Identification and Validation of Lipid Metabolism-Related LncRNA Prognostic Signature for Patients with Osteosarcoma

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Background: Osteosarcoma(OS) is the most common primary bone malignancy in ado-lescents. The function of lipid metabolism-related lncRNAs in disease progression and prognosis of osteosarcoma remains unclear. This study aimed to explore the role of lipid metabolism-related lncRNAs in osteosarcoma development and prognosis. Methods: Pearson correlation was used for identification of lipid metabolism-related lncRNAs, and univariate and multivariate Cox regression analyses were used to construct and validate a risk signature to predict the prognosis of OS patients. Functional analysis using Gene set enrichment analysis (GSEA) to elucidate underlying mechanisms. Analysis of potential regulatory mechanisms of lipid metabolism-related lncRNAs using ceRNA networks, and they were preliminarily verified in our tissues using immunohistochemistry (IHC). Results: We screened two lipid metabolism-related lncRNAs (SNHG17 and LINC00837) to con-struct a risk signature and validated them in the GEO database. The results showed that this risk model was an independent prognostic factor for OS patients. GSEA analysis showed that this signature may be associated with cell proliferation and metabolism-related pathways in OS patients. Cox regression, ROC curve analysis, and a nomogram indicated that the risk model was an independent prognostic factor and it showed potent potential for survival prediction in osteosarcoma. Nomogram integrating risk model and clinical characteristics could predict the prognosis of osteosarcoma patients accurately. Immunohistochemical results showed that CSNK2A2, MIF and VDAC2 were up-regulated in tumor tissues. Conclusions: In summary, our study demonstrates that lipid-metabolism related-lncRNA could be applied to predict the prognosis of in osteosarcoma accurately.