BACKGROUND: Osteosarcoma (OS) is the most widespread bone tumour among childhood cancers, and distant metastasis is the dominant factor in poor prognosis for patients with OS. Therefore, it is necessary to identify new prognostic biomarkers for identifying patients with aggressive disease. METHODS: Two OS datasets (GSE21257 and GSE33383) were downloaded from the Gene Expression Omnibus (GEO) and subsequently subjected to weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis (DGE) to screen candidate genes. A prognostic model was constructed using OS data derived from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program to further screen key genes and perform gene ontology (GO) analysis. The prognostic values of key genes were assessed using the Kaplan-Meier (KM) plotter. The GEO dataset was used for immune infiltration analysis and association analysis of key genes. In addition, quantitative real-time polymerase chain reaction (qRT-PCR) was employed to validate the expression levels of potentially crucial genes in OS cell lines. RESULTS: In the present study, we found 114 genes with a highly significant correlation in the module and 44 downregulated genes; 25 candidate genes overlapped in the two parts of the genes. Among these, three key genes, C1QA, C1QB, and C1QC, were the most significant hub genes, which had the highest node degrees, were clustered into one group, and implicated in most significant biological processes (regulation of immune effector process). Moreover, these three key genes were negatively associated with the prognosis of OS and positively associated with three immune cells (follicular helper T cells, memory B cells, and CD8 T cells). Additionally, compared to non-metastatic OS cell lines, the expression of three key genes was significantly downregulated in metastatic OS cell lines. CONCLUSION: Our results revealed that three key genes (C1QA, C1QB, and C1QC) were implicated in tumour immune infiltration and may be promising biomarkers for predicting metastasis and prognosis of patients with OS.