Glioma Bioinformatics Analysis Of The TCGA Transcriptome Data

Glioma is the most common intracranial malignant tumor,accounting for about45% of primary central nervous system tumors.Its treatment has always been a thorny problem in neurosurgery,about 77% of malignant Patients with glioma die within 1year after diagnosis,especially glioblastoma,with a median survival of only 14.6months.The occurrence and malignant progression of glioma is a multi-step process of progressive accumulation and multiple genetic alterations.The molecular pathways of the same histopathological tumor are also different and can be divided into different molecular subtypes.Different types of gliomas may have different molecular pathogenesis.In 2006,the American Cancer Genome Atlas(TCGA)carried out multi-platform,high-throughput genomic analysis with the most malignant and poor prognosis of glioblastoma,and achieved a series of important breakthroughs.The purpose of this project is to analyze the relationship between glioma occurrence and development of molecular markers and prognosis by bioinformatics methods using glioma transcriptome data from the TCGA database.The main tools used are perl and R.The specific work is as follows:1.By using the command line to download glioblastoma transcriptome data,low-grade glioma data in the database,and collation and merging of adjacent cancer sample data,a total of 169 glioblastoma transcriptome data were obtained,transcriptome data of 529 low-grade glioma samples,and 5 transcriptome data of adjacent cancer samples;First,differential genetic analysis was performed on paracancerous and glioblastoma,paracancerous and low-grade glioma,low-grade glioma and glioblastoma.The screening criteria were | Fold Change |?4,padj<0.01,respectively A total of 6185 differentially expressed genes(3499 differential genes were up-regulated and 2686 differential genes were down-regulated)were obtained between the paracancerous and glioblastoma groups.1939 differential expression was screened for differential genes between adjacent and low-grade glioma groups.Genes(614 differentially raised genes,1325 differentially expressed genes),3007 differentially expressed genes between differentially expressed genes in low-grade gliomas and high-grade gliomas(up to 2183 differential genes and 824 differentially expressed genes).Then,using Venn diagram analysis,co-differential gene analysis was performed on differentially expressed genomes of paracancerous and glioblastoma,differential genomic tissues of adjacent and low-grade gliomas,and low-grade gliomas and high-grade gliomas.,169 differentially expressed genes of paracancerous,glioblastoma,and low-grade glioma were obtained.Further screening of 169co-differentiated genes,removal of non-coding genes,and 135 coding co-differentiated genes.2.In order to understand the relevant biological processes involved in the differential gene,the 135 co-differentiated genes were subjected to GO gene enrichment analysis by using the Database for Annotation(visualization and integrated discovery,DAVID).The screening criteria were FDR less than 0.05;it was found through analysis that these differential genes mainly involved plasma membrane composition,ion channel and signal transduction,and cell cycle-related biological processes,and the number of genes involved in these biological processes was 69.3.To further understand the biological functions of the interaction between genes,Pathway analysis of co-differentiated genes was performed to determine the major biochemical metabolic pathways and signal transduction mechanisms involved in co-differentiated genes.The results showed that the co-differentiated genes are mainly involved in Neuroactive ligand-receptor interaction,Calcium signaling pathway,Morphine addiction,Morphine addiction,Circadian entrainment,c AMP signaling pathway,Serotonergic synapse,and Dopaminergic synapse,GABAergic synapse,Retrograde endocannabinoid signaling,Long-term potentiation,Amphetamine addiction,Glutamatergic synapse,Amyotrophic lateral sclerosis(ALS),Aldosterone synthesis and secretion,Synaptic vesicle cycle and Cholinergic synapse of synaptic vesicle circulation,cholinergic synapses,etc.,involve 34 common differential genes involved in these pathways.4.In order to further screen out the real key genes in co-differentially expressed genes,PPI network analysis of co-differentially expressed genes was performed using protein interaction data(https://string-db.org)and R.The results showed that 10 Hubgenes,SYT1,GABRG2,GRM4,MCHR2,GRIN1,CAMK2 A,GRIN2B,HTR2 A,CACNA1B and RYR2,were identified according to the results of the genes related to the significance of GO and KEGG.5.In order to further understand the key genes closely related to the prognosis of glioma,R software was used to analyze the relationship between key genes and prognosis.The results showed that the 10 key genes screened above were closely related to prognosis,especially CACNA1 B,GRIN1,HTR2 A and GRM4.The 2-year survival rate of high expression of CACNA1B(p=0)gene was 83.93%,the 2-year survival rate of low expression was 53.2%,and the 2-year survival rate of high expression of GRIN1(p=0)gene was 83.5%.The 2-year survival rate of low expression was 53.58%,the 2-year survival rate of high expression of HTR2A(p=0)was 84.2%,the 2-year survival rate of low expression was 54.21%,the 2-year survival rate of high expression of GRM4(p=0)was 84.4%,and the 2-year survival rate of low expression was 53.5%.