A novel prognostic risk score model based on RNA editing level in lower-grade glioma.

BACKGROUND: Lower-grade glioma (LGG) refers to WHO grade 2 and 3 gliomas. Surgery combined with radiotherapy and chemotherapy can significantly improve the prognosis of LGG patients, but tumor progression is still unavoidable. As a form of posttranscriptional regulation, RNA editing (RE) has been reported to be involved in tumorigenesis and progression and has been intensively studied recently. METHODS: Survival data and RE data were subjected to univariate and multivariate Cox regression analysis and lasso regression analysis to establish an RE risk score model. A nomogram combining the risk score and clinicopathological features was built to predict the 1-, 3-, and 5-year survival probability of patients. The relationship among ADAR1, SOD2 and SOAT1 was verified by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) RESULTS: A risk model associated with RE was constructed and patients were divided into different risk groups based on risk scores. The model demonstrated strong prognostic capability, with the area under the ROC curve (AUC) values of 0.882, 0.938, and 0.947 for 1-, 3-, and 5-year survival predictions, respectively. Through receiver operating characteristic curve (ROC) curves and calibration curves, it was verified that the constructed nomogram had better performance than age, grade, and risk score in predicting patient survival probability. Apart from this functional analysis, the results of correlation analyses between risk differentially expressed genes (RDEGs) and RE help us to understand the underlying mechanism of RE in LGG. ADAR may regulate the expression of SOD2 and SOAT1 through gene editing. CONCLUSION: In conclusion, this study establishes a novel and accurate 17-RE model and a nomogram for predicting the survival probability of LGG patients. ADAR may affect the prognosis of glioma patients by influencing gene expression.

Sleep loss-induced oncogenic pathways are mediated via the neuron-specific interleukin-1 receptor accessory protein (AcPb).

Interleukin-1ß (IL1), a pleiotropic cytokine, is involved in sleep regulation, tumor ontogeny, and immune responses. IL1 receptor adaptor proteins, including the IL1 receptor accessory protein (AcP), and its neuron-specific isoform, AcPb, are required for IL1 signaling. The AcPb isoform is resultant from alternate splicing of the AcP transcript. Our previous studies using AcPb null (AcPb-/-) mice characterized its participation in sleep regulation and emergent neuronal/glial network properties. Here, we investigated the impact of acute sleep disruption (SD) on brain cancer-related pathways in wild-type (WT) and AcPb-/- mice, employing RNA sequencing methods. In WT mice, SD increased AcPb mRNA levels, but not AcP mRNA, confirming prior similar work in rats. Transcriptome and pathway enrichment analyses demonstrated significant alterations in cancer, immune, and viral disease-related pathways in WT mice after SD, which were attenuated in AcPb-/- mice including multiple upregulated Src phosphorylation-signaling-dependent genes associated with cancer progression and metastasis. Our RNAseq findings, were analyzed within the context of The Cancer Genome Atlas Program (TCGA) data base; revealing an upregulation of sleep- and cancer-linked genes (e.g., IL-17B, IL-17RA, LCN2) across various tumors, including brain tumors, compared to normal tissues. Sleep-linked factors, identified through TCGA analyses, significantly impact patient prognosis and survival, particularly in low-grade glioma (LGG) and glioblastoma multiforme (GBM) patients. Overall, our findings suggest that SD promotes a pro-tumor environment through AcPb-modulated pathways.

Pan-Cancer Analysis Reveals Long Non-coding RNA (lncRNA) Embryonic Stem Cell-Related Gene (ESRG) as a Promising Diagnostic and Prognostic Biomarker.

BACKGROUND: Embryonic stem cell-related gene (ESRG; also known as HESRG) is a long non-coding RNA (lncRNA). It is involved in the regulation of human pluripotent stem cells (hPSCs) self-renewal. ESRG gene has the ability to interact with chromatins, different RNA types, and RNA binding proteins (RBP); thus making ESRG be considered an oncogenic lncRNA, where its expression is detected in various tumor tissues. This study aimed to evaluate the prospective diagnostic and prognostic values of ESRG in various human cancers. MATERIALS AND METHODS: The expression of ESRG in various cancers was analyzed using the Gene Expression Profiling Interactive Analysis (GEPIA), Tumor Immune Estimation Resource (TIMER), and University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN) databases. Moreover, the correlation between the expression of ESRG and clinical pathological parameters was analyzed using UALCAN. The effect of ESRG expression on the survival outcome was evaluated using Kaplan-Meier plotter, UALCAN, GEPIA, and TIMER. The correlation between ESRG expression and immune cell infiltration was studied by TIMER. Additionally, the genetic alterations were investigated cBioportal. Our findings were validated using the GEO2R database. RESULTS: Our results showed ESRG to be significantly up-regulated in colon adenocarcinoma (COAD) and lung squamous cell carcinoma (LUSC) with p<0.001, in addition to rectum adenocarcinoma (READ), and uterine carcinosarcoma (UCEC) with p<0.01. Regarding pathogenic stages, there was a significant upregulation in stages 2, 3, and 4 compared to normal in COAD and stages 1, 2, and 3 for LUSC patients. The combined prognostic analysis showed that the up-regulated expression of ESRG was associated with better survival outcomes in patients with brain lower-grade glioma (LGG). Our results demonstrate a significant negative correlation between ESRG expression and the abundance of CD8+T cells in COAD, READ, LUSC, and UCEC. Additionally, ESRG was mutated in 0.77 (<1%) of the queried samples, and the most prevalent ESRG mutations are deep deletion mutations, followed by amplification. CONCLUSION: Analysis of ESRG across various cancer types elucidated its potential to be used as a diagnostic biomarker in COAD, LUSC, READ, and UCEC and a promising prognostic biomarker in LGG. Our findings provide useful insights for future research.

AB083. Epilepsy and low-grade glioma-seizure control after surgical resection: a retrospective cohort study.

BACKGROUND: Seizures are a common manifestation in patients with low grade glioma (60-75%), and 60-90% patients attain seizure freedom after resection. Seizure control varies with histopathology, extent of resection and type of seizures. There is inconsistency in literature regarding utility of anti-epileptic drugs (AEDs) after tumor resection. We aimed to determine factors associated with seizure control in patients after low-grade glioma (LGG) resection. METHODS: It was a retrospective cohort study. Medical record of all patients who underwent LGG resection at our center from 2019 to 2021 were reviewed; 77 patients fulfilled the selection criteria. Patients were also contacted via phone calls to collect information about their seizure control as per Engel Classification. Data was analyzed using SPSSv21. RESULTS: The mean age was 34.9±11.3 years, and there was male predominance (62; 80.5%). Generalized seizures were the most common type (54; 70%), and Levetiracetam was the most commonly prescribed AED (60; 77.9%). The median duration of pre-operative AED use was 4 [interquartile range (IQR): 1-24] months. Frontal lobe was the most common location of tumor (36; 46.8%). Most of the patients had their surgery under general anesthesia (51; 61.4%), while 29 (37.7%) underwent awake craniotomy. Nearly half of the patients had a gross total resection (31; 40.3%), and another 15 (19.5%) had near-total resection. Sixteen patients (20.8%) had their AEDs stopped within first 6 months post-operatively (at variable intervals), and all of them had Engel Class IA to ID control at time of follow-up (P=0.008). The 12 patients with grade I glioma also had optimum seizure control (P=0.03). CONCLUSIONS: Patients with grade I glioma have better seizure control after surgery. Tumor biopsy is associated with worse seizure outcome, though not statistically significant. Larger studies are needed to determine the ideal time and patient group for discontinuing AED after surgery.

A patient-derived cell model for malignant transformation in IDH-mutant glioma.

Malignant transformation (MT) is commonly seen in IDH-mutant gliomas. There has been a growing research interest in revealing its underlying mechanisms and intervening prior to MT at the early stages of the transforming process. Here we established a unique pair of matched 3D cell models: 403L, derived from a low-grade glioma (LGG), and 403H, derived from a high-grade glioma (HGG), by utilizing IDH-mutant astrocytoma samples from the same patient when the tumor was diagnosed as WHO grade 2 (tumor mutational burden (TMB) of 3.96/Mb) and later as grade 4 (TMB of 70.07/Mb), respectively. Both cell models were authenticated to a patient's sample retaining endogenous expression of IDH1 R132H. DNA methylation profiles of the parental tumors referred to LGG and HGG IDH-mutant glioma clusters. The immunopositivity of SOX2, NESTIN, GFAP, OLIG2, and beta 3-Tubulin suggested the multilineage potential of both models. 403H was more prompt to cell invasion and developed infiltrative HGG in vivo. The differentially expressed genes (DEGs) from the RNA sequencing analysis revealed the tumor invasion and aggressiveness related genes exclusively upregulated in the 403H model. Pathway analysis showcased an enrichment of genes associated with epithelial-mesenchymal transition (EMT) and Notch signaling pathways in 403H and 403L, respectively. Mass spectrometry-based targeted metabolomics and hyperpolarized (HP) 1-13C pyruvate in-cell NMR analyses demonstrated significant alterations in the TCA cycle and fatty acid metabolism. Citrate, glutamine, and 2-HG levels were significantly higher in 403H. To our knowledge, this is the first report describing the development of a matched pair of 3D patient-derived cell models representative of MT and temozolomide (TMZ)-induced hypermutator phenotype (HMP) in IDH-mutant glioma, providing insights into genetic and metabolic changes during MT/HMP. This novel in vitro model allows further investigation of the mechanisms of MT at the cellular level.

Prognostic value of anoikis-related genes revealed using multi-omics analysis and machine learning based on lower-grade glioma features and tumor immune microenvironment.

Background: The investigation explores the involvement of anoikis-related genes (ARGs) in lower-grade glioma (LGG), seeking to provide fresh insights into the disease's underlying mechanisms and to identify potential targets for therapy. Methods: We applied unsupervised clustering techniques to categorize LGG patients into distinct molecular subtypes based on ARGs with prognostic significance. Additionally, various machine learning algorithms were employed to pinpoint genes most strongly correlated with patient outcomes, which were then used to develop and assess risk profiles. Results: Our analysis identified two distinct molecular subtypes of LGG, each with significantly different prognoses. Patients in Cluster 2 had a median survival of 2.036 years, markedly shorter than the 7.994 years observed in Cluster 1 (P < 0.001). We also constructed a six-gene ARG signature that efficiently classified patients into two risk categories, showing median survival durations of 4.084 years for the high-risk group and 10.304 years for the low-risk group (P < 0.001). Significantly, the immune profiles, tumor mutation characteristics, and drug sensitivity varied greatly among these risk groups. The high-risk group was characterized by a "cold" tumor microenvironment (TME), a lower IDH1 mutation rate (61.7 % vs. 91.4 %), a higher TP53 mutation rate (53.7 % vs. 38.9 %), and greater sensitivity to targeted therapies such as QS11 and PF-562271. Furthermore, our nomogram, integrating risk scores with clinicopathological features, demonstrated strong predictive accuracy for clinical outcomes in LGG patients, with an AUC of 0.903 for the first year. The robustness of this prognostic model was further validated through internal cross-validation and across three external cohorts. Conclusions: The evidence from our research suggests that ARGs could potentially serve as reliable indicators for evaluating immunotherapy effectiveness and forecasting clinical results in patients with LGG.

Role of surgery in the treatment of pediatric low-grade glioma with various degrees of brain stem involvement.

OBJECTIVE: Posterior fossa pediatric low-grade glioma involving the brainstem and cerebellar peduncles (BS-pLGG) are a subgroup with higher risks at surgery. We retrospectively analyzed the role of surgery in the interdisciplinary armamentarium of treatment options in our institutional series of BS-pLGG with various degrees of brainstem involvement. MATERIAL AND METHODS: We analyzed data of 52 children with BS-pLGG after surgical intervention for clinical/molecular characteristics, neurological outcome, factors influencing recurrence/progression pattern, and tumor volumetric analysis of exclusively surgically treated patients to calculate tumor growth velocity (TGV). Tumors were stratified according to primary tumor origin in four groups: (1) cerebellar peduncle, (2) 4th ventricle, (3) pons, (4) medulla oblongata. RESULTS: The mean FU was 6.44 years. Overall survival was 98%. The mean PFS was 34.07 months. Two patients had biopsies only. Fifty-two percent of patients underwent remission or remained in stable disease (SD) after initial surgery. Patients with progression underwent further 23 resections, 15 chemotherapies, 4 targeted treatments, and 2 proton radiations. TGV decreased after the 2nd surgery compared to TGV after the 1st surgery (p < 0.05). The resection rates were significantly higher in Groups 1 and 2 and lowest in medulla oblongata tumors (Group 4) (p < 0.05). More extended resections were achieved in tumors with KIAA1549::BRAF fusion (p = 0.021), which mostly occurred in favorable locations (Groups 1 and 2). Thirty-one patients showed postoperatively new neurological deficits. A total of 27/31 improved within 12 months. At the end of FU, 6% had moderate deficits, 52% had mild deficits not affecting activities, and 36% had none. Fifty percent of patients were free of disease or showed remission, 38% were in SD, and 10% showed progression. CONCLUSION: The first surgical intervention in BS-pLGG can control disease alone in overall 50% of cases, with rates differing greatly according to location (Groups 1 > 2 > 3 > 4), with acceptable low morbidity. The second look surgery is warranted except in medullary tumors. With multimodality treatments almost 90% of patients can obtain remission or stable disease after > 5 years of follow-up. An integrated multimodal and multidisciplinary approach aiming at minimal safe residual disease, combining surgery, chemo-, targeted therapy, and, as an exception, radiation therapy, is mandatory.

STAT3 drives the malignant progression of low-grade gliomas through modulating the expression of STAT1, FOXO1, and MYC.

Low-grade glioma (LGG) is a prevalent and lethal primary brain malignancy, with most patients succumbing to recurrence and progression. The signal transducer and activator of transcription (STAT) family has long been implicated in tumor initiation and progression. However, a comprehensive evaluation of the expression status and overall function of STAT genes in LGG remains largely unreported. In this study, we investigated the association between the expression of STAT family genes and the progression of LGG. Through a comprehensive analysis that combined bioinformatics screening and validation assays, we determined that STAT1, STAT3, and STAT5A were upregulated and contributed to the malignant progression of LGG. Notably, our findings suggest that STAT3 is a critical prognostic marker that regulates the progression of LGG. STAT3 emerged as the most significant prognostic indicator governing the advancement of LGG. Additionally, our inquiry into the STAT3-binding proteins and differentially expressed-correlated genes (DEGs) revealed that STAT3 played a pivotal role in the progression of LGG by stimulating the expression of STAT1, FOXO1, and MYC. In summary, our recent study conducted a thorough analysis of the STAT family genes and revealed that directing therapeutic interventions towards STAT3 holds potential as a viable strategy for treating patients with LGG.

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

Purpose: 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. Methods: 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. Results: 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. Conclusion: Our study sifted out ten invasion-related biomarkers of LGG, providing a reference for treatments and prognostic prediction in LGG.

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.

Identification of Novel Prognostic Signature of Recurrent Low-Grade Glioma.

OBJECTIVES: The prognosis of patients with recurrent low-grade glioma (rLGG) varies greatly. Some patients can survive >10 years after recurrence, whereas other patients have <1 year of survival. METHODS: To identify the related risk factors affecting the prognosis of patients with rLGG, we performed a series of bioinformatics analyses on RNA sequencing data of rLGG based on the Chinese Glioma Genome Altas database. RESULTS: We constructed a 12-gene prognostic signature, dividing all the patients with rLGG into high- and low-risk subgroups. The result showed an excellent predictive effect in both the training cohort and the validation cohort using LASSO-Cox regression. Moreover, multivariate Cox analysis identified 4 independent prognostic factors of rLGG; among them, ZCWPW1 is identified as a high-value protective factor. CONCLUSIONS: In all, this prognostic model displayed robust predictive capability for the overall survival of patients with rLGG, providing a new monitoring method for rLGG. The 4 independent prognostic factors, especially ZCWPW1, can be potential targets for rLGG, bringing new possibilities for the treatment of patients with rLGG.

Leveraging FAM features to predict the prognosis of LGG patients and immunotherapy outcome.

Heterogeneity at biological and transcriptomic levels poses a challenge in defining and typing low-grade glioma (LGG), leading to a critical need for specific molecular signatures to enhance diagnosis, therapy, and prognostic evaluation of LGG. This study focused on fatty acid metabolism (FAM) related genes and prognostic features to investigate the mechanisms and treatment strategies for LGG cell metastasis and invasion. By screening 158 FAM-related genes and clustering 512 LGG samples into two subtypes (C1 and C2), differential gene expression analysis and functional enrichment were performed. The immune cell scores and prognosis were compared between the two subtypes, with C1 showing poorer outcomes and higher immune scores. A four-gene signature (PHEX, SHANK2, HOPX, and LGALS1) was identified and validated across different datasets, demonstrating a stable predictive effect. Cellular experiments confirmed the roles of LGALS1 and HOPX in promoting tumor cell proliferation, migration, and invasion, while SHANK2 exhibited a suppressive effect. This four-gene signature based on FAM-related genes offers valuable insights for understanding the pathogenesis and clinical management of LGG.

Fibroblast growth factor receptor 1 gene mutation as a potential risk factor for spontaneous intracranial hemorrhage in pediatric low-grade glioma patients.

Background: Fibroblast growth factor receptor 1 (FGFR1) mutations have been associated with poorer prognoses in pediatric central nervous system tumor patients. A recent study highlighted a link between FGFR1 mutations and spontaneous intracranial hemorrhage (ICH), demonstrating that all patients with an FGFR1 alteration experienced hemorrhage at some point during their course of treatment. Methods: The current study examined 50 out of 67 pediatric patients with low-grade gliomas (LGGs) who had genomic testing between 2011 and 2022 at our institution to determine whether a correlation exists between FGFR1 mutations and spontaneous ICH. Results: We found that of the 50 patients with genomic data, 7 (14%) experienced ICH, and an additional spontaneous hemorrhage was recorded; however, no genomic testing was performed for this case. Five of the seven patients (71.4%) had an FGFR1 modification. In our patient population, 6 expressed a detectable FGFR1 mutation (66.7% [4/6] had N546K alteration, 16.7% [1/6] FGFR1 exons duplication, and 16.7% [1/6] had a variant of unknown significance [VUS]). The patient with the FGFR1 VUS had no reported spontaneous hemorrhage. Statistical analysis found a significant association between FGFR1 and spontaneous intracranial hemorrhage (P-value = < .0001). In the patient population, all cases of PTPN11 alterations (n = 3) co-occurred with FGFR1 mutations. Conclusions: Our case series highlights this link between the FGFR1 mutation and spontaneous intracranial hemorrhage in pediatric LGGs.

Intramedullary pediatric low-grade glioma of the spine.

PURPOSE: Pediatric intramedullary spinal cord low-grade gliomas (pLGGs) are rare diagnoses among central nervous system (CNS) tumors in the pediatric population. The classic presentation of the patients includes some degree of neurologic deficit, although many times the symptoms are vague which leads to delayed diagnosis. MATERIAL AND METHODS: The first step in the diagnosis includes special parameters in spinal imaging, particularly magnetic resonance imaging (MRI), and surgical resection remains the cornerstone for both diagnosis and treatment. Yet, recent years advancement in molecular and genetic understanding of CNS tumors allows for better adjustment of the treatment and follow-up regimens. Based on postoperative status, adjuvant therapy may provide additional therapeutic advantage for some types of tumors. CONCLUSION: Ultimately, patients have a very promising prognosis when treated appropriately in most of the cases of pediatric spinal cord LGG with continued advances arising. This manuscript summarizes the most contemporary evidence regarding clinical and treatment features of intramedullary pLGGs.

DNMT3A promotes glioma growth and malignancy via TNF-α/NF-κB signaling pathway.

Background: DNMT3A is the main molecule responsible for DNA methylation in cells. DNMT3A affects the progression of inflammation, degenerative diseases, and malignant tumors, and exhibits significant aberrantly expression in tumor tissues. Methods: Transcriptome data and relevant clinical information were downloaded from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) datasets. Differential expression analysis and prognostic analysis were conducted based on above statistics. We constructed a clinical prognostic model and identified DNMT3A as an independent prognostic factor to accurately predict patient prognosis. Differential gene enrichment analysis revealed that DNMT3A affects the progression of glioma through multiple pathways, among which the tumor necrosis factor-α (TNF-α)/nuclear factor-kappa B (NF-κB) pathway shows a strong correlation. Immunological analysis also revealed a certain correlation between DNMT3A and tumor immunity. We demonstrated through gene editing that DNMT3A can affect the release of TNF-α in cells, thereby affecting the progression of glioma. Functional experiments have also demonstrated that DNMT3A plays a crucial role in tumors. Results: RNA-sequencing and survival analyses of lower-grade glioma (LGG) patients in TCGA, CGGA, and GEO cohorts showed that high DNMT3A expression correlated with poor prognosis of LGG patients. Univariate and multivariate Cox regression analyses showed that DNMT3A expression was an independent prognostic indicator in LGG. The prognosis prediction nomogram with age, World Health Organization (WHO) grading, and DNMT3A expression showed reliable performance in predicting the 1-, 3-, and 5-year overall survival (OS) of LGG patients. Functional enrichment analysis, gene set enrichment analysis (GSEA), and ESTIMATE algorithm analyses showed that DNMT3A expression was associated with the tumor infiltration of immune cells and predicted response to immunotherapy in two immunotherapy cohorts of pan-cancer patients. Furthermore, short hairpin RNA (shRNA)-mediated knockdown of DNMT3A in the LGG cell lines suppressed proliferation, migration, and invasion of LGG cells by downregulating the TNF-α/NF-κB signaling pathway. Conclusions: Our data showed that DNMT3A was a potential prognostic biomarker in glioma. DNMT3A promoted proliferation and malignancy of LGG cells through the TNF-α/NF-κB signaling pathway. DNMT3A is a promising therapeutic target for treating patients with LGG.

Identification and clinical validation of diverse cell-death patterns-associated prognostic features among low-grade gliomas.

Low-grade glioma (LGG) is heterogeneous at biological and transcriptomic levels, and it is still controversial for the definition and typing of LGG. Therefore, there is an urgent need for specific and practical molecular signatures for accurate diagnosis, individualized therapy, and prognostic evaluation of LGG. Cell death is essential for maintaining homeostasis, developing and preventing hyperproliferative malignancies. Based on diverse programmed cell death (PCD) related genes and prognostic characteristics of LGG, this study constructed a model to explore the mechanism and treatment strategies for LGG cell metastasis and invasion. We screened 1161 genes associated with PCD and divided 512 LGG samples into C1 and C2 subtypes by consistent cluster analysis. We analyzed the two subtypes' differentially expressed genes (DEGs) and performed functional enrichment analysis. Using R packages such as ESTIMATE, CIBERSOTR, and MCPcounter, we assessed immune cell scores for both subtypes. Compared with C1, the C2 subtype has a poor prognosis and a higher immune score, and patients in the C2 subtype are more strongly associated with tumor progression. LASSO and COX regression analysis screened four characteristic genes (CLU, FHL3, GIMAP2, and HVCN1). Using data sets from different platforms to validate the four-gene feature, we found that the expression and prognostic correlation of the four-gene feature had a high degree of stability, showing stable predictive effects. Besides, we found downregulation of CLU, FHL3, and GIMAP2 significantly impairs the growth, migration, and invasive potential of LGG cells. Take together, the four-gene feature constructed based on PCD-related genes provides valuable information for further study of the pathogenesis and clinical treatment of LGG.

A cuproptosis-based prognostic model for predicting survival in low-grade glioma.

BACKGROUND: It is unknown what variables contribute to the formation and multiplication of low-grade gliomas (LGG). An emerging process of cell death is called cuproptosis. Our research aims to increase therapeutic options and gain a better understanding of the role that cuproptosis-related genes play in the physical characteristics of low-grade gliomas. METHODS: The TCGA database was utilized to find cuproptosis genes that may be used to develop LGG risk model. Cox analysis in three different formats: univariate, multivariate, and LASSO. The gene signature's independent predictive ability was assessed using ROC curves and Cox regression analysis based on overall survival. Use of CGGA data and nomogram model for external validation Immunohistochemistry, gene mutation, and functional enrichment analysis are also employed to clarify risk models' involvement. Next, we analyzed changes in the immunological microenvironment in the risk model and forecasted possible chemotherapeutic drugs to target each group. Finally, we validated the protein expression levels of cuproptosis-related genes using LGG and adjacent normal tissues in a small self-case-control study. RESULTS: This study developed a glioma predictive model based on five cuproptosis-associated genes. Compared to the high-risk group, the low-risk group's OS was significantly longer. The ROC curves showed high genetic signature performance in both groups. The signature-based categorisation was also linked to clinical characteristics and molecular subgroups. The prognosis of individuals with grade 2 or 3 glioma is also influenced by our risk model. Immunological testing revealed that the high-risk group had more immune cells and immunological function. The risk model also predicted immunotherapy and chemotherapy medication results. Also, this study confirmed that the expression of cuproptosis-related genes by Western blot. CONCLUSION: We developed a prediction model for LGG patients using genes associated with cuproptosis. With acceptable prediction performance, this risk model may effectively stratify the prognosis of glioma patients.

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.

Autophagy and UPS pathway contribute to nicotine-induced protection effect in Parkinson's disease.

The gradual nature of age-related neurodegeneration causes Parkinson's disease (PD) and impairs movement, memory, intellectual ability, and social interaction. One of the most prevalent neurodegenerative conditions affecting the central nervous system (CNS) among the elderly is PD. PD affects both motor and cognitive functions. Degeneration of dopaminergic (DA) neurons and buildup of the protein α-synuclein (α-Syn) in the substantia nigra pars compacta (SNpc) are two major causes of this disorder. Both UPS and ALS systems serve to eliminate α-Syn. Autophagy and UPS deficits, shortened life duration, and lipofuscin buildup accelerate PD. This sickness has no cure. Innovative therapies are halting PD progression. Bioactive phytochemicals may provide older individuals with a natural substitute to help delay the onset of neurodegenerative illnesses. This study examines whether nicotine helps transgenic C. elegans PD models. According to numerous studies, nicotine enhances synaptic plasticity and dopaminergic neuronal survival. Upgrades UPS pathways, increases autophagy, and decreases oxidative stress and mitochondrial dysfunction. At 100, 150, and 200 µM nicotine levels, worms showed reduced α-Syn aggregation, repaired DA neurotoxicity after 6-OHDA intoxication, increased lifetime, and reduced lipofuscin accumulation. Furthermore, nicotine triggered autophagy and UPS. We revealed nicotine's potential as a UPS and autophagy activator to prevent PD and other neurodegenerative diseases.