A novel necroptosis-related lncRNAs signature effectively predicts the prognosis for osteosarcoma and is associated with immunity - Liu, Binfeng; Feng, Chengyao; Liu, Zhongyue; Tu, Chao; Li, Zhihong (Frontiers in Pharmacology, 2022)
Abstract Backgroud: Necroptosis is closely related to tumorigenesis and development. Accumulating evidence has revealed that long non-coding RNAs (lncRNAs) are also central players in osteosarcoma (OS). However, the role of necroptosis-related lncRNAs in OS remains unclear. In the present study, we aim to craft a prognostic signature based on necroptosis-related lncRNAs to improve the OS prognosis prediction. Methods: The signature-based on necroptosis-related lncRNAs was discovered using univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis. The prognosis efficiency of the signature was then estimated employing a variety of bioinformatics methods. Subsequently, immunological analysis and Gene Set Enrichment Analysis (GSEA) were used to explore the association between necroptosis-related lncRNAs with clinical outcomes and immune status. More importantly, several necroptosis-related lncRNAs were validated with RT-qPCR. Results: Consequently, a novel prognosis signature was success constructed based on eight necroptosis-related lncRNAs. Meanwhile, the novel necroptosis-related lncRNAs model could distribute OS patients into two different risk groups and was stable and accurate. Additionally, the GSEA and immune analysis revealed that the necroptosis-related lncRNAs signature affect the development and prognosis of OS by regulating the immune status. The necroptosis-related lncRNAs signature was closely correlated with multiple anticancer agent susceptibility. Moreover, the RT-qPCR results indicated several necroptosis-related lncRNAs were significantly differently expressed in osteosarcoma and osteoblast cell lines. Conclusion: In this summary, a novel prognostic signature integrating necroptosis-related lncRNAs was firstly constructed and could accurately predict the prognosis of OS. This study may increase the predicted value and guide the personalized chemotherapy treatment for OS.