A Combination Of RNA-seq And CHIP-seq Analysis For Determining Super-enhancer-associated Genes To Evaluate Prognosis And Immunity Of Glioma

Background Gliomas is one of the most common primary brain tumor in adults and is characterized by a short survival and high resistance to chemotherapy.Despite there are surgery,radiation and chemotherapy,clinical recurrence or progression is nearly universal,finding new therapeutic targets is imperative to increasing overall survival period.Super enhancer(SE)are enhancer clusters with cell type specificity,which drives higher levels of transcription of their target genes to promote the expression of a variety of oncogenes and enhances the biological function of tumor cells.Method Our research used GEO database transcriptome RNA-seq and H3K27 ac Chipseq of glioma,by combining the results of the two analyses,obtained 33 SE-associated risk genes.Then,we examined the gene profiles from CGGA and TCGA glioma database,regarding the CGGA and TCGA dataset as the training and validation set.Lasso regression and Cox analysis were performed to constructing an SE-associatedgene based risk score model in glioma.Three methods(Time-dependent receiver operating characteristic analysis and multivariate and univariate Cox regression analysis)were applied to assess the independent prognostic effect of texture parameters.The Consensus clustering was used to classify two clusters.Besides,functional and immune analyses were performed to assess the malignant process and immune microenvironment.Immunotherapy and anticancer drug response prediction were adopted to evaluate immune checkpoint and chemotherapy sensitivity.Finally,the effect of model gene on malignant phenotype of glioma cells was verified by in vitro experiments.Result The results revealed that the 10-gene signature has strong predictive power for glioma prognosis.Consensus clustering showed that the signature was closely related to a series of molecular and prognostic features such as WHO grade,IDH mutation,1p19 q codeletion,survival,age and PRS type.The validation set result revealed that the signature has exceptional accuracy and repeatability.Functional analysis showed that SE-associated gene signature was closely associated with the malignant process and prognosis of tumors.The immune analysis indicated that SE-associated gene signature is strongly related to immune infiltration and may direct various tumor immune microenvironment types.Immunotherapy and anticancer drug response prediction indicated that SE-associated gene signature is positively correlated with responding to the immune checkpoints and chemotherapy sensitivity.Finally,FCGR2 C is selected for phenotype detection.The silencing of FCGR2 C inhibited the migration and invasion of glioma cells.Conclusion Collectively,the SE-associated risk model can provide a novel signature to evaluate the prognosis and immune for glioma.