Metabolism is widely involved in the occurrence and development of cancer. However, its role in osteosarcoma (OS) has not been elucidated.
The open-accessed data included in this study were downloaded from The Cancer Genome Atlas (TCGA) database (TARGET-OS project). All the analysis was performed in R environments.
Based on the single sample gene set enrichment analysis algorithm, we quantified 21 metabolism terms in OS patients. Among these, sphingolipid metabolism was upregulated in the metastatic OS tissue and associated with a worse prognosis, therefore aroused our interest and selected for further analysis. Our result showed that sphingolipid metabolism could activate the Notch signaling and angiogenesis pathway, which might be responsible for the metastasis ability and poor prognosis. A protein-protein interaction network was constructed to illustrate the interaction of the differentially expressed genes between high and low sphingolipid metabolism. Immune analysis showed that multiple immune terms were upregulated in patients with high sphingolipid metabolism activity. Then, a prognosis model was established based on the identified DEGs between patients with high and low sphingolipid metabolism, which showed great prediction efficiency. Pathway enrichment showed the pathway of myogenesis, spermatogenesis, peroxisome, KRAS signaling, pancreas beta cells, apical surface, MYC target, WNT beta-catenin signaling, late estrogen response and apical junction was significantly enriched in high risk patients. Moreover, we found that the model genes MAGEB1, NPIPA2, PLA2G4B and MAGEA3 could effectively indicate sphingolipid metabolism and risk group.
In summary, our result showed that sphingolipid metabolism is associated with osteosarcoma metastasis and prognosis, which has the potential to be a therapeutic target for OS.