Identification Of Aberrantly Methylated Genes In Osteosarcoma By Integrated Bioinformatics Analysis

Background:Osteosarcoma(OS)is a relatively rare primary malignant stromal tumor and the most common primary malignant tumors of bone.The 5-year survival rate of patients with osteosarcoma has increased to about 70%through the combined treatment of surgery and chemotherapy.However,surgical treatment has a serious impact on the function of the limbs.Chemotherapy also has diverse side effects while treating patients.Therefore,it is urgent to find new treatments and improve early diagnosis.In recent years,recognizing the changes in gene-specific methylation have gradually been applied to early diagnosis and treatment of cancer.Although recent studies have shown that aberrant methylation of specific genes has profound effects on the survival and prognosis of osteosarcoma.However,the aberrantly methylated genes that are significantly associated with osteosarcoma have not yet been studied.Nowadays,the incidence of osteosarcoma is increasing worldwide.It is urgent to find more sensitive and specific biomarkers and therapeutic targets to improve the early diagnosis and prognosis of osteosarcoma patientsMethods:Part1:The miRNA datasets GSE28423 and GSE65071,the mRNA dataset GSE36001 and the methylation dataset GSE36002 were downloaded from the GEO database.The GSE28423 was contained data from 19 OS and 4 normal bone samples.GSE65071 was included data of 20 OS and 15 normal bone samples.GSE36001 and GSE36002 were included data of 19 OS cell lines and 6 normal osteoblasts and bones samples.GEO2R was used to screen for the differentially expressed mRNAs(DEGs),miRNAs(DEMs)and methylated genes(DMGs)from the respective datasets using |logFC|>1 or log|β|>0.2(for DMGs)and p-value<0.05 as the thresholds.The putative target genes of the overlapping DEMs of GSE28423 and GSE65071 datasets were predicted using the RNA22 tool.Part2:The expression matrix of the DEGs was analyzed by the GSEA tool according to p values<0.05 and q values<0.05.Biological process enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)analysis were performed using the ClusterProfiler package of R software,with P<0.05 as the threshold.The STRING database was used to construct the PPI networks,which were then visualized using CYTOSCAPE.Part3:The prognostic value of the 8 TSGs was determined by survival analysis using the online database R2.The correlation between TSGs methylation and expression was performed by R software.The MG63 cells were treated with 5μM 5-Aza or DMSO(vehicle)for 48h.The relative mRNA expression levels were detected by qPCR analysis.Part4:The MG63 cells were treated with 5μM 5-Aza or DMSO(vehicle)for 48h.Cell proliferation was detected by the cck 8 method.The effects of aberrant methylation on cell proliferation,migration and invasion were examined by CCK-8 assay,Wound-healing assay and transwell assay,respectively.Results:1.We identified DEGs,DMGs,DEMs and the potential targets of DEMs using the dataset mentioned above.The overlap between these targets,DEGs and DMGs revealed 187 hypermethylated down-regulated genes and only 3 hypomethylated up-regulated genes.To further identify the DEGs in OS,we conducted GSEA based on the GSE36001 dataset.Ten KEGG gene sets was significantly enriched in OS including a total of 539 mRNAs.Overlapping of the 539 mRNAs of KEGG gene sets,DEGs,DMGs and 18,809 target genes of the 15 DEMs,revealed 47 hypermethylated down-regulated genes that are likely involved in OS2.Gene ontology(GO)analysis indicated that these genes may participated in positive regulation of response to external stimulus.KEGG pathway enrichment analysis showed that most genes were enriched in several cancer-related pathways,such as the JAK-STAT and PI3K-Akt.The PPI network further demonstrated complex interactions between the downregulated and hypermethylated mRNAs at the protein level.3.we screened for known TSGs among the 47 OS-related DEGs,and identified eight.Patients expressing low levels of six TSGs had worse metastasis free survival compared to the corresponding high expression group(P<0.05).Correlation analysis of the gene expression and DNA methylation data revealed a significant inverse correlation between DNA methylation and the respective gene expression levels(P<0.05).qPCR results showed that mRNA levels of six TSGs were significantly increased after 5-Aza treatment,thereby confirming the in silico data(P<0.05).4.Blocking DNA methylation not only decreased the survival of the OS cells in vitro,but also markedly diminished their migration and invasion capacities compared to the DMSO controls(P<0.05).Conclusions:TSGs including PYCARD,STAT5A,CDH5,CXCL12 and CXCL14 were aberrantly methylated in OS,and are potential prognostic biomarkers and therapeutic targets.Our findings provide new insights into the role of methylation in OS progression.