA modification (MRM) plays a crucial role in regulating the expression of key mitochondrial genes and promoting tumor metastasis. Despite its significance, comprehensive studies on MRM in lower grade gliomas (LGGs) remain unknown. Single-cell RNA-seq data (GSE89567) was used to evaluate the distribution functional status, and correlation of MRM-related genes in different cell types of LGG microenvironment. We developed an MRM scoring system by selecting potential MRM-related genes using LASSO regression analysis and the Random Survival Forest algorithm, based on multiple bulk RNA-seq datasets from TCGA, CGGA, GSE16011, and E-MTAB-3892. Analysis was performed on prognostic and immunological features, signaling pathways, metabolism, somatic mutations and copy number variations (CNVs), treatment responses, and forecasting of potential small-molecule agents. A total of 35 MRM-related genes were selected from the literature. Differential expression analysis of 1120 normal brain tissues and 529 LGGs revealed that 22 and 10 genes were upregulated and downregulated, respectively. Most genes were associated with prognosis of LGG. METLL8, METLL2A, TRMT112, and METTL2B were extensively expressed in all cell types and different cell cycle of each cell type. Almost all cell types had clusters related to mitochondrial RNA processing, ribosome biogenesis, or oxidative phosphorylation. Cell–cell communication and Pearson correlation analyses indicated that MRM may promoting the development of microenvironment beneficial to malignant progression via modulating NCMA signaling pathway and ICP expression. A total of 11 and 9 MRM-related genes were observed by LASSO and the RSF algorithm, respectively, and finally 6 MRM-related genes were used to establish MRM scoring system (TRMT2B, TRMT11, METTL6, METTL8, TRMT6, and TRUB2). The six MRM-related genes were then validated by qPCR in glioma and normal tissues. MRM score can predict the malignant clinical characteristics, abundance of immune infiltration, gene variation, clinical outcome, the enrichment of signaling pathways and metabolism. In vitro experiments demonstrated that silencing METTL8 significantly curbs glioma cell proliferation and enhances apoptosis. Patients with a high MRM score showed a better response to immunotherapies and small-molecule agents such as arachidonyl trifluoromethyl ketone, MS.275, AH.6809, tacrolimus, and TTNPB. These novel insights into the biological impacts of MRM within the glioma microenvironment underscore its potential as a target for developing precise therapies, including immunotherapeutic approaches.

A cuproptosis-related gene DLAT as a novel prognostic marker and its relevance to immune infiltration in low-grade gliomas

DLAT has been recognized as a cuproptosis-related gene that is crucial for cuproptosis in earlier research. The study is to look at how DLAT affects individuals with low-grade glioma's prognosis and immune infiltration. The Genotype-Tissue Expression (GTEx) database and the TCGA database were used in this work to download RNAseq data in TPM format. DLAT was found to be overexpressed in LGG by comparing DLAT expression levels between LGG and normal brain tissue, and the expression of DLAT was verified by immunohistochemistry and semi-quantitative analysis. Then, the functional enrichment analysis revealed that the biological functional pathways and possible signal transduction pathways involved were primarily focused on extracellular matrix organization, transmembrane transporter complex, ion channel complex, channel activity, neuroactive ligand-receptor interaction, complement and coagulation cascades, and channel activity. The level of immune cell infiltration by plasmacytoid dendritic cells and CD8 T cells was subsequently evaluated using single-sample gene set enrichment analysis, which showed that high DLAT expression was inversely connected with that level of infiltration. The link between the methylation and mRNA transcription of DLAT was then further investigated via the MethSurv database, and the results showed that DLAT's hypomethylation status was linked to a poor outcome. Finally, by evaluating the prognostic value of DLAT using the Cox regression analysis and Kaplan-Meier technique, a column line graph was created to forecast the overall survival (OS) rate at 1, 3, and 5 years after LGG identification. The aforementioned results demonstrated that high DLAT expression significantly decreased OS and DSS, and that overexpression of DLAT in LGG was significantly linked with WHO grade, IDH status, primary therapy outcome, overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) events. DLAT was discovered as a separate predictive sign of OS in the end. DLAT might thus represent a brand-new predictive biomarker.

Glutathione metabolism-related gene signature predicts prognosis and treatment response in low-grade glioma.

Cancer cells can induce molecular changes that reshape cellular metabolism, creating specific vulnerabilities for targeted therapeutic interventions. Given the importance of reactive oxygen species (ROS) in tumor development and drug resistance, and the abundance of reduced glutathione (GSH) as the primary cellular antioxidant, we examined an integrated panel of 56 glutathione metabolism-related genes (GMRGs) across diverse cancer types. This analysis revealed a remarkable association between GMRGs and low-grade glioma (LGG) survival. Unsupervised clustering and a GMRGs-based risk score (GS) categorized LGG patients into two groups, linking elevated glutathione metabolism to poorer prognosis and treatment outcomes. Our GS model outperformed established clinical prognostic factors, acting as an independent prognostic factor. GS also exhibited correlations with pro-tumor M2 macrophage infiltration, upregulated immunosuppressive genes, and diminished responses to various cancer therapies. Experimental validation in glioma cell lines confirmed the critical role of glutathione metabolism in glioma cell proliferation and chemoresistance. Our findings highlight the presence of a unique metabolic susceptibility in LGG and introduce a novel GS system as a highly effective tool for predicting the prognosis of LGG.

A multi-omics analysis-based model to predict the prognosis of low-grade gliomas

Lower-grade gliomas (LGGs) exhibit highly variable clinical behaviors, while classic histology characteristics cannot accurately reflect the authentic biological behaviors, clinical outcomes, and prognosis of LGGs. In this study, we carried out analyses of whole exome sequencing, RNA sequencing and DNA methylation in primary vs. recurrent LGG samples, and also combined the multi-omics data to construct a prognostic prediction model. TCGA-LGG dataset was searched for LGG samples. 523 samples were used for whole exome sequencing analysis, 532 for transcriptional analysis, and 529 for DNA methylation analysis. LASSO regression was used to screen genes with significant association with LGG survival from the frequently mutated genes, differentially expressed genes, and differentially methylated genes, whereby a prediction model for prognosis of LGG was further constructed and validated. The most frequently mutated diver genes in LGGs were IDH1 (77%), TP53 (48%), ATRX (37%), etc. Top significantly up-regulated genes were C6orf15, DAO, MEOX2, etc., and top significantly down-regulated genes were DMBX1, GPR50, HMX2, etc. 2077 genes were more and 299 were less methylated in recurrent vs. primary LGG samples. Thirty-nine genes from the above analysis were included to establish a prediction model of survival, which showed that the high-score group had a very significantly shorter survival than the low-score group in both training and testing sets. ROC analysis showed that AUC was 0.817 for the training set and 0.819 for the testing set. This study will be beneficial to accurately predict the survival of LGGs to identify patients with poor prognosis to take specific treatment as early, which will help improve the treatment outcomes and prognosis of LGG.

Comprehensive analyses of m1A regulator-mediated modification patterns determining prognosis in lower-grade glioma (running title: m1A in LGG)

N1-methyladenosine (m1A) modification is a crucial post-transcriptional regulatory mechanism of messenger RNA (mRNA) in living organisms. Few studies have focused on analysis of m1A regulators in lower-grade gliomas (LGG). We employed the Nonnegative Matrix Factorization (NMF) technique on The Cancer Genome Atlas (TCGA) dataset to categorize LGG patients into 2 groups. These groups exhibited substantial disparities in terms of both overall survival (OS) and levels of infiltrating immune cells. We collected the significantly differentially expressed immune-related genes between the 2 clusters, and performed LASSO regression analysis to obtain m1AScores, and established an m1A-related immune-related gene signature (m1A-RIGS). Next, we categorized all patients with LGG into high- and low-risk subgroups, predictive significance of m1AScore was confirmed by conducting univariate/multivariate Cox regression analyses. Additionally, we confirmed variations in immune-related cells and ssGSEA and among the high-/low-risk subcategories in the TCGA dataset. Finally, our study characterized the effects of MSR1 and BIRC5 on LGG cells utilizing Edu assay and flow cytometry to explore the effects of modulation of these genes on glioma. The results of this study suggested that m1A-RIGS may be an excellent prognostic indicator for patients with LGG, and could also promote development of novel immune-based treatment strategies for LGG. Additionally, BIRC5 and MSR1 may be potential therapeutic targets for LGG.

Predictive value of procollagen c-protease enhancer protein on the prognosis of glioma patients

Procollagen c-protease enhancer protein (PCOLCE) performs an essential action in improving the recreation of procollagen c-protease and promoting the reconstruction of extracellular matrix. High PCOLCE expression was associated with a negative prognosis of stomach cancer, ovarian cancer, and osteosarcoma. The goal of this work is to investigate the function of PCOLCE in glioma. Multiple bioinformatics techniques have been employed to investigate the roles of PCOLCE in glioma, consisting of the correlation between PCOLCE and prognosis, immune checkpoints, immune cell infiltrates, and tumor microenvironment (TME). The gene ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to assess the potential function of PCOLCE in glioma. PCOLCE was found to be increased in glioma. We revealed that PCOLCE was a potential prognostic factor and related to tumor grade. Up-regulated PCOLCE was related to poor prognosis in lower-grade glioma (LGG), glioblastoma multiforme (GBM), and recurrent glioma. PCOLCE was correlated with immune cell infiltration, particularly B cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells (DCs) in LGG, and DCs infiltration in GBM. PCOLCE was co-expressed with many genes related to the immune and the immune checkpoint. In addition, glioma patients with low expression of PCOLCE had a higher response to the immunological checkpoint blockade (ICB). Additionally, PCOLCE may exert its roles via several immune-related biological processes or pathways, such as leukocyte migration, activation of T cells, adaptive immune response, neutrophil-mediated immunity, NF-κB, and TNF signaling pathways. In conclusion, PCOLCE may be a new immune-related gene and regulate tumor development through immunological pathways.

Potential role of POFUT1 as a prognostic predictor in low-grade gliomas: Immune microenvironment insights from a pan-cancer analysis

The POFUT1 gene, known to be up-regulated in various tumor tissues and associated with tumor biology, has yet to be explored for its potential role in immune response regulation and tumor immune microenvironment. The normalized pan-cancer dataset (TCGA Pan-Cancer) was downloaded from the UCSC database, followed by analysis of POFUT1 expression in various tumors and functional enrichment analysis. The correlation between POFUT1 expression levels and patient prognosis was assessed. GSEA of POFUT1 based on low-grade glioma (LGG) samples and immune infiltration analyses of LGG and glioblastoma (GBM) were conducted. The correlation between POFUT1 expression levels and infiltration levels of 22 immune cells in LGG and GBM was examined, as well as the correlation between immune cell infiltration levels and LGG patient prognosis. Additionally, the relationship between POFUT1 expression levels and characteristic gene expression of identified immune cells was evaluated. Lastly, external dataset validation was performed using the integrated CGGA dataset. Significant differences were observed in POFUT1 expression levels across 20 tumor types. High POFUT1 expression correlated with poor prognosis in GBMLGG, and LGG patients. Enrichment analysis and GSEA of POFUT1 in LGG demonstrated involvement in tumor-related and immune-related pathways. A positive correlation was identified between POFUT1 expression levels and infiltration levels of resting memory CD4+ T cells, as well as M2 macrophages or M2-like TAMs in the LGG immune microenvironment, potentially contributing to poor prognosis. External dataset validation revealed a positive correlation between M2 macrophages or M2-like TAMs and POFUT1 expression levels in LGG, and a negative correlation with LGG patient prognosis. POFUT1's negative impact on LGG prognosis may result from its influence on M2 macrophage and M2-like TAM infiltration levels within the immune microenvironment. This suggests its potential as a prognostic predictor and therapeutic target for LGG.

WD repeat domain 76 predicts poor prognosis in lower grade glioma and provides an original target for immunotherapy

BackgroundThe WD40 repeat (WDR) domain provides scaffolds for numerous protein–protein interactions in multiple biological processes. WDR domain 76 (WDR76) has complex functionality owing to its diversified interactions; however, its mechanism in LGG has not yet been reported.MethodsTranscriptomic data from public databases were multifariously analyzed to explore the role of WDR76 in LGG pathology and tumor immunity. Laboratory experiments were conducted to confirm these results.ResultsThe results first confirmed that high expression of WDR76 in LGG was not only positively associated with clinical and molecular features of malignant LGG, but also served as an independent prognostic factor that predicted shorter survival in patients with LGG. Furthermore, high expression of WDR76 resulted in the upregulation of oncogenes, such as PRC1 and NUSAP1, and the activation of oncogenic mechanisms, such as the cell cycle and Notch signaling pathway. Finally, WDR76 was shown to be involved in LGG tumor immunity by promoting the infiltration of immune cells, such as M2 macrophages, and the expression of immune checkpoints, such as PDCD1 (encoding PD-1).ConclusionsThis study shows for the first time the diagnostic and prognostic value of WDR76 in LGG and provides a novel personalized biomarker for future targeted therapy and immunotherapy. Thus, WDR76 may significantly improve the prognosis of patients with LGG.

ITGB4 upregulation is associated with progression of lower grade glioma

Gliomas originating in the neuroepithelium account for about 80% of brain malignancies and are the most common cancer of the central nervous system. Clinical management of gliomas remains challenging despite significant advances in comprehensive therapies, including radiotherapy, chemotherapy, and surgery. The ITGB4 (Integrin subunit beta 4) gene encodes a receptor for laminins and its upregulation in tumor tissues is associated with poor prognosis. However, its role in glioma is not well understood. First, we performed a pan cancer analysis of ITGB4 expression in The Cancer Genome Atlas (TCGA) dataset. Survival analysis was done on Chinese Glioma Genome Atlas (CGGA) and TCGA. Immunohistochemistry was then used to validate the expression and role of ITGB4 in glioma. We finally analyzed the possible mechanism by immune infiltration and single-cell sequencing analysis. Here, we found that ITGB4 is upregulated in glioma and accurately predicts the prognosis of lower grade glioma (LGG). Univariate and multivariate Cox regression analyses showed that ITGB4 is a risk factor for LGG. Immunohistochemical analysis confirmed that ITGB4 accurately predicts LGG prognosis. Non-negative matrix factorization (NMF) cluster analysis showed that ITGB4 was closely related to immune related genes. Immune cell infiltration and single cell sequencing analyses indicated that ITGB4 may be closely related to the microenvironment of gliomas, especially tumor-associated fibroblasts. ITGB4 is a promising diagnostic and therapeutic factor in LGG patients.

Exploring the prognostic potential of m6A methylation regulators in low-grade glioma: implications for tumor microenvironment modulation

BackgroundThe biological behavior of low-grade glioma (LGG) is significantly affected by N6-methyladenosine (m6A) methylation, an essential epigenetic alteration. Therefore, it is crucial to create a prognostic model for LGG by utilizing genes that regulate m6A methylation.MethodsUsing TCGA and GTEx databases. We examined m6A modulator levels in LGG and normal tissues, and investigated PD-L1 and PD-1 expression, immune scores, immune cell infiltration, tumor immune microenvironment (TIME) and potential underlying mechanisms in different LGG clusters. We also performed immunohistochemistry and RT-qPCR to identify essential m6A adjustment factor.ResultsThe results showed that m6A regulatory element expression was significantly increased in LGG tissues and was significantly associated with TMIE. A substantial increase in PD-L1 and PD-1 levels in LGG tissues and high-risk cohorts was observed. PD-L1 expression was positively correlated with FTO, ZCCHC4, and HNRNPD, whereas PD-1 expression was negatively correlated with FTO, ZC3H7B, and HNRNPD. The prognostic signature created using regulators of m6A RNA methylation was shown to be strongly associated with the overall survival of LGG patients, and FTO and ZCCHC4 were confirmed as independent prognostic markers by clinical samples. Furthermore, the results revealed different TIME characteristics between the two groups of patients, indicating disrupted signaling pathways associated with LGG.ConclusionOur results present that the m6A regulators play vital role in regulating PD-L1/PD-1 expression and the infiltration of immune cells, thereby exerting a sizable impact on the TIME of LGG. Therefore, m6A regulators have precise predictive value in the prognosis of LGG.

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.

Expression and clinical significance of RBBP4 gene in lower-grade glioma: An integrative analysis

This study investigated the expression pattern of retinoblastoma binding protein 4 (RBBP4) gene in glioma and explored its associations with clinicopathologic characteristics and prognosis of patients. Data retrieved from the GEPIA, CGGA, HPA and TIMER databases were processed to analyze RBBP4 expression in glioma and investigate its relationship with clinicopathologic characteristics, tumor immune infiltration and prognosis in glioma patients. Immunohistochemistry was applied to determine the expression of RBBP4 protein in glioma tissue. Additionally, the Coexpedia database was visited to identify co-expressed genes for RBBP4 gene, while the Cytoscape software was run to visualize the enriched GO entries and KEGG pathways of these co-expressed genes. The expression levels of RBBP4 in lower-grade glioma (LGG) and glioblastoma (GBM) tissues were markedly elevated when compared to normal tissues (both p < 0.05). The up-regulation of RBBP4 expression was associated with an increase in WHO grade (II-IV), wild-type IDH, and 1p/19q non-codeletion (all p < 0.05). Multi-variate Cox regression analysis showed that both increased abundance of infiltrating macrophages and up-regulated RBBP4 expression independently predicted poor survival outcomes in LGG patients (both p < 0.05). Furthermore, RBBP4 expression exhibited significant positive correlations with the abundance of infiltrating B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil, and dendritic cell in LGG (all p < 0.05). Functional enrichment analyses indicated that the co-expressed genes associated with RBBP4 were highly involved in pathways such as the p53 signaling pathway, cell cycle, DNA replication, glutathione metabolism, as well as biological processes including cell cycle process, DNA replication, and DNA repair. High levels of RBBP4 are predictive for the poor survival outcome of LGG patients. RBBP4 gene, therefore, is expected to be a potential biomarker for prognosis of LGG and a target for immunotherapy.

Comprehensive Analysis of Ferroptosis Regulators with Regard to PD-L1 and Immune Infiltration in Low-Grade Glioma.

The prognosis of low-grade glioma (LGG) is highly variable and requires more accurate predictors. Ferroptosis, a newly discovered programmed cell death, has been demonstrated to play a crucial role in some types of tumors. However, prognostic prediction based on ferroptosis-related genes (FRGs) and the influence on the tumor microenvironment (TME) in LGG remains elusive. We derived expression profiles for LGG from public databases. Based on the expression of 25 FRGs in LGG, two independent subtypes and a risk model were successfully constructed. Different methods were applied to assess the tumor heterogeneity, tumor microenvironment, and the prognostic value. In addition, a competing endogenous RNA (ceRNA) regulatory axis was constructed. The subtypes had independent tumor heterogeneity, tumor microenvironments, and prognoses. LPCAT3, SLC1A5, HSPA5, and NFE2L2 were identified as the potential prognostic FRGs. Based on these four FRGs, our risk model possesses excellent potential to predict prognosis and varied immune infiltration abundance. The ceRNA regulatory axis provides a potential therapeutic target for LGG. Our molecular subtypes, risk model, and ceRNA regulatory axis have strong immune prediction and prognostic prediction capabilities which could guide LGG treatment.

Low-grade glial tumors: The experience of an oncology hospital in Türkiye

Objective: Several factors are important in the prognosis of low grade gliomas, besides genetic changes. The present study aims to examine the effect of other factors on prognosis except for genetic changes in low grade gliomas (LGGs). Materials and Methods: Patients diagnosed with “brain malignant neoplasm” who were referred to Hacettepe University Oncology Hospital were screened. Among these patients, 148 patients with a supratentorial low grade gliomas whose data are completely available were included. Patients were followed for at least five years after diagnosis or death within this period. Results: Mean age of diagnosis was 36.2±10.7 years, and 52.7% of patients (n=78) were females, Most common subtype was oligodendroglioma (n=86, 58.1%). Sixty-two of patients relapsed (41.9%). The 5-year mortality rate was 35.1% (n=52). Kaplan-Meier analysis of the variables, the only difference was between histopathological subtypes (p=0.03). Astrocytoma histology was related to wporse prognosis. Cox regression analysis of factors affecting 5-year mortality, advancing age (HR: 1.03, 95% CI: 1.00-1.06, p=0.03), astrocytoma (HR: 2.59, 95% CI: 1.35-4.98, p=0.004) and oligoastrocytoma (HR: 2.13, 95% CI: 1.02-4.43, p=0.04) were identified to increase the mortality risk. Conclusion: The age of the patients and the histopathologic subtype of the tumor must be taken into consideration during the follow-up and treatment of low grade gliomas.

A prognostic model based on the Augmin family genes for LGG patients

Gliomas are the most prevalent primary tumors in the central nervous system. Despite some breakthroughs in the treatment of glioma in recent years, survival rates remain low. Although genes of the Augmin family play a key role in microtubule nucleation, the role they play in gliomas is unclear. Transcriptome data were extracted from UCSC XENA and GTEx for low-grade glioma (LGG) and normal tissues, respectively. The protein interaction network associated with Augmin family genes was established using STRING and GeneMANIA databases. Enrichment analysis of gene-related functions and pathways was used to explore potential biological pathways and TIMER to assess immune cell infiltration. Regression analysis and Kaplan–Meier analysis were used to look at the clinical characteristics of the Augmin family genes and the association with the prognosis of patients with glioma. The results showed that the mRNA expression of Augmin family genes was significantly elevated in LGG tissues, except for HAUS7. Immunoregulation, cell cycle, apoptosis and other signaling pathways may be involved in the development and progression of LGG. Except for HAUS4 and HAUS7, the expression of all genes was positively correlated with immune cell infiltration. High expression of HAUS1, HAUS3, HAUS5, HAUS7, HAUS8 and low expression of HAUS4, HAUS6 in LGG was associated with poor prognosis. The risk models constructed based on the pivotal genes HAUS2, HAUS4 and HAUS8 were validated by nomogram and confirmed to be clinically useful for predicting the prognosis of LGG.

Decreased SPTBN2 expression regulated by the ceRNA network is associated with poor prognosis and immune infiltration in low‑grade glioma.

The majority of low-grade gliomas (LGGs) in adults invariably progress to glioblastoma over time. Spectrin β non-erythrocytic 2 (SPTBN2) is detected in numerous tumors and is involved in tumor occurrence and metastasis. However, the specific roles and detailed mechanisms of SPTBN2 in LGG are largely unknown. The present study performed pan-cancer analysis for the expression and prognosis of SPTBN2 in LGG using The Cancer Genome Atlas and The Genotype-Tissue Expression. Western blotting was used to detect the amount of SPTBN2 between glioma tissues and normal brain tissues. Subsequently, based on expression, prognosis, correlation and immune infiltration, non-coding RNAs (ncRNAs) were identified that regulated SPTBN2 expression. Finally, tumor immune infiltrates associated with SPTBN2 and prognosis were performed. Lower expression of SPTBN2 was correlated with an unfavorable outcome in LGG. A significant correlation between the low SPTBN2 mRNA expression and poor clinicopathological features was observed, including wild-type isocitrate dehydrogenase status (P<0.001), 1p/19q non-codeletion (P<0.001) and elders (P=0.019). The western blotting results revealed that, compared with normal brain tissues, the amount of SPTBN2 was significantly lower in LGG tissues (P=0.0266). Higher expression of five microRNAs (miRs/miRNAs), including hsa-miR-15a-5p, hsa-miR-15b-5p, hsa-miR-16-5p, hsa-miR-34c-5p and hsa-miR-424-5p, correlated with poor prognosis by targeting SPTBN2 in LGG. Subsequently, four long ncRNAs (lncRNAs) [ARMCX5-GPRASP2, BASP1-antisense RNA 1 (AS1), EPB41L4A-AS1 and LINC00641] were observed in the regulation of SPTBN2 via five miRNAs. Moreover, the expression of SPTBN2 was significantly correlated with tumor immune infiltration, immune checkpoint expression and biomarkers of immune cells. In conclusion, SPTBN2 was lowly expressed and correlated with an unfavorable prognosis in LGG. A total of six miRNAs and four lncRNAs were identified as being able to modulate SPTBN2 in a lncRNA-miRNA-mRNA network of LGG. Furthermore, the current findings also indicated that SPTBN2 possessed anti-tumor roles by regulating tumor immune infiltration and immune checkpoint expression.