Screening of disorders associated with osteosarcoma by integrated network analysis

Abstract

Abstract Osteosarcoma is a common malignant bone tumor in children and adolescents under the age of 20. However, research on the pathogenesis and treatment of osteosarcoma is still insufficient. In the present study, based on gene-phenotype correlation network, an analysis was performed to screen disorders related to osteosarcoma. First, we analyzed the differential expression of osteosarcoma in two groups according to different types of osteosarcoma and screened the differentially expressed genes (DEGs) related to osteosarcoma. Further, these DEG coexpression modules were obtained. Finally, we identified a series of regulatory factors, such as endogenous genes, transcription factors (TFs), and ncRNAs, which have potential regulatory effects on osteosarcoma, based on the prediction analysis of related network of gene phenotypes. A total of 3767 DEGs of osteosarcoma were identified and clustered them into 20 osteosarcoma-related dysfunction modules. And there were 38 endogenous genes (including ARF1, HSP90AB1, and TUBA1B), 53 TFs (including E2F1, NFKB1, and EGR1), and 858 ncRNAs (including MALAT1, miR-590-3p, and TUG1) were considered as key regulators of osteosarcoma through a series of function enrichment analysis and network analysis. Based on the results of the present study, we can show a new way for biologists and pharmacists to reveal the potential molecular mechanism of osteosarcoma typing, and provide valuable reference for different follow-up treatment options.