CGGA Dataset Research Articles

Identification of m6A methyltransferase-related WTAP and ZC3H13 predicts immune infiltrates in glioblastoma

Glioblastoma (GBM) is a prevalent and highly fatal primary malignant brain tumor. N6-methyladenosine (m6A) modification plays a critical role in the development of brain tumor. WTAP and ZC3H13 have been identified across various species. Immune contexture, which includes the tumor microenvironment (TME), plays a significant role in cancer progression and treatment. This study aimed to explore the potential impact between WTAP and ZC3H13 on the immunological characteristics of GBM. We utilized data from TCGA-GBM, GEO and CGGA datasets to obtain platform and probe data. Patients with GBM were stratified into two clusters based on the expression of WTAP and ZC3H13 using consensus clustering approach. Immune infiltration within the tumor microenvironment was assessed using ESTIMATE, CIBERSORT and ssGSEA methodologies. Functional disparities were determined through gene set enrichment analysis (GSEA). Tumor mutation burden (TMB) and immune checkpoint inhibitors (ICIs) were also analyzed. Co-expression network analysis (WGCNA) was used to identify genes associated with WTAP/ZC3H13 and immunity. Validation was performed using GEO and CGGA datasets. Our analysis revealed that cluster1 exhibited higher WTAP expression but lower ZC3H13 expression compared to cluster2. Cluster1 showed higher levels of immune infiltration and TMB compared to cluster2. WGCNA identified 15 genes closely associated with WTAP/ZC3H13 expression and immune scores, notably CTLA4, CD27, ICOS, and LAG3. Our results suggested that WTAP and ZC3H13 influence on immune contexture of GBM, providing new insights into tumor immunity in GBM.

Integration of histone modification-based risk signature with drug sensitivity analysis reveals novel therapeutic strategies for lower-grade glioma.

Lower-grade glioma (LGG) exhibits significant heterogeneity in clinical outcomes, and current prognostic markers have limited predictive value. Despite the growing recognition of histone modifications in tumor progression, their role in LGG remains poorly understood. This study aimed to develop a histone modification-based risk signature and investigate its relationship with drug sensitivity to guide personalized treatment strategies. We performed single-cell RNA sequencing analysis on LGG samples (n = 4) to characterize histone modification patterns. Through integrative analysis of TCGA-LGG (n = 513) and CGGA datasets (n = 693 and n = 325), we constructed a histone modification-related risk signature (HMRS) using machine learning approaches. The model's performance was validated in multiple independent cohorts. We further conducted comprehensive analyses of molecular mechanisms, immune microenvironment, and drug sensitivity associated with the risk stratification. We identified distinct histone modification patterns across five major cell populations in LGG and developed a robust 20-gene HMRS from 129 candidate genes that effectively stratified patients into high- and low-risk groups with significantly different survival outcomes (training set: AUC = 0.77, 0.73, and 0.71 for 1-, 3-, and 5-year survival; P < 0.001). Integration of HMRS with clinical features further improved prognostic accuracy (C-index >0.70). High-risk tumors showed activation of TGF-β and IL6-JAK-STAT3 signaling pathways, and distinct mutation profiles including TP53 (63% vs 28%), IDH1 (68% vs 85%), and ATRX (46% vs 20%) mutations. The high-risk group demonstrated significantly elevated immune and stromal scores (P < 0.001), with distinct patterns of immune cell infiltration, particularly in memory CD4+ T cells (P < 0.001) and CD8+ T cells (P = 0.001). Drug sensitivity analysis revealed significant differential responses to six therapeutic agents including Temozolomide and targeted drugs (P < 0.05). Our study establishes a novel histone modification-based prognostic model that not only accurately predicts LGG patient outcomes but also reveals potential therapeutic targets. The identified associations between risk stratification and drug sensitivity provide valuable insights for personalized treatment strategies. This integrated approach offers a promising framework for improving LGG patient care through molecular-based risk assessment and treatment selection.

TMIC-05. AGING-SPECIFIC MICRORNA EXPRESSION SIGNATURE IN ELDERLY GLIOBLASTOMA

Abstract PURPOSE The rise in aging population worldwide is increasing death from cancer, including glioblastoma. MicroRNAs (miRNAs/miRs) are small non-coding RNAs that mediate the posttranscriptional silencing of specific target mRNAs and that are currently recognized as important regulators of tumorigenesis and development. Here, we explore the impact of brain aging and aging-specific miRNAs on elderly glioblastomas. METHODS We comprehensively analyzed miRNAs expression using the TCGA dataset and identified miRNAs that are specifically expressed in elderly glioblastomas. To create the Ehime Glioma Genome Atlas (EGGA), RNA sequencing was performed using tumor tissues from 8 glioblastoma patients (4 elderly and 4 non-elderly). First, we evaluated the impact of the identified miRNAs on prognosis using TCGA and CGGA datasets and searched for target genes of specific miRNAs using TargetScan. The expression patterns of the identified target genes were verified using EGGA, TCGA, and CGGA datasets. RESULTS We divided the TCGA dataset into elderly and non-elderly groups based on three ages (75 years-old, 70 years-old, and 65 years-old) and analyzed the expression of miRNAs in tumor tissues. There were 3 miRNAs that showed abnormalities (1 increased miRNA, 2 decreased miRNAs), and among these, miR-210 (increased expression) and miR-507 (increased expression) were identified as miRNAs related to prognosis. Next, we analyzed the expression of EGGA and identified 410 mRNAs (368 increased mRNAs, 42 decreased mRNAs) that showed significantly abnormal expression in the elderly group. The target genes searched using TargetScan were 4,048 genes for miR-210 and 4,704 genes for miR-507. When compared with the 410 genes identified using EGGA, PLA2G3, a target gene to miR-507, was identified. The expression of PLA2G3 was also specifically increased in elderly glioblastoma in the TCGA dataset, and it had a strong influence on prognosis. CONCLUSION Our results found an aging-specific miRNA “miR-507” and its target gene “PLA2G3” that suggested as potential new therapeutic target molecules for improving the prognosis of elderly glioblastomas.

Pan-cancer analysis and experimental validation of FPR3 as a prognostic and immune infiltration-related biomarker for glioma.

Formyl peptide receptor 3 (FPR3) is known to have implications in the progression of various cancer types. Despite this, its biological significance within pan-cancer datasets has yet to be investigated. In this investigation, we scrutinized FPR3's expression profiles, genetic alterations, prognostic significance, immune-related characteristics, methylation status, tumor mutation burden (TMB), and microsatellite instability (MSI) across different types of cancer. We utilized TISCH's single-cell data to identify immune cells closely associated with FPR3. The predictive significance of FPR3 was evaluated independently in gliomas using data from TCGA and CGGA datasets, leading to the development of a prognostic nomogram. Immunohistochemistry and Western blot analysis confirmed FPR3 expression in gliomas. Lastly, the CCK-8 and wound-healing assays were employed to assess the impact of FPR3 on the proliferation and metastasis of GBM cell lines. In numerous cancer types, heightened FPR3 expression correlated with adverse outcomes, immune cell infiltration, immune checkpoints, TMB, and MSI. In glioma, FPR3 emerged as a notable risk factor, with the prognostic model effectively forecasting patient results. The potential biological relevance of FPR3 was confirmed in glioma, and it was shown to have significant involvement in the processes of glioma growth, immune infiltration, and metastasis. Our results imply a potential association of FPR3 with tumor immunity, indicating its viability as a prognostic indicator in glioma.

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.

Clinical sequencing reveals diagnostic, therapeutic, and prognostic biomarkers for adult-type diffuse gliomas

Diffuse gliomas in adults are highly infiltrative and largely incurable. Whole exome sequencing (WES) has been demonstrated very useful in genetic analysis. Here WES was performed to characterize genomic landscape of adult-type diffuse gliomas to discover the diagnostic, therapeutic and prognostic biomarkers. Somatic and germline variants of 66 patients with adult-type diffuse gliomas were detected by WES based on the next-generation sequencing. TCGA and CGGA datasets were included to analyze the integrated diagnosis and prognosis. Among 66 patients, the diagnosis of 9 cases was changed, in which 8 cases of astrocytoma were corrected into IDH-wildtype glioblastoma (GBM), and 1 oligodendroglioma without 1p/19q co-deletion into astrocytoma. The distribution of mutations including ATRX/TP53 differed in three cohorts. The genetic mutations in GBM mainly concentrated on the cell cycle, PI3K and RTK pathways. The mutational landscape of astrocytoma was more similar to that of GBM, with the highest frequency in germline variants. Patients with IDH-mutant astrocytoma harboring SNVs of PIK3CA and PIK3R1 showed a significantly worse overall survival (OS) than wild-type patients. AEBP1 amplification was associated with shorter OS in GBM. Our study suggests that clinical sequencing can recapitulate previous findings, which may provide a powerful approach to discover diagnostic, therapeutic and prognostic markers for precision medicine in adult-type diffuse gliomas.

Exploring the prognostic value of BRMS1 + microglia based on single-cell anoikis regulator patterns in the immunologic microenvironment of GBM

BackgroundAnoikis is a specialized form of programmed cell death induced by the loss of cell adhesion to the extracellular matrix (ECM). Acquisition of anoikis resistance is a significant marker for cancer cell invasion, metastasis, therapy resistance, and recurrence. Although current research has identified multiple factors that regulate anoikis resistance, the pathological mechanisms of anoikis-mediated tumor microenvironment (TME) in glioblastoma (GBM) remain largely unexplored.MethodsUtilizing single-cell RNA sequencing (scRNA-seq) data and employing non-negative matrix factorization (NMF), we identified and characterized TME cell clusters with distinct anoikis-associated gene signatures. Prognostic and therapeutic response analyses were conducted using TCGA and CGGA datasets to assess the clinical significance of different TME cell clusters. The spatial relationship between BRMS1 + microglia and tumor cells was inferred from spatial transcriptome RNA sequencing (stRNA-seq) data. To simulate the tumor immune microenvironment, co-culture experiments were performed with microglia (HMC3) and GBM cells (U118/U251), and microglia were transfected with a BRMS1 overexpression lentivirus. Western blot or ELISA were used to detect BRMS1, M2 macrophage-specific markers, PI3K/AKT signaling proteins, and apoptosis-related proteins. The proliferation and apoptosis capabilities of tumor cells were evaluated using CCK-8, colony formation, and apoptosis assays, while the invasive and migratory abilities of tumor cells were assessed using Transwell assays.ResultsNMF-based analysis successfully identified CD8 + T cell and microglia cell clusters with distinct gene signature characteristics. Trajectory analysis, cell communication, and gene regulatory network analyses collectively indicated that anoikis-mediated TME cell clusters can influence tumor cell development through various mechanisms. Notably, BRMS1 + AP-Mic exhibited an M2 macrophage phenotype and had significant cell communication with malignant cells. Moreover, high expression of BRMS1 + AP-Mic in TCGA and CGGA datasets was associated with poorer survival outcomes, indicating its detrimental impact on immunotherapy. Upregulation of BRMS1 in microglia may lead to M2 macrophage polarization, activate the PI3K/AKT signaling pathway through SPP1/CD44-mediated cell interactions, inhibit tumor cell apoptosis, and promote tumor proliferation and invasion.ConclusionThis pioneering study used NMF-based analysis to reveal the important predictive value of anoikis-regulated TME in GBM for prognosis and immunotherapeutic response. BRMS1 + microglial cells provide a new perspective for a deeper understanding of the immunosuppressive microenvironment of GBM and could serve as a potential therapeutic target in the future.

Integrative analysis reveals the potential prognostic roles and immunological values of unc-5 netrin receptor A (UNC5A) in glioma

BackgroundUNC5A had been reported to play crucial roles in multiple cancers. However, little was known about the associations among UNC5A and glioma. Therefore, we first combined scRNA-seq, proteomics, as well as bulk RNA-seq in order to investigate UNC5A’s functions in gliomas.MethodsOnline databases provided scRNA-seq, proteomics, as well as bulk RNA-seq data on UNC5A in gliomas. The following procedures were conducted in order: QRT-PCR, Norman chart, gene set enrichment analysis (GSEA), and univariate/multifactor Cox regression analyses. We further explored the associations among UNC5A and tumor immunity.ResultsBy comparing gliomas with normal tissues, the TCGA dataset showed a significantly reduced expression of UNC5A, which was also confirmed by GSE50161, GSE4290, and QRT-PCR findings (p < 0.05). In both the TCGA and CGGA datasets, gliomas patients with low-UNC5A expression would have poorer overall survival (OS) prognoses (p < 0.05). ScRNA-seq analysis by the CancerSEA online website presented that UNC5A had a low expression in various glioma clusters and significantly associated with six functional states. Moreover, UNC5A might be a reliable independent biomarker of OS in gliomas patients (p < 0.05). Based on the results of GSEA, UNC5A might be connected to three significant pathways in gliomas. We also successfully created a Norman chart to assess the OS prognoses of these patients. Additionally, in aspects of tumor immunity, the infiltration levels of immune cells in LGG, the immune cell pathways, tumor immune microenvironment, as well as immune checkpoints in both LGG and GBM were revealed to be significantly influenced by UNC5A (p < 0.05).ConclusionsUNC5A was found to have prognostic and immunological significance in gliomas, offering patients with gliomas new treatment options.

Single-cell transcriptomic analysis identifies downregulated phosphodiesterase 8B as a novel oncogene in IDH-mutant glioma.

Glioma, a prevalent and deadly brain tumor, is marked by significant cellular heterogeneity and metabolic alterations. However, the comprehensive cell-of-origin and metabolic landscape in high-grade (Glioblastoma Multiforme, WHO grade IV) and low-grade (Oligoastrocytoma, WHO grade II) gliomas remains elusive. In this study, we undertook single-cell transcriptome sequencing of these glioma grades to elucidate their cellular and metabolic distinctions. Following the identification of cell types, we compared metabolic pathway activities and gene expressions between high-grade and low-grade gliomas. Notably, astrocytes and oligodendrocyte progenitor cells (OPCs) exhibited the most substantial differences in both metabolic pathways and gene expression, indicative of their distinct origins. The comprehensive analysis identified the most altered metabolic pathways (MCPs) and genes across all cell types, which were further validated against TCGA and CGGA datasets for clinical relevance. Crucially, the metabolic enzyme phosphodiesterase 8B (PDE8B) was found to be exclusively expressed and progressively downregulated in astrocytes and OPCs in higher-grade gliomas. This decreased expression identifies PDE8B as a metabolism-related oncogene in IDH-mutant glioma, marking its dual role as both a protective marker for glioma grading and prognosis and as a facilitator in glioma progression.

The Potential Significance of the EMILIN3 Gene in Augmenting the Aggressiveness of Low-Grade Gliomas is Noteworthy.

Low-grade gliomas (LGG) are common brain tumors with high mortality rates. Cancer cell invasion is a significant factor in tumor metastasis. Novel biomarkers are urgently needed to predict LGG prognosis effectively. The data for LGG were obtained from the Bioinformatics database. A consensus clustering analysis was performed to identify molecular subtypes linked with invasion in LGG. Differential expression analysis was performed to identify differentially expressed genes (DEGs) between the identified clusters. Enrichment analyses were then conducted to explore the function for DEGs. Prognostic signatures were placed, and their predictive power was assessed. Furthermore, the invasion-related prognostic signature was validated using the CGGA dataset. Subsequently, clinical specimens were procured in order to validate the expression levels of the distinct genes examined in this research, and to further explore the impact of these genes on the glioma cell line LN229 and HS-683. Two invasion-related molecular subtypes of LGG were identified, and we sifted 163 DEGs between them. The enrichment analyses indicated that DEGs are mainly related to pattern specification process. Subsequently, 10 signature genes (IGF2BP2, SRY, CHI3L1, IGF2BP3, MEOX2, ABCC3, HOXC4, OTP, METTL7B, and EMILIN3) were sifted out to construct a risk model. Besides, the survival (OS) in the high-risk group was lower. The performance of the risk model was verified. Furthermore, a highly reliable nomogram was generated. Cellular experiments revealed the ability to promote cell viability, value-addedness, migratory ability, invasive ability, and colony-forming ability of the glioma cell line LN229 and HS-683. The qRT-PCR analysis of clinical glioma samples showed that these 10 genes were expressed at higher levels in high-grade gliomas than in low-grade gliomas, suggesting that these genes are associated with poor prognosis of gliomas. Our study sifted out ten invasion-related biomarkers of LGG, providing a reference for treatments and prognostic prediction in LGG.

Selenoprotein GPX3 is a novel prognostic indicator for stomach adenocarcinoma and brain low-grade gliomas: Evidence from an integrative pan-cancer analysis

BackgroundThe antioxidant enzyme GPX3 is a selenoprotein that transports selenium in blood and maintains its levels in peripheral tissues. Aberrant GPX3 expression is strongly linked to the development of some tumors. However, there is a scarcity of studies examining the pan-cancer expression patterns and prognostic relevance of GPX3. MethodsGPX3 expression levels in normal tissues and multiple tumors were analyzed using TCGA, CCLE, GTEx, UALCAN and HPA databases. Forest plots and KM survival curves were utilized to evaluate the correlation between GPX3 expression and the outcome of tumor patients. The prognostic value of GPX3 in LGG was assessed utilizing the CGGA datasets, and that in STAD was tested by TCGA and GEO databases. A nomogram was then constructed to predict OS in STAD using R software. Additionally, the impact of GPX3 on post-chemoradiotherapy OS in patients with LGG and STAD was evaluated using the KM method. The multiplicative interaction of GPX3 expression, chemotherapy and radiotherapy on STAD and LGG was analyzed using logistic regression models. The correlation of GPX3 with the immune infiltration, immune neoantigens and MMR genes were investigated in TCGA cohort. ResultsGPX3 exhibited downregulation across 21 tumor types, including STAD, with its decreased expression significantly associated with improved OS, DFS, PFS and DSS. Conversely, in LGG, low levels of GPX3 expression were indicative of a poorer prognosis. Univariate and multivariate Cox models further identified GPX3 as an independent predictor of STAD, and a nomogram based on GPX3 expression and other independent factors showed high level of predictive accuracy. Moreover, low GPX3 expression and chemotherapy prolonged the survival of STAD. In LGG patients, chemoradiotherapy, GPX3 and chemotherapy, and GPX3 and chemoradiotherapy may improve prognosis. Our observations reveal a notable connection between GPX3 and immune infiltration, immune neoantigens, and MMR genes. ConclusionsThe variations in GPX3 expression are linked to the controlling tumor development and could act as a promising biomarker that impacts the prognosis of specific cancers like STAD and LGG.

CLEC7A regulates M2 macrophages to suppress the immune microenvironment and implies poorer prognosis of glioma.

Gliomas constitute a category of malignant tumors originating from brain tissue, representing the majority of intracranial malignancies. Previous research has demonstrated the pivotal role of CLEC7A in the progression of various cancers, yet its specific implications within gliomas remain elusive. The primary objective of this study was to investigate the prognostic significance and immune therapeutic potential of CLEC7A in gliomas through the integration of bioinformatics and clinical pathological analyses. This investigation involved examining and validating the relationship between CLEC7A and glioma using samples from Hospital, along with data from TCGA, GEO, GTEx, and CGGA datasets. Subsequently, we explored its prognostic value, biological functions, expression location, and impact on immune cells within gliomas. Finally, we investigated its potential impact on the chemotaxis and polarization of macrophages. The expression of CLEC7A is upregulated in gliomas, and its levels escalate with the malignancy of tumors, establishing it as an independent prognostic factor. Functional enrichment analysis revealed a significant correlation between CLEC7A and immune function. Subsequent examination of immune cell differential expression demonstrated a robust association between CLEC7A and M2 macrophages. This conclusion was further substantiated through single-cell analysis, immunofluorescence, and correlation studies. Finally, the knockout of CLEC7A in M2 macrophages resulted in a noteworthy reduction in macrophage chemotaxis and polarization factors. CLEC7A expression is intricately linked to the pathology and molecular characteristics of gliomas, establishing its role as an independent prognostic factor for gliomas and influencing macrophage function. It could be a promising target for immunotherapy in gliomas.

IDH1 mutation produces R-2-hydroxyglutarate (R-2HG) and induces mir-182-5p expression to regulate cell cycle and tumor formation in glioma

BackgroundMutations in isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2), are present in most gliomas. IDH1 mutation is an important prognostic marker in glioma. However, its regulatory mechanism in glioma remains incompletely understood.ResultsmiR-182-5p expression was increased within IDH1-mutant glioma specimens according to TCGA, CGGA, and online dataset GSE119740, as well as collected clinical samples. (R)-2-hydroxyglutarate ((R)-2HG) treatment up-regulated the expression of miR-182-5p, enhanced glioma cell proliferation, and suppressed apoptosis; miR-182-5p inhibition partially eliminated the oncogenic effects of R-2HG upon glioma cells. By direct binding to Cyclin Dependent Kinase Inhibitor 2 C (CDKN2C) 3’UTR, miR-182-5p inhibited CDKN2C expression. Regarding cellular functions, CDKN2C knockdown promoted R-2HG-treated glioma cell viability, suppressed apoptosis, and relieved cell cycle arrest. Furthermore, CDKN2C knockdown partially attenuated the effects of miR-182-5p inhibition on cell phenotypes. Moreover, CDKN2C knockdown exerted opposite effects on cell cycle check point and apoptosis markers to those of miR-182-5p inhibition; also, CDKN2C knockdown partially attenuated the functions of miR-182-5p inhibition in cell cycle check point and apoptosis markers. The engineered CS-NPs (antagomir-182-5p) effectively encapsulated and delivered antagomir-182-5p, enhancing anti-tumor efficacy in vivo, indicating the therapeutic potential of CS-NPs(antagomir-182-5p) in targeting the miR-182-5p/CDKN2C axis against R-2HG-driven oncogenesis in mice models.ConclusionsThese insights highlight the potential of CS-NPs(antagomir-182-5p) to target the miR-182-5p/CDKN2C axis, offering a promising therapeutic avenue against R-2HG’s oncogenic influence to glioma.

Gelsolin knockdown confers radiosensitivity to glioblastoma cells.

Radiotherapy (RT) is a cornerstone of the glioblastoma (GBM) treatment. However, the resistance of tumour cells to radiation results in early recurrence. The mechanisms underlying GBM radioresistance remain unclear. Screening for differentially expressed genes (DEGs) related to radiation might be a potential solution to this problem. RT-associated DEGs were screened based on the RNA sequencing of 15 paired primary and recurrent GBMs. The mRNA and protein expression of candidate genes were validated in RNA sequencing of The Chinese Genome Atlas (CGGA) dataset and 18 cases of GBM samples. The relationship between the candidate gene and radiation was confirmed in irradiated GBM cells. The association of candidate gene with clinical characteristics and survival was investigated in the CGGA and TCGA dataset. Biological function and pathway analysis were explored by gene ontology analysis. The association of the candidate gene with radiosensitivity was verified using cell counting Kit-8, comet, and colony formation assays invitro and subcutaneous tumour xenograft experiments invivo. Gelsolin (GSN) was selected for further study. GSN expression was significant elevated in recurrent GBM and up-regulated in irradiated GBM cell lines. High expression of GSN was enriched in malignant phenotype of glioma. Moreover, high expression of GSN was associated with poor prognosis. Further investigation demonstrated that GSN-knockdown (GSN-KD) combined with RT significantly inhibited cell proliferation and enhanced radiosensitivity invivo and invitro. Mechanistically, GSN-KD could lead to more serious DNA damage and promotes apoptosis after RT. Radiation induced up-regulated of GSN. GSN-KD could enhance the radiosensitivity of GBM.

LncRNA NDUFA6-DT: A Comprehensive Analysis of a Potential LncRNA Biomarker and Its Regulatory Mechanisms in Gliomas.

Gliomas are the most prevalent primary malignant tumors affecting the brain, with high recurrence and mortality rates. Accurate diagnoses and effective treatment challenges persist, emphasizing the need for identifying new biomarkers to guide clinical decisions. Long noncoding RNAs (lncRNAs) hold potential as diagnostic and therapeutic biomarkers in cancer. However, only a limited subset of lncRNAs in gliomas have been explored. Therefore, this study aims to identify lncRNA signatures applicable to patients with gliomas across all grades and explore their clinical significance and potential biological mechanisms. Data used in this study were obtained from TCGA, CGGA, and GEO datasets to identify key lncRNA signatures in gliomas through differential and survival analyses and machine learning algorithms. We examined their associations with the clinical characteristics, gene mutations, diagnosis, and prognosis of gliomas. Functional enrichment analysis was employed to elucidate the potential biological mechanisms associated with these significant lncRNA signatures. We explored competing endogenous RNA (ceRNA) regulatory networks. We found that NDUFA6-DT emerged as a significant lncRNA signature in gliomas, with reduced NDUFA6-DT expression associated with a worse prognosis in gliomas. Nomogram analysis incorporating NDUFA6-DT expression levels exhibited excellent prognostic and predictive capabilities. Functional annotation suggested that NDUFA6-DT might influence immunological responses and synaptic transmission, potentially modifying glioma initiation and progression. The associated ceRNA network revealed the possible presence of the NDUFA6-DT-miR-455-3p-YWHAH/YWHAG axis in low-grade glioma (LGG) and glioblastoma multiforme (GBM), regulating the PI3K-AKT signaling pathway and influencing glioma cell survival and apoptosis. We believe that NDUFA6-DT is a novel lncRNA linked to glioma diagnosis and prognosis, potentially becoming a pivotal biomarker for glioma.

Integration of Single-Cell and Bulk RNA-seq Data to Identify the Cancer-Associated Fibroblast Subtypes and Risk Model in Glioma.

Cancer-associated fibroblasts (CAFs) are an important component of the stroma. Studies showed that CAFs were pivotally in glioma progression which have long been considered a promising therapeutic target. Therefore, the identification of prognostic CAF markers might facilitate the development of novel diagnostic and therapeutic approaches. A total of 1333 glioma samples were obtained from the TCGA and CGGA datasets. The EPIC, MCP-counter, and xCell algorithms were used to evaluate the relative proportion of CAFs in glioma. CAF markers were identified by the single-cell RNA-seq datasets (GSE141383) from the Tumor Immune Single-Cell Hub database. Unsupervised consensus clustering was used to divide the glioma patients into different distinct subgroups. The least absolute shrinkage and selection operator regression model was utilized to establish a CAF-related signature (CRS). Finally, the prognostic CAF markers were further validated in clinical specimens by RT‒qPCR. Combined single-cell RNA-seq analysis and differential expression analysis of samples with high and low proportions of CAFs revealed 23 prognostic CAF markers. By using unsupervised consensus clustering, glioma patients were divided into two distinct subtypes. Subsequently, based on 18 differentially expressed prognostic CAF markers between the two CAF subtypes, we developed and validated a new CRS model (including PCOLCE, TIMP1, and CLIC1). The nomogram and calibration curves indicated that the CRS was an accurate prognostic marker for glioma. In addition, patients in the high-CRS score group had higher immune infiltration and tumor mutation burden levels. Moreover, the CRS score had the potential to predict the response to immune checkpoint blockade (ICB) therapy and chemotherapy. Finally, the expression profiles of three CAF markers were verified by RT‒qPCR. In general, our study classified glioma patients into distinct subgroups based on CAF markers, which will facilitate the development of individualized therapy. We also provided insights into the role of the CRS in predicting the response to ICB and chemotherapy in glioma patients.

SP140 inhibitor suppressing TRIM22 expression regulates glioma progress through PI3K/AKT signaling pathway.

SP gene family, consisting of SP100, SP110, SP140, and SP140L, has been implicated in the initiation and advancement of numerous malignancies. Nevertheless, their clinical significance in glioma remains incompletely understood. Expression levels and prognostic significance of SP family members were evaluated in the TCGA and CGGA datasets. Multifactorial analysis was used to identify SP gene family members that can independently impact the prognosis of glioma patients. A SP140-based predictive risk model/nomogram was developed in TCGA dataset and validated in CGGA dataset. The model's performance was evaluated through receiver operating characteristic (ROC) curves, calibration plots, and decision curve analyses. Phenotypic associations of SP140 and TRIM22 were examined through CancerSEA and TIMER. The effect of SP140 inhibitor in glioma progress and TRIM22/PI3K/AKT signaling pathway was confirmed in U251/U87 glioma cells. The SP family members exhibited elevated expression in gliomas and were negatively correlated with prognosis. SP140 emerged as an independent prognostic factor, and a SP140-based nomogram/predictive risk model demonstrated high accuracy. SP140 inhibitor, GSK761, lead to the suppression of TRIM22 expression and the PI3K/AKT signaling pathway. GSK761 also restrain glioma proliferation, migration, and invasion. Furthermore, SP140 and TRIM22 coexpressed in glioma cells with high level of vascular proliferation, TRIM22 is closely associated with the immune cell infiltration. SP140-based nomogram proved to be a practical tool for predicting the survival of glioma patients. SP140 inhibitor could suppress glioma progress via TRIM22/PI3K/AKT signaling pathway.

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.

Integrated multiomic analysis reveals disulfidptosis subtypes in glioblastoma: implications for immunotherapy, targeted therapy, and chemotherapy.

Glioblastoma (GBM) presents significant challenges due to its malignancy and limited treatment options. Precision treatment requires subtyping patients based on prognosis. Disulfidptosis, a novel cell death mechanism, is linked to aberrant glucose metabolism and disulfide stress, particularly in tumors expressing high levels of SLC7A11. The exploration of disulfidptosis may provide a new perspective for precise diagnosis and treatment of glioblastoma. Transcriptome sequencing was conducted on samples from GBM patients treated at Tiantan Hospital (January 2022 - December 2023). Data from CGGA and TCGA databases were collected. Consensus clustering based on disulfidptosis features categorized GBM patients into two subtypes (DRGclusters). Tumor immune microenvironment, response to immunotherapy, and drug sensitivity were analyzed. An 8-gene disulfidptosis-based subtype predictor was developed using LASSO machine learning algorithm and validated on CGGA dataset. Patients in DRGcluster A exhibited improved overall survival (OS) compared to DRGcluster B. DRGcluster subtypes showed differences in tumor immune microenvironment and response to immunotherapy. The predictor effectively stratified patients into high and low-risk groups. Significant differences in IC50 values for chemotherapy and targeted therapy were observed between risk groups. Disulfidptosis-based classification offers promise as a prognostic predictor for GBM. It provides insights into tumor immune microenvironment and response to therapy. The predictor aids in patient stratification and personalized treatment selection, potentially improving outcomes for GBM patients.

Association Between Diverse Cell Death Patterns Related Gene Signature and Prognosis, Drug Sensitivity, and Immune Microenvironment in Glioblastoma

Glioblastoma (GBM) is the most invasive type of glioma and is difficult to treat. Diverse programmed cell death (PCD) patterns have a significant association with tumor initiation and progression. A novel prognostic model based on PCD genes may serve as an effective tool to predict the prognosis of GBM. The study incorporated 11 PCD patterns, namely apoptosis, necroptosis, pyroptosis, ferroptosis, cuproptosis, entotic cell death, netotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis, and oxeiptosis, to develop the model. To construct and validate the model, both bulk and single-cell transcriptome data, along with corresponding clinical data from GBM cases, were obtained from the TCGA-GBM, REMBRANDT, CGGA, and GSE162631 datasets. A cell death-related signature containing 14 genes was constructed with the TCGA-GBM cohort and validated in the REMBRANDT and CGGA datasets. GBM patients with a higher cell death index (CDI) were significantly associated with poorer survival outcomes. Two separate clusters associated with clinical outcomes emerged from unsupervised analysis. A multivariate Cox regression analysis was conducted to examine the association of CDI with clinical characteristics, and a prognostic nomogram was developed. Drug sensitivity analysis revealed high-CDI GBM patients might be resistant to carmustine while sensitive to 5-fluorouracil. Less abundance of natural killer cells was found in GBM cases with high CDI and bulk transcriptome data. A cell death-related prognostic model that could predict the prognosis of GBM patients with good performance was established, which could discriminate between the prognosis and drug sensitivity of GBM.