ObjectiveGliomas are the most aggressive intracranial tumors accounting for the vast majority of brain tumors with very poor prognosis and overall survival (OS). Cancer-derived immunoglobulin G (cancer-IgG) has been found to be widely expressed in several malignancies such as breast cancer, colorectal cancer, and lung cancer. Cancer-IgG could promote tumorigenesis and progression. However, its role in glioma has not been revealed yet.MethodsWe mined open databases including the Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) to study the role of IGHG1, which encodes cancer-IgG in glioma. Examination of the differential expression of IGHG1 was carried out in the GEO and TCGA databases. Furthermore, its expression in different molecular subtypes was analyzed. Stratified analysis was performed with clinical features. Subsequently, immune infiltration analysis was conducted using single-sample gene set enrichment analysis (ssGSEA). GSEA was performed to reveal the mechanisms of IGHG1. Lastly, immunohistochemistry was processed to validate our findings.ResultsIn this study, we found that the expression of IGHG1 was higher in glioma and molecular subtypes with poor prognosis. The overall survival of patients with a high expression of IGHG1 was worse in the stratified analysis. Immune infiltration analysis indicated that the expression level of IGHG1 was positively correlated with the stromal score, ESTIMATE score, and immune score and negatively correlated with tumor purity. Results from the GSEA and DAVID demonstrated that IGHG1 may function in phagosome, antigen processing and presentation, extracellular matrix structural constituent, antigen binding, and collagen-containing extracellular matrix. Finally, immunohistochemistry assay validated our findings that patients with a high expression of cancer-IgG had poor OS and disease-free survival (DFS).ConclusionCancer-IgG is a promising biomarker of diagnosis and treatment for patients with glioma.

ObjectiveGlioma is the most frequent type of malignant cerebral tumors. DNA damage repair genes (DDRGs) play a crucial role in the development of cancer. In this study, we constructed a DDRGs signature and investigated the potential mechanisms involved in this disease.MethodsRNA sequence data, microarray data, and corresponding clinical information of gliomas were downloaded from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO). Subsequently, we identified candidate genes by differential analysis and Cox regression analysis. The least absolute shrinkage and selection operator Cox regression model was utilized to construct a DDRGs signature using TCGA training dataset. According to this signature, patients with glioma were divided into low- and high-risk groups. The predictive ability of the signature was validated by prognostic analysis, receiver operating characteristic curves, principal component analysis, and stratification analysis in TCGA testing and CGGA verification datasets. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were used to evaluate the immune microenvironment of glioma. Moreover, we conducted GSEA to determine the functions and pathways in the low- and high-risk groups. Finally, a nomogram was constructed by combining the signature and other clinical features.ResultsA total of 1,431 samples of glioma (592 from TCGA, 686 from the CGGA, and 153 from the GEO) and 23 samples of normal brain tissue from the GEO were analyzed in this study. There were 51 prognostic differentially expressed DDRGs. Additionally, five DDRGs (CDK4、HMGB2、WEE1、SMC3 and GADD45G) were selected to construct a DDRGs signature for glioma, stratifying patients into low- and high-risk groups. The survival analysis showed that the DDRGs signature could differentiate the outcome of the low- and high-risk groups, showing that high-risk gliomas were associated with shorter overall survival. The immune microenvironment analysis revealed that more immunosuppressive cells, such as tumor associated macrophages and regulatory T cells, were recruited in the high-risk group. GSEA also showed that high-risk glioma was correlated with the immune and extracellular matrix pathways.ConclusionThe five DDRGs signature and its impact on the infiltration of immunosuppressive cells could precisely predict the prognosis and provide guidance on the treatment of glioma.

There is a growing interest in the use of electrocorticographic (ECoG) signals in brain–machine interfaces (BMIs). However, there is still a lack of studies involving the long-term evaluation of the tissue response related to electrode implantation. Here, we investigated biocompatibility, including chronic tissue response to subdural electrodes and a fully implantable wireless BMI device. We implanted a half-sized fully implantable device with subdural electrodes in six beagles for 6 months. Histological analysis of the surrounding tissues, including the dural membrane and cortices, was performed to evaluate the effects of chronic implantation. Our results showed no adverse events, including infectious signs, throughout the 6-month implantation period. Thick connective tissue proliferation was found in the surrounding tissues in the epidural space and subcutaneous space. Quantitative measures of subdural reactive tissues showed minimal encapsulation between the electrodes and the underlying cortex. Immunohistochemical evaluation showed no significant difference in the cell densities of neurons, astrocytes, and microglia between the implanted sites and contralateral sites. In conclusion, we established a beagle model to evaluate cortical implantable devices. We confirmed that a fully implantable wireless device and subdural electrodes could be stably maintained with sufficient biocompatibility in vivo.

Among the most common types of brain tumor, gliomas are the most aggressive and have the poorest prognosis. Dolichyl-diphosphooligosaccharide protein glycosyltransferase non-catalytic subunit (DDOST) encodes a component of the oligosaccharide transferase complex and is related to the N-glycosylation of proteins. The role of DDOST in gliomas, however, is not yet known. First, we performed a pan cancer analysis of DDOST in the TCGA cohort. The expression of DDOST was compared between glioma and normal brain tissues in the GEO and Chinese Glioma Genome Atlas (CGGA) databases. In order to explore the role of DDOST in glioma, we analyze the impact of DDOST on the prognosis of glioma patients, with the CGGA 325 dataset as a test set and the CGGA 693 dataset as a validation set. Immunohistochemistry was performed on tissue microarrays to examine whether DDOST has an impact on glioma patient survival. Next, using single-cell sequencing analysis, GSEA, immune infiltration analysis, and mutation analysis, we explored how DDOST affected the glioma tumor microenvironment. Finally, we evaluated the clinical significance of DDOST for glioma treatment by constructing nomograms and decision curve analysis (DCA) curves. We found that DDOST was overexpressed in patients with high grade, IDH wild type, 1p19q non-codel and MGMT un-methylated, which was associated with poor prognosis. Patients with high levels of DDOST, regardless of their clinical characteristics, had a worse prognosis. Immunohistochemical analysis confirmed the results of the above bioinformatics analysis. Mechanistic analysis revealed that DDOST was closely associated with the glioma microenvironment and negatively related to tumor-infiltrating B cells and CD4+ T cells and positively related to CAFs and tumor-associated macrophages. In conclusion, these findings suggested that DDOST mediated the immunosuppressive microenvironment of gliomas and could be an important biomarker in diagnosing and treating gliomas.

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