Relationship of N6-Methyladenosine-Related lncRNAs With Tumor Microenvironment and Clinical Prognosis in Osteosarcoma

Background: The aberrant expression of long non-coding RNAs (lncRNAs) can affect the occurrence and progression of various cancers, including osteosarcoma (OS), by regulation of N6-methyladenosine (m6A) modification. However, their interaction involved in the prognostic value of OS and tumor microenvironment remains unclear. Methods: : We collected data from TCGA and GEO datasets. Using Pearson correlation, univariate, multivariate, LASSO Cox regression analyses, we identified the prognostic m6A-related lncRNAs and conducted the prognostic cluster and model. Survival analyses were used to analyze different clusters and models, respectively. The receiver operating characteristic (ROC) curve and independent prognosis analysis was used to evaluate the performance of the risk model. We also examined the relationship of the risk model and cluster with immune checkpoint (PD1 and CTLA-4) and tumor microenvironment (TME). Results: : A total of 43 m6A-related lncRNAs have significant prognostic significance for OS patients. Patients of cluster 2 have a longer survival time than cluster 1. CD8+ T cells, resting NK cells, and Monocytes were highly inflamed tissues in cluster 2, while gamma delta T cells and M0 macrophages were lowly in cluster 1. Meantime, OS patients with lower prognosis scores had better overall survival status, and ROC curves proved that the risk model had better prognostic abilities with the area under the curve (AUC) of 0.938 and 0.924 in train and test datasets, respectively. The risk score of 17 m6A-related lncRNAs was identified as an independent risk factor for OS. Both PD1 and CTLA-4 were closely associated with m6A-related lncRNAs and prognostic scores. The risk score was higher in cluster 2, while cluster 1 had a lower purity of tumor cells and a higher density of immune-related cells in the TME. Conclusions: : We established a new m6A-related lncRNAs prognostic biomarker that can predict the prognostic risk of OS was significantly linked with the OS tumor microenvironment.