Weighted gene correlation network analysis identifies the critical long non-coding RNAs participate in the progression of osteosarcoma.

Abstract

This study aimed to identify more biomarkers associated with osteosarcoma progression via lncRNA-mRNA co-expression network. Dataset GSE99671 was downloaded from GEO database. The mRNAs and lncRNAs that were differentially expressed between tumor and normal samples were screened out. Functional enrichment analysis of differentially expressed mRNAs was carried out, followed by weighted gene correlation network analysis (WGCNA). Based on the lncRNAs and mRNAs, a lncRNA-mRNA co-expression network was constructed. Total 703 mRNAs and 7 lncRNAs were differentially expressed between tumor and normal tissues. The mRNAs were significantly enriched in functions associated with inflammatory response as well as autoimmune thyroid disease and ribosome pathways. WGCNA revealed that ME2 module had a high correlation with tumor, and ST3GAL4, UCK2, PSAT1 etc. had higher connectivity degrees in this module. lncRNA-mRNA co-expression network showed that 12 mRNAs, such as PEMT, COL10A1 and GSTA1, were synergistically expressed with lncRNA TTTY14. Inflammatory response and ribosome synthesis may play important role in osteosarcoma progression. lncRNA TTTY14 may affect the development of osteosarcoma by cooperative expression with PEMT, COL10A1, GSTA1, etc. ST3GAL4, UCK2, PSAT1 as well as TTTY14 may serve as key biomarkers in osteosarcoma.