Molecular Classification And Biomarkers In Anaplastic Gliomas Based On High Throughput Data

Identification of high risk anaplastic gliomas by a diagnostic and prognostic signature derived from expression profilingBackground: Whole genome m RNA expression profiling based molecular classifications of primary glioblastoma multiforme or all grades of gliomas have been widely accepted.But there are few studies focusing on the substratification of anaplastic gliomas.Methods: To identify a more objective and applicable classification of anaplastic gliomas,we downloaded whole genome m RNA expression profiling of three independent datasets for analysis.Univariate Cox regression,linear risk score formula and receiver operating characteristic(ROC)curve were applied to derive a gene signature with best prognostic performance.The corresponding clinical and molecular information were further analyzed for interpretation of the different prognosis and the independence of the signature.Gene ontology(GO),Gene Set Variation Analysis(GSVA)and Gene Set Enrichment Analysis(GSEA)were performed for functional annotation of the differences.Results: A 3-gene signature was identified,by applying which,the anaplastic gliomas could be divided into low risk and high risk group.The two groups separately showed a high concordance with grade II and grade IV gliomas.The high risk group was more aggressive and complex than the low risk one.Conclusions: The 3-gene signature showed diagnostic and prognostic value in anaplastic gliomas.And anaplastic gliomas were more like a group of grade II and grade IV like gliomas,which needed their corresponding therapies individually.Phosphohistone H3(p HH3)is a prognostic and epithelial to mesenchymal transition marker in diffuse gliomasBackground: The World Health Organization(WHO)grading of gliomas stratifies tumors by histology.However,the aggressiveness of tumors in each grade still shows great heterogeneity.Phosphohistone H3(p HH3)has been reported as an accurate marker of cells within the mitotic phase of the cell cycle in many kinds of cancers.Methods: To evaluate the role of p HH3 in predicting patient outcome and to annotate the functions of p HH3 in WHO grade II-IV gliomas,we analyzed the expression pattern of p HH3 and p HH3 associated genes by IHC and m RNA expression profiling.Gene set enrichment analysis(GSEA)was used for further functional annotation of p HH3 in gliomas.Results: Phosphohistone H3,m RNA enrichment of histone H3 and associated gene signature all showed prognostic value in adult diffuse gliomas.Gene set enrichment analysis suggested that the expression of p HH3 had positive correlation with both epithelial to mesenchymal transition and immune response.Conclusions: These findings suggest that subgroups of diffuse gliomas defined by p HH3 and p HH3 signatures possess distinctive prognostic and biological characteristics.Tumor Purity As an Underlying Key Factor in GliomaBackground: Gliomas consist not only of glioma cells but also glioma-associated non-tumor cells,such as stromal cells and immune cells.These non-tumor cells dilute the purity of glioma cells and play important roles in glioma biology.Currently,the implications of variation in glioma purity are not sufficiently clarified.Methods: Here,glioma purity was inferred for 2249 cases from five cohorts.Based on the profiling method,we classified CGGA and TCGA-RNAseq cohorts as the RNAseq set for discovery.Cases from TCGA microarray,REMBRANDT,and GSE16011 cohorts were grouped as a microarray set for validation.Tissues from the CGGA cohort were reviewed for histopathologic validation.Results: We found that glioma purity was highly associated with major clinical and molecular features.Low purity cases were more likely to be diagnosed as malignant entities and independently correlated with reduced survival time.Integrating glioma purity into prognostic nomogram significantly improved the predictive validity.Moreover,most recognized prognostic indicators were no longer significantly effective under different purity conditions.These results highlighted the clinical importance of glioma purity.Further analyses found distinct genomic patterns associated with glioma purity.Low purity cases were distinguished by enhanced immune phenotypes.Among types of immune cells,macrophages,microglia,and neutrophils were mutually associated and enriched in low purity gliomas,while only macrophages and neutrophils served as robust indicators for poor prognosis.Conclusions: In summary,glioma purity and relevant non-tumor cells within a microenvironment confer important clinical,genomic and biological implications,which should be fully valued for precise classification and clinical prediction.