Osteosarcoma is the most common primary bone malignancy in children and adolescents. Although improvements in therapeutic strategies were achieved, the outcome remains poor for most patients with metastatic or recurrent osteosarcoma[25]. Therefore, it is imperative to identify novel and effective prognostic biomarker and therapeutic targets for the disease. Studies have emphasized that both lipid metabolism and lncRNA can be involved in the proliferation, metastasis and drug resistance of tumor cells[7, 26, 27]. Thus, lipid metabolism-related lncRNA abnormalities may be a potential predictor of osteosarcoma metastasis and patient survivorship. In the present study, we identified a potential prognostic two-lipid metabolism-related lncRNAs signature from GEO database, which included SNHG17 and LINC00837.
Small nucleolar RNA host gene 17 (SNHG17) is a novel cancer-related lncRNA of the SNHG family which is highly expressed in various tumors as well as may be in-volved in proliferation, apoptosis, invasion, metastasis, drug resistance and other bio-logical functions of cancer cells[28]. SNHG17 also can regulate some gene expression via binding to relative miRNA as a competitive endogenous RNA (ceRNA)[29]. A large number of studies have also shown that SNHG17 plays an important pathogenic role in a variety of tumor-associated diseases. Such as SNHG17 can upregulated PAX6 to exert its carcinogenic role acted as a ceRNA of miR-375[30], promoting epithelial-mesenchymal transition (EMT) progress, proliferation and invasion of ESCC cells by sponging miR-338-3p, thereby activating SOX4[31], and may regulate H2AX signaling via miR-328-3p in renal cell carcinoma[32]. In summary, numerous evidences indicate that SNHG17 plays an important role in tumor development and has important clinical application value in tumor diagnosis and prognosis. At present, there are few studies on LINC00837, only one study shows that LINC00837 may be positively correlated with resting dendritic cells, but its impact on tumorigenesis, diagnosis and prognosis is still unclear[33].
Therefore, we speculate that the abnormal expression of SNHG17 and LINC00837 may be related to the prognosis and immunosuppressive microenvironment of OS patients. To further evaluate the prognostic value of SNHG17 and LINC00837, we con-structed a prognostic risk model for lipid metabolism-related lncRNAs using univariate and multivariate COX regression analysis in GEO training cohort. And subsequently, we constructed a prognostic nomogram that integrated the risk score based on this model and some significant clinical features including sex, age and metastasis. The results showed that the risk score effectively predicted prognosis in the GEO training cohort and was validated in the GEO internal validation cohort. The signature and nomogram were further validated by Kaplan–Meier survival analysis, calibration plots, receiver operating characteristic (ROC) curves and decision curve analysis (DCA). And the AUC values of 1, 3, 5 years of the nomogram reached 0.935, 0.772, 0.828, respectively, suggesting that the nomogram exhibited superior survival predictive ability. In summarising, several validation methods have proven the robustness of the risk model, and we have confidence that the risk model will be extensively applied to individualised risk management. In an addition, we discovered that the label-based risk score was significantly associated with metastasis, which indicated that labeling was also a better predictor of osteosarcoma metastasis.
To identify pathways associated with the risk model, we performed a GSEA to examine potential pathways and features in both high and low risk groups. KEGG results suggest that lipid metabolism-related lncRNA risk features may be associated with cell proliferation and metabolism-related pathways. When lipid metabolism is dysregulated, it can lead to impaired tumour microenvironment and bone remodelling, resulting in poor prognosis of osteosarcoma[34]. Studies have shown that metabolic re-programming is an important feature of immune cell activation, which can affect their immune function because of different metabolic characteristics[35, 36]. The infiltration level of immune cells in tumors is an important indicator for prognostic judgment and treatment effect evaluation[37]. Given the closeness of metabolic reprogramming to the tumour immune microenvironment, the immune environment between high- and low-risk populations was explored. Subsequently, we then calculated the level of infiltration of 24 immune cells in patients with OS. Spearman's correlation analysis yielded a significant negative correlation between risk score and central memory CD8 T cells, macrophages, natural killer cells and plasmacytoid dendritic cells. It is suggested that the lower the risk score of OS patients, the higher the degree of immune cell infiltration. On these grounds, it is plausible to conclude that risk score and immune status are inter-related with poor prognosis.
To date, few studies have focused on the roles of two lncRNAs, SNHG17 and LINC00837, in the occurrence and progression of osteosarcoma [31]. To further elucidate how the lipid metabolism-related lncRNA (SNHG17 and LINC00837) regulate lipid metabolism-related gene, via sponging miRNAs in OS, we searched for miRNAs interacting with SNHG17 and LINC00837, respectively. Results show that no miRNAs are expected to bind to LINC00837, ceRNA network analysis of SNHG17 showed that SNHG17 could regulate the expression of four genes including CSNK2A2, MIF, ODC1 and VDAC2 via binding to different miRNAs. But the relationship between these genes and the pathogenesis and prognosis of osteosarcoma remains to be further studied. Therefore, in this study, we performed immunohistochemical detection on tumor tis-sues and adjacent tissues of patients with osteosarcoma, and the results showed that CSNK2A2, MIF and VDAC2 genes were up-regulated in tumor tissues of patients with osteosarcoma, but there was no significant difference in the expression of ODC1 gene, which may be due to the large difference in positive signal values between different samples. Previous study showed that CSNK2A2 gene can be used as a prognostic biomarker for hepatocellular carcinoma and may be involved in the pathological process of abdominal aortic aneurysm[38, 39]. MIF is an inflammatory cytokine involved in the carcinogenesis of many cancer types, it has important roles in angiogenesis, im-munity and metastasis in melanoma cell lines[40]. And VDAC2 can induces apoptosis and affects tumor development[41, 42].Taken together, these data and results may demonstrate that SNHG17 may as a competing endogenous RNA (ceRNA) to regulate the expression of lipid metabolism related genes including CSNK2A2, MIF and VDAC2 through binding with hsa-miR-505-3p, hsa-miR-451a, hsa-miR-6839-3p and hsa-miR-370-3p respectively, thereby further regulating the formation and development of osteosarcoma.
Combining the above findings, this study constructed a risk model based on two lipid metabolism-related lncRNA signature, and evaluated the model using multiple validation methods to further validate the robustness and accuracy of the risk model. In particular, we not only investigated the accuracy of the risk model predictions, but also analysed the possible regulatory mechanisms of the two lipid metabolism-related lncRNAs with prognostic value, providing guidance for subsequent studies on the molecular mechanisms of osteosarcoma and targeted therapies.
However, there were certain limitations to our study, this was a retrospective study with a small sample size of osteosarcoma and lacked the support of more experimental evidence. There is therefore a need for further studies to validate the accuracy of the model using independent cohorts combined with experiments such as immunohistochemical analysis or PCR. Notwithstanding these limitations, we are constructed two lipid metabolism-related lncRNA signatures that have good prognostic value in osteosarcoma. They require further research to elucidate their roles in the progression of osteosarcoma.