Background: RGS protein family members have recently became new potentially promising therapeutic targets in many cancers. However, as a key member of RGS family, RGS16 has seldom been studied in glioma. The present study was designed to investigate the prognostic value and biological function of RGS16 based on large‐scale databases and functional assays in vitro.Methods: Here, we performed comprehensive analysis for the expression characteristic of RGS16 in Chinese Glioma Genome Atlas (CGGA) microarray database with 301 patients and validated in The Cancer Genome Atlas (TCGA) microarray and RNA sequencing database. Student's t‐test, one‐way ANOVA test and long‐rank test were used to assess differences between groups. Kaplan‐Meier survival, univariate and multivariate Cox analysis and ROC curve were used to estimate the survival distributions. Biological implication of abnormal expression of RGS16 in glioma was also explored. Functional analysis of RGS16 was performed in several glioblastoma (GBM) cell lines. R language and SPSS were used for statistical analysis and graphical work.Results: We found that the expression of RGS16 was positively related to the grade of glioma. High level of RGS16 commonly gathered in glioma of mesenchymal subtype and wild‐type IDH1. Moreover, higher expression level of RGS16 was found to be significantly correlated with poor prognosis. The univariate and multivariate Cox regression analysis and ROC curve showed that RGS16 was an independent prognostic factor for glioma patients. Gene ontology analysis, gene set enrichment analysis, and gene set variation analysis suggested that the overexpression of RGS16 tightly related to cell proliferation, migration, epithelial‐mesenchymal transition (EMT), immune and inflammatory response of glioma. Knockdown of RGS16 in glioma cell lines also showed that RGS16 promoted the malignant progress of glioma cell lines.Conclusions: RGS16 plays an important role in glioma progression and serves as an independent prognostic factor, especially in GBM patients.

Increasing evidence has shown that long non-coding RNAs (lncRNAs) are important prognostic biomarkers and epigenetic regulators with critical roles in cancer initiation and progression. However, the expression and clinical prognostic value of antisense lncRNAs in diffuse glioma patients remain unknown. Here, we profiled differentially expressed antisense lncRNAs in glioma using RNA sequencing data from Chinese Glioma Genome Atlas database. Cox regression was performed to evaluate the prognostic value. Gene oncology (GO) and gene set enrichment analysis (GSEA) were used for functional analysis of antisense LncRNAs. Expression profiling identified 169 aberrantly expressed antisense lncRNAs between lower grade glioma (LGG) (grade II and III) and glioblastoma multiforme (GBM), 113 antisense lncRNAs between LGG IDH-wt and IDH-mut samples, and 70 antisense lncRNAs between GBM IDH-wt and IDH-mut samples, respectively. Among them, three antisense lncRNAs (WDFY3-AS2, MCM3AP-AS1 and LBX2-AS1) were significantly associated with prognosis and malignant progression of patients. WDFY3-AS2, the top one of downregulated antisense lncRNAs in GBM with fold change of 0.441 (P < 0.001), showed specific decreased expression in classical, mesenchymal, LGG IDH-wt, GBM IDH-wt or MGMT promoter unmethylated stratified patients. Chi square test found that WDFY3-AS2 was significantly associated with the clinical and molecular features of glioma. Univariate and multivariate Cox regression analysis indicated that WDFY3-AS2 was independently correlated with overall survival (OS) of patients. Kaplan–Meier analysis found that patients with high WDFY3-AS2 expression had longer OS than the low expression ones in the stratified cohorts. Additionally, GO and GSEA showed that gene sets correlated with WDFY3-AS2 expression were involved in regulation of synaptic transmission, glutamate receptor and TNF signaling pathway. Our findings provided convincing evidence that WDFY3-AS2 is a novel valuable prognostic biomarker for diffuse glioma.

Background: Gliomas are the most common and malignant brain tumors. The standard therapy is surgery combined with radiotherapy, chemotherapy, and/or other comprehensive methods. However, the emergence of chemoresistance is the main obstacle in treatment and its mechanism is still unclear. Methods: We firstly developed a multi-gene signature by integrated analysis of cancer stem cell and drug resistance related genes. The Chinese Glioma Genome Atlas (CGGA, 325 samples) and The Cancer Genome Atlas (TCGA, 699 samples) datasets were then employed to verify the efficacy of the risk signature and investigate its significance in glioma prognosis. GraphPad Prism, SPSS and R language were used for statistical analysis and graphical work. Results: This signature could distinguish the prognosis of patients, and patients with high risk score exhibited short survival time. The Cox regression and Nomogram model indicated the independent prognostic performance and high prognostic accuracy of the signature for survival. Combined with a well-known chemotherapy impact factor-MGMT promoter methylation status, this risk signature could further subdivide patients with distinct survival. Functional analysis of associated genes revealed signature-related biological process of cell proliferation, immune response and cell stemness. These mechanisms were confirmed in patient samples. Conclusions: The signature was an independent and powerful prognostic biomarker in glioma, which would improve risk stratification and provide a more accurate assessment of personalized treatment.

RNA editing by adenosine deaminases acting on RNA (ADARs) converts adenosines to inosines (A-to-I) in RNA, that alters gene expression and generates protein diversity. Dysregulation of A-to-I editing has been found associated with a number of nervous system diseases. However, the role of ADAR3, a brain specific high expression adenosine deaminase, in gliomas has rarely been investigated. In this study we illuminated the clinical significance and molecular features of ADAR3 in patients with glioma. 309 glioma samples from Chinese Glioma Genome Atlas were enrolled into this study. In validation sets, 601 glioma samples in TCGA, 410 glioma samples in REMBRANDT and 258 glioma samples in GSE16011 were obtained. Relationships between ADAR3 expression and prognosis-related genomic alteration, outcome and gene ontology analysis were investigated. Moreover, the characteristic of GRIA2Q607R editing in gliomas has been investigated. Graphpad Prism 5.0, SPSS 16.0 and R language were used to perform statistical analysis and graphical work. ADAR3 expression was down regulated along with glioma grade progression in CGGA dataset. ADAR3 was characteristically highly expressed in neural subtype and IDH1/2 mutant preference. Moreover, high expression of ADAR3 predicted a better prognosis in lower-grade glioma (LGG) patients and multivariate analysis suggested ADAR3 expression was an independent prognostic indicator. The results of the three other validation datasets showed similar findings. Bioinformatics analyses suggested that ADAR3 may play a role in the malignant transformation of glioma cells by affecting cell proliferation, angiogenesis or cell adhesion. Furthermore, the editing level of GRIA2Q607R was significantly correlated with ADAR3 expression. Our study demonstrated the clinical and molecular characterization of ADAR3 in glioma development and progression. ADAR3 expression was negatively associated with tumor malignant in the overall glioma patients. And it was a favorable independent prognostic indicator of LGG patients. ADAR3 appeared to act as a tumor suppressor in glioma cells. Therefore, ADAR3 represented a potential therapeutic target and useful prognostic factor for glioma patients.

As the core element of material and energy metabolism pathways, the biological functions and prognostic significance of ATP metabolism in diffuse gliomas have so far remained unclear. Based on comprehensive analysis of ATP metabolism‐related gene expression profiles, we constructed an ATP metabolism‐related risk signature to determine the role of ATP metabolism. We found that this ATP metabolism‐related gene expression profile could divide patients into 2 robust groups with distinct clinical characteristics and prognosis. Patients in the high‐risk group tended to be predicted as malignant entities, indicating that the activation of ATP metabolism may promote the malignant progress of diffuse gliomas. Cox regression and Kaplan‐Meier analyses suggested that this risk signature was an independent predictor for prognosis. Furthermore, we constructed an individualized prognosis prediction model through nomogram and time‐dependent receiver operating characteristic (ROC) curve analyses. Functional analysis suggested that, in addition to material and energy metabolism, ATP metabolism also played an essential role in the regulation of the tumor immune microenvironment. In brief, the ATP metabolism‐related signature was tightly associated with regulation of the tumor immune microenvironment and could serve as an independent prognostic biomarker in diffuse gliomas.

BACKGROUND. Aberrant expression of RNA processing genes may drive the alterative RNA profile in lower-grade gliomas (LGGs). Thus, we aimed to further stratify LGGs based on the expression of RNA processing genes. METHODS. This study included 446 LGGs from The Cancer Genome Atlas (training set) and 171 LGGs from the Chinese Glioma Genome Atlas (validation set). The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was conducted to develop a risk signature. The receiver operating characteristic curves and Kaplan-Meier curves were used to study the prognostic value of the risk signature. RESULTS. Among the tested 784 RNA processing genes, 276 were significantly correlated with the overall survival of LGGs. Further LASSO Cox regression identified a 19-gene risk signature, whose risk score was also an independent prognosis factor ( P < 0.0001, multiplex Cox regression) in the validation data set. The signature had better prognostic value than the traditional factors “age,” “grade,” and “WHO 2016 classification” for 3- and 5-year survival both data sets (AUCs >85%). Importantly, the risk signature could further stratify the survival of LGGs in specific subgroups of WHO 2016 classification. Furthermore, alternative splicing events for genes such as EGFR and FGFR were found to be associated with the risk score. mRNA expression levels for genes, which participated in cell proliferation and other processes, were significantly correlated to the risk score. CONCLUSIONS. Our results highlight the role of RNA processing genes for further stratifying the survival of patients with LGGs and provide insight into the alternative splicing events underlying this role. FUNDING. The National Natural Science Foundation of China (81773208, 81402052), the Beijing Nova Program (Z16110004916082), and the National Key Research and Development Plan (2016YFC0902500).