Abstract
BACKGROUND: Osteosarcoma was the most common primary bone malignancy in children and adolescents. It was imperative to identify effective prognostic biomarkers for this cancer. This study was aimed to identify potential crucial genes of osteosarcoma by integrated bioinformatics analysis. METHODS: Identification of differentially expressed genes from public data gene expression profiles (GSE42352), functional and pathway enrichment analysis, protein-protein interaction (PPI) network construction and module analysis, Cox regression and survival analysis was conducted. RESULTS: Totally 17 co-differential genes were found to be differentially expressed. These genes were enriched in biological processes, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) pathway of inflammatory immune response. PPI network was constructed with 63 differentially expressed genes that co-existed between the test set and the validation set. The area under the receiver operating characteristic curve (AUC value) was 0.855, which indicated that the expression of PODN had a good diagnostic value for osteosarcoma. Furthermore, Cox regression and survival analysis revealed 5 genes were statistically significant. CONCLUSIONS: PODN was regarded as a potential biomarker for the diagnosis and prognosis of osteosarcoma, ACTA2, COL6A1, FAP, OLFML2B and COL6A3, can be used as potential prognostic indicators for osteosarcoma.