Comprehensive Characterization of Prognostic Long Noncoding RNAs in Osteosarcoma

The molecular mechanism of osteosarcoma (OS) based on protein-coding genes has largely been studied in the past decades. However, much remains to be explored when it comes to the role that long noncoding RNAs (lncRNAs) play in the pathogenesis and progression of OS and how they are associated with OS metastasis. In the present study, we collected RNA-seq-based gene expression data of 82 OS samples from the Therapeutically Applicable Research To Generate Effective Treatments (TARGET) database, along with their clinical information. We found that 50 lncRNAs were significantly associated with patients' survival by univariable Cox regression model. Moreover, we built multivariable Cox regression model based on 7 lncRNAs and successfully stratified patients into two risk groups, which exhibited significantly different prognostic outcomes. Significantly enriched Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways detected by differential expression analysis on DEGs between the two groups with different prognostic outcomes were both immune-related, indicating that such GO terms and pathways are critical for OS survival. Among the seven lncRNA signatures, AC011442.1 was predicted to act as an oncogenic driver in OS by correlation analysis of copy number alteration (CNA) and lncRNA expression, and it was predicted to regulate AMPK and hedgehog signaling pathways. In summary, the identification of novel prognostic lncRNAs in OS could not only improved our understanding of the lncRNAs involved in OS tumorigenesis or progression but also assist the diagnosis and development of molecularly targeted therapies for OS, which in turn benefit patients' survival.