Prognosis Of Low-grade Gliomas Research Articles

Evaluating KLHDC8A as a biomarker for glioma: impact on survival and proliferation through the Wnt/β-catenin pathway

Glioma is one of the most common malignant tumors and shows a high metastasis rate and poor prognosis. KLHDC8A has been implicated in several cancers, but its role in glioma and its potential as a biomarker remain unclear. We conducted a pan-cancer analysis of KLHDC8A using multiple databases and assessed its expression levels, survival associations, and diagnostic utility. Kaplan–Meier survival analysis and Receiver Operating Characteristic (ROC) curves were utilized to evaluate KLHDC8A’s prognostic and diagnostic potential. Additionally, we investigated KLHDC8A's role in glioma cell proliferation and its involvement in the Wnt/β-catenin signaling pathway. Our pan-cancer analysis revealed significant dysregulation of KLHDC8A across various tumors. Elevated KLHDC8A expression was associated with poor overall survival (OS) in cancers including ACC, KIRP, LGG, and STAD. Disease-specific survival (DSS) analysis indicated worse outcomes in ACC, KIRP, and LGG with high KLHDC8A levels. ROC curve analysis demonstrated KLHDC8A's strong diagnostic potential for glioblastoma multiforme (GBM) and lower-grade gliomas (LGG), with AUC values of 0.920 and 0.748, respectively. In glioma patients, high KLHDC8A expression correlated with shorter OS and DSS in LGG, while no significant correlation was observed in GBM. Multivariate Cox regression confirmed KLHDC8A as an independent prognostic factor for OS and DSS in LGG. Knockdown experiments in glioma cell lines U251 and U87 showed that KLHDC8A silencing led to reduced cell proliferation and colony formation, which was associated with downregulation of key proteins in the Wnt/β-catenin pathway. Overall, KLHDC8A is a promising biomarker for the diagnosis and prognosis of LGG, and its high expression is linked to poor survival outcomes. The gene's involvement in the Wnt/β-catenin signaling pathway underscores its role in glioma progression, highlighting KLHDC8A’s potential as a therapeutic target and diagnostic marker, particularly for LGG.

DSN1 may predict poor prognosis of lower-grade glioma patients and be a potential target for immunotherapy

ABSTRACT DSN1 has been previously found to be positively correlated with various cancers. However, the effect of DSN1 or its methylation on the prognosis, molecular characteristics, and immune cell infiltration of low-grade glioma (LGG) has not yet been studied. We obtained 1046 LGG samples from the The Cancer Genome Atlas, The Chinese Glioma Genome Atlas (CGGA) microarray, and CGGA RNA-Seq databases. Bioinformatic methods (gene set enrichment analysis (GSEA), chi-square test, multivariate), and laboratory validation were used to investigate DSN1 in LGG. The expression levels of DSN1 mRNA and protein in LGG were substantially higher than those in normal brain tissue, and their expression was negatively regulated by methylation. The survival time of patients with low expression of DSN1 and cg12601032 hypermethylation was considerably prolonged. DSN1 was a risk factor, and of good diagnostic and prognostic value for LGG. Importantly, the expression of DSN1 is related to many types of tumor-infiltrating immune cells and has a positive correlation with PDL1. DSN1 promoted the activation of multiple cancer-related pathways, such as the cell cycle. Additionally, knockdown of DSN1 substantially inhibited the proliferation and invasion of LGG cells. To the best of our knowledge, this study is the first comprehensive analysis of the mechanism of DSN1 leading to poor prognosis of LGG, which provides a new perspective for revealing the pathogenesis of LGG. DSN1 or its methylation has diagnostic value for the prognosis of glioma, and may become a new biological target of anti-tumor immunotherapy.

Spermine Synthase : A Potential Prognostic Marker for Lower-Grade Gliomas.

The objective of this study was to assess the relationship between spermine synthase (SMS) expression, tumor occurrence, and prognosis in lower-grade gliomas (LGGs). A total of 523 LGG patients and 1152 normal brain tissues were included as controls. Mann-Whitney U test was performed to evaluate SMS expression in the LGG group. Functional annotation analysis was conducted to explore the biological processes associated with high SMS expression. Immune cell infiltration analysis was performed to examine the correlation between SMS expression and immune cell types. The association between SMS expression and clinical and pathological features was assessed using Spearman correlation analysis. In vitro experiments were conducted to investigate the effects of overexpressing or downregulating SMS on cell proliferation, apoptosis, migration, invasion, and key proteins in the protein kinase B (AKT)/epithelialmesenchymal transition signaling pathway. The study revealed a significant upregulation of SMS expression in LGGs compared to normal brain tissues. High SMS expression was associated with certain clinical and pathological features, including older age, astrocytoma, higher World Health Organization grade, poor disease-specific survival, disease progression, non-1p/19q codeletion, and wild-type isocitrate dehydrogenase. Cox regression analysis identified SMS as a risk factor for overall survival. Bioinformatics analysis showed enrichment of eosinophils, T cells, and macrophages in LGG samples, while proportions of dendritic (DC) cells, plasmacytoid DC (pDC) cells, and CD8+ T cells were decreased. High SMS expression in LGGs may promote tumor occurrence through cellular proliferation and modulation of immune cell infiltration. These findings suggest the prognostic value of SMS in predicting clinical outcomes for LGG patients.

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.

Screening of potential key pathogenic and intervention targets of low-grade glioma based on bioinformatics.

Sialic acid-binding immunoglobulin-like lectin 8 (SIGLEC8) is involved in the progression of numerous diseases. This study aimed to examine the relationship between SIGLEC8 and the prognosis of patients with low-grade glioma (LGG) and the related mechanisms. First, screening of the differentially expressed genes (DEGs) SIGLEC8 in The Cancer Genome Atlas (TCGA) database was performed. The expression was then correlated with the prognosis of patients with LGG and then verified using the Tumor Immune Estimation Resource (TIMER) and TCGA databases. Cox regression was employed to conduct multifactorial analysis and was followed by the construction of an internally validated nomogram based on these results. To investigate the possible mechanisms, we used gene set enrichment analysis (GSEA). We conducted a retrospective analysis of the clinical information of patients with LGG who were treated at Longgang Central Hospital of Shenzhen from January 2018 to December 2020 and from whom tumor and peritumoral tissues were taken during surgery. Expression of essential genes was identified by employing quantitative real-time polymerase chain reaction (qRT-PCR). Multivariate analysis, via Cox regression, was employed to determine the prognostic factors for patients with LGG. The transcriptional activity of SIGLEC8 was found to be elevated in LGG neoplastic tissues compared to neighboring nonneoplastic tissues. Overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) were improved in patients with LGG with reduced expression of SIGLEC8 as compared to those with increased expression of SIGLEC8. The nomogram's C-index is 0.804 (0.781-0.827). indicating good predictive accuracy. GSEA revealed that SIGLEC8 might influence LGG biological events by participating in the PD-1, IL3, JAK/STAT, and PI3KCI signal transduction pathways, as well as cytokine and inflammatory response, cell cycle, homeostasis, and extracellular matrix. This study included 72 patients with LGG. qRT-PCR showed upregulated SIGLEC8 expression in LGG tumor tissues, which was significantly associated with tumor number and metastasis to the lymph nodes (P<0.05). Multivariate analysis using Cox regression identified the high expression of SIGLEC8 as an independent risk factor in LGG prognosis (P<0.05). For the prognosis of patients with LGG, the transcriptional activity of SIGLEC8 is increased in LGG tissues and is an independent risk factor. Interference with SIGLEC8 could promote tumor progression by regulating the JAK/STAT signaling pathway, indicating that SIGLEC8 may function as a distinctive predictive biomarker for patients with 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.