Our research endeavors are directed towards unraveling the stem cell characteristics of lower-grade glioma patients, with the ultimate goal of formulating personalized treatment strategies. We computed enrichment stemness scores and performed consensus clustering to categorize phenotypes. Subsequently, we constructed a prognostic risk model using weighted gene correlation network analysis (WGCNA), random survival forest regression analysis as well as full subset regression analysis. To validate the expression differences of key genes, we employed experimental methods such as quantitative Polymerase Chain Reaction (qPCR) and assessed cell line proliferation, migration, and invasion. Three subtypes were assigned to patients diagnosed with LGG. Notably, Cluster 2 (C2), exhibiting the poorest survival outcomes, manifested characteristics indicative of the subtype characterized by immunosuppression. This was marked by elevated levels of M1 macrophages, activated mast cells, along with higher immune and stromal scores. Four hub genes-CDCA8, ORC1, DLGAP5, and SMC4-were identified and validated through cell experiments and qPCR. Subsequently, these validated genes were utilized to construct a stemness risk signature. Which revealed that Lower-Grade Glioma (LGG) patients with lower scores were more inclined to demonstrate favorable responses to immune therapy. Our study illuminates the stemness characteristics of gliomas, which lays the foundation for developing therapeutic approaches targeting CSCs and enhancing the efficacy of current immunotherapies. By identifying the stemness subtype and its correlation with prognosis and TME patterns in glioma patients, we aim to advance the development of personalized treatments, enhancing the ability to predict and improve overall patient prognosis.

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.

UNASSIGNED: mRNA vaccines represent a promising and innovative strategy within the realm of cancer immunotherapy. However, their efficacy in treating lower-grade glioma (LGG) requires evaluation. Ferroptosis exhibits close associations with the initiation, evolution, and suppression of cancer. In this study, we explored the landscape of the ferroptosis-associated tumor microenvironment to facilitate the development of mRNA vaccines for LGG patients.
UNASSIGNED: Genomic and clinical data of the LGG patients was obtained from the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Ferroptosis-related tumor antigens were identified based on differential expression, mutation status, correlation with antigen-presenting cells, and prognosis, relevance to immunogenic cell death (ICD). Antigen expression levels in LGG specimens and cell lines were validated using real time-polymerase chain reaction (RT-PCR). Consensus clustering was employed for patient classification. The immune landscapes of ferroptosis subtypes were further characterized, including immune responses, prognostic ability, tumor microenvironment, and tumor-related signatures.
UNASSIGNED: Five tumor antigens, namely, HOTAIR, IDO1, KIF20A, NR5A2, and RRM2 were identified in LGG. RT-PCR demonstrated higher expression of these genes in LGG compared to the control. Twelve gene modules and four ferroptosis subtypes (FS1-FS4) of LGG were defined. FS2 and FS4, characterized as \"cold\" tumors due to their decreased tumor mutation burden (TMB) and immune checkpoint proteins (ICPs), were deemed appropriate candidates for the mRNA vaccine.
UNASSIGNED: HOTAIR, IDO1, KIF20A, NR5A2, and RRM2 were identified as promising candidate antigens for the development of an LGG mRNA vaccine, particularly offering potential benefits to FS2 and FS4 patients.

OBJECTIVE: To investigate the differential expression of vascular related ceRNA regulatory genes in LGG with different mutations of IDH1 and MGMT, and to verify imaging gene markers that can be closely associated with vascular related ceRNA regulatory genes.
METHODS: Five hundred fifteen patients with LGG were collected from TCGA database. CeRNA network analysis, GO analysis and Cox risk regression were used to find vascular ceRNA regulatory genes and their genetic markers related to survival. The preoperative MRI image data and postoperative tumor tissues of 14 patients with WHO grade III glioma were collected for full transcriptome analysis. The correlation between image characteristics of LGG and survival related vascular ceRNA regulatory genes was compared using nonparametric U test and Pearson correlation coefficient analysis.
RESULTS: Vascular related genes ranked first in the functional enrichment analysis of differentially expressed genes in LGG. EPHA2, ETS1, YAP1 and MEIS1 could significantly affect the survival of patients in each group of LGG. The volume of enhanced region was negatively correlated with IDH1 (r = -0.622, P = 0.009) mutation and TMEM100 (r = -0.535, P = 0.024), and positively correlated with MEIS1 (r = 0.551, P = 0.021), rCBFmax value was negatively correlated with TMEM100 (r = -0.492, P = 0.037).
CONCLUSIONS: Under different IDH1 mutations, lncRNA-dominated vascular-related ceRNA regulatory genes were the first differentially expressed subset of each group, and could be used as an effective risk factor affecting the survival of LGG. The image characteristics of LGG was an ideal image gene marker. It was a reliable imaging biological marker which can truly reflect the pathophysiological characteristics of glioma.

Few large studies have investigated quality of life (QOL) for adults diagnosed with lower grade glioma (LGG).
QOL was assessed for 320 adults with LGG (World Health Organization grade 2/3) enrolled in the International Low Grade Glioma Registry by using the Medical Outcomes Study 36-Item Short Form health survey. Data on symptoms were also collected. QOL outcomes were examined by treatment group and also compared to those from a population-based case-control study of meningioma (the Meningioma Consortium), in which 1722 meningioma cases diagnosed among residents of Connecticut, Massachusetts, California, Texas, and North Carolina from May 1, 2006 through March 14, 2013 were enrolled and frequency matched to 1622 controls by age, sex, and geography.
The LGG sample average age is 45 years at the time of interview and 53.1% male. Almost 55% of patients had received radiation and chemotherapy (primarily temozolomide); 32.4% had received neither treatment. Two-thirds of participants with LGG report difficulty with speaking, memory, or thinking, and over one of three reports personality change or difficulty driving. After controlling for age and other comorbidities, individuals with LGG report levels of physical, emotional, and mental health functioning below those reported in a meningioma as well as a general healthy population.
Despite being relatively young, persons with LGG report significantly reduced QOL compared to persons with nonmalignant brain tumors and to a control population, which highlights the need to better acknowledge and manage these symptoms for this group of patients diagnosed in the prime of life.

Glioma stem cells (GSCs) remodel their tumor microenvironment to sustain a supportive niche. Identification and stratification of stemness related characteristics in patients with glioma might aid in the diagnosis and treatment of the disease. In this study, we calculated the mRNA stemness index in bulk and single-cell RNA-sequencing datasets using machine learning methods and investigated the correlation between stemness and clinicopathological characteristics. A glioma stemness-associated score (GSScore) was constructed using multivariate Cox regression analysis. We also generated a GSC cell line derived from a patient diagnosed with glioma and used glioma cell lines to validate the performance of the GSScore in predicting chemotherapeutic responses. Differentially expressed genes (DEGs) between GSCs with high and low GSScores were used to cluster lower-grade glioma (LGG) samples into three stemness subtypes. Differences in clinicopathological characteristics, including survival, copy number variations, mutations, tumor microenvironment, and immune and chemotherapeutic responses, among the three LGG stemness-associated subtypes were identified. Using machine learning methods, we further identified genes as subtype predictors and validated their performance using the CGGA datasets. In the current study, we identified a GSScore that correlated with LGG chemotherapeutic response. Through the score, we also identified a novel classification of the LGG subtype and associated subtype predictors, which might facilitate the development of precision therapy.

The association between SLC10A3 (solute carrier family 10 member 3) and lower grade glioma (LGG) remains unclear.
We used public databases and bioinformatics analysis to analyze SLC10A3. These included The Cancer Genome Atlas, Genotype-Tissue Expansion, Chinese Glioma Genome Atlas, Human Protein Atlas, GeneCards, cBioPortal, Search Tool for the Retrieval of Interacting Genes/Proteins, Gene Expression Profiling Interactive Analysis, Tumor Immune Estimation Resource, Tumor-Immune System Interaction Database, receiver operating characteristic curve analysis, Kaplan-Meier analysis, Cox analysis, nomograms, calibration plots, gene ontology/Kyoto Encyclopedia of Genes and Genomes enrichment analysis, gene set enrichment analysis, single-sample gene set enrichment analysis, and Spearman\'s correlation analysis.
SLC10A3 was upregulated in adrenocortical carcinoma, glioblastoma, and LGG and was associated with good overall survival (OS) in adrenocortical carcinoma and poor OS in LGG and glioblastoma. SLC10A3 was increased with increased World Health Organization grade, upregulated in isocitrate dehydrogenase-wild type, 1p/19q (chromosome arms 1p and 19q) non-co-deleted, and higher in astrocytoma. Patients with LGG were grouped by the occurrence of the clinical outcome endpoints (i.e., OS, disease-specific survival [DSS], and progression-free interval events). Genetic alterations in SLC10A3 were associated with poor progression-free survival in LGG. Most of clinical characteristics were associated with the SLC10A3 expression level. SLC10A3 with diagnostic and prognostic value (OS, DSS, and progression-free interval) was an independent prognostic factor in LGG. Moreover, Nomograms (WHO grade, 1p/19q codeletion, age and SLC10A3) had moderately accurate predictive for OS and DSS. Functional analysis showed that SLC10A3 might participate in the transport of multiple substances, neurogenic signaling, immune response, and programmed cell death in LGG. SLC10A3 correlated with immune infiltration in LGG and moderately correlated with the gene signature of pyroptosis, lysosome-dependent cell death, necroptosis, apoptosis, ferroptosis, alkaliptosis, and autophagy-dependent cell death.
SLC10A3 is a potential diagnostic and prognostic biomarker for LGG and might be associated with substance transport, neurogenic signaling, immune infiltration, and programmed cell death in LGG.

OBJECTIVE: The alternative extension of the telomeres (ALT) mechanism is activated in lower grade glioma (LGG), but the role of the ALT mechanism has not been well discussed. The primary purpose was to demonstrate the significance of the ALT mechanism in prognosis estimation for LGG patients.
METHODS: Gene expression and clinical data of LGG patients were collected from the Chinese Glioma Genome Atlas (CGGA) and the Cancer Genome Atlas (TCGA) cohort, respectively. ALT-related genes obtained from the TelNet database and potential prognostic genes related to ALT were selected by LASSO regression to calculate an ALT-related risk score. Multivariate Cox regression analysis was performed to construct a prognosis signature, and a nomogram was used to represent this signature. Possible pathways of the ALT-related risk score are explored by enrichment analysis.
RESULTS: The ALT-related risk score was calculated based on the LASSO regression coefficients of 22 genes and then divided into high-risk and low-risk groups according to the median. The ALT-related risk score is an independent predictor of LGG (HR and 95% CI in CGGA cohort: 5.70 (3.79, 8.58); in TCGA cohort: 1.96 (1.09, 3.54)). ROC analysis indicated that the model contained ALT-related risk score was superior to conventional clinical features (AUC: 0.818 vs 0.729) in CGGA cohorts. The results in the TCGA cohort also shown a powerful ability of ALT-related risk score (AUC: 0.766 vs 0.691). The predicted probability and actual probability of the nomogram are consistent. Enrichment analysis demonstrated that the ALT mechanism was involved in the cell cycle, DNA repair, immune processes, and others.
CONCLUSIONS: ALT-related risk score based on the 22-gene is an important factor in predicting the prognosis of LGG patients.

Cornichon family AMPA receptor auxiliary protein 4 (CNIH4) functions as an oncogene in several types of tumor. Nevertheless, the potential function of CNIH4 in lower-grade glioma (LGG) remains unclear. Pan-cancer analysis was implemented to comprehensively explore CNIH4 expression patterns and prognostic value in multiple cancers. Further, a systematic investigation of correlations between CNIH4 expression and clinical features, prognosis, biological functions, immune properties, genomic mutations, and treatment response was conducted, based on LGG expression patterns. CNIH4 expression levels and specific roles in LGG were also evaluated using in vitro experiments. Aberrant CNIH4 overexpression was detected in various tumors, and higher CNIH4 expression was linked with inferior prognosis, including in patients with LGG. Univariate and multivariate Cox regression analysis indicated that CNIH4 expression was an independent prognostic biomarker in patients with LGG. Our data also revealed that CNIH4 expression was strongly related to immune-associated signatures, immune cell infiltration, immune checkpoint genes, copy number alteration burden, tumor mutation burden, and treatment response in patients with LGG. In vitro experiments confirmed that CNIH4 was unusually elevated and crucial for cell proliferation, migration, invasion and cell cycle regulation in LGG. Together, our data validate CNIH4 may be an independent prognostic biomarker that could serve as a novel therapeutic target for improvement of prognosis in patients with LGG.

OBJECTIVE: We previously reported that expression of dickkopf-3 (DKK3), which is involved in the Wnt/β-catenin pathway, is significantly associated with prognosis in patients with glioblastoma multiforme (GBM). The aim of this study was to compare the association of DKK3 with other Wnt/β-catenin pathway-related genes and immune responses between lower grade glioma (LGG) and GBM.
METHODS: We obtained the clinicopathological data of 515 patients with LGG (World Health Organization [WHO] grade II and III glioma) and 525 patients with GBM from the Cancer Genome Atlas (TCGA) database. We performed Pearson\'s correlation analysis to investigate the relationships between Wnt/β-catenin-related gene expression in LGG and GBM. Linear regression analysis was performed to identify the association between DKK3 expression and immune cell fractions in all grade II to IV gliomas.
RESULTS: A total of 1,040 patients with WHO grade II to IV gliomas were included in the study. As the grade of glioma increased, DKK3 showed a tendency to be more strongly positively correlated with the expression of other Wnt/β-catenin pathway-related genes. DKK3 was not associated with immunosuppression in LGG but was associated with downregulation of immune responses in GBM. We hypothesized that the role of DKK3 in the Wnt/β-catenin pathway might be different between LGG and GBM.
CONCLUSIONS: According to our findings, DKK3 expression had a weak effect on LGG but a significant effect on immunosuppression and poor prognosis in GBM. Therefore, DKK3 expression seems to play different roles, through the Wnt/β-catenin pathway, between LGG and GBM.