Background Immune checkpoints target regulatory pathways in T cells that enhance antitumor immune responses and elicit durable clinical responses. As a novel immune checkpoint, CD96 is an attractive key target for cancer immunotherapy. However, there has been no integrative investigation of CD96 in glioma. Our study explored the relationship between CD96 expression and clinical prognosis in glioma. Methods RNA and clinical data for a total of 1,001 samples were included in this study, including 325 samples from the Chinese Glioma Genome Atlas (CGGA) database and 676 samples from The Cancer Genome Atlas (TCGA) dataset. The R programming language was employed to perform statistical analysis and draw figures. Results CD96 had a consistently positive relationship with glioblastoma and was highly enriched in IDH-wildtype and mesenchymal subtype glioma. Gene ontology enrichment and gene set variation analysis analyses suggested that CD96 was mostly involved in immune functions and was especially related to T cell-mediated immune response in glioma. Subsequent immune infiltration analysis showed that CD96 was positively correlated with infiltrating levels of CD4 + T and CD8 + T cells, macrophages, neutrophils, and DCs in glioblastoma multiforme and low-grade glioma. Additionally, CD96 was tightly associated with other immune checkpoints, including PD-1 , CTLA-4 , TIGIT , and TIM-3 . Univariate and multivariate Cox analysis demonstrated that CD96 acts as an independent indicator of poor prognosis in glioma. Conclusion CD96 expression was increased in malignant phenotype and negatively associated with overall survival in glioma. CD96 also showed a positive correlation with other immune checkpoints, immune response, and inflammatory activity. Our findings indicate that CD96 is a promising clinical target for further immunotherapeutic use in glioma patients.
Introduction: As one of the most prevalent and malignant brain cancers, glioblastoma multiforme (GBM) presents a poor prognosis and the molecular mechanisms remain poorly understood. Consequently, molecular research, including various biomarkers, is essential to exploit the occurrence and development of glioma. Methods: Weighted gene co-expression network analysis (WGCNA) was used to construct gene co-expression modules and networks based on the Chinese Glioma Genome Atlas (CGGA) glioblastoma specimens. Then, protein-protein interaction (PPI) and gene ontology (GO) analyses were performed to mine hub genes. RT-PCR and immunohistochemistry were employed to examine the expression level of GRPR, CXCL5, and CXCL11 in glioma patients. Results: We confirmed two gene modules by protein-protein interaction networks. Functional enrichment analysis was performed to identify the significance of gene modules. Prognostic biomarkers GRPR, CXCL5, and CXCL11 related to the survival time of GBM samples were mined in The Cancer Genome Atlas (TCGA) dataset. qRT-PCR revealed that GRPR, CXCL5, and CXCL11 led to a significant increase in GBM sample compared to control. Conclusion:In this study, we developed and confirmed three mRNA signatures (GRPR, CXCL5, and CXCL11) for evaluating overall survival in GBM patients. Our research assists in existing understanding of GBM diagnosis and prognosis.
ObjectiveIntracerebral hemorrhage (ICH) is a subtype of stroke with high mortality and morbidity rates. Our aim was to comprehensively analyze transcriptome and proteome in an experimental ICH model.MethodsAll mice were divided into ICH model (n = 3) and sham groups (n = 3). ICH was induced by collagenase VII. The ipsilateral hemisphere was used for whole transcriptome and proteomics resequencing. After preprocessing, differentially expressed lncRNAs (DElncRNAs), mRNAs (DEmRNAs), miRNAs (DEmiRNAs), and DEproteins between ICH and sham groups were identified. Functional enrichment analysis was performed using the clusterProfiler package, followed by protein–protein interaction (PPI) analysis. After that, the Pearson correlation coefficient between DEmRNAs and DElncRNAs or between DEmRNAs and DEproteins was calculated. DElncRNAs with similar functions were analyzed by the GOSemSim package. After prediction of DEmiRNA–DEmRNA and DElncRNA–DEmiRNA relationships, a competing endogenous RNA (ceRNA) network was constructed. Several DEmRNAs and DElncRNAs were validated in ipsilateral hemisphere tissues of the ICH model and control groups using RT-qPCR and western blot.ResultsBetween the ICH and sham groups, 31 DElncRNAs, 367 DEmRNAs, 35 DEmiRNAs, and 96 DEproteins were identified. DEmRNAs were mainly enriched in inflammation, such as cytokine–cytokine receptor interaction, IL-17, and TNF signaling pathways. A PPI network of DEmRNAs was constructed and hub genes were identified, such as IL6 (degree = 59), TNF (degree = 44), and CXCR2 (degree = 39). 24 DElncRNAs with similar functions were identified, including 15 up- and 9 down-regulated lncRNAs. After integration of DEmiRNA–DEmRNA and DElncRNA–DEmiRNA relationships, we constructed a ceRNA network, composed of 71 DEmRNAs, 17 DEmiRNAs, and 12 DElncRNAs. RT-qPCR and western blot results confirmed that C3, Fga, and Slc4a1 proteins were more lowly expressed and Penk was more highly expressed in ICH than control groups, which could become potential markers for ICH.ConclusionOur findings identified ICH-related DE-RNAs and proteins and potential molecular mechanisms of ICH by transcriptome resequencing and quantitative proteomic analyses.
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