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Lower WHO grade II and III gliomas (LGGs) are characterized by widespread genetic and transcriptional heterogeneity, yet little is known about the heterogeneity of the DNA Damage Repair (DDR), its function in tumor biology, coupling with the transcriptome and tumor microenvironment (TM) and its possible impact for tumor development. In this study, the DNA damage repair (DDR) alterations among LGG have been studied via multi-omics data integration. For this, LGG patients have been grouped into distinct subtypes (DDR-activated and the DDR-suppressed subtype) based on different clinicalparameters and molecular characteristics. The differences in gene mutation, immune spectrum, and immune cell infiltration between the two DDR subtypes were compared. We generated DDR subtype features (DDR scores) to implement DDR classification in LGG and confirmed the results using a multi-layer data cohort.The DDR activation subgroup was found to be associated with poorer overall survival based on molecular subtypes, and clinicopathological features of advanced-age and higher-grade were more common in the DDR-activated subgroup. DDR-suppressed subtypes also exhibited more frequent mutations in IDH1. We also found significant upregulation of activated immune cells in the DDR-activated subgroup, which indicates significant influence posed by infiltration of immune cells on tumor progression as well as immunotherapeutic responses. In addition, six DDR genes were selected to construct a DDR signature of LGG, dividing patients into low- and high-risk groups. The QRT-PCR results showed that the expression levels of CDK1, CDK2, TYMS, SMC4, and WEE1 were found to be considerably higher for LGG samples compared to normal brain tissue samples (p

The compatibility of deep brain stimulation (DBS) hardware and MRI scans has greatly improved the diagnostic rate of postoperative peri-lead edema (PLE). However, the etiology, incidence, and prognostic outcomes of this complication have not been established.The incidence of PLE and associated symptoms, the process of occurrence and progression of this complication, as well as treatment strategies were evaluated.We conducted a Preferred Reporting Items for Systematic Reviews and Meta-Analyses compliant systematic review of all studies that reported on incidences of PLE and associated symptoms after DBS implantation. Through systematic literature review, we evaluated its causes, neuropsychiatric symptoms, duration, treatment methods, and prognostic outcomes.Our search retrieved 10 articles, including 5 articles on PLE and 10 articles on symptomatic PLE. The incidence of PLE was 35.8% (95% CI: 17.0%-54.6%), while the incidence of symptomatic PLE was 3.1% (95% CI: 1.5%-4.7%) accounting for 8.7% of PLE.This complication is not as rare as previously reported. Therefore, it requires significant attention after DBS implantation. The correlation between its causes, duration, symptoms, and the area involved in edema should be assessed in long-term prospective clinical studies with large sample sizes.

Background: Although many studies have highlighted RNA modification processes such as N1-methyladenosine (m1A), N6-methyladenosine (m6A), N7-methylguanosine (m7G), and 5-methylcytosine methylation (m5C)’s role in the prognosis of patients suffering from different cancers, their prospective involvement in lower-grade gliomas (LGG) has not yet been outlined. Methods: This work aims to assess the 64 genes related to m1A/m6A/m7G/m5C modification. Based on the expression of methylation-related regulators (MRRs), unsupervised clustering was conducted to identify molecular subtypes. The m1A/m6A/m7G/m5C modification patterns, tumor microenvironment (TME) cell infiltration features, and correlation with immune infiltration markers were assessed. Additionally, the first stage of MMR screening was conducted using univariate Cox analysis, and the prognostic model for the m1A/m6A/m7G/m5C risk score was constructed using different machine learning algorithms analysis. Results: The m1A/m6A/m7G/m5C risk model, including five genes illustrated better prognostic ability for LGG in both the training and validation datasets, wherein the patients were classified into the low and high-risk groups. The LGG patients who were categorized into the high-risk groups displayed poor prognoses. In addition, the role played by five genes at the protein expression level was confirmed using immunohistochemical sections in the HPA database. Finally, functional analysis revealed the richness of pathways and biological processes related to MRR regulation and immune function. Conclusion: An m1A/m6A/m7G/m5C-related risk model was developed and validated in this study to offer valuable new insights into the role played by m1A/m6A/m7G/m5C modification patterns in predicting the prognosis of LGG patients from three continents and developing better and improved treatment strategies for LGG.

Background: N7-methylguanosine (m7G) modification signature has been found recently in cancer and is now known as an essential regulator of tumor progression and treatment. As a result of the function of m7G methylation modification genes in tumorigenesis and progression, there isn't much information related to the genomic profile of lower-grade gliomas(LGGs). Methods: In this research, bioinformatics analysis methods were used to characterize m7G modifications in individuals with LGG from The Chinese Glioma Genome Atlas(CGGA) and The Cancer Genome Atlas(TCGA). Afterward, gene set enrichment analysis(GSEA), single sample GSEA(ssGSEA), CIBERSORT algorithm, ESTIMATE algorithm, R package "GSVA," and TIDE were used to evaluate the association between m7G modification patterns, TME cell infiltration properties as well as the correlation regarding immune infiltration markers. The m7G scoring scheme using principal component analysis(PCA) was employed to investigate the m7G modification patterns of individual tumors quantitatively. We examined the m7G modification hub genes' expression levels in normal samples, refractory epilepsy samples, and lower-grade glioma samples using immunohistochemistry, western-blotting, and QRT-PCR. Result: It was discovered that individuals with LGG were categorized into two groups in terms of m7G scores (high and low) as per the properties of m7G. After observing the anti-PD-1 cohort, it has been noted that individuals having a high m7G score had significant clinical benefit, along with considerably prolonged survival duration. Opposing this, individuals in the anti-PD-L1 cohort having low m7G scores had improved prognostic outcomes and were more likely to have CR(Complete Response) / PR(Partial Response). Different m7G subtypes have different TMB(Tumor Mutational Burden) and immune profiles and might have varied responses to immunotherapy. Moreover, five potential genetic markers were found that were highly correlated with the index of the m7G score signature. Conclusion: Conclusively, a thorough investigation of the features and classification associated with m7G methylation modifications may improve the clinical outcome of LGG.

Background: Lower WHO grade II and III gliomas (LGGs) are characterized by widespread genetic and transcriptional heterogeneity, yet little is known about the heterogeneity of the DNA Damage Repair (DDR), its function in tumor biology, coupling with the transcriptome and tumor microenvironment (TM) and its possible impact for tumor development. Methods: In this study, we analyzed gene expression profiles downloaded from TCGA, CGGA, and GEO databases. The DNA damage repair (DDR) alterations among LGG have been studied via multi-omics data integration. For this, LGG patients have been grouped into distinct subtypes (DDR-activated and the DDR-suppressed subtype) based on different clinicalparameters and molecular characteristics. The differences in gene mutation, immune spectrum, and immune cell infiltration between the two DDR subtypes were compared. We generated DDR subtype features (DDR scores) to implement DDR classification in LGG and confirmed the results using a multi-layer data cohort. In addition, the characteristics of DDR subtypes predicted by immunotherapy responses and their roles in the tumor immune microenvironment (TIM) were explored. Result: The DDR activation subgroup was found to be associated with poorer overall survival based on molecular subtypes, and clinicopathological features of advanced-age and higher-grade were more common in the DDR-activated subgroup. DDR-suppressed subtypes also exhibited more frequent mutations in IDH1. We also found significant upregulation of activated immune cells in the DDR-activated subgroup, which indicates significant influence posed by infiltration of immune cells on tumor progression as well as immunotherapeutic responses. In addition, six DDR genes were selected to construct a DDR signature of LGG, dividing patients into low- and high-risk groups. Within the IMvigor210 cohort, there were fewer CR/PR groups in the high-score patients, as well as concomitant shorter survival times. CR/PR group had higher DDR characteristics scores compared to the SD/PD group. QRT-PCR results showed that the expression levels of CDK1, CDK2, TYMS, SMC4, and WEE1 were found to be considerably higher for LGG samples compared to normal brain tissue samples (p < 0.05). Conclusion: In conclusion, our work sheds light on the DDR heterogeneity of LGG and advances our knowledge of the molecular pathways in DDR that lead to LGG.

Autophagy is a highly conserved lysosomal degradation process essential in tumorigenesis. However, the involvement of autophagy-related long noncoding RNAs (lncRNAs) in low-grade glioma (LGG) remains unclear. In this study, we established an autophagy-related lncRNA prognostic signature for patients with LGG and assess its underlying functions. We used univariate Cox, least absolute shrinkage and selection operator and multivariate Cox regression models to establish an autophagy-related lncRNA prognostic signature. Kaplan-Meier survival analysis, receiver operating characteristic curve, nomogram, C-index, calibration curve and clinical decision-making curve were used to assess the predictive capability of the identified signature. A signature comprising nine autophagy-related lncRNAs (AL136964.1, ARHGEF26-AS1, PCED1B-AS1, AS104072.1, PRKCQ-AS1, LINC00957, AS125616.1, PSMB8-AS1 and AC087741.1) was identified as a prognostic model. Patients with LGG were divided into the high- and low-risk cohorts based on the median model-based risk score. The survival analysis revealed a 10-year survival rate of 9.3% (95% CI 1.91-45.3%) and 13.48% (95% CI 4.52-40.2%) in high-risk patients in the training and validation sets, respectively, and 48.4% (95% CI 24.7-95.0%) and 48.4% (95% CI 28.04-83.4%) in low-risk patients in the training and validation sets, respectively. This finding suggested a relatively low survival in high-risk patients. In addition, the lncRNA signature was independently prognostic and potentially associated with the progression of LGG. Therefore, the 9-autophagy-related-lncRNA signature may play a crucial role in the diagnosis and treatment of LGG, which may offer new avenues for tumour-targeted therapy.

Long non-coding RNAs (lncRNAs) comprise an integral part of the eukaryotic transcriptome. Alongside proteins, lncRNAs modulate lncRNA-based gene signatures of unstable transcripts, play a crucial role as antisense lncRNAs to control intracellular homeostasis and are implicated in tumorigenesis. However, the role of genomic instability-associated lncRNAs in low-grade gliomas (LGG) has not been fully explored. In this study, lncRNAs expression and somatic mutation profiles in low-grade glioma genome were used to identify eight novel mutant-derived genomic instability-associated lncRNAs including H19, FLG-AS1, AC091932.1, AC064875.1, AL138767.3, AC010273.2, AC131097.4 and ISX-AS1. Patients from the LGG gene mutagenome atlas were grouped into training and validation sets to test the performance of the signature. The genomic instability-associated lncRNAs signature (GILncSig) was then validated using multiple external cohorts. A total of 59 novel genomic instability-associated lncRNAs in LGG were used for least absolute shrinkage and selection operator (Lasso), single and multifactor Cox regression analysis using the training set. Furthermore, the independent predictive role of risk features in the training and validation sets were evaluated through survival analysis, receiver operating feature analysis and construction of a nomogram. Patients with IDH1 mutation status were grouped into two different risk groups based on the GILncSig score. The low-risk group showed a relatively higher rate of IDH1 mutations compared with patients in the high-risk group. Furthermore, patients in the low-risk group had better prognosis compared with patients in the high-risk group. In summary, this study reports a reliable prognostic prediction signature and provides a basis for further investigation of the role of lncRNAs on genomic instability. In addition, lncRNAs in the signature can be used as new targets for treatment of LGG.

Glioma is one of the most common neurological malignancies worldwide. Delta-like ligand 3 (DLL3), an inhibitory ligand-driven activation of the Notch pathway, has been shown to be significantly associated with overall survival in patients with glioma. Therefore, the purpose of this study was to determine whether DLL3 as a biomarker in glioma is associated with patients' clinicopathological features and prognosis. We identified differences in transcriptome and promoter methylation in the Chinese Glioma Genome Atlas (CGGA) in patients with malignant glioma with shorter (less than 1 year) and longer (greater than 3 years) survival time. Further analysis of The Cancer Genome Atlas (TCGA) revealed that four genes (DLL3, TSPAN15, RTN1, PAK7) are highly associated with patient prognosis and play an indispensable role in evolution. We chose the expression level of DLL3 in glioma patients for our study. Patients were divided into groups with low and high expression of DLL3 according to the cutoff values obtained, and Kaplan–Meier and Cox analysis were used to examine the correlation between DLL3 gene expression and patient survival. We then performed a gene set enrichment analysis (GSEA) to identify significantly enriched signaling pathways. Our results confirmed that the overall survival of patients with low DLL3 expression was significantly shorter than that of patients with high DLL3 expression. GSEA showed that the signaling pathways of the immune process and immune response, among others, were enhanced with the DLL3 low-expression phenotype. Collectively, our findings signify that DLL3 is a potent prognostic factor for glioma, which can provide a viable approach for glioma prognostic assessment and valuable insights for anti-tumor immune-targeted therapies.

Background Parkinson's disease (PD) has a high incidence in the elderly, and the late stage seriously affects the daily life of the patients. Most of the initial symptoms of PD are not obvious or atypical, which brings difficulties to the early diagnosis. Replacement therapy and neuroprotection after early diagnosis can significantly improve the prognosis and quality of life of patients. More and more evidence shows that 11C-2β-carbomethoxy-3β-(4-fluorophenyl) tropane positron emission tomography ( 11C-CFT PET) combined with 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) can effectively improve the accuracy of early diagnosis. However, there is no consistent conclusion at present. The purpose of this study is to evaluate the efficacy of 11C-CFT PET combined with 18F-FDG PET in the diagnosis of early PD. Methods We will search 7 electronic databases (PubMed, EMBASE, Web of Science, Cochrane library, PsycINFO, AMED, Scopus), ongoing trials and grey literature to collect related randomized controlled trials and will use Review Manager Software 5.2 and STATA Software 16.0 for analysis and synthesis. Results We will integrate the existing randomized controlled trials to evaluate the value of 11C-CFT PET combined with 18F-FDG PET in the diagnosis of early PD. Conclusion Our study may prove that 11C-CFT PET combined with 18F-FDG PET can effectively diagnose early PD. Registration number International Prospective Register of Systematic Reviews (PROSPERO): CRD42020203442.