Journal of Cellular Physiology · 2019 · 29 citations · 28 references
MedicineImmunologyOncologyCancer ImmunologyMolecular OncologyTumor MicroenvironmentCancer BiomarkersCytokine BiologyCytokines In Tumor ImmunityGlioblastomaMolecular Tumor ProfilingTumor Immune MicroenvironmentCytokine Receptor ExpressionEnrichment AnalysisGene Ontology EnrichmentGlioblastoma ImmunologyGlioblastoma Tumor MicroenvironmentLocal Immune ResponseLocal Tissue ResponseTissue Expression Profiles
Glioblastoma (GBM) is the most lethal cancer in central nervous system. It is urgently needed to look for novel therapeutics for GBM. Oncostatin M receptor (OSMR) is a cytokine receptor gene of IL-6 family and has been reported to be involved in regulating GBM tumorigenesis. However, the role of OSMR regulating the disrupted immune response in GBM need to be further investigated. Three gene expression profiles, Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), and Gene Expression Omnibus (GEO) data set (GSE16011), were enrolled in our study and used for OSMR expression and survival analysis. The expression of OSMR was further verified with immunohistochemistry and western blot analysis in glioma tissues. Microenvironment cell populations-counter (MCP-counter) was applied for analyzing the relationship between OSMR expression and nontumor cells. The functions of OSMR in GBM was investigated by Gene Ontology, Gene set enrichment analysis (GSEA), gene set variation analysis and so on. The analysis of cytokine receptor activity-related genes in glioma identifies OSMR as a gene with an independent predictive factor for progressive malignancy in GBM. Furthermore, OSMR expression is a prognostic marker in the response prediction to radiotherapy and chemotherapy. OSMR contributes to the regulation of local immune response and extracellular matrix process in GBM. Our findings define an important role of OSMR in the regulation of local immune response in GBM, which may suggest OSMR as a possible biomarker in developing new therapeutic immune strategies in GBM.
28
pROC: an open-source package for R and S+ to analyze and compare ROC curves
Xavier Robin, Natacha Turck, Alexandre Hainard et al. · BMC Bioinformatics · 2011 · 14K citations · Full text
Inferring tumour purity and stromal and immune cell admixture from expression data
Kosuke Yoshihara, Maria Shahmoradgoli, Emmanuel Martínez et al. · Nature Communications · 2013 · 10.7K citations · Full text