Background: Gliomas account for the majority of fatal primary brain tumors, and there is much room for research in the underlying pathogenesis, the multistep progression of glioma, and how to improve survival. In our study, we aimed to identify potential biomarkers or therapeutic targets of glioma and study the mechanism underlying the tumor progression.Methods: We downloaded the microarray datasets (GSE43378 and GSE7696) from the Gene Expression Omnibus (GEO) database. Then, we used weighted gene co-expression network analysis (WGCNA) to screen potential biomarkers or therapeutic targets related to the tumor progression. ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumors using Expression data) algorithm and TIMER (Tumor Immune Estimation Resource) database were used to analyze the correlation between the selected genes and the tumor microenvironment. Real-time reverse transcription polymerase chain reaction was used to measure the selected gene. Transwell and wound healing assays were used to measure the cell migration and invasion capacity. Western blotting was used to test the expression of epithelial-mesenchymal transition (EMT) related markers.Results: We identified specific module genes that were positively correlated with the WHO grade but negatively correlated with OS of glioma. Importantly, we identified that 6 collagen genes (COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2) could regulate the immunosuppressive microenvironment of glioma. Moreover, we found that these collagen genes were significantly involved in the EMT process of glioma. Finally, taking COL3A1 as a further research object, the results showed that knockdown of COL3A1 significantly inhibited the migration, invasion, and EMT process of SHG44 and A172 cells.Conclusions: In summary, our study demonstrated that collagen genes play an important role in regulating the immunosuppressive microenvironment and EMT process of glioma and could serve as potential therapeutic targets for glioma management.

Tumor mutation burden (TMB) is a useful biomarker to predict prognosis and the efficacy of immune checkpoint inhibitors (ICIs). In this study, we aimed to explore the prognostic value of TMB and the potential association between TMB and immune infiltration in lower-grade gliomas (LGGs). Somatic mutation and RNA-sequencing (RNA-seq) data were downloaded from the Cancer Genome Atlas (TCGA) database. TMB was calculated and patients were divided into high- and low-TMB groups. After performing differential analysis between high- and low-risk groups, we identified six hub TMB and immune-related genes that were correlated with overall survival in LGGs. Then, Gene Set Enrichment Analysis was performed to screen significantly enriched GO terms between the two groups. Moreover, an immune-related risk score system was developed by LASSO Cox analysis based on the six hub genes and was validated with the Chinese Glioma Genome Atlas dataset. Using the TIMER database, we further systematically analyzed the relationships between mutants of the six hub genes and immune infiltration levels, as well as the relationships between the immune-related risk score system and the immune microenvironment in LGGs. The results showed that TMB was negatively correlated with OS and high TMB might inhibit immune infiltration in LGGs. Furthermore, the risk score system could effectively stratify patients into low- and high-risk groups in both the training and validation datasets. Multivariate Cox analysis demonstrated that TMB was not an independent prognostic factor, but the risk score was. Higher infiltration of immune cells (B cells, CD4⁺ T cells, CD8⁺ T cells, neutrophils, macrophages, and dendritic cells) and higher levels of immune checkpoints (PD-1, CTLA-4, LAG-3, and TIM-3) were found in patients in the high-risk group. Finally, a novel nomogram model was constructed and evaluated to estimate the overall survival of LGG patients. In summary, our study provided new insights into immune infiltration in the tumor microenvironment and immunotherapies for LGGs.

Background: The emergence of vaccine-associated paralytic poliomyelitis has become an ongoing burden of poliomyelitis. During this special period from OPV to IPV-only immunization schedule, we did a meta-analysis to compare the immunogenicity of sequential IPV and OPV versus IPV alone in healthy infants. Methods: This systematic review and meta-analysis was registered at international prospective register of systematic reviews (PROSPERO), and the number was CRD42017054889. We performed it as described. Results: Finally, 6 articles were qualified for our review. The results showed that seroconversion rates against all 3 serotype polioviruses were non-inferior and Geometric mean antibody titers (GMTs) were superior in sequential schedules compared with IPV-only schedule. Thus, the sequential vaccination schedules could induce a stronger immunogenicity. Conclusions: To decrease vaccine-associated and vaccine-derived poliomyelitis, it is a reasonable option to select sequential schedules during this special transition from OPV to IPV-only immunization schedule, which coincides with the current WHO recommendations.

Background: N6-methyladenosine (m6A) modification is involved in tumorigenesis and progression as well as closely correlated with stem cell differentiation and pluripotency. Moreover, tumor progression includes the acquisition of stemness characteristics and accumulating loss of differentiation phenotype. Therefore, we integrated m6A modification and stemness indicator mRNAsi to classify patients and predict prognosis for LGG. Methods: We performed consensus clustering, weighted gene co-expression network analysis, and least absolute shrinkage and selection operator Cox regression analysis to identify an m6A regulation- and mRNAsi-related prognostic index (MRMRPI). Based on this prognostic index, we also explored the differences in immune microenvironments between high- and low-risk populations. Next, immunotherapy responses were also predicted. Moreover, single-cell RNA sequencing data was further used to verify the expression of these genes in MRMRPI. At last, the tumor-promoting and tumor-associated macrophage polarization roles of TIMP1 in LGG were validated by in vitro experiments. Results: Ten genes (DGCR10, CYP2E1, CSMD3, HOXB3, CABP4, AVIL, PTCRA, TIMP1, CLEC18A, and SAMD9) were identified to construct the MRMRPI, which was able to successfully classify patients into high- and low-risk group. Significant differences in prognosis, immune microenvironment, and immunotherapy responses were found between distinct groups. A nomogram integrating the MRMRPI and other prognostic factors were also developed to accurately predict prognosis. Moreover, in vitro experiments illustrated that inhibition of TIMP1 could inhibit the proliferation, migration, and invasion of LGG cells and also inhibit the polarization of tumor-associated macrophages. Conclusion: These findings provide novel insights into understanding the interactions of m6A methylation regulation and tumor stemness on LGG development and contribute to guiding more precise immunotherapy strategies.

Background: Gliomas account for the majority of fatal primary brain tumors, and there is much room for research in the underlying pathogenesis, the multistep progression of glioma, and how to improve survival. In our study, we aimed to identify potential biomarkers or therapeutic targets of glioma and study the mechanism underlying the tumor progression. Methods: We downloaded the microarray datasets (GSE43378 and GSE7696) from the Gene Expression Omnibus (GEO) database. Then, we used weighted gene co-expression network analysis (WGCNA) to screen potential biomarkers or therapeutic targets related to the tumor progression. ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumors using Expression data) algorithm and TIMER (Tumor Immune Estimation Resource) database were used to analyze the correlation between the selected genes and the tumor microenvironment. Real-time reverse transcription polymerase chain reaction was used to measure the selected gene. Transwell and wound healing assay were used to measure the cell migration and invasion capacity.Results: We identified specific module genes that were positively correlated with the WHO grade but negatively correlated with OS of glioma. Importantly, we identified that 6 collagen genes (COL1A1, COL1A2, COL3A1, COL4A1, COL4A2, and COL5A2) could regulate the immunosuppressive microenvironment of glioma. Moreover, we found that these collagen genes were significantly involved in the epithelial-mesenchymal transition (EMT) process of glioma. Finally, taking COL5A2 as a further research object, the results showed that knockdown of COL5A2 significantly inhibited the migration and invasion of SHG44 and A172 cells. Conclusions: In summary, our study demonstrated that collagen genes play an important role in regulating the immunosuppressive microenvironment and EMT process of glioma and could serve as potential therapeutic targets for glioma management.

Background: Accumulating evidence demonstrated the effectiveness of mRNA vaccine against many cancers, however, their development in LGGs is still urgently needed. In addition, increasing evidence demonstrated that Immunogenic cell death (ICD) was associated with antitumor immune response. Thus, the aim of our study was to identify potential LGG tumor antigens for mRNA vaccine development and select suitable patients for vaccination based on ICD subtypes. Methods: Gene expression matrix and matched clinical information of LGG were downloaded from the UCSC Xena website and CGGA databases. Differential expression analysis was conducted by GEPIA, and altered genomes were obtained from cBioPortal. TIMER was used for immune cell infiltration analysis, consensus clustering for typing ICD subtypes, and WGCNA for identifying hub modules and genes related to ICD subtypes. Eighty-two glioma tissue samples were collected and immunohistochemical staining was used to validate the correlation between tumor antigens and co-stimulatory factors. Results: We identified seven potential LGG tumor antigens significantly correlated with poor prognosis and strongly positively correlated with infiltration of antigen-presenting cells, including CREB3L2, DDR2, IRF2, NCSTN, RECQL, REST, and TGFBR1. Furthermore, we identified two ICD subtypes in LGGs with different clinical, cellular, and molecular characteristics. Icds1 is an immunological "hot" and immunosuppression phenotype with a worse prognosis, while Icds2 is an immunological cold phenotype with a better prognosis. Finally, WGCNA identified hub immune-related genes associated with ICD subtypes, which could be potential vaccination biomarkers. Conclusion: In summary, CREB3L2, DDR2, IRF2, NCSTN, RECQL, REST, and TGFBR1 are LGGs’ potential tumor antigens for mRNA vaccine development. The Icds2 subtype is suitable for vaccination.