Gliomas are the most common and malignant intracranial tumors in adults. Recent studies have revealed the significance of functional genomics for glioma pathophysiological studies and treatments. However, access to comprehensive genomic data and analytical platforms is often limited. Here, we developed the Chinese Glioma Genome Atlas (CGGA), a user-friendly data portal for the storage and interactive exploration of cross-omics data, including nearly 2000 primary and recurrent glioma samples from Chinese cohort. Currently, open access is provided to whole-exome sequencing data (286 samples), mRNA sequencing (1018 samples) and microarray data (301 samples), DNA methylation microarray data (159 samples), and microRNA microarray data (198 samples), and to detailed clinical information (age, gender, chemoradiotherapy status, WHO grade, histological type, critical molecular pathological information, and survival data). In addition, we have developed several tools for users to analyze the mutation profiles, mRNA/microRNA expression, and DNA methylation profiles, and to perform survival and gene correlation analyses of specific glioma subtypes. This database removes the barriers for researchers, providing rapid and convenient access to high-quality functional genomic data resources for biological studies and clinical applications. CGGA is available at http://www.cgga.org.cn.

Background Clinical outcomes of patients with glioma are still poor, even after standard treatments, including surgery combined with radiotherapy and chemotherapy. New therapeutic strategies and targets for glioma are urgently needed. Plasminogen activator urokinase receptor (PLAUR), a highly glycosylated integral membrane protein, is reported to modulate plasminogen activation and extracellular matrix degradation in many malignant cancers, but its role in gliomas remains unclear. Methods Glioma samples with mRNA sequencing data and clinical information from the Chinese Glioma Genome Atlas (CGGA, n = 310) dataset and The Cancer Genome Atlas (TCGA, n = 611) dataset were collected for this study. Analyses using Kaplan‐Meier plots, time‐dependent ROC [receiver operating characteristic] curves, Cox regression, and nomograms were conducted to evaluate the prognostic performance of PLAUR expression. Analyses using Metascape, ESTIMATE, EPIC, and immunohistochemical staining were performed to reveal the potential biological mechanism. The statistical analysis and graphical work were completed using SPSS, R language, and Graphpad Prism. Results PLAUR was highly expressed in phenotypes associated with glioma malignancy and could serve as an independent prognostic indicator. Functional analysis revealed the correlation between PLAUR and immune response. Further studies found that samples with higher PLAUR expression were infiltrated with fewer CD8 T cells and many more M2 macrophages. Strong positive correlation was demonstrated between PLAUR expression and some immunosuppressive markers, including immune checkpoints and cytokines. These findings were also confirmed in patient samples. Conclusion Our results elucidated the clinical significance and immunosuppressive effect of PLAUR in gliomas, which might provide some clues in glioma immunotherapy. Implications for Practice While the efficacy of immunotherapy has been verified in other tumors, its application in glioma is impeded due to the unique microenvironment. Tumor‐associated macrophages, which are particularly abundant in a glioma mass, contribute much to the immunosuppressive microenvironment and offer new opportunities in glioma immunotherapy. The results of this study identified PLAUR expression as a potential marker to predict the infiltration of macrophages and the status of immune microenvironment in patients with glioma, suggesting that treatment decisions could be based on PLAUR level when administering immunotherapeutics. The soluble PLAUR in blood and other body fluids would make this approach easy to implement in the clinic.

Immunoreactions regulated by TAMs (Tumor-associated macrophages) play a pivotal role in tumorigenesis and metastasis. In recent decades, treatments based on immune regulation have achieved revolutionary breakthroughs in cancer targeted therapies. The phenotypes of TAMs in gliomas are more heterogeneous and inherently complex than can be simply defined by classification into the M1 and M2 polarized states. The detailed mechanisms surrounding infiltrating macrophage phenotype and glioma characteristics remain undefined. SAMD9 (Sterile Alpha Motif Domain-Containing Protein 9) was found to be highly expressed in glioma and closely related to histological and genetic features in CGGA and TCGA databases. Simultaneously, we present evidence to show that there was a positive association between SAMD9 and malignancy characters in LGG. Univariable and Multivariate proportional hazard Cox analysis showed that SAMD9 was an independent prognostic factor for LGG. Surprisingly, Gene Ontology (GO) analysis showed SAMD9 expression level was remarkably well correlated with immunological responses and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis supported the connection with immune responses and tumorigenesis. Immune infiltration analysis demonstrated that high SAMD9 expression resulted in an accumulation of macrophages by CIBERSORT and TIMER databases, especially positively related to macrophage total marker gene AIF1 and Macrophage M2 marker gene CD163. IHC staining further indicated a high correlation of SAMD9 with those specific macrophage markers in the immune response. Human THP-1 cells were induced into M2 macrophages, which were then co-cultured with LN229 cells. Silencing of SAMD9 by shRNA in LN229 cells attenuated the infiltration abilities of M2 macrophage. SAMD9 explored immune response via relating of M2 macrophage in vitro. Our results revealed SAMD9 acted as the malignancy characters in LGG, enrichment with M2 macrophage.

Aims: Gliomas are the primary malignant brain tumor and characterized as the striking cellular heterogeneity and intricate tumor microenvironment (TME), where chemokines regulate immune cell trafficking by shaping local networks. This study aimed to construct a chemokine‐based gene signature to evaluate the prognosis and therapeutic response in glioma.Methods: In this study, 1024 patients (699 from TCGA and 325 from CGGA database) with clinicopathological information and mRNA sequencing data were enrolled. A chemokine gene signature was constructed by combining LASSO and SVM‐RFE algorithm. GO, KEGG, and GSVA analyses were performed for function annotations of the chemokine signature. Candidate mRNAs were subsequently verified through qRT‐PCR in an independent cohort including 28 glioma samples. Then, through immunohistochemical staining (IHC), we detected the expression of immunosuppressive markers and explore the role of this gene signature in immunotherapy for glioma. Lastly, the Genomics of Drug Sensitivity in Cancer (GDSC) were leveraged to predict the potential drug related to the gene signature in glioma.Results: A constructed chemokine gene signature was significantly associated with poorer survival, especially in glioblastoma, IDH wildtype. It also played an independent prognostic factor in both datasets. Moreover, biological function annotations of the predictive signature indicated the gene signature was positively associated with immune‐relevant pathways, and the immunosuppressive protein expressions (PD‐L1, IBA1, TMEM119, CD68, CSF1R, and TGFB1) were enriched in the high‐risk group. In an immunotherapy of glioblastoma cohort, we confirmed the chemokine signature showed a good predictor for patients' response. Lastly, we predicted twelve potential agents for glioma patients with higher riskscore.Conclusion: In all, our results highlighted a potential 4‐chemokine signature for predicting prognosis in glioma and reflected the intricate immune landscape in glioma. It also threw light on integrating tailored risk stratification with precision therapy for glioblastoma.

Glioma is the most common primary malignant brain tumor with limited treatment options and poor prognosis. To investigate the potential relationships between transcriptional characteristics and clinical phenotypes, we applied weighted gene co-expression network analysis (WGCNA) to construct a free-scale gene co-expression network yielding four modules in gliomas. Turquoise and yellow modules were positively correlated with the most malignant glioma subtype (IDH-wildtype glioblastomas). Of them, genes in turquoise module were mainly involved in immune-related terms and were regulated by NFKB1, RELA, SP1, STAT1 and STAT3. Meanwhile, genes in yellow module mainly participated in cell-cycle and division processes and were regulated by E2F1, TP53, E2F4, YBX1 and E2F3. Furthermore, 14 genes in turquoise module were screened as hub genes. Among them, five prognostic hub genes (TNFRSF1B, LAIR1, TYROBP, VAMP8, and FCGR2A) were selected to construct a prognostic risk score model via LASSO method. The risk score of this immune-related gene signature is associated with clinical features, malignant phenotype, and somatic alterations. Moreover, this signature showed an accurate prediction of prognosis across different clinical and pathological subgroups in three independent datasets including 1619 samples. Our results showed that the high-risk group was characterized by active immune-related activities while the low-risk group enriched in neurophysiological-related pathway. Importantly, the high-risk score of our immune signature predicts an enrichment of glioma-associated microglia/macrophages and less response to immune checkpoint blockade (ICB) therapy in gliomas. This study not only provides new insights into the molecular pathogenesis of glioma, but may also help optimize the immunotherapies for glioma patients.

Background: Increases in human telomerase reverse transcriptase (TERT) expression and telomerase activity are frequently seen in nasopharyngeal carcinoma (NPC). Recently, a variable tandem-repeats polymorphism, MNS16A, located in the downstream region of the TERT gene, was identified and reported to have an effect on TERT expression and telomerase activity. We examined whether the functional MNS16A was related to the risk of occurrence or progression of NPC in the Chinese population. Methods: We genotyped the MNS16A polymorphism in a case-control study of 855 patients with NPC and 1036 cancer-free controls using PCR, and determined genotype by classifying the DNA band of 243 or 272 base pairs (bp) as the short (S) allele and 302 or 333 bp as the long (L) allele. The genetic associations with the risk of NPC were analyzed by logistic regression. Results: The MNS16A genotype was not associated with the progression of NPC. However, individuals carrying the S alleles (SL + SS genotype) had a significantly reduced risk of NPC occurrence compared with those carrying the LL genotype (odds ratio (OR) = 0. 71, 95% confidence interval (CI) = 0. 52 to 0. 96, P = 0. 025). Using a immunohistochemical assay on the NPC tissues, the SL genotype carriers were found to have lower TERT expression than the LL genotype carriers (P = 0. 035). Conclusions: Our study indicates that the TERT MNS16A polymorphism may contribute to the risk of NPC onset in Chinese population.