ABSTRACT
Background: Osteosarcoma (OS) is a disease with high mortality in children and adolescents, and metastasis is one of its important clinical features. However, the molecular mechanism of OS occurrence is not completely clear. Thus, we screened potential biomarkers of OS and analyze their prognostic value. Methods: The Cancer Genome Atlas (TCGA) datasets were used to analyze the differential lncRNAs in patients with OS of different immune score and the lncRNAs expressed by immune cells. Cox regression was used to develop the prognosis prediction model and specify the prognosis outcomes. Risk-proportional regression model was constructed, and the samples were divided into high and low groups based on the risk scores for the survival analysis. The areas under the receiver operating characteristic (ROC) curve were calculated and the risk-score model was verified. Finally, using 4 gene sets (comprising chemokines, immune checkpoint blockades, immune activity-related genes, and immune cells), and 4 analysis tools (CIBERSORT, TIMER, XCELL and MCP) to evaluated tumor immune infiltration. Results: Twenty-nine long non-coding ribonucleic acids (lncRNAs) were obtained from the intersection of the screened lncRNAs. Caspase recruitment domain-containing protein 8-antisense RNA 1 (CARD8-AS1), lncRNA five prime to Xist (FTX), KAT8 regulatory NSL complex unit 1-antisense RNA 1 (KANSL1-AS1), Neuroplastin Intronic Transcript 1 (NPTN-IT1), oligodendrocyte maturation-associated long intervening non-coding RNA (OLMALINC) and RPARP Antisense RNA 1 (RPARP-AS1) were found to be correlated with survival. Univariate and multivariate regression analysis showed risk score [HR (hazard ratio) 3.5, P value 0.0043; HR 3.7, P value 0.0033] and metastasis (HR 4.7, P value 6.60E-05; HR 4.8, P value 8.36E-05) were the key factors of patients with OS. The areas under curves (AUCs) of the 1-, 3-, and 5-year ROC curves of the prognostic model were 0.715, 0.729, and 0.771. The low-risk patients tended to have a high abundance of immune cells. Conclusions: This study showed that a risk score based on 6 lncRNAs has potential value in the prognosis of OS, and patients with low-risk scores have high immune cell infiltration and good prognosis. This study may enrich understandings of underlying mechanisms related to the occurrence and development of OS.
ABSTRACT
BACKGROUND: Osteosarcoma is a disease with high mortality in children and adolescents, and metastasis is one of the important clinical features of osteosarcoma. N6-Methyladenosine (m6A) is the most abundant methylation modification in mRNA, which is regulated by m6A regulators. It is reported that it is related to the occurrence and development of tumors. However, the mechanism of its action in osteosarcoma is rarely known. The purpose of this study was to identify the potential role of m6A regulatory factor in osteosarcoma and its clinical prognostic value. METHODS: Here, we used The Cancer Genome Atlas (TCGA) to comprehensively analyze the relationship between m6A regulatory factors and osteosarcoma (metastasis group and non-metastasis group). We analyzed their survival relationship and analyzed all the m6A regulatory factors in TCGA tumor data set by using the univariate Cox proportional hazard regression model. Finally, we selected two survival-related methylation regulators (FTO and IGF2BP2) as risk gene signature. RESULTS: According to the median risk, patients were divided into low-risk group and high-risk group. Multivariate Cox regression analysis showed that these two risk genes were considered to be the key factors independently predicting the prognosis of patients with osteosarcoma. In addition, we verified their characteristics with gene expression omnibus (GEO) DataSets and confirmed that they are related to tumor and immune-related signaling pathways through gene set enrichment analysis (GESA) and immune infiltration analysis. CONCLUSIONS: In conclusion, m6A regulators might play an important role in the metastasis of osteosarcoma and have potential important value for the prognosis and treatment strategy of osteosarcoma patients.
